diff --git a/.github/workflows/BuildNDeployDev.yml b/.github/workflows/BuildNDeployDev.yml
index 564d473..c985fcf 100644
--- a/.github/workflows/BuildNDeployDev.yml
+++ b/.github/workflows/BuildNDeployDev.yml
@@ -1,27 +1,29 @@
 name: Build and Deploy Development Data
 
-on: # run this workflow when a push has been made to `Jekyll-Alf` branch
+on: # run this workflow when a push has been made to development branch
   push:
     branches:
       - development
 
-
 jobs:
   deploy:
     runs-on: ubuntu-20.04
+    env:
+      # Service Account info to trigger open-sdg-site-starter workflow
+      PAT_USERNAME: ${{ secrets.PAT_USERNAME }}
+      PAT_TOKEN: ${{ secrets.PAT_TOKEN }}
+      CLOUDFRONT_DIST_ID: ${{ secrets.CDN_DISTRIBUTION_ID_DEV }}
     steps:   
  ###########################################################################################################
  #      This is the CI portion
  ###########################################################################################################
         - name: Checkout repo
           uses: actions/checkout@v2
-          
-          
+             
  ###########################################################################################################
  #      This is the CD portion
  ###########################################################################################################       
           
-      
         - name: Setup Python
           uses: actions/setup-python@v1 # sets up python in our environment
           with:
@@ -31,15 +33,12 @@ jobs:
         - name: Install Python dependencies requirements
           run: pip3 install -r scripts/requirements.txt
 
-        
-        
         - name: Build site data
           run: python3 scripts/build_data.py
         
         - name: Install AWS CLI
           run: pip3 install awscli --upgrade --user # install the cli with upgrade to any requirements and into the subdir of the user
-          
-          
+            
         - name: Configure AWS Credentials
           uses: aws-actions/configure-aws-credentials@v1 # use the official GitHub Action from AWS to setup credentials
           with:
@@ -48,12 +47,22 @@ jobs:
             aws-region: ${{ secrets.AWS_REGION }}
             mask-aws-account-id: true
         
-    
         - name: Push Contents to S3 # push the current working directory to the S3 bucket
           run: aws s3 sync _site/ s3://${{ secrets.S3_BUCKET_NAME_DEV }} --exclude ".git/*" --exclude ".github/*" --delete # have the bucket have the same content in the repo & exclude the git related directories.
         
         - name: Invalidate CloudFront Cache # Invalidate the CloudFront Distribution Cache to get contents from the S3 bucket
-          run: aws cloudfront create-invalidation --distribution-id ${{ secrets.CDN_DISTRIBUTION_ID_DEV }} --paths "/*"
-              
-          
-          
\ No newline at end of file
+          run: aws cloudfront create-invalidation --distribution-id "$CLOUDFRONT_DIST_ID" --paths "/*"
+
+        - name: Check Invalidation is Complete
+          run: ./scripts/check_invalidations.sh
+
+        - name: Trigger open-sdg-site-starter workflow
+          run: |
+            curl \
+            -X POST \
+            -u "$PAT_USERNAME:$PAT_TOKEN" \
+            -H "Accept: application/vnd.github.v3+json" \
+            -H "Content-Type: application/json" \
+            https://api.github.com/repos/CityOfLosAngeles/open-sdg-site-starter/dispatches \
+            -d '{"event_type":"dev_triggered_from_open-sdg-data-starter"}'
+        
\ No newline at end of file
diff --git a/.github/workflows/BuildNDeployProd.yml b/.github/workflows/BuildNDeployProd.yml
index cec98a8..c6f3519 100644
--- a/.github/workflows/BuildNDeployProd.yml
+++ b/.github/workflows/BuildNDeployProd.yml
@@ -1,46 +1,44 @@
 name: Build and Deploy Production Data
 
-on: # run this workflow when a push has been made to `Jekyll-Alf` branch
+on: # run this workflow when a push has been made to production branch
   push:
     branches:
       - production
 
-
 jobs:
   deploy:
     runs-on: ubuntu-20.04
+    env:
+      # Service Account info to trigger open-sdg-site-starter workflow
+      PAT_USERNAME: ${{ secrets.PAT_USERNAME }}
+      PAT_TOKEN: ${{ secrets.PAT_TOKEN }}
+      CLOUDFRONT_DIST_ID: ${{ secrets.CDN_DISTRIBUTION_ID_PROD }}
     steps:   
  ###########################################################################################################
  #      This is the CI portion
  ###########################################################################################################
         - name: Checkout repo
           uses: actions/checkout@v2
-          
-          
+               
  ###########################################################################################################
  #      This is the CD portion
  ###########################################################################################################       
-          
-        #- uses: actions/checkout@v1 # checks out the code in the repository
+
         - name: Setup Python
           uses: actions/setup-python@v1 # sets up python in our environment
           with:
             python-version: '3.x' # install python version 3.x, default architecture is x64
                  
-          
           # this Action should follow steps to set up Python build environment
         - name: Install Python dependencies requirements
           run: pip3 install -r scripts/requirements.txt
-
-        
-        
+      
         - name: Build site data
           run: python3 scripts/build_data.py
         
         - name: Install AWS CLI
           run: pip3 install awscli --upgrade --user # install the cli with upgrade to any requirements and into the subdir of the user
           
-          
         - name: Configure AWS Credentials
           uses: aws-actions/configure-aws-credentials@v1 # use the official GitHub Action from AWS to setup credentials
           with:
@@ -49,12 +47,21 @@ jobs:
             aws-region: ${{ secrets.AWS_REGION }}
             mask-aws-account-id: true
         
-    
         - name: Push Contents to S3 # push the current working directory to the S3 bucket
           run: aws s3 sync _site/ s3://${{ secrets.S3_BUCKET_NAME_PROD }} --exclude ".git/*" --exclude ".github/*" --delete # have the bucket have the same content in the repo & exclude the git related directories.
         
         - name: Invalidate CloudFront Cache # Invalidate the CloudFront Distribution Cache to get contents from the S3 bucket
-          run: aws cloudfront create-invalidation --distribution-id ${{ secrets.CDN_DISTRIBUTION_ID_PROD }} --paths "/*"
-              
-          
-          
+          run: aws cloudfront create-invalidation --distribution-id "$CLOUDFRONT_DIST_ID" --paths "/*"
+
+        - name: Check Invalidation is Complete
+          run: ./scripts/check_invalidations.sh
+
+        - name: Trigger open-sdg-site-starter workflow
+          run: |
+            curl \
+            -X POST \
+            -u "$PAT_USERNAME:$PAT_TOKEN" \
+            -H "Accept: application/vnd.github.v3+json" \
+            -H "Content-Type: application/json" \
+            https://api.github.com/repos/CityOfLosAngeles/open-sdg-site-starter/dispatches \
+            -d '{"event_type":"prod_triggered_from_open-sdg-data-starter"}'
diff --git a/_prose.yml b/_prose.yml
index e6eb834..4abd7b5 100644
--- a/_prose.yml
+++ b/_prose.yml
@@ -85,7 +85,7 @@ prose:
       - name: "national_target_line"
         field:
             element: text
-            label: "Target line"
+            label: "Local target"
             scope: national
       - name: "national_geographical_coverage"
         field:
@@ -153,6 +153,8 @@ prose:
                 value: 'New'
               - name: 'Non-Statistical'
                 value: 'Non-Statistical'
+              - name: 'Proxy'
+                value: 'Proxy'
             scope: national
        ######### Data Info #########
       - name: "reporting_status"
diff --git a/data/indicator_1-1-1.csv b/data/indicator_1-1-1.csv
index eb69e66..29eafb5 100755
--- a/data/indicator_1-1-1.csv
+++ b/data/indicator_1-1-1.csv
@@ -145,4 +145,25 @@ Year,Age,Gender,Race,Education Attainment,Employment Status,Units,Value
 2018,,,,Bachelor's Degree or Higher,,Percent by Education,3.5
 2018,,,,,,Percentage by Employment,6.8
 2018,,,,,Employed (full-time),Percentage by Employment,0.5
-2018,,,,,Unemployed,Percentage by Employment,20.1
\ No newline at end of file
+2018,,,,,Unemployed,Percentage by Employment,20.1
+2019,,,,,,Percent by Age,7.3
+2019,Under 18 years,,,,,Percent by Age,10.1
+2019,18 to 64 years,,,,,Percent by Age,7.0
+2019,65 years and over,,,,,Percent by Age,4.8
+2019,,,,,,Percent by Gender,7.3
+2019,,Male,,,,Percent by Gender,6.7
+2019,,Female,,,,Percent by Gender,7.9
+2019,,,,,,Percent by Race,7.3
+2019,,,White,,,Percent by Race,6.3
+2019,,,Black or African American,,,Percent by Race,12.1
+2019,,,American Indian and Alaska Native,,,Percent by Race,8.0
+2019,,,Asian,,,Percent by Race,7.3
+2019,,,Native Hawaiian and Other Pacific Islander,,,Percent by Race,11.7
+2019,,,Hispanic or Latino origin (any race),,,Percent by Race,7.9
+2019,,,,,,Percent by Education,7.3
+2019,,,,Less than High School,,Percent by Education,9.2
+2019,,,,High School Graduate,,Percent by Education,6.8
+2019,,,,Bachelor's Degree or Higher,,Percent by Education,3.4
+2019,,,,,,Percentage by Employment,7.3
+2019,,,,,Employed (full-time),Percentage by Employment,0.7
+2019,,,,,Unemployed,Percentage by Employment,21.6
\ No newline at end of file
diff --git a/data/indicator_1-2-1.csv b/data/indicator_1-2-1.csv
index 3ba6221..bee9a23 100755
--- a/data/indicator_1-2-1.csv
+++ b/data/indicator_1-2-1.csv
@@ -1,148 +1,169 @@
-Year,Age,Gender,Race,Education Attainment,Employment Status,Units,Value
-2012,,,,,,Percent by Age,23.3
-2012,Under 18 years,,,,,Percent by Age,34
-2012,18 to 64 years,,,,,Percent by Age,20.8
-2012,65 years and over,,,,,Percent by Age,16.6
-2012,,,,,,Percent by Gender,23.3
-2012,,Male,,,,Percent by Gender,21.6
-2012,,Female,,,,Percent by Gender,24.9
-2012,,,,,,Percent by Race,23.3
-2012,,,White,,,Percent by Race,18.5
-2012,,,Black or African American,,,Percent by Race,30.2
-2012,,,American Indian and Alaska Native,,,Percent by Race,28.7
-2012,,,Asian,,,Percent by Race,16.1
-2012,,,Native Hawaiian and Other Pacific Islander,,,Percent by Race,26.8
-2012,,,Hispanic or Latino origin (any race),,,Percent by Race,30.3
-2012,,,,,,Percent by Education,23.3
-2012,,,,Less than High School,,Percent by Education,31.7
-2012,,,,High School Graduate,,Percent by Education,20.9
-2012,,,,Bachelor's Degree or Higher,,Percent by Education,8.1
-2012,,,,,,Percentage by Employment,23.3
-2012,,,,,Employed,Percentage by Employment,11.2
-2012,,,,,Unemployed,Percentage by Employment,35.6
-2013,,,,,,Percent by Age,23
-2013,Under 18 years,,,,,Percent by Age,33.8
-2013,18 to 64 years,,,,,Percent by Age,20.5
-2013,65 years and over,,,,,Percent by Age,16.6
-2013,,,,,,Percent by Gender,23
-2013,,Male,,,,Percent by Gender,21.4
-2013,,Female,,,,Percent by Gender,24.5
-2013,,,,,,Percent by Race,23
-2013,,,White,,,Percent by Race,19.4
-2013,,,Black or African American,,,Percent by Race,28.8
-2013,,,American Indian and Alaska Native,,,Percent by Race,33.2
-2013,,,Asian,,,Percent by Race,15.8
-2013,,,Native Hawaiian and Other Pacific Islander,,,Percent by Race,20.9
-2013,,,Hispanic or Latino origin (any race),,,Percent by Race,29.5
-2013,,,,,,Percent by Education,23
-2013,,,,Less than High School,,Percent by Education,30.6
-2013,,,,High School Graduate,,Percent by Education,20.8
-2013,,,,Bachelor's Degree or Higher,,Percent by Education,8.7
-2013,,,,,,Percentage by Employment,23
-2013,,,,,Employed,Percentage by Employment,11.5
-2013,,,,,Unemployed,Percentage by Employment,37.7
-2014,,,,,,Percent by Age,22.4
-2014,Under 18 years,,,,,Percent by Age,33
-2014,18 to 64 years,,,,,Percent by Age,19.8
-2014,65 years and over,,,,,Percent by Age,16.7
-2014,,,,,,Percent by Gender,22.4
-2014,,Male,,,,Percent by Gender,20.6
-2014,,Female,,,,Percent by Gender,24
-2014,,,,,,Percent by Race,22.4
-2014,,,White,,,Percent by Race,19.4
-2014,,,Black or African American,,,Percent by Race,28.7
-2014,,,American Indian and Alaska Native,,,Percent by Race,20.3
-2014,,,Asian,,,Percent by Race,15.8
-2014,,,Native Hawaiian and Other Pacific Islander,,,Percent by Race,17.1
-2014,,,Hispanic or Latino origin (any race),,,Percent by Race,29.3
-2014,,,,,,Percent by Education,22.4
-2014,,,,Less than High School,,Percent by Education,31.3
-2014,,,,High School Graduate,,Percent by Education,21.2
-2014,,,,Bachelor's Degree or Higher,,Percent by Education,8
-2014,,,,,,Percentage by Employment,22.4
-2014,,,,,Employed,Percentage by Employment,11.3
-2014,,,,,Unemployed,Percentage by Employment,37.2
-2015,,,,,,Percent by Age,20.5
-2015,Under 18 years,,,,,Percent by Age,29.6
-2015,18 to 64 years,,,,,Percent by Age,18.4
-2015,65 years and over,,,,,Percent by Age,15.6
-2015,,,,,,Percent by Gender,20.5
-2015,,Male,,,,Percent by Gender,19.1
-2015,,Female,,,,Percent by Gender,21.9
-2015,,,,,,Percent by Race,20.5
-2015,,,White,,,Percent by Race,17.4
-2015,,,Black or African American,,,Percent by Race,26.2
-2015,,,American Indian and Alaska Native,,,Percent by Race,29.4
-2015,,,Asian,,,Percent by Race,15.5
-2015,,,Native Hawaiian and Other Pacific Islander,,,Percent by Race,
-2015,,,Hispanic or Latino origin (any race),,,Percent by Race,26.4
-2015,,,,,,Percent by Education,20.5
-2015,,,,Less than High School,,Percent by Education,29.3
-2015,,,,High School Graduate,,Percent by Education,19.2
-2015,,,,Bachelor's Degree or Higher,,Percent by Education,7.4
-2015,,,,,,Percentage by Employment,20.5
-2015,,,,,Employed,Percentage by Employment,10.2
-2015,,,,,Unemployed,Percentage by Employment,37.1
-2016,,,,,,Percent by Age,19.5
-2016,Under 18 years,,,,,Percent by Age,28.5
-2016,18 to 64 years,,,,,Percent by Age,17.5
-2016,65 years and over,,,,,Percent by Age,15.1
-2016,,,,,,Percent by Gender,19.5
-2016,,Male,,,,Percent by Gender,17.6
-2016,,Female,,,,Percent by Gender,21.3
-2016,,,,,,Percent by Race,19.5
-2016,,,White,,,Percent by Race,16.3
-2016,,,Black or African American,,,Percent by Race,27.4
-2016,,,American Indian and Alaska Native,,,Percent by Race,22.8
-2016,,,Asian,,,Percent by Race,15.4
-2016,,,Native Hawaiian and Other Pacific Islander,,,Percent by Race,15
-2016,,,Hispanic or Latino origin (any race),,,Percent by Race,24.1
-2016,,,,,,Percent by Education,19.5
-2016,,,,Less than High School,,Percent by Education,28.2
-2016,,,,High School Graduate,,Percent by Education,18.4
-2016,,,,Bachelor's Degree or Higher,,Percent by Education,7.1
-2016,,,,,,Percentage by Employment,19.5
-2016,,,,,Employed,Percentage by Employment,9.7
-2016,,,,,Unemployed,Percentage by Employment,32.8
-2017,,,,,,Percent by Age,17.4
-2017,Under 18 years,,,,,Percent by Age,24.7
-2017,18 to 64 years,,,,,Percent by Age,15.5
-2017,65 years and over,,,,,Percent by Age,15.2
-2017,,,,,,Percent by Gender,17.4
-2017,,Male,,,,Percent by Gender,16
-2017,,Female,,,,Percent by Gender,18.7
-2017,,,,,,Percent by Race,17.4
-2017,,,White,,,Percent by Race,15.3
-2017,,,Black or African American,,,Percent by Race,23.6
-2017,,,American Indian and Alaska Native,,,Percent by Race,16
-2017,,,Asian,,,Percent by Race,14.5
-2017,,,Native Hawaiian and Other Pacific Islander,,,Percent by Race,
-2017,,,Hispanic or Latino origin (any race),,,Percent by Race,21.1
-2017,,,,,,Percent by Education,17.4
-2017,,,,Less than High School,,Percent by Education,24.8
-2017,,,,High School Graduate,,Percent by Education,16.9
-2017,,,,Bachelor's Degree or Higher,,Percent by Education,7.3
-2017,,,,,,Percentage by Employment,17.4
-2017,,,,,Employed,Percentage by Employment,8.1
-2017,,,,,Unemployed,Percentage by Employment,29.3
-2018,,,,,,Percent by Age,16.5
-2018,Under 18 years,,,,,Percent by Age,22.9
-2018,18 to 64 years,,,,,Percent by Age,14.6
-2018,65 years and over,,,,,Percent by Age,16.2
-2018,,,,,,Percent by Gender,16.5
-2018,,Male,,,,Percent by Gender,15.2
-2018,,Female,,,,Percent by Gender,17.8
-2018,,,,,,Percent by Race,16.5
-2018,,,White,,,Percent by Race,15
-2018,,,Black or African American,,,Percent by Race,23.9
-2018,,,American Indian and Alaska Native,,,Percent by Race,16.5
-2018,,,Asian,,,Percent by Race,13.2
-2018,,,Native Hawaiian and Other Pacific Islander,,,Percent by Race,14.5
-2018,,,Hispanic or Latino origin (any race),,,Percent by Race,19.7
-2018,,,,,,Percent by Education,16.5
-2018,,,,Less than High School,,Percent by Education,23.7
-2018,,,,High School Graduate,,Percent by Education,17.3
-2018,,,,Bachelor's Degree or Higher,,Percent by Education,6.8
-2018,,,,,,Percentage by Employment,16.5
-2018,,,,,Employed,Percentage by Employment,7.6
-2018,,,,,Unemployed,Percentage by Employment,29.7
+Year,Age,Gender,Race,Education Attainment,Employment Status,Units,Value
+2012,,,,,,Percent by Age,23.3
+2012,Under 18 years,,,,,Percent by Age,34
+2012,18 to 64 years,,,,,Percent by Age,20.8
+2012,65 years and over,,,,,Percent by Age,16.6
+2012,,,,,,Percent by Gender,23.3
+2012,,Male,,,,Percent by Gender,21.6
+2012,,Female,,,,Percent by Gender,24.9
+2012,,,,,,Percent by Race,23.3
+2012,,,White,,,Percent by Race,18.5
+2012,,,Black or African American,,,Percent by Race,30.2
+2012,,,American Indian and Alaska Native,,,Percent by Race,28.7
+2012,,,Asian,,,Percent by Race,16.1
+2012,,,Native Hawaiian and Other Pacific Islander,,,Percent by Race,26.8
+2012,,,Hispanic or Latino origin (any race),,,Percent by Race,30.3
+2012,,,,,,Percent by Education,23.3
+2012,,,,Less than High School,,Percent by Education,31.7
+2012,,,,High School Graduate,,Percent by Education,20.9
+2012,,,,Bachelor's Degree or Higher,,Percent by Education,8.1
+2012,,,,,,Percentage by Employment,23.3
+2012,,,,,Employed,Percentage by Employment,11.2
+2012,,,,,Unemployed,Percentage by Employment,35.6
+2013,,,,,,Percent by Age,23
+2013,Under 18 years,,,,,Percent by Age,33.8
+2013,18 to 64 years,,,,,Percent by Age,20.5
+2013,65 years and over,,,,,Percent by Age,16.6
+2013,,,,,,Percent by Gender,23
+2013,,Male,,,,Percent by Gender,21.4
+2013,,Female,,,,Percent by Gender,24.5
+2013,,,,,,Percent by Race,23
+2013,,,White,,,Percent by Race,19.4
+2013,,,Black or African American,,,Percent by Race,28.8
+2013,,,American Indian and Alaska Native,,,Percent by Race,33.2
+2013,,,Asian,,,Percent by Race,15.8
+2013,,,Native Hawaiian and Other Pacific Islander,,,Percent by Race,20.9
+2013,,,Hispanic or Latino origin (any race),,,Percent by Race,29.5
+2013,,,,,,Percent by Education,23
+2013,,,,Less than High School,,Percent by Education,30.6
+2013,,,,High School Graduate,,Percent by Education,20.8
+2013,,,,Bachelor's Degree or Higher,,Percent by Education,8.7
+2013,,,,,,Percentage by Employment,23
+2013,,,,,Employed,Percentage by Employment,11.5
+2013,,,,,Unemployed,Percentage by Employment,37.7
+2014,,,,,,Percent by Age,22.4
+2014,Under 18 years,,,,,Percent by Age,33
+2014,18 to 64 years,,,,,Percent by Age,19.8
+2014,65 years and over,,,,,Percent by Age,16.7
+2014,,,,,,Percent by Gender,22.4
+2014,,Male,,,,Percent by Gender,20.6
+2014,,Female,,,,Percent by Gender,24
+2014,,,,,,Percent by Race,22.4
+2014,,,White,,,Percent by Race,19.4
+2014,,,Black or African American,,,Percent by Race,28.7
+2014,,,American Indian and Alaska Native,,,Percent by Race,20.3
+2014,,,Asian,,,Percent by Race,15.8
+2014,,,Native Hawaiian and Other Pacific Islander,,,Percent by Race,17.1
+2014,,,Hispanic or Latino origin (any race),,,Percent by Race,29.3
+2014,,,,,,Percent by Education,22.4
+2014,,,,Less than High School,,Percent by Education,31.3
+2014,,,,High School Graduate,,Percent by Education,21.2
+2014,,,,Bachelor's Degree or Higher,,Percent by Education,8
+2014,,,,,,Percentage by Employment,22.4
+2014,,,,,Employed,Percentage by Employment,11.3
+2014,,,,,Unemployed,Percentage by Employment,37.2
+2015,,,,,,Percent by Age,20.5
+2015,Under 18 years,,,,,Percent by Age,29.6
+2015,18 to 64 years,,,,,Percent by Age,18.4
+2015,65 years and over,,,,,Percent by Age,15.6
+2015,,,,,,Percent by Gender,20.5
+2015,,Male,,,,Percent by Gender,19.1
+2015,,Female,,,,Percent by Gender,21.9
+2015,,,,,,Percent by Race,20.5
+2015,,,White,,,Percent by Race,17.4
+2015,,,Black or African American,,,Percent by Race,26.2
+2015,,,American Indian and Alaska Native,,,Percent by Race,29.4
+2015,,,Asian,,,Percent by Race,15.5
+2015,,,Native Hawaiian and Other Pacific Islander,,,Percent by Race,
+2015,,,Hispanic or Latino origin (any race),,,Percent by Race,26.4
+2015,,,,,,Percent by Education,20.5
+2015,,,,Less than High School,,Percent by Education,29.3
+2015,,,,High School Graduate,,Percent by Education,19.2
+2015,,,,Bachelor's Degree or Higher,,Percent by Education,7.4
+2015,,,,,,Percentage by Employment,20.5
+2015,,,,,Employed,Percentage by Employment,10.2
+2015,,,,,Unemployed,Percentage by Employment,37.1
+2016,,,,,,Percent by Age,19.5
+2016,Under 18 years,,,,,Percent by Age,28.5
+2016,18 to 64 years,,,,,Percent by Age,17.5
+2016,65 years and over,,,,,Percent by Age,15.1
+2016,,,,,,Percent by Gender,19.5
+2016,,Male,,,,Percent by Gender,17.6
+2016,,Female,,,,Percent by Gender,21.3
+2016,,,,,,Percent by Race,19.5
+2016,,,White,,,Percent by Race,16.3
+2016,,,Black or African American,,,Percent by Race,27.4
+2016,,,American Indian and Alaska Native,,,Percent by Race,22.8
+2016,,,Asian,,,Percent by Race,15.4
+2016,,,Native Hawaiian and Other Pacific Islander,,,Percent by Race,15
+2016,,,Hispanic or Latino origin (any race),,,Percent by Race,24.1
+2016,,,,,,Percent by Education,19.5
+2016,,,,Less than High School,,Percent by Education,28.2
+2016,,,,High School Graduate,,Percent by Education,18.4
+2016,,,,Bachelor's Degree or Higher,,Percent by Education,7.1
+2016,,,,,,Percentage by Employment,19.5
+2016,,,,,Employed,Percentage by Employment,9.7
+2016,,,,,Unemployed,Percentage by Employment,32.8
+2017,,,,,,Percent by Age,17.4
+2017,Under 18 years,,,,,Percent by Age,24.7
+2017,18 to 64 years,,,,,Percent by Age,15.5
+2017,65 years and over,,,,,Percent by Age,15.2
+2017,,,,,,Percent by Gender,17.4
+2017,,Male,,,,Percent by Gender,16
+2017,,Female,,,,Percent by Gender,18.7
+2017,,,,,,Percent by Race,17.4
+2017,,,White,,,Percent by Race,15.3
+2017,,,Black or African American,,,Percent by Race,23.6
+2017,,,American Indian and Alaska Native,,,Percent by Race,16
+2017,,,Asian,,,Percent by Race,14.5
+2017,,,Native Hawaiian and Other Pacific Islander,,,Percent by Race,
+2017,,,Hispanic or Latino origin (any race),,,Percent by Race,21.1
+2017,,,,,,Percent by Education,17.4
+2017,,,,Less than High School,,Percent by Education,24.8
+2017,,,,High School Graduate,,Percent by Education,16.9
+2017,,,,Bachelor's Degree or Higher,,Percent by Education,7.3
+2017,,,,,,Percentage by Employment,17.4
+2017,,,,,Employed,Percentage by Employment,8.1
+2017,,,,,Unemployed,Percentage by Employment,29.3
+2018,,,,,,Percent by Age,16.5
+2018,Under 18 years,,,,,Percent by Age,22.9
+2018,18 to 64 years,,,,,Percent by Age,14.6
+2018,65 years and over,,,,,Percent by Age,16.2
+2018,,,,,,Percent by Gender,16.5
+2018,,Male,,,,Percent by Gender,15.2
+2018,,Female,,,,Percent by Gender,17.8
+2018,,,,,,Percent by Race,16.5
+2018,,,White,,,Percent by Race,15
+2018,,,Black or African American,,,Percent by Race,23.9
+2018,,,American Indian and Alaska Native,,,Percent by Race,16.5
+2018,,,Asian,,,Percent by Race,13.2
+2018,,,Native Hawaiian and Other Pacific Islander,,,Percent by Race,14.5
+2018,,,Hispanic or Latino origin (any race),,,Percent by Race,19.7
+2018,,,,,,Percent by Education,16.5
+2018,,,,Less than High School,,Percent by Education,23.7
+2018,,,,High School Graduate,,Percent by Education,17.3
+2018,,,,Bachelor's Degree or Higher,,Percent by Education,6.8
+2018,,,,,,Percentage by Employment,16.5
+2018,,,,,Employed,Percentage by Employment,7.6
+2018,,,,,Unemployed,Percentage by Employment,29.7
+2019,,,,,,Percent by Age,16.7
+2019,Under 18 years,,,,,Percent by Age,24.5
+2019,18 to 64 years,,,,,Percent by Age,14.4
+2019,65 years and over,,,,,Percent by Age,16.3
+2019,,,,,,Percent by Gender,16.7
+2019,,Male,,,,Percent by Gender,15.4
+2019,,Female,,,,Percent by Gender,18.0
+2019,,,,,,Percent by Race,16.7
+2019,,,White,,,Percent by Race,14.4
+2019,,,Black or African American,,,Percent by Race,24.6
+2019,,,American Indian and Alaska Native,,,Percent by Race,16.9
+2019,,,Asian,,,Percent by Race,13.6
+2019,,,Native Hawaiian and Other Pacific Islander,,,Percent by Race,15.5
+2019,,,Hispanic or Latino origin (any race),,,Percent by Race,20.2
+2019,,,,,,Percent by Education,16.7
+2019,,,,Less than High School,,Percent by Education,23.8
+2019,,,,High School Graduate,,Percent by Education,17.2
+2019,,,,Bachelor's Degree or Higher,,Percent by Education,6.9
+2019,,,,,,Percentage by Employment,16.7
+2019,,,,,Employed,Percentage by Employment,3.9
+2019,,,,,Unemployed,Percentage by Employment,35.8
\ No newline at end of file
diff --git a/data/indicator_1-2-2.csv b/data/indicator_1-2-2.csv
index 0acb638..ebfe5d5 100644
--- a/data/indicator_1-2-2.csv
+++ b/data/indicator_1-2-2.csv
@@ -1,127 +1,56 @@
-Year,Gender,Age Group,Units,Value
-2017,,,Less than 50 percent of the poverty level,8.5
-2017,male,,Less than 50 percent of the poverty level,7.5
-2017,female,,Less than 50 percent of the poverty level,9.5
-2017,,,Less than 50 percent of the poverty level,8.5
-2017,,Under 18 years,Less than 50 percent of the poverty level,11.4
-2017,,18 to 64 years,Less than 50 percent of the poverty level,8.4
-2017,,65 years and over,Less than 50 percent of the poverty level,4.1
-2017,,,Less than 100 percent of the poverty level,20.4
-2017,male,,Less than 100 percent of the poverty level,18.8
-2017,female,,Less than 100 percent of the poverty level,21.9
-2017,,,Less than 100 percent of the poverty level,20.4
-2017,,Under 18 years,Less than 100 percent of the poverty level,29.5
-2017,,18 to 64 years,Less than 100 percent of the poverty level,18.2
-2017,,65 years and over,Less than 100 percent of the poverty level,15.9
-2017,,,Less than 125 percent of the poverty level,26.7
-2017,male,,Less than 125 percent of the poverty level,25.2
-2017,female,,Less than 125 percent of the poverty level,28.3
-2017,,,Less than 125 percent of the poverty level,26.7
-2017,,Under 18 years,Less than 125 percent of the poverty level,37.8
-2017,,18 to 64 years,Less than 125 percent of the poverty level,24
-2017,,65 years and over,Less than 125 percent of the poverty level,22.5
-2016,,,Less than 50 percent of the poverty level,9
-2016,male,,Less than 50 percent of the poverty level,8.1
-2016,female,,Less than 50 percent of the poverty level,10
-2016,,,Less than 50 percent of the poverty level,9
-2016,,Under 18 years,Less than 50 percent of the poverty level,12.4
-2016,,18 to 64 years,Less than 50 percent of the poverty level,8.8
-2016,,65 years and over,Less than 50 percent of the poverty level,4
-2016,,,Less than 100 percent of the poverty level,21.5
-2016,male,,Less than 100 percent of the poverty level,19.9
-2016,female,,Less than 100 percent of the poverty level,23.1
-2016,,,Less than 100 percent of the poverty level,21.5
-2016,,Under 18 years,Less than 100 percent of the poverty level,31.4
-2016,,18 to 64 years,Less than 100 percent of the poverty level,19.2
-2016,,65 years and over,Less than 100 percent of the poverty level,16.2
-2016,,,Less than 125 percent of the poverty level,28
-2016,male,,Less than 125 percent of the poverty level,26.4
-2016,female,,Less than 125 percent of the poverty level,29.6
-2016,,,Less than 125 percent of the poverty level,28
-2016,,Under 18 years,Less than 125 percent of the poverty level,39.6
-2016,,18 to 64 years,Less than 125 percent of the poverty level,25.2
-2016,,65 years and over,Less than 125 percent of the poverty level,22.8
-2015,,,Less than 50 percent of the poverty level,9.4
-2015,male,,Less than 50 percent of the poverty level,8.5
-2015,female,,Less than 50 percent of the poverty level,10.4
-2015,,,Less than 50 percent of the poverty level,9.4
-2015,,Under 18 years,Less than 50 percent of the poverty level,13.2
-2015,,18 to 64 years,Less than 50 percent of the poverty level,9.1
-2015,,65 years and over,Less than 50 percent of the poverty level,3.8
-2015,,,Less than 100 percent of the poverty level,22.1
-2015,male,,Less than 100 percent of the poverty level,20.5
-2015,female,,Less than 100 percent of the poverty level,23.7
-2015,,,Less than 100 percent of the poverty level,22.1
-2015,,Under 18 years,Less than 100 percent of the poverty level,32.2
-2015,,18 to 64 years,Less than 100 percent of the poverty level,19.8
-2015,,65 years and over,Less than 100 percent of the poverty level,16.2
-2015,,,Less than 125 percent of the poverty level,28.8
-2015,male,,Less than 125 percent of the poverty level,27.3
-2015,female,,Less than 125 percent of the poverty level,30.3
-2015,,,Less than 125 percent of the poverty level,28.8
-2015,,Under 18 years,Less than 125 percent of the poverty level,40.6
-2015,,18 to 64 years,Less than 125 percent of the poverty level,26
-2015,,65 years and over,Less than 125 percent of the poverty level,23.1
-2014,,,Less than 50 percent of the poverty level,9.5
-2014,male,,Less than 50 percent of the poverty level,8.6
-2014,female,,Less than 50 percent of the poverty level,10.5
-2014,,,Less than 50 percent of the poverty level,9.5
-2014,,Under 18 years,Less than 50 percent of the poverty level,13.3
-2014,,18 to 64 years,Less than 50 percent of the poverty level,9.2
-2014,,65 years and over,Less than 50 percent of the poverty level,3.7
-2014,,,Less than 100 percent of the poverty level,22.4
-2014,male,,Less than 100 percent of the poverty level,20.8
-2014,female,,Less than 100 percent of the poverty level,24
-2014,,,Less than 100 percent of the poverty level,22.4
-2014,,Under 18 years,Less than 100 percent of the poverty level,32.6
-2014,,18 to 64 years,Less than 100 percent of the poverty level,20
-2014,,65 years and over,Less than 100 percent of the poverty level,16.3
-2014,,,Less than 125 percent of the poverty level,29.3
-2014,male,,Less than 125 percent of the poverty level,27.7
-2014,female,,Less than 125 percent of the poverty level,30.9
-2014,,,Less than 125 percent of the poverty level,29.3
-2014,,Under 18 years,Less than 125 percent of the poverty level,41.2
-2014,,18 to 64 years,Less than 125 percent of the poverty level,26.4
-2014,,65 years and over,Less than 125 percent of the poverty level,23.2
-2013,,,Less than 50 percent of the poverty level,9.5
-2013,male,,Less than 50 percent of the poverty level,8.5
-2013,female,,Less than 50 percent of the poverty level,10.4
-2013,,,Less than 50 percent of the poverty level,9.5
-2013,,Under 18 years,Less than 50 percent of the poverty level,13.2
-2013,,18 to 64 years,Less than 50 percent of the poverty level,9.2
-2013,,65 years and over,Less than 50 percent of the poverty level,3.6
-2013,,,Less than 100 percent of the poverty level,22
-2013,male,,Less than 100 percent of the poverty level,20.4
-2013,female,,Less than 100 percent of the poverty level,23.5
-2013,,,Less than 100 percent of the poverty level,22
-2013,,Under 18 years,Less than 100 percent of the poverty level,31.7
-2013,,18 to 64 years,Less than 100 percent of the poverty level,19.6
-2013,,65 years and over,Less than 100 percent of the poverty level,15.6
-2013,,,Less than 125 percent of the poverty level,28.7
-2013,male,,Less than 125 percent of the poverty level,27.1
-2013,female,,Less than 125 percent of the poverty level,30.3
-2013,,,Less than 125 percent of the poverty level,28.7
-2013,,Under 18 years,Less than 125 percent of the poverty level,40.2
-2013,,18 to 64 years,Less than 125 percent of the poverty level,25.8
-2013,,65 years and over,Less than 125 percent of the poverty level,22.6
-2012,,,Less than 50 percent of the poverty level,8.9
-2012,male,,Less than 50 percent of the poverty level,7.9
-2012,female,,Less than 50 percent of the poverty level,9.9
-2012,,,Less than 50 percent of the poverty level,8.9
-2012,,Under 18 years,Less than 50 percent of the poverty level,12.3
-2012,,18 to 64 years,Less than 50 percent of the poverty level,8.6
-2012,,65 years and over,Less than 50 percent of the poverty level,3.5
-2012,,,Less than 100 percent of the poverty level,21.2
-2012,male,,Less than 100 percent of the poverty level,19.6
-2012,female,,Less than 100 percent of the poverty level,22.7
-2012,,,Less than 100 percent of the poverty level,21.2
-2012,,Under 18 years,Less than 100 percent of the poverty level,30.6
-2012,,18 to 64 years,Less than 100 percent of the poverty level,18.9
-2012,,65 years and over,Less than 100 percent of the poverty level,15
-2012,,,Less than 125 percent of the poverty level,27.9
-2012,male,,Less than 125 percent of the poverty level,26.2
-2012,female,,Less than 125 percent of the poverty level,29.5
-2012,,,Less than 125 percent of the poverty level,27.9
-2012,,Under 18 years,Less than 125 percent of the poverty level,39.2
-2012,,18 to 64 years,Less than 125 percent of the poverty level,24.8
-2012,,65 years and over,Less than 125 percent of the poverty level,22.5
\ No newline at end of file
+Year,Education Attainment,Race/ Ethnicity,Units,Value
+2015,,,Percent by Education Level,42
+2015,Less than High School,,Percent by Education Level,79
+2015,High School Diploma,,Percent by Education Level,60
+2015,Some College,,Percent by Education Level,41
+2015,College degree or higher,,Percent by Education Level,20
+2015,,,Percent by Race/ Ethnicity,42
+2015,,Latino,Percent by Race/ Ethnicity,62
+2015,,Native American/ Alaska Native,Percent by Race/ Ethnicity,33
+2015,,African American,Percent by Race/ Ethnicity,45
+2015,,Asian American/ Pacific Islander,Percent by Race/ Ethnicity,36
+2015,,White,Percent by Race/ Ethnicity,24
+2016,,,Percent by Education Level,44
+2016,Less than High School,,Percent by Education Level,79
+2016,High School Diploma,,Percent by Education Level,61
+2016,Some College,,Percent by Education Level,45
+2016,College degree or higher,,Percent by Education Level,21
+2016,,,Percent by Race/ Ethnicity,44
+2016,,Latino,Percent by Race/ Ethnicity,63
+2016,,Native American/ Alaska Native,Percent by Race/ Ethnicity,47
+2016,,African American,Percent by Race/ Ethnicity,47
+2016,,Asian American/ Pacific Islander,Percent by Race/ Ethnicity,39
+2016,,White,Percent by Race/ Ethnicity,26
+2017,,,Percent by Education Level,42
+2017,Less than High School,,Percent by Education Level,77
+2017,High School Diploma,,Percent by Education Level,60
+2017,Some College,,Percent by Education Level,43
+2017,College degree or higher,,Percent by Education Level,21
+2017,,,Percent by Race/ Ethnicity,42
+2017,,Latino,Percent by Race/ Ethnicity,61
+2017,,Native American/ Alaska Native,Percent by Race/ Ethnicity,28
+2017,,African American,Percent by Race/ Ethnicity,46
+2017,,Asian American/ Pacific Islander,Percent by Race/ Ethnicity,36
+2017,,White,Percent by Race/ Ethnicity,24
+2018,,,Percent by Education Level,41
+2018,Less than High School,,Percent by Education Level,75
+2018,High School Diploma,,Percent by Education Level,58
+2018,Some College,,Percent by Education Level,41
+2018,College degree or higher,,Percent by Education Level,20
+2018,,,Percent by Race/ Ethnicity,41
+2018,,Latino,Percent by Race/ Ethnicity,59
+2018,,Native American/ Alaska Native,Percent by Race/ Ethnicity,44
+2018,,African American,Percent by Race/ Ethnicity,45
+2018,,Asian American/ Pacific Islander,Percent by Race/ Ethnicity,36
+2018,,White,Percent by Race/ Ethnicity,23
+2019,,,Percent by Education Level,40
+2019,Less than High School,,Percent by Education Level,75
+2019,High School Diploma,,Percent by Education Level,56
+2019,Some College,,Percent by Education Level,42
+2019,College degree or higher,,Percent by Education Level,19
+2019,,,Percent by Race/ Ethnicity,40
+2019,,Latino,Percent by Race/ Ethnicity,58
+2019,,Native American/ Alaska Native,Percent by Race/ Ethnicity,53
+2019,,African American,Percent by Race/ Ethnicity,43
+2019,,Asian American/ Pacific Islander,Percent by Race/ Ethnicity,34
+2019,,White,Percent by Race/ Ethnicity,22
\ No newline at end of file
diff --git a/data/indicator_1-4-1.csv b/data/indicator_1-4-1.csv
index 42faf91..d359f72 100644
--- a/data/indicator_1-4-1.csv
+++ b/data/indicator_1-4-1.csv
@@ -1,49 +1,37 @@
-Year,Service Type,Units,Value
-2018,Complete Plumbing Facilities,Percent With Service,99.4
-2018,Complete Kitchen Facilities,Percent With Service,98.2
-2018,Telephone Service,Percent With Service,98.5
-2018,Complete Plumbing Facilities,Total Population With Service,8137
-2018,Complete Kitchen Facilities,Total Population With Service,25039
-2018,Telephone Service,Total Population With Service,20250
-2017,Complete Plumbing Facilities,Percent With Service,99.4
-2017,Complete Kitchen Facilities,Percent With Service,98.2
-2017,Telephone Service,Percent With Service,98.7
-2017,Complete Plumbing Facilities,Total Population With Service,8076
-2017,Complete Kitchen Facilities,Total Population With Service,24775
-2017,Telephone Service,Total Population With Service,17996
-2016,Complete Plumbing Facilities,Percent With Service,99.3
-2016,Complete Kitchen Facilities,Percent With Service,97.9
-2016,Telephone Service,Percent With Service,97.4
-2016,Complete Plumbing Facilities,Total Population With Service,9072
-2016,Complete Kitchen Facilities,Total Population With Service,28331
-2016,Telephone Service,Total Population With Service,35848
-2015,Complete Plumbing Facilities,Percent With Service,99.3
-2015,Complete Kitchen Facilities,Percent With Service,98.1
-2015,Telephone Service,Percent With Service,97.5
-2015,Complete Plumbing Facilities,Total Population With Service,8888
-2015,Complete Kitchen Facilities,Total Population With Service,25947
-2015,Telephone Service,Total Population With Service,34403
-2014,Complete Plumbing Facilities,Percent With Service,99.3
-2014,Complete Kitchen Facilities,Percent With Service,97.9
-2014,Telephone Service,Percent With Service,97.6
-2014,Complete Plumbing Facilities,Total Population With Service,9017
-2014,Complete Kitchen Facilities,Total Population With Service,27779
-2014,Telephone Service,Total Population With Service,32421
-2013,Complete Plumbing Facilities,Percent With Service,99.4
-2013,Complete Kitchen Facilities,Percent With Service,98.1
-2013,Telephone Service,Percent With Service,97.9
-2013,Complete Plumbing Facilities,Total Population With Service,7340
-2013,Complete Kitchen Facilities,Total Population With Service,24738
-2013,Telephone Service,Total Population With Service,27156
-2012,Complete Plumbing Facilities,Percent With Service,99.4
-2012,Complete Kitchen Facilities,Percent With Service,98
-2012,Telephone Service,Percent With Service,97.8
-2012,Complete Plumbing Facilities,Total Population With Service,7645
-2012,Complete Kitchen Facilities,Total Population With Service,26201
-2011,Telephone Service,Total Population With Service,29490
-2011,Complete Plumbing Facilities,Percent With Service,99.1
-2011,Complete Kitchen Facilities,Percent With Service,97.6
-2011,Telephone Service,Percent With Service,97.4
-2011,Complete Plumbing Facilities,Total Population With Service,12126
-2011,Complete Kitchen Facilities,Total Population With Service,31435
-2011,Telephone Service,Total Population With Service,33708
\ No newline at end of file
+Year,Service Type,Value
+2019,Complete Plumbing Facilities,99.6
+2019,Complete Kitchen Facilities,98.3
+2019,Telephone Service,99.1
+2019,At Least One Vehicle Available,87.9
+2018,Complete Plumbing Facilities,99.4
+2018,Complete Kitchen Facilities,98.2
+2018,Telephone Service,98.5
+2018,At Least One Vehicle Available,88.3
+2017,Complete Plumbing Facilities,99.4
+2017,Complete Kitchen Facilities,98.2
+2017,Telephone Service,98.7
+2017,At Least One Vehicle Available,88.3
+2016,Complete Plumbing Facilities,99.3
+2016,Complete Kitchen Facilities,97.9
+2016,Telephone Service,97.4
+2016,At Least One Vehicle Available,87.8
+2015,Complete Plumbing Facilities,99.3
+2015,Complete Kitchen Facilities,98.1
+2015,Telephone Service,97.5
+2015,At Least One Vehicle Available,87.9
+2014,Complete Plumbing Facilities,99.3
+2014,Complete Kitchen Facilities,97.9
+2014,Telephone Service,97.6
+2014,At Least One Vehicle Available,86.7
+2013,Complete Plumbing Facilities,99.4
+2013,Complete Kitchen Facilities,98.1
+2013,Telephone Service,97.9
+2013,At Least One Vehicle Available,87
+2012,Complete Plumbing Facilities,99.4
+2012,Complete Kitchen Facilities,98
+2012,Telephone Service,97.8
+2012,At Least One Vehicle Available,86.4
+2011,Complete Plumbing Facilities,99.1
+2011,Complete Kitchen Facilities,97.6
+2011,Telephone Service,97.4
+2011,At Least One Vehicle Available,86.2
\ No newline at end of file
diff --git a/data/indicator_1-a-2.csv b/data/indicator_1-a-2.csv
index ee906e4..d29e347 100644
--- a/data/indicator_1-a-2.csv
+++ b/data/indicator_1-a-2.csv
@@ -1,7 +1,11 @@
-Year,Group,Value
-2015,A,1
-2015,B,3
-2015,,2
-2016,A,1
-2016,B,3
-2016,,2
+Year,Agency,Value
+2020,Los Angeles Unified School District,10.6
+2020,Los Angeles County Public Social Services Department,4.44
+2020,Los Angeles County Department of Mental Health,3.55
+2020,Los Angeles County Health Services Department,1.36
+2020,Los Angeles County Public Health Department,1.19
+2021,Los Angeles Unified School District,11.8
+2021,Los Angeles County Public Social Services Department,4.62
+2021,Los Angeles County Department of Mental Health,3.51
+2021,Los Angeles County Health Services Department,1.51
+2021,Los Angeles County Public Health Department,1.74
\ No newline at end of file
diff --git a/data/indicator_10-2-1.csv b/data/indicator_10-2-1.csv
index 5ac77db..9b260aa 100644
--- a/data/indicator_10-2-1.csv
+++ b/data/indicator_10-2-1.csv
@@ -1,109 +1,22 @@
-Year,Earning Group,Gender,Value
-2009,"less than $25,000",,32.7
-2009,"$25,000 - $50,000",,33.3
-2009,"$50,000 - $75,000",,16.2
-2009,"over $75,000",,17.8
-2009,"less than $25,000",Male,32.5
-2009,"$25,000 - $50,000",Male,32.2
-2009,"$50,000 - $75,000",Male,15.4
-2009,"over $75,000",Male,20
-2009,"less than $25,000",Female,33
-2009,"$25,000 - $50,000",Female,34.9
-2009,"$50,000 - $75,000",Female,17.3
-2009,"over $75,000",Female,14.7
-2010,"less than $25,000",,31.6
-2010,"$25,000 - $50,000",,32.8
-2010,"$50,000 - $75,000",,16.7
-2010,"over $75,000",,18.8
-2010,"less than $25,000",Male,31.2
-2010,"$25,000 - $50,000",Male,31.8
-2010,"$50,000 - $75,000",Male,15.9
-2010,"over $75,000",Male,21.2
-2010,"less than $25,000",Female,32.2
-2010,"$25,000 - $50,000",Female,34.2
-2010,"$50,000 - $75,000",Female,18
-2010,"over $75,000",Female,15.6
-2011,"less than $25,000",,30.2
-2011,"$25,000 - $50,000",,32.8
-2011,"$50,000 - $75,000",,17
-2011,"over $75,000",,20.1
-2011,"less than $25,000",Male,30.2
-2011,"$25,000 - $50,000",Male,31.7
-2011,"$50,000 - $75,000",Male,15.8
-2011,"over $75,000",Male,22.3
-2011,"less than $25,000",Female,30.2
-2011,"$25,000 - $50,000",Female,34.4
-2011,"$50,000 - $75,000",Female,18.6
-2011,"over $75,000",Female,16.8
-2012,"less than $25,000",,29.6
-2012,"$25,000 - $50,000",,32.4
-2012,"$50,000 - $75,000",,17.2
-2012,"over $75,000",,20.8
-2012,"less than $25,000",Male,29.3
-2012,"$25,000 - $50,000",Male,31.5
-2012,"$50,000 - $75,000",Male,16.1
-2012,"over $75,000",Male,23
-2012,"less than $25,000",Female,29.8
-2012,"$25,000 - $50,000",Female,33.7
-2012,"$50,000 - $75,000",Female,18.8
-2012,"over $75,000",Female,17.8
-2013,"less than $25,000",,29.9
-2013,"$25,000 - $50,000",,31.9
-2013,"$50,000 - $75,000",,16.8
-2013,"over $75,000",,21.5
-2013,"less than $25,000",Male,29.9
-2013,"$25,000 - $50,000",Male,30.8
-2013,"$50,000 - $75,000",Male,15.8
-2013,"over $75,000",Male,23.6
-2013,"less than $25,000",Female,29.7
-2013,"$25,000 - $50,000",Female,33.4
-2013,"$50,000 - $75,000",Female,18.3
-2013,"over $75,000",Female,18.6
-2014,"less than $25,000",,29.5
-2014,"$25,000 - $50,000",,31.8
-2014,"$50,000 - $75,000",,16.9
-2014,"over $75,000",,21.9
-2014,"less than $25,000",Male,29.6
-2014,"$25,000 - $50,000",Male,30.7
-2014,"$50,000 - $75,000",Male,16
-2014,"over $75,000",Male,23.7
-2014,"less than $25,000",Female,29.5
-2014,"$25,000 - $50,000",Female,33.1
-2014,"$50,000 - $75,000",Female,18.2
-2014,"over $75,000",Female,19.2
-2015,"less than $25,000",,29.5
-2015,"$25,000 - $50,000",,31.6
-2015,"$50,000 - $75,000",,17.1
-2015,"over $75,000",,22
-2015,"less than $25,000",Male,29.4
-2015,"$25,000 - $50,000",Male,30.6
-2015,"$50,000 - $75,000",Male,16.1
-2015,"over $75,000",Male,23.9
-2015,"less than $25,000",Female,29.5
-2015,"$25,000 - $50,000",Female,32.8
-2015,"$50,000 - $75,000",Female,18.3
-2015,"over $75,000",Female,19.4
-2016,"less than $25,000",,28.4
-2016,"$25,000 - $50,000",,33.7
-2016,"$50,000 - $75,000",,17.2
-2016,"over $75,000",,22.7
-2016,"less than $25,000",Male,28
-2016,"$25,000 - $50,000",Male,31
-2016,"$50,000 - $75,000",Male,14.2
-2016,"over $75,000",Male,24.6
-2016,"less than $25,000",Female,28.9
-2016,"$25,000 - $50,000",Female,32.6
-2016,"$50,000 - $75,000",Female,18.4
-2016,"over $75,000",Female,20
-2017,"less than $25,000",,26.7
-2017,"$25,000 - $50,000",,31.6
-2017,"$50,000 - $75,000",,17.5
-2017,"over $75,000",,23.8
-2017,"less than $25,000",Male,26.4
-2017,"$25,000 - $50,000",Male,31.6
-2017,"$50,000 - $75,000",Male,16.4
-2017,"over $75,000",Male,25.7
-2017,"less than $25,000",Female,27.4
-2017,"$25,000 - $50,000",Female,32.5
-2017,"$50,000 - $75,000",Female,19
-2017,"over $75,000",Female,21
\ No newline at end of file
+Year,Gender,Value
+2013,,31
+2013,Male,31.5
+2013,Female,30.5
+2014,,30.3
+2014,Male,30.1
+2014,Female,30.7
+2015,,28.8
+2015,Male,28.2
+2015,Female,29.6
+2016,,27
+2016,Male,26.7
+2016,Female,27.5
+2017,,23.3
+2017,Male,22.7
+2017,Female,24.2
+2018,,20.7
+2018,Male,19.7
+2018,Female,22
+2019,,19.2
+2019,Male,17.9
+2019,Female,20.9
\ No newline at end of file
diff --git a/data/indicator_10-4-2.csv b/data/indicator_10-4-2.csv
index ac74938..327bcfc 100644
--- a/data/indicator_10-4-2.csv
+++ b/data/indicator_10-4-2.csv
@@ -5,4 +5,5 @@ Year,Value
 2015,0.5305
 2016,0.5335
 2017,0.5226
-2018,0.5244
\ No newline at end of file
+2018,0.5244
+2019,0.5232
\ No newline at end of file
diff --git a/data/indicator_10-7-4.csv b/data/indicator_10-7-4.csv
index ee906e4..e7637ba 100644
--- a/data/indicator_10-7-4.csv
+++ b/data/indicator_10-7-4.csv
@@ -1,7 +1,36 @@
-Year,Group,Value
-2015,A,1
-2015,B,3
-2015,,2
-2016,A,1
-2016,B,3
-2016,,2
+Year,World Region of Origin,Units,Value
+2015,,Percent foreign born,37.4
+2015,Europe,Foreign born by region of birth (%),6.3
+2015,Asia,Foreign born by region of birth (%),29.6
+2015,Africa,Foreign born by region of birth (%),1.6
+2015,Oceania,Foreign born by region of birth (%),0.3
+2015,Latin America,Foreign born by region of birth (%),61.1
+2015,Northern America,Foreign born by region of birth (%),1
+2016,,Percent foreign born,37.7
+2016,Europe,Foreign born by region of birth (%),6.5
+2016,Asia,Foreign born by region of birth (%),29.9
+2016,Africa,Foreign born by region of birth (%),1.6
+2016,Oceania,Foreign born by region of birth (%),0.3
+2016,Latin America,Foreign born by region of birth (%),60.8
+2016,Northern America,Foreign born by region of birth (%),0.8
+2017,,Percent foreign born,36.9
+2017,Europe,Foreign born by region of birth (%),6.2
+2017,Asia,Foreign born by region of birth (%),29.9
+2017,Africa,Foreign born by region of birth (%),2
+2017,Oceania,Foreign born by region of birth (%),0.5
+2017,Latin America,Foreign born by region of birth (%),60.4
+2017,Northern America,Foreign born by region of birth (%),1.1
+2018,,Percent foreign born,37.2
+2018,Europe,Foreign born by region of birth (%),6.3
+2018,Asia,Foreign born by region of birth (%),29.4
+2018,Africa,Foreign born by region of birth (%),2.1
+2018,Oceania,Foreign born by region of birth (%),0.5
+2018,Latin America,Foreign born by region of birth (%),60.7
+2018,Northern America,Foreign born by region of birth (%),0.9
+2019,,Percent foreign born,36.4
+2019,Europe,Foreign born by region of birth (%),6.1
+2019,Asia,Foreign born by region of birth (%),30.6
+2019,Africa,Foreign born by region of birth (%),2.1
+2019,Oceania,Foreign born by region of birth (%),0.4
+2019,Latin America,Foreign born by region of birth (%),59.8
+2019,Northern America,Foreign born by region of birth (%),1
\ No newline at end of file
diff --git a/data/indicator_10-c-1.csv b/data/indicator_10-c-1.csv
new file mode 100644
index 0000000..9bb1a6e
--- /dev/null
+++ b/data/indicator_10-c-1.csv
@@ -0,0 +1,106 @@
+Year,Grade,Planet,Fruit,Value
+2010,,,,15.1591
+2011,,,,16.3583
+2012,,,,16.2244
+2013,,,,14.3392
+2014,,,,15.79
+2015,,,,14.0988
+2016,,,,15.5934
+2010,A,,,14.1695
+2010,B,,,16.1488
+2011,A,,,15.5065
+2011,B,,,17.2102
+2012,A,,,16.6152
+2012,B,,,15.8335
+2013,A,,,14.3857
+2013,B,,,14.2927
+2014,A,,,14.6857
+2014,B,,,16.8942
+2015,A,,,14.8525
+2015,B,,,13.3451
+2016,A,,,16.5992
+2016,B,,,14.5875
+2010,A,Mercury,,17.3458
+2010,A,Venus,,13.3825
+2010,A,Earth,,11.7802
+2010,B,Mercury,,16.4394
+2010,B,Venus,,16.5942
+2010,B,Earth,,15.4127
+2011,A,Mercury,,15.669
+2011,A,Venus,,16.9856
+2011,A,Earth,,13.8649
+2011,B,Mercury,,13.2586
+2011,B,Venus,,19.4585
+2011,B,Earth,,18.9134
+2012,A,Mercury,,16.2654
+2012,A,Venus,,18.3479
+2012,A,Earth,,15.2324
+2012,B,Mercury,,15.6618
+2012,B,Venus,,13.9548
+2012,B,Earth,,17.8839
+2013,A,Mercury,,11.8379
+2013,A,Venus,,16.8824
+2013,A,Earth,,14.4367
+2013,B,Mercury,,11.1883
+2013,B,Venus,,16.0526
+2013,B,Earth,,15.6371
+2014,A,Mercury,,16.2951
+2014,A,Venus,,10.9936
+2014,A,Earth,,16.7684
+2014,B,Mercury,,14.5468
+2014,B,Venus,,19.9637
+2014,B,Earth,,16.1722
+2015,A,Mercury,,13.309
+2015,A,Venus,,16.5238
+2015,A,Earth,,14.7246
+2015,B,Mercury,,11.8639
+2015,B,Venus,,14.424
+2015,B,Earth,,13.7473
+2016,A,Mercury,,16.5154
+2016,A,Venus,,14.8001
+2016,A,Earth,,18.4822
+2016,B,Mercury,,12.4133
+2016,B,Venus,,15.1595
+2016,B,Earth,,16.1897
+2010,,Mercury,,16.8926
+2010,,Venus,,14.9884
+2010,,Earth,,13.5965
+2011,,Mercury,,14.4638
+2011,,Venus,,18.222
+2011,,Earth,,16.3891
+2012,,Mercury,,15.9636
+2012,,Venus,,16.1514
+2012,,Earth,,16.5582
+2013,,Mercury,,11.5131
+2013,,Venus,,16.4675
+2013,,Earth,,15.0369
+2014,,Mercury,,15.4209
+2014,,Venus,,15.4786
+2014,,Earth,,16.4703
+2015,,Mercury,,12.5865
+2015,,Venus,,15.4739
+2015,,Earth,,14.236
+2016,,Mercury,,14.4644
+2016,,Venus,,14.9798
+2016,,Earth,,17.336
+2010,,,Apples,14.8497
+2010,,,Oranges,14.6733
+2010,,,Lemons,15.9544
+2011,,,Apples,13.4712
+2011,,,Oranges,18.2388
+2011,,,Lemons,17.365
+2012,,,Apples,16.4877
+2012,,,Oranges,16.0224
+2012,,,Lemons,16.163
+2013,,,Apples,14.3664
+2013,,,Oranges,13.5446
+2013,,,Lemons,15.1066
+2014,,,Apples,14.7726
+2014,,,Oranges,14.6493
+2014,,,Lemons,17.948
+2015,,,Apples,13.0809
+2015,,,Oranges,13.7446
+2015,,,Lemons,15.4709
+2016,,,Apples,13.7839
+2016,,,Oranges,15.0604
+2016,,,Lemons,17.9358
diff --git a/data/indicator_11-1-1.csv b/data/indicator_11-1-1.csv
index 262f052..199974c 100755
--- a/data/indicator_11-1-1.csv
+++ b/data/indicator_11-1-1.csv
@@ -130,4 +130,36 @@ Year,Sheltered/Unsheltered,Gender,Race/Ethnicity,Age,Sexual Orientation,Health/D
 2016,,,,,,physical disability,,Total by Health/ Disability,
 2016,,,,,,,,Total by DV/IPV,28464
 2016,,,,,,,Domestic/Intimate Partner Violence Experience,Total by DV/IPV,4938
-2016,,,,,,,Homeless Due to Fleeing Domestic/Intimate Partner,Total by DV/IPV,
\ No newline at end of file
+2016,,,,,,,Homeless Due to Fleeing Domestic/Intimate Partner,Total by DV/IPV,
+2020,,,,,,,,Percent of Total Population,1.04
+2020,,,,,,,,Total by Sheltered/Unsheltered,41290
+2020,sheltered,,,,,,,Total by Sheltered/Unsheltered,12438
+2020,unsheltered,,,,,,,Total by Sheltered/Unsheltered,28852
+2020,,,,,,,,Total by Gender,41290
+2020,,male,,,,,,Total by Gender,27790
+2020,,female,,,,,,Total by Gender,13330
+2020,,transgender,,,,,,Total by Gender,666
+2020,,gender non-conforming,,,,,,Total by Gender,170
+2020,,,,,,,,Total by Race/ Ethnicity,41290
+2020,,,American Indian/ Alaska Native,,,,,Total by Race/ Ethnicity,430
+2020,,,Asian,,,,,Total by Race/ Ethnicity,502
+2020,,,Black/ African American,,,,,Total by Race/ Ethnicity,15622
+2020,,,Hispanic/ Latino,,,,,Total by Race/ Ethnicity,13424
+2020,,,Native Hawaiian/ Other Pacific Islander,,,,,Total by Race/ Ethnicity,76
+2020,,,White,,,,,Total by Race/ Ethnicity,10293
+2020,,,Multi-Racial/Other,,,,,Total by Race/ Ethnicity,943
+2020,,,,,,,,Total by Age Group,41290
+2020,,,,under 18,,,,Total by Age Group,4923
+2020,,,,18-24,,,,Total by Age Group,2910
+2020,,,,25-54,,,,Total by Age Group,23479
+2020,,,,55-61,,,,Total by Age Group,5898
+2020,,,,62 and over,,,,Total by Age Group,4080
+2020,,,,,,,,Total by Health/ Disability,41290
+2020,,,,,,substance use disorder,,Total by Health/ Disability,10357
+2020,,,,,,HIV/AIDS,,Total by Health/ Disability,904
+2020,,,,,,serious mental illness,,Total by Health/ Disability,9123
+2020,,,,,,developmental disability,,Total by Health/ Disability,4064
+2020,,,,,,physical disability,,Total by Health/ Disability,6955
+2020,,,,,,,,Total by DV/IPV,41290
+2020,,,,,,,Domestic/Intimate Partner Violence Experience,Total by DV/IPV,11622
+2020,,,,,,,Homeless Due to Fleeing Domestic/Intimate Partner,Total by DV/IPV,2741
\ No newline at end of file
diff --git a/data/indicator_11-2-1.csv b/data/indicator_11-2-1.csv
index 92fc27b..35a2890 100644
--- a/data/indicator_11-2-1.csv
+++ b/data/indicator_11-2-1.csv
@@ -1 +1,19 @@
-Year,LA City,LA County,Method of Travel,Bus and Rail Ridership (County of LA),Units,Value2014,LA City,,Taxi,,Percentage (%),0.12013,LA City,,Taxi,,Percentage (%),0.12015,LA City,,Taxi,,Percentage (%),0.12016,LA City,,Taxi,,Percentage (%),0.22017,LA City,,Motorcycle,,Percentage (%),0.22015,LA City,,Motorcycle,,Percentage (%),0.22013,LA City,,Motorcycle,,Percentage (%),0.22016,LA City,,Motorcycle,,Percentage (%),0.32014,LA City,,Motorcycle,,Percentage (%),0.32017,LA City,,Taxi,,Percentage (%),0.32017,LA City,,Bicycle,,Percentage (%),0.92016,LA City,,Bicycle,,Percentage (%),1.12017,LA City,,Other,,Percentage (%),1.12015,LA City,,Bicycle,,Percentage (%),1.22013,LA City,,Bicycle,,Percentage (%),1.22014,LA City,,Bicycle,,Percentage (%),1.32014,LA City,,Other,,Percentage (%),1.32016,LA City,,Other,,Percentage (%),1.42015,LA City,,Other,,Percentage (%),1.42013,LA City,,Other,,Percentage (%),1.62017,LA City,,Walked,,Percentage (%),3.32014,LA City,,Walked,,Percentage (%),3.42016,LA City,,Walked,,Percentage (%),3.52013,LA City,,Walked,,Percentage (%),3.62015,LA City,,Walked,,Percentage (%),3.62013,LA City,,Worked At Home,,Percentage (%),5.42014,LA City,,Worked At Home,,Percentage (%),5.82015,LA City,,Worked At Home,,Percentage (%),5.92016,LA City,,Worked At Home,,Percentage (%),6.12017,LA City,,Worked At Home,,Percentage (%),6.32015,LA City,,Carpooled,,Percentage (%),8.32016,LA City,,Carpooled,,Percentage (%),8.72014,LA City,,Carpooled,,Percentage (%),8.92017,LA City,,Public Transit,,Percentage (%),8.92017,LA City,,Carpooled,,Percentage (%),9.12016,LA City,,Public Transit,,Percentage (%),9.22015,LA City,,Public Transit,,Percentage (%),9.52013,LA City,,Carpooled,,Percentage (%),9.92014,LA City,,Public Transit,,Percentage (%),10.62013,LA City,,Public Transit,,Percentage (%),10.82013,LA City,,Drove Alone,,Percentage (%),67.12014,LA City,,Drove Alone,,Percentage (%),68.32016,LA City,,Drove Alone,,Percentage (%),69.72015,LA City,,Drove Alone,,Percentage (%),69.72017,LA City,,Drove Alone,,Percentage (%),69.72013,,,,Bus (LA County),Number (Passenger Boardings),3633194982014,,,,Bus (LA County),Number (Passenger Boardings),3520581382015,,,,Bus (LA County),Number (Passenger Boardings),3339711872013,,,,Rail (LA County),Number (Passenger Boardings),1147900462014,,,,Rail (LA County),Number (Passenger Boardings),1125352602015,,,,Rail (LA County),Number (Passenger Boardings),1069746672016,,,,Bus (LA County),Number (Passenger Boardings),3041608572017,,,,Bus (LA County),Number (Passenger Boardings),2847082902018,,,,Bus (LA County),Number (Passenger Boardings),2757776612016,,,,Rail (LA County),Number (Passenger Boardings),1114584732017,,,,Rail (LA County),Number (Passenger Boardings),1127830752018,,,,Rail (LA County),Number (Passenger Boardings),1080175252017,,LA County,Worked At Home,,Percentage (%),5.62017,,LA County,Other,,Percentage (%),1.02017,,LA County,Walked,,Percentage (%),2.52017,,LA County,Bicycle,,Percentage (%),0.72017,,LA County,Motorcycle,,Percentage (%),0.22017,,LA County,Taxi,,Percentage (%),0.32017,,LA County,Public Transit,,Percentage (%),5.72017,,LA County,Carpooled,,Percentage (%),9.32017,,LA County,Drove Alone,,Percentage (%),74.62016,,LA County,Walked,,Percentage (%),2.82016,,LA County,Taxi,,Percentage (%),0.12016,,LA County,Other,,Percentage (%),1.12016,,LA County,Public Transit,,Percentage (%),6.02016,,LA County,Bicycle,,Percentage (%),0.82016,,LA County,Carpooled,,Percentage (%),9.62016,,LA County,Worked At Home,,Percentage (%),5.42016,,LA County,Drove Alone,,Percentage (%),73.92016,,LA County,Motorcycle,,Percentage (%),0.22015,,LA County,Motorcycle,,Percentage (%),0.32015,,LA County,Drove Alone,,Percentage (%),74.12015,,LA County,Worked At Home,,Percentage (%),5.42015,,LA County,Carpooled,,Percentage (%),9.12015,,LA County,Other,,Percentage (%),1.22015,,LA County,Public Transit,,Percentage (%),6.12015,,LA County,Walked,,Percentage (%),2.82015,,LA County,Taxi,,Percentage (%),0.12015,,LA County,Bicycle,,Percentage (%),1.02014,,LA County,Public Transit,,Percentage (%),6.92014,,LA County,Drove Alone,,Percentage (%),73.12014,,LA County,Bicycle,,Percentage (%),1.02014,,LA County,Taxi,,Percentage (%),0.02014,,LA County,Walked,,Percentage (%),2.72014,,LA County,Motorcycle,,Percentage (%),0.32014,,LA County,Other,,Percentage (%),1.12014,,LA County,Carpooled,,Percentage (%),9.72014,,LA County,Worked At Home,,Percentage (%),5.12013,,LA County,Taxi,,Percentage (%),0.12013,,LA County,Walked,,Percentage (%),2.82013,,LA County,Carpooled,,Percentage (%),10.02013,,LA County,Other,,Percentage (%),1.22013,,LA County,Motorcycle,,Percentage (%),0.22013,,LA County,Public Transit,,Percentage (%),6.92013,,LA County,Worked At Home,,Percentage (%),5.22013,,LA County,Bicycle,,Percentage (%),0.92013,,LA County,Drove Alone,,Percentage (%),72.7
\ No newline at end of file
+Year,Bus or Rail,Value
+2015,,440945854
+2015,Bus,333971187
+2015,Rail,106974667
+2016,,415619330
+2016,Bus,304160857
+2016,Rail,111458473
+2017,,397491365
+2017,Bus,284708290
+2017,Rail,112783075
+2018,,383795186
+2018,Bus,275777661
+2018,Rail,108017525
+2019,,370480743
+2019,Bus,277308845
+2019,Rail,93171898
+2020,,213090477
+2020,Bus,161171528
+2020,Rail,51918949
\ No newline at end of file
diff --git a/data/indicator_11-2-2.csv b/data/indicator_11-2-2.csv
new file mode 100644
index 0000000..b763c04
--- /dev/null
+++ b/data/indicator_11-2-2.csv
@@ -0,0 +1,31 @@
+Year,Means of transportation to work,Value
+2015,"car, truck, or van",78
+2015,public transportation,9.5
+2015,walking,3.6
+2015,bicycle,1.2
+2015,work from home,5.9
+2015,other,1.8
+2016,"car, truck, or van",78.3
+2016,public transportation,9.2
+2016,walking,3.5
+2016,bicycle,1.1
+2016,work from home,6.1
+2016,other,1.8
+2017,"car, truck, or van",78.8
+2017,public transportation,8.9
+2017,walking,3.3
+2017,bicycle,0.9
+2017,work from home,6.3
+2017,other,1.7
+2018,"car, truck, or van",78.4
+2018,public transportation,8.7
+2018,walking,3.5
+2018,bicycle,0.8
+2018,work from home,6.4
+2018,other,2.2
+2019,"car, truck, or van",78.6
+2019,public transportation,8.8
+2019,walking,3.4
+2019,bicycle,0.8
+2019,work from home,6.5
+2019,other,2
\ No newline at end of file
diff --git a/data/indicator_11-6-1.csv b/data/indicator_11-6-1.csv
index 9029836..7a0e24c 100644
--- a/data/indicator_11-6-1.csv
+++ b/data/indicator_11-6-1.csv
@@ -1 +1,7 @@
-Year,Solid Resource Type,Value2015,Bulky,82502015,Recycling,371602015,Refuse,1390642015,Yard Trimmings,684462016,Bulky,576852016,Recycling,2220352016,Refuse,8588892016,Yard Trimmings,4088442017,Bulky,647702017,Recycling,2193962017,Refuse,8796242017,Yard Trimmings,4306022018,Bulky,680542018,Recycling,2063902018,Refuse,8833302018,Yard Trimmings,412492
\ No newline at end of file
+Year,Value
+2015,100
+2016,100
+2017,100
+2018,100
+2019,100
+2020,100
\ No newline at end of file
diff --git a/data/indicator_11-6-2.csv b/data/indicator_11-6-2.csv
index 04b4688..bb63797 100755
--- a/data/indicator_11-6-2.csv
+++ b/data/indicator_11-6-2.csv
@@ -12,4 +12,6 @@ Year,Units,Value
 2018,Fine Particulates PM2.5,12.58
 2018,Suspended Particulates PM10,34.1
 2019,Fine Particulates PM2.5,10.85
-2019,Suspended Particulates PM10,25.5
\ No newline at end of file
+2019,Suspended Particulates PM10,25.5
+2020,Fine Particulates PM2.5,12.31
+2020,Suspended Particulates PM10,23
\ No newline at end of file
diff --git a/data/indicator_12-5-1.csv b/data/indicator_12-5-1.csv
index 611fa91..ebf2121 100644
--- a/data/indicator_12-5-1.csv
+++ b/data/indicator_12-5-1.csv
@@ -6,4 +6,8 @@ Year,Units,Value
 2017,Recycling tonnage,219396
 2017,Recycling rate,13.8
 2018,Recycling tonnage,206390
-2018,Recycling rate,13.1
\ No newline at end of file
+2018,Recycling rate,13.1
+2019,Recycling tonnage,210422
+2019,Recycling rate,13
+2020,Recycling tonnage,263459
+2020,Recycling rate,15
\ No newline at end of file
diff --git a/data/indicator_12-c-2.csv b/data/indicator_12-c-2.csv
new file mode 100644
index 0000000..0975f48
--- /dev/null
+++ b/data/indicator_12-c-2.csv
@@ -0,0 +1,15 @@
+Year,Fuel Type,Value
+2015,Gas,0.360
+2015,Diesel,0.13
+2016,Gas,0.278
+2016,Diesel,0.16
+2017,Gas,0.297
+2017,Diesel,0.16
+2018,Gas,0.417
+2018,Diesel,0.36
+2019,Gas,0.473
+2019,Diesel,0.36
+2020,Gas,0.505
+2020,Diesel,0.385
+2021,Gas,0.511
+2021,Diesel,0.389
\ No newline at end of file
diff --git a/data/indicator_16-1-4.csv b/data/indicator_16-1-4.csv
index e2473a4..8855b8e 100644
--- a/data/indicator_16-1-4.csv
+++ b/data/indicator_16-1-4.csv
@@ -1,7 +1,19 @@
-Year,Value
-2012,85.9
-2013,90.4
-2014,88.2
-2015,93.9
-2016,94.6
-2017,93.2
\ No newline at end of file
+Year,Gender,Value
+2015,,44.1
+2016,,44.2
+2017,,45.2
+2018,,43.7
+2019,,28.5
+2020,,30.3
+2015,Male,46.9
+2016,Male,48.7
+2017,Male,48.6
+2018,Male,47.3
+2019,Male,33
+2020,Male,33.5
+2015,Female,41.5
+2016,Female,39.8
+2017,Female,41.9
+2018,Female,40.3
+2019,Female,24.3
+2020,Female,27.2
\ No newline at end of file
diff --git a/data/indicator_2-1-2.csv b/data/indicator_2-1-2.csv
index 572bcd0..84fba72 100644
--- a/data/indicator_2-1-2.csv
+++ b/data/indicator_2-1-2.csv
@@ -1,32 +1,36 @@
 Year,Gender,Race,Value
-2013,,Asian,36.4
-2014,,Asian,33.8
-2015,,Asian,
-2016,,Asian,25.6
-2017,,Asian,
-2018,,Asian,21
-2019,,Asian,23
-2013,,African American,43
-2014,,African American,55.3
-2015,,African American,54.2
-2016,,African American,51.9
-2017,,African American,
-2018,,African American,36
-2019,,African American,51.6
-2013,,White,45.1
-2014,,White,26
-2015,,White,42
-2016,,White,41.4
-2017,,White,33.8
-2018,,White,38
-2019,,White,24.9
+2013,,Asian (non-Latino),36.4
+2014,,Asian (non-Latino),33.8
+2015,,Asian (non-Latino),26
+2016,,Asian (non-Latino),25.6
+2017,,Asian (non-Latino),16.8
+2018,,Asian (non-Latino),21
+2019,,Asian (non-Latino),23.7
+2020,,Asian (non-Latino),27.4
+2013,,Black of African American (non-Latino),43
+2014,,Black of African American (non-Latino),55.3
+2015,,Black of African American (non-Latino),54.2
+2016,,Black of African American (non-Latino),51.9
+2017,,Black of African American (non-Latino),59.6
+2018,,Black of African American (non-Latino),36
+2019,,Black of African American (non-Latino),51
+2020,,Black of African American (non-Latino),50.1
+2013,,White (non-Latino),45.1
+2014,,White (non-Latino),26
+2015,,White (non-Latino),42
+2016,,White (non-Latino),41.4
+2017,,White (non-Latino),33.8
+2018,,White (non-Latino),38
+2019,,White (non-Latino),24.4
+2020,,White (non-Latino),35
 2013,,Latino,49.5
 2014,,Latino,40.7
 2015,,Latino,47.1
 2016,,Latino,45.8
 2017,,Latino,42.2
 2018,,Latino,37.2
-2019,,Latino,45.7
+2019,,Latino,45.2
+2020,,Latino,38.8
 2013,,,46.7
 2013,Male,,48.2
 2013,Female,,45.3
@@ -43,4 +47,11 @@ Year,Gender,Race,Value
 2017,Male,,39.9
 2017,Female,,40.4
 2018,,,34.8
-2019,,,40.9
\ No newline at end of file
+2018,Male,,31.4
+2018,Female,,37.5
+2019,,,41
+2019,Male,,39.3
+2019,Female,,42.1
+2020,,,38.3
+2020,Male,,37.4
+2020,Female,,39
\ No newline at end of file
diff --git a/data/indicator_2-2-1.csv b/data/indicator_2-2-1.csv
index a55da28..b3e296d 100644
--- a/data/indicator_2-2-1.csv
+++ b/data/indicator_2-2-1.csv
@@ -2,4 +2,5 @@ Year,Value
 2009–2010,3.1
 2011-2012,3.5
 2013-2014,3.8
-2015-2016,2.3
\ No newline at end of file
+2015-2016,2.3
+2017-2018,3.4
\ No newline at end of file
diff --git a/data/indicator_2-2-2.csv b/data/indicator_2-2-2.csv
index da6bcd8..0bdaaf2 100644
--- a/data/indicator_2-2-2.csv
+++ b/data/indicator_2-2-2.csv
@@ -6,7 +6,9 @@ Year,Weight category,Units,Value
 2015,,under 5 overweight,9
 2016,,under 5 overweight,29.5
 2017,,under 5 overweight,12.4
-2018,,under 5 overweight,7.1
+2018,,under 5 overweight,
+2019,,under 5 overweight,12.2
+2020,,under 5 overweight,17.9
 2011,0 - 18.49 (Underweight),adult BMI,2
 2012,0 - 18.49 (Underweight),adult BMI,1.9
 2013,0 - 18.49 (Underweight),adult BMI,0.9
@@ -15,6 +17,8 @@ Year,Weight category,Units,Value
 2016,0 - 18.49 (Underweight),adult BMI,1.6
 2017,0 - 18.49 (Underweight),adult BMI,1.9
 2018,0 - 18.49 (Underweight),adult BMI,3.3
+2019,0 - 18.49 (Underweight),adult BMI,2.5
+2020,0 - 18.49 (Underweight),adult BMI,2.7
 2011,18.5 - 22.99 (Increasing but acceptable risk),adult BMI,21.6
 2012,18.5 - 22.99 (Increasing but acceptable risk),adult BMI,22.4
 2013,18.5 - 22.99 (Increasing but acceptable risk),adult BMI,21
@@ -23,6 +27,8 @@ Year,Weight category,Units,Value
 2016,18.5 - 22.99 (Increasing but acceptable risk),adult BMI,18.8
 2017,18.5 - 22.99 (Increasing but acceptable risk),adult BMI,21.7
 2018,18.5 - 22.99 (Increasing but acceptable risk),adult BMI,19.7
+2019,18.5 - 22.99 (Increasing but acceptable risk),adult BMI,20.4
+2020,18.5 - 22.99 (Increasing but acceptable risk),adult BMI,19.4
 2011,23.0 - 27.49 (Increased risk),adult BMI,35.4
 2012,23.0 - 27.49 (Increased risk),adult BMI,34.4
 2013,23.0 - 27.49 (Increased risk),adult BMI,37.6
@@ -31,6 +37,8 @@ Year,Weight category,Units,Value
 2016,23.0 - 27.49 (Increased risk),adult BMI,35.1
 2017,23.0 - 27.49 (Increased risk),adult BMI,35.6
 2018,23.0 - 27.49 (Increased risk),adult BMI,36.5
+2019,23.0 - 27.49 (Increased risk),adult BMI,35
+2020,23.0 - 27.49 (Increased risk),adult BMI,34
 2011,27.5 or higher (Higher high risk),adult BMI,41
 2012,27.5 or higher (Higher high risk),adult BMI,41.3
 2013,27.5 or higher (Higher high risk),adult BMI,40.5
@@ -38,4 +46,6 @@ Year,Weight category,Units,Value
 2015,27.5 or higher (Higher high risk),adult BMI,43.6
 2016,27.5 or higher (Higher high risk),adult BMI,44.5
 2017,27.5 or higher (Higher high risk),adult BMI,40.8
-2018,27.5 or higher (Higher high risk),adult BMI,40.6
\ No newline at end of file
+2018,27.5 or higher (Higher high risk),adult BMI,40.6
+2019,27.5 or higher (Higher high risk),adult BMI,42.1
+2020,27.5 or higher (Higher high risk),adult BMI,43.9
\ No newline at end of file
diff --git a/data/indicator_2-3-2.csv b/data/indicator_2-3-2.csv
index 43ad98b..1b44720 100644
--- a/data/indicator_2-3-2.csv
+++ b/data/indicator_2-3-2.csv
@@ -1,4 +1,10 @@
 Year,Gender,Value
+2019,,22525
+2019,Male,25476
+2019,Female,19522
+2018,,21511
+2018,Male,24037
+2018,Female,18658
 2017,,21239
 2017,Male,22396
 2017,Female,17955
diff --git a/data/indicator_3-1-2.csv b/data/indicator_3-1-2.csv
index b4e3d72..6262db7 100755
--- a/data/indicator_3-1-2.csv
+++ b/data/indicator_3-1-2.csv
@@ -1,51 +1,45 @@
-Year,Attendant Type,Payment Type,Value
-2012,,,131664
-2012,Doctor of Medicine(MD),,121547
-2012,Doctor of Osteopathy(DO),,2503
-2012,Certified Nurse Midwife(CNM),,6828
-2012,Other or Unknown,,786
-2013,,,128598
-2013,Doctor of Medicine(MD),,117340
-2013,Doctor of Osteopathy(DO),,3262
-2013,Certified Nurse Midwife(CNM),,7058
-2013,Other or Unknown,,938
-2014,,,130289
-2014,Doctor of Medicine(MD),,117817
-2014,Doctor of Osteopathy(DO),,3882
-2014,Certified Nurse Midwife(CNM),,7642
-2014,Other or Unknown,,948
-2015,,,124641
-2015,Doctor of Medicine(MD),,111750
-2015,Doctor of Osteopathy(DO),,4052
-2015,Certified Nurse Midwife(CNM),,7824
-2015,Other or Unknown,,1015
-2016,,,118512
-2016,Doctor of Medicine(MD),,109782
-2016,Certified Nurse Midwife(CNM),,7717
-2016,Other or Unknown,,1013
-2017,,,116950
-2017,Doctor of Medicine(MD),,102657
-2017,Doctor of Osteopathy(DO),,5098
-2017,Certified Nurse Midwife(CNM),,8128
-2017,Other or Unknown,,1067
-2018,,,110240
-2018,Doctor of Medicine(MD),,95179
-2018,Doctor of Medicine(MD),Medicaid,43332
-2018,Doctor of Medicine(MD),Private Insurance,42760
-2018,Doctor of Medicine(MD),Self-pay,4289
-2018,Doctor of Medicine(MD),Other or Unknown,4798
-2018,Doctor of Osteopathy(DO),,5694
-2018,Doctor of Osteopathy(DO),Medicaid,3145
-2018,Doctor of Osteopathy(DO),Private Insurance,2170
-2018,Doctor of Osteopathy(DO),Selfpay,297
-2018,Doctor of Osteopathy(DO),Other or Unknown,82
-2018,Certified Nurse Midwife(CNM),,8306
-2018,Certified Nurse Midwife(CNM),Medicaid,1680
-2018,Certified Nurse Midwife(CNM),Private Insurance,6365
-2018,Certified Nurse Midwife(CNM),Selfpay,207
-2018,Certified Nurse Midwife(CNM),Other or Unknown,54
-2018,Other or Unknown,,1061
-2018,Other or Unknown,Medicaid,310
-2018,Other or Unknown,Private Insurance,195
-2018,Other or Unknown,Self pay,527
-2018,Other or Unknown,Other,29
+Year,Attendant Type,Value
+2012,,131664
+2012,Doctor of Medicine(MD),121547
+2012,Doctor of Osteopathy(DO),2503
+2012,Certified Nurse Midwife(CNM),6828
+2012,Other or Unknown,786
+2013,,128598
+2013,Doctor of Medicine(MD),117340
+2013,Doctor of Osteopathy(DO),3262
+2013,Certified Nurse Midwife(CNM),7058
+2013,Other or Unknown,938
+2014,,130289
+2014,Doctor of Medicine(MD),117817
+2014,Doctor of Osteopathy(DO),3882
+2014,Certified Nurse Midwife(CNM),7642
+2014,Other or Unknown,948
+2015,,124641
+2015,Doctor of Medicine(MD),111750
+2015,Doctor of Osteopathy(DO),4052
+2015,Certified Nurse Midwife(CNM),7824
+2015,Other or Unknown,1015
+2016,,118512
+2016,Doctor of Medicine(MD),109782
+2016,Certified Nurse Midwife(CNM),7717
+2016,Other or Unknown,1013
+2017,,116950
+2017,Doctor of Medicine(MD),102657
+2017,Doctor of Osteopathy(DO),5098
+2017,Certified Nurse Midwife(CNM),8128
+2017,Other or Unknown,1067
+2018,,110271
+2018,Doctor of Medicine(MD),95179
+2018,Doctor of Osteopathy(DO),5700
+2018,Certified Nurse Midwife(CNM),8306
+2018,Other or Unknown,1086
+2019,,107231
+2019,Doctor of Medicine(MD),92161
+2019,Doctor of Osteopathy(DO),5859
+2019,Certified Nurse Midwife(CNM),8285
+2019,Other or Unknown,926
+2020,,98060
+2020,Doctor of Medicine(MD),82413
+2020,Doctor of Osteopathy(DO),6172
+2020,Certified Nurse Midwife(CNM),8421
+2020,Other or Unknown,1054
\ No newline at end of file
diff --git a/data/indicator_3-2-2.csv b/data/indicator_3-2-2.csv
index fbf2596..59d3a9f 100755
--- a/data/indicator_3-2-2.csv
+++ b/data/indicator_3-2-2.csv
@@ -1,43 +1,33 @@
-Year,Age of Infant,Units,Value
-2011,,Total Number of Deaths,193
-2011,1-6 days,Total Number of Deaths,103
-2011,7-27 days,Total Number of Deaths,90
-2011,,"Death Rate per 1,000",1.48
-2011,1-6 days,"Death Rate per 1,000",0.79
-2011,7-27 days,"Death Rate per 1,000",0.69
-2012,,Total Number of Deaths,187
-2012,1-6 days,Total Number of Deaths,93
-2012,7-27 days,Total Number of Deaths,94
-2012,,"Death Rate per 1,000",1.42
-2012,1-6 days,"Death Rate per 1,000",0.71
-2012,7-27 days,"Death Rate per 1,000",0.71
-2013,,Total Number of Deaths,153
-2013,1-6 days,Total Number of Deaths,92
-2013,7-27 days,Total Number of Deaths,61
-2013,,"Death Rate per 1,000",1.19
-2013,1-6 days,"Death Rate per 1,000",0.72
-2013,7-27 days,"Death Rate per 1,000",0.47
-2014,,Total Number of Deaths,162
-2014,1-6 days,Total Number of Deaths,81
-2014,7-27 days,Total Number of Deaths,81
-2014,,"Death Rate per 1,000",1.24
-2014,1-6 days,"Death Rate per 1,000",0.62
-2014,7-27 days,"Death Rate per 1,000",0.62
-2015,,Total Number of Deaths,162
-2015,1-6 days,Total Number of Deaths,80
-2015,7-27 days,Total Number of Deaths,82
-2015,,"Death Rate per 1,000",1.3
-2015,1-6 days,"Death Rate per 1,000",0.64
-2015,7-27 days,"Death Rate per 1,000",0.66
-2016,,Total Number of Deaths,162
-2016,1-6 days,Total Number of Deaths,88
-2016,7-27 days,Total Number of Deaths,74
-2016,,"Death Rate per 1,000",1.32
-2016,1-6 days,"Death Rate per 1,000",0.71
-2016,7-27 days,"Death Rate per 1,000",0.6
-2017,,Total Number of Deaths,132
-2017,1-6 days,Total Number of Deaths,69
-2017,7-27 days,Total Number of Deaths,63
-2017,,"Death Rate per 1,000",1.13
-2017,1-6 days,"Death Rate per 1,000",0.59
-2017,7-27 days,"Death Rate per 1,000",0.54
\ No newline at end of file
+Year,Mother's Race,Units,Value
+2015,,Total Deaths,510
+2015,Asian or Pacific Islander,Total Deaths,74
+2015,Black or African American,Total Deaths,93
+2015,White,Total Deaths,342
+2015,,"Death Rate per 1,000",4.09
+2015,Asian or Pacific Islander,"Death Rate per 1,000",3.57
+2015,Black or African American,"Death Rate per 1,000",9.40
+2015,White,"Death Rate per 1,000",3.65
+2016,,Total Deaths,529
+2016,Asian or Pacific Islander,Total Deaths,72
+2016,Black or African American,Total Deaths,89
+2016,White,Total Deaths,367
+2016,,"Death Rate per 1,000",4.30
+2016,Asian or Pacific Islander,"Death Rate per 1,000",3.33
+2016,Black or African American,"Death Rate per 1,000",8.76
+2016,White,"Death Rate per 1,000",4.04
+2017,,Total Deaths,469
+2017,Asian or Pacific Islander,Total Deaths,54
+2017,Black or African American,Total Deaths,80
+2017,White,Total Deaths,332
+2017,,"Death Rate per 1,000",4.01
+2017,Asian or Pacific Islander,"Death Rate per 1,000",2.66
+2017,Black or African American,"Death Rate per 1,000",8.18
+2017,White,"Death Rate per 1,000",3.84
+2018,,Total Deaths,443
+2018,Asian or Pacific Islander,Total Deaths,57
+2018,Black or African American,Total Deaths,81
+2018,White,Total Deaths,304
+2018,,"Death Rate per 1,000",4.02
+2018,Asian or Pacific Islander,"Death Rate per 1,000",3.15
+2018,Black or African American,"Death Rate per 1,000",8.76
+2018,White,"Death Rate per 1,000",3.68
\ No newline at end of file
diff --git a/data/indicator_3-4-1.csv b/data/indicator_3-4-1.csv
index a6424a1..7a2c20d 100644
--- a/data/indicator_3-4-1.csv
+++ b/data/indicator_3-4-1.csv
@@ -1,69 +1,43 @@
 Year,Cause of death,Units,Value
 2011,,Number of deaths,58356
-2011,,Rate per 1000 deaths,
 2011,respiratory disease,Number of deaths,5584
-2011,respiratory disease,Rate per 1000 deaths,95.6
 2011,circulatory disease,Number of deaths,21374
-2011,circulatory disease,Rate per 1000 deaths,366.2
 2011,cancer,Number of deaths,13939
-2011,cancer,Rate per 1000 deaths,238.8
 2011,diabetes mellitus,Number of deaths,2198
-2011,diabetes mellitus,Rate per 1000 deaths,37.6
 2012,,Number of deaths,58675
-2012,,Rate per 1000 deaths,
 2012,respiratory disease,Number of deaths,5328
-2012,respiratory disease,Rate per 1000 deaths,90.8
 2012,circulatory disease,Number of deaths,21275
-2012,circulatory disease,Rate per 1000 deaths,362.5
 2012,cancer,Number of deaths,14164
-2012,cancer,Rate per 1000 deaths,241.3
 2012,diabetes mellitus,Number of deaths,2211
-2012,diabetes mellitus,Rate per 1000 deaths,37.6
 2013,,Number of deaths,59883
-2013,,Rate per 1000 deaths,
 2013,respiratory disease,Number of deaths,5802
-2013,respiratory disease,Rate per 1000 deaths,96.8
 2013,circulatory disease,Number of deaths,21525
-2013,circulatory disease,Rate per 1000 deaths,359.4
 2013,cancer,Number of deaths,13888
-2013,cancer,Rate per 1000 deaths,231.9
 2013,diabetes mellitus,Number of deaths,2185
-2013,diabetes mellitus,Rate per 1000 deaths,36.4
 2014,,Number of deaths,58786
-2014,,Rate per 1000 deaths,
 2014,respiratory disease,Number of deaths,5398
-2014,respiratory disease,Rate per 1000 deaths,91.8
 2014,circulatory disease,Number of deaths,21911
-2014,circulatory disease,Rate per 1000 deaths,372.7
 2014,cancer,Number of deaths,14156
-2014,cancer,Rate per 1000 deaths,240.8
 2014,diabetes mellitus,Number of deaths,2302
-2014,diabetes mellitus,Rate per 1000 deaths,39.1
 2015,,Number of deaths,62408
-2015,,Rate per 1000 deaths,
 2015,respiratory disease,Number of deaths,5667
-2015,respiratory disease,Rate per 1000 deaths,90.8
 2015,circulatory disease,Number of deaths,22078
-2015,circulatory disease,Rate per 1000 deaths,353.7
 2015,cancer,Number of deaths,14523
-2015,cancer,Rate per 1000 deaths,5.6
 2015,diabetes mellitus,Number of deaths,2384
-2015,diabetes mellitus,Rate per 1000 deaths,38.2
 2016,,Number of deaths,63185
-2016,,Rate per 1000 deaths,
 2016,respiratory disease,Number of deaths,5805
-2016,respiratory disease,Rate per 1000 deaths,91.87
 2016,circulatory disease,Number of deaths,22349
-2016,circulatory disease,Rate per 1000 deaths,353.7
 2016,cancer,Number of deaths,14516
-2016,cancer,Rate per 1000 deaths,229.7
 2016,diabetes mellitus,Number of deaths,2491
-2016,diabetes mellitus,Rate per 1000 deaths,39.4
 2017,,Number of deaths,63792
-2017,,Rate per 1000 deaths,
 2017,respiratory disease,Number of deaths,5659
-2017,respiratory disease,Rate per 1000 deaths,88.7
 2017,circulatory disease,Number of deaths,22349
-2017,circulatory disease,Rate per 1000 deaths,350.3
 2017,diabetes mellitus,Number of deaths,2670
-2017,diabetes mellitus,Rate per 1000 deaths,41.8
\ No newline at end of file
+2018,,Number of deaths,31234
+2018,respiratory disease,Number of deaths,5887
+2018,circulatory disease,Number of deaths,22645
+2018,diabetes mellitus,Number of deaths,2702
+2019,,Number of deaths,30974
+2019,respiratory disease,Number of deaths,5366
+2019,circulatory disease,Number of deaths,22635
+2019,diabetes mellitus,Number of deaths,2973
\ No newline at end of file
diff --git a/data/indicator_3-4-3.csv b/data/indicator_3-4-3.csv
index 64ded0d..721ba89 100644
--- a/data/indicator_3-4-3.csv
+++ b/data/indicator_3-4-3.csv
@@ -1,14 +1,25 @@
-Year,Gender,Race/ Ethnicity,Education Attainment,Units,Value
-2018,,,,Percentage by Gender,50.8
-2018,Male,,,Percentage by Gender,51.3
-2018,Female,,,Percentage by Gender,50.2
-2018,,,,Percentage by Race/Ethnicity,50.8
-2018,,Latino,,Percentage by Race/Ethnicity,46
-2018,,White,,Percentage by Race/Ethnicity,55.2
-2018,,African American,,Percentage by Race/Ethnicity,59.4
-2018,,Asian,,Percentage by Race/Ethnicity,39.4
-2018,,,,Percentage by Education Attainment,50.8
-2018,,,Less than high school,Percentage by Education Attainment,47.6
-2018,,,High school,Percentage by Education Attainment,41.3
-2018,,,Some college or trade school,Percentage by Education Attainment,54.7
-2018,,,College or post graduate degree,Percentage by Education Attainment,56.7
\ No newline at end of file
+Year,Sexual Orientation,Value
+2019,,9.40
+2019,Heterosexual,7.80
+2019,"Gay, Lesbian or Bisexual",16.40
+2019,Not sure,18.80
+2017,,8.40
+2017,Heterosexual,6.50
+2017,"Gay, Lesbian or Bisexual",25.90
+2017,Not sure,17.60
+2015,,8.40
+2015,Heterosexual,6.10
+2015,"Gay, Lesbian or Bisexual",24.00
+2015,Not sure,31.00
+2013,,8.40
+2013,Heterosexual,6.30
+2013,"Gay, Lesbian or Bisexual",23.30
+2013,Not sure,22.20
+2011,,10.80
+2011,Heterosexual,8.50
+2011,"Gay, Lesbian or Bisexual",26.80
+2011,Not sure,28.20
+2009,,8.80
+2009,Heterosexual,7.80
+2009,"Gay, Lesbian or Bisexual",20.10
+2009,Not sure,13.80
\ No newline at end of file
diff --git a/data/indicator_3-4-4.csv b/data/indicator_3-4-4.csv
new file mode 100644
index 0000000..3e8d4b6
--- /dev/null
+++ b/data/indicator_3-4-4.csv
@@ -0,0 +1,14 @@
+Year,Gender,Race/ Ethnicity,Education Attainment,Units,Value
+2018,,,,Percentage by Gender,50.8
+2018,Male,,,Percentage by Gender,51.3
+2018,Female,,,Percentage by Gender,50.2
+2018,,,,Percentage by Race/Ethnicity,50.8
+2018,,Latino,,Percentage by Race/Ethnicity,46
+2018,,White,,Percentage by Race/Ethnicity,55.2
+2018,,African American,,Percentage by Race/Ethnicity,59.4
+2018,,Asian,,Percentage by Race/Ethnicity,39.4
+2018,,,,Percentage by Education Attainment,50.8
+2018,,,Less than high school,Percentage by Education Attainment,47.6
+2018,,,High school,Percentage by Education Attainment,41.3
+2018,,,Some college or trade school,Percentage by Education Attainment,54.7
+2018,,,College or post graduate degree,Percentage by Education Attainment,56.7
diff --git a/data/indicator_3-6-1.csv b/data/indicator_3-6-1.csv
index e4acb51..da63dd7 100755
--- a/data/indicator_3-6-1.csv
+++ b/data/indicator_3-6-1.csv
@@ -1,76 +1,56 @@
-Year,Victim Mode,Value
-2003,,242
-2004,,221
-2005,,203
-2006,,227
-2007,,211
-2008,,227
-2009,,181
-2010,,184
-2011,,157
-2012,,200
-2013,,201
-2014,,191
-2015,,183
-2016,,253
-2017,,245
-2003,Bicyclists,10
-2004,Bicyclists,10
-2005,Bicyclists,5
-2006,Bicyclists,11
-2007,Bicyclists,9
-2008,Bicyclists,9
-2009,Bicyclists,5
-2010,Bicyclists,10
-2011,Bicyclists,7
-2012,Bicyclists,9
-2013,Bicyclists,17
-2014,Bicyclists,6
-2015,Bicyclists,15
-2016,Bicyclists,21
-2017,Bicyclists,18
-2003,Motorcyclists,15
-2004,Motorcyclists,16
-2005,Motorcyclists,17
-2006,Motorcyclists,16
-2007,Motorcyclists,23
-2008,Motorcyclists,29
-2009,Motorcyclists,25
-2010,Motorcyclists,14
-2011,Motorcyclists,22
-2012,Motorcyclists,35
-2013,Motorcyclists,28
-2014,Motorcyclists,32
-2015,Motorcyclists,34
-2016,Motorcyclists,49
-2017,Motorcyclists,31
-2003,Vehicle Occupants,92
-2004,Vehicle Occupants,87
-2005,Vehicle Occupants,83
-2006,Vehicle Occupants,87
-2007,Vehicle Occupants,79
-2008,Vehicle Occupants,91
-2009,Vehicle Occupants,70
-2010,Vehicle Occupants,88
-2011,Vehicle Occupants,76
-2012,Vehicle Occupants,91
-2013,Vehicle Occupants,87
-2014,Vehicle Occupants,87
-2015,Vehicle Occupants,74
-2016,Vehicle Occupants,115
-2017,Vehicle Occupants,135
-2003,Pedestrians,125
-2004,Pedestrians,108
-2005,Pedestrians,98
-2006,Pedestrians,113
-2007,Pedestrians,100
-2008,Pedestrians,98
-2009,Pedestrians,81
-2010,Pedestrians,72
-2011,Pedestrians,52
-2012,Pedestrians,65
-2013,Pedestrians,69
-2014,Pedestrians,66
-2015,Pedestrians,60
-2016,Pedestrians,68
-2017,Pedestrians,61
\ No newline at end of file
+Year,Victim Mode,Race/ Ethnicity,Units,Value
+2012,,,City of Los Angeles,200
+2013,,,City of Los Angeles,201
+2014,,,City of Los Angeles,191
+2015,,,City of Los Angeles,183
+2016,,,City of Los Angeles,253
+2017,,,City of Los Angeles,245
+2012,Bicyclists,,City of Los Angeles,9
+2013,Bicyclists,,City of Los Angeles,17
+2014,Bicyclists,,City of Los Angeles,6
+2015,Bicyclists,,City of Los Angeles,15
+2016,Bicyclists,,City of Los Angeles,21
+2017,Bicyclists,,City of Los Angeles,18
+2012,Motorcyclists,,City of Los Angeles,35
+2013,Motorcyclists,,City of Los Angeles,28
+2014,Motorcyclists,,City of Los Angeles,32
+2015,Motorcyclists,,City of Los Angeles,34
+2016,Motorcyclists,,City of Los Angeles,49
+2017,Motorcyclists,,City of Los Angeles,31
+2012,Vehicle Occupants,,City of Los Angeles,91
+2013,Vehicle Occupants,,City of Los Angeles,87
+2014,Vehicle Occupants,,City of Los Angeles,87
+2015,Vehicle Occupants,,City of Los Angeles,74
+2016,Vehicle Occupants,,City of Los Angeles,115
+2017,Vehicle Occupants,,City of Los Angeles,135
+2012,Pedestrians,,City of Los Angeles,65
+2013,Pedestrians,,City of Los Angeles,69
+2014,Pedestrians,,City of Los Angeles,66
+2015,Pedestrians,,City of Los Angeles,60
+2016,Pedestrians,,City of Los Angeles,68
+2017,Pedestrians,,City of Los Angeles,61
+2015,,,Los Angeles County,806
+2015,,Hispanic or Latino,Los Angeles County,392
+2015,,Asian or Pacific Islander,Los Angeles County,65
+2015,,Black or African American,Los Angeles County,101
+2015,,White (not Hispanic or Latino),Los Angeles County,253
+2016,,,Los Angeles County,1025
+2016,,Hispanic or Latino,Los Angeles County,504
+2016,,Asian or Pacific Islander,Los Angeles County,101
+2016,,Black or African American,Los Angeles County,125
+2016,,White (not Hispanic or Latino),Los Angeles County,301
+2017,,,Los Angeles County,932
+2017,,Hispanic or Latino,Los Angeles County,435
+2017,,Asian or Pacific Islander,Los Angeles County,88
+2017,,Black or African American,Los Angeles County,154
+2017,,White (not Hispanic or Latino),Los Angeles County,255
+2018,,,Los Angeles County,936
+2018,,Hispanic or Latino,Los Angeles County,453
+2018,,Asian or Pacific Islander,Los Angeles County,80
+2018,,Black or African American,Los Angeles County,144
+2018,,White (not Hispanic or Latino),Los Angeles County,258
+2019,,,Los Angeles County,896
+2019,,Hispanic or Latino,Los Angeles County,448
+2019,,Asian or Pacific Islander,Los Angeles County,75
+2019,,Black or African American,Los Angeles County,134
+2019,,White (not Hispanic or Latino),Los Angeles County,238
\ No newline at end of file
diff --git a/data/indicator_3-7-1.csv b/data/indicator_3-7-1.csv
index a91ab99..a40ef0a 100644
--- a/data/indicator_3-7-1.csv
+++ b/data/indicator_3-7-1.csv
@@ -7,4 +7,13 @@ Year,Use of Birth Control,Value
 2016,No male sexual partner,5.6
 2017,Uses birth control to prevent pregnancy,62.4
 2017,Does not use birth control to prevent pregnancy,32.7
-2017,No male sexual partner,4.9
\ No newline at end of file
+2017,No male sexual partner,4.9
+2018,Uses birth control to prevent pregnancy,61.5
+2018,Does not use birth control to prevent pregnancy,31.5
+2018,No male sexual partner,7
+2019,Uses birth control to prevent pregnancy,58.4
+2019,Does not use birth control to prevent pregnancy,34.1
+2019,No male sexual partner,7.4
+2020,Uses birth control to prevent pregnancy,59.4
+2020,Does not use birth control to prevent pregnancy,32
+2020,No male sexual partner,8.6
\ No newline at end of file
diff --git a/data/indicator_3-7-2.csv b/data/indicator_3-7-2.csv
index 0a16acf..da71712 100644
--- a/data/indicator_3-7-2.csv
+++ b/data/indicator_3-7-2.csv
@@ -1,4 +1,10 @@
 Year,Mother Age Group,Value
+2020,,3003
+2020,Under 15,25
+2020,15 to 19,2978
+2019,,3664
+2019,Under 15,21
+2019,15 to 19,3643
 2018,,4091
 2018,Under 15,32
 2018,15 to 19,4059
diff --git a/data/indicator_3-9-3.csv b/data/indicator_3-9-3.csv
index 3064dba..71f5ed8 100644
--- a/data/indicator_3-9-3.csv
+++ b/data/indicator_3-9-3.csv
@@ -1,4 +1,8 @@
 Year,Units,Value
+2019,Deaths,1244
+2019,"Rate per 100,000",12.4
+2018,Deaths,970
+2018,"Rate per 100,000",9.6
 2017,Deaths,897
 2017,"Rate per 100,000",8.8
 2016,Deaths,807
diff --git a/data/indicator_3-9-4.csv b/data/indicator_3-9-4.csv
index cb07ef0..7d303da 100644
--- a/data/indicator_3-9-4.csv
+++ b/data/indicator_3-9-4.csv
@@ -1,21 +1,41 @@
-Year,Gender,Race/Ethnicity,Disability,Units,Value
-2018,,,,Percent by Gender,6.7
-2018,Male,,,Percent by Gender,4.9
-2018,Female,,,Percent by Gender,8.4
-2018,,,,Percent by Race/Ethnicity,6.7
-2018,,Latino,,Percent by Race/Ethnicity,5.1
-2018,,White,,Percent by Race/Ethnicity,7.8
-2018,,African American,,Percent by Race/Ethnicity,13.7
-2018,,Asian,,Percent by Race/Ethnicity,4.7
-2018,,,,Percent by Disability Status,6.7
-2018,,,Yes,Percent by Disability Status,12.6
-2018,,,No,Percent by Disability Status,4.7
-2015,,,,Percent by Gender,7.4
-2015,Male,,,Percent by Gender,5.5
-2015,Female,,,Percent by Gender,8.2
-2015,,,,Percent by Race/Ethnicity,7.4
-2015,,Latino,,Percent by Race/Ethnicity,6.4
-2015,,White,,Percent by Race/Ethnicity,6.1
-2015,,African American,,Percent by Race/Ethnicity,17.8
-2015,,Asian,,Percent by Race/Ethnicity,6.4
-2015,,,,Percent by Disability Status,7.4
+Year,Gender,Race/Ethnicity,Value
+2015,,,88.7
+2015,Male,,112.5
+2015,Female,,63.3
+2015,,Hispanic,50
+2015,,White,48.8
+2015,,African-American,277.5
+2015,,Asian/ Pacific Islander,28.3
+2015,,American Indian/ Alaskan Native,
+2016,,,88.5
+2016,Male,,112.3
+2016,Female,,63.6
+2016,,Hispanic,86.9
+2016,,White,45.5
+2016,,African-American,281
+2016,,Asian/ Pacific Islander,34.7
+2016,,American Indian/ Alaskan Native,65.2
+2017,,,82.5
+2017,Male,,103.6
+2017,Female,,60.4
+2017,,Hispanic,81.7
+2017,,White,41.3
+2017,,African-American,254.8
+2017,,Asian/ Pacific Islander,29
+2017,,American Indian/ Alaskan Native,
+2018,,,77.5
+2018,Male,,97.2
+2018,Female,,56.7
+2018,,Hispanic,77.9
+2018,,White,36.6
+2018,,African-American,238.8
+2018,,Asian/ Pacific Islander,29.1
+2018,,American Indian/ Alaskan Native,48.2
+2019,,,75.2
+2019,Male,,92.9
+2019,Female,,56.5
+2019,,Hispanic,76.6
+2019,,White,31.1
+2019,,African-American,228.3
+2019,,Asian/ Pacific Islander,25.1
+2019,,American Indian/ Alaskan Native,
\ No newline at end of file
diff --git a/data/indicator_3-a-1.csv b/data/indicator_3-a-1.csv
index 530653c..cc703ec 100755
--- a/data/indicator_3-a-1.csv
+++ b/data/indicator_3-a-1.csv
@@ -1,59 +1,49 @@
-Year,Gender,Race/ Ethnicity,Education Attainment,Age Group,Units,Unit,Value
-2018,,,,,By Gender,Current Smoker,11.2
-2018,Male,,,,By Gender,Current Smoker,14.6
-2018,Female,,,,By Gender,Current Smoker,8.1
-2018,,,,,By Race/Ethnicity,Current Smoker,11.2
-2018,,Latino,,,By Race/Ethnicity,Current Smoker,10.2
-2018,,White,,,By Race/Ethnicity,Current Smoker,12.2
-2018,,African American,,,By Race/Ethnicity,Current Smoker,17
-2018,,Asian,,,By Race/Ethnicity,Current Smoker,9.8
-2018,,Native Hawaiian and Other Pacific Islander,,,By Race/Ethnicity,Current Smoker,23.9
-2018,,American Indian/Alaska Native,,,By Race/Ethnicity,Current Smoker,23.2
-2018,,,,,By Education Attainment,Current Smoker,11.2
-2018,,,Less than high school,,By Education Attainment,Current Smoker,13.3
-2018,,,High school,,By Education Attainment,Current Smoker,13.5
-2018,,,Some college or trade school,,By Education Attainment,Current Smoker,13.4
-2018,,,College or post graduate degree,,By Education Attainment,Current Smoker,5.9
-2018,,,,,By Gender,Used an Electronic Cigarette in the Past Month,6.3
-2018,Male,,,,By Gender,Used an Electronic Cigarette in the Past Month,8.7
-2018,Female,,,,By Gender,Used an Electronic Cigarette in the Past Month,3.8
-2018,,,,,By Age Group,Used an Electronic Cigarette in the Past Month,6.3
-2018,,,,18-24,By Age Group,Used an Electronic Cigarette in the Past Month,15.7
-2018,,,,25-29,By Age Group,Used an Electronic Cigarette in the Past Month,10.8
-2018,,,,30-39,By Age Group,Used an Electronic Cigarette in the Past Month,8.1
-2018,,,,40-49,By Age Group,Used an Electronic Cigarette in the Past Month,5.5
-2018,,,,50-59,By Age Group,Used an Electronic Cigarette in the Past Month,2.6
-2018,,,,,By Education Attainment,Used an Electronic Cigarette in the Past Month,6.3
-2018,,,Less than high school,,By Education Attainment,Used an Electronic Cigarette in the Past Month,2.8
-2018,,,High school,,By Education Attainment,Used an Electronic Cigarette in the Past Month,9.4
-2018,,,Some college or trade school,,By Education Attainment,Used an Electronic Cigarette in the Past Month,7.9
-2018,,,College or post graduate degree,,By Education Attainment,Used an Electronic Cigarette in the Past Month,4.8
-2015,,,,,By Gender,Current Smoker,13.3
-2015,Male,,,,By Gender,Current Smoker,18.4
-2015,Female,,,,By Gender,Current Smoker,8.4
-2015,,,,,By Race/Ethnicity,Current Smoker,13.3
-2015,,Latino,,,By Race/Ethnicity,Current Smoker,12.3
-2015,,White,,,By Race/Ethnicity,Current Smoker,13.4
-2015,,African American,,,By Race/Ethnicity,Current Smoker,17.4
-2015,,Asian,,,By Race/Ethnicity,Current Smoker,13.1
-2015,,Native Hawaiian and Other Pacific Islander,,,By Race/Ethnicity,Current Smoker,26.2
-2015,,American Indian/Alaska Native,,,By Race/Ethnicity,Current Smoker,19.7
-2015,,,,,By Education Attainment,Current Smoker,13.3
-2015,,,Less than high school,,By Education Attainment,Current Smoker,15.6
-2015,,,High school,,By Education Attainment,Current Smoker,15.1
-2015,,,Some college or trade school,,By Education Attainment,Current Smoker,14.1
-2015,,,College or post graduate degree,,By Education Attainment,Current Smoker,9
-2015,,,,,By Gender,Used an Electronic Cigarette in the Past Month,3.5
-2015,Male,,,,By Gender,Used an Electronic Cigarette in the Past Month,4.8
-2015,Female,,,,By Gender,Used an Electronic Cigarette in the Past Month,2.2
-2015,,,,,By Age Group,Used an Electronic Cigarette in the Past Month,3.5
-2015,,,,18-24,By Age Group,Used an Electronic Cigarette in the Past Month,7.2
-2015,,,,25-29,By Age Group,Used an Electronic Cigarette in the Past Month,7.4
-2015,,,,30-39,By Age Group,Used an Electronic Cigarette in the Past Month,4
-2015,,,,40-49,By Age Group,Used an Electronic Cigarette in the Past Month,2.7
-2015,,,,50-59,By Age Group,Used an Electronic Cigarette in the Past Month,1.7
-2015,,,,,By Education Attainment,Used an Electronic Cigarette in the Past Month,3.5
-2015,,,Less than high school,,By Education Attainment,Used an Electronic Cigarette in the Past Month,1.5
-2015,,,High school,,By Education Attainment,Used an Electronic Cigarette in the Past Month,3.6
-2015,,,Some college or trade school,,By Education Attainment,Used an Electronic Cigarette in the Past Month,5.9
-2015,,,College or post graduate degree,,By Education Attainment,Used an Electronic Cigarette in the Past Month,2.3
\ No newline at end of file
+Year,Gender,Race/ Ethnicity,Units,Value
+2015,,,By Gender,12.2
+2015,Male,,By Gender,16.3
+2015,Female,,By Gender,8.3
+2015,,,By Race/Ethnicity,12.2
+2015,,Latino,By Race/Ethnicity,10.6
+2015,,White (non-latino),By Race/Ethnicity,13.2
+2015,,Black or African American (non-latino),By Race/Ethnicity,18.8
+2015,,Asian (non-latino),By Race/Ethnicity,10
+2016,,,By Gender,11.4
+2016,Male,,By Gender,16.3
+2016,Female,,By Gender,6.7
+2016,,,By Race/Ethnicity,11.4
+2016,,Latino,By Race/Ethnicity,10.9
+2016,,White (non-latino),By Race/Ethnicity,10.9
+2016,,Black or African American (non-latino),By Race/Ethnicity,22.5
+2016,,Asian (non-latino),By Race/Ethnicity,
+2017,,,By Gender,8.9
+2017,Male,,By Gender,12.8
+2017,Female,,By Gender,5.2
+2017,,,By Race/Ethnicity,8.9
+2017,,Latino,By Race/Ethnicity,8.4
+2017,,White (non-latino),By Race/Ethnicity,9.6
+2017,,Black or African American (non-latino),By Race/Ethnicity,15
+2017,,Asian (non-latino),By Race/Ethnicity,
+2018,,,By Gender,10.3
+2018,Male,,By Gender,14.2
+2018,Female,,By Gender,6.7
+2018,,,By Race/Ethnicity,10.3
+2018,,Latino,By Race/Ethnicity,9.8
+2018,,White (non-latino),By Race/Ethnicity,9.7
+2018,,Black or African American (non-latino),By Race/Ethnicity,14.3
+2018,,Asian (non-latino),By Race/Ethnicity,9.6
+2019,,,By Gender,6
+2019,Male,,By Gender,7.3
+2019,Female,,By Gender,4.8
+2019,,,By Race/Ethnicity,6
+2019,,Latino,By Race/Ethnicity,5.9
+2019,,White (non-latino),By Race/Ethnicity,6
+2019,,Black or African American (non-latino),By Race/Ethnicity,9.3
+2019,,Asian (non-latino),By Race/Ethnicity,3.9
+2020,,,By Gender,5.9
+2020,Male,,By Gender,8
+2020,Female,,By Gender,4
+2020,,,By Race/Ethnicity,5.9
+2020,,Latino,By Race/Ethnicity,5.2
+2020,,White (non-latino),By Race/Ethnicity,6.6
+2020,,Black or African American (non-latino),By Race/Ethnicity,8.2
+2020,,Asian (non-latino),By Race/Ethnicity,5.6
\ No newline at end of file
diff --git a/data/indicator_3-c-1.csv b/data/indicator_3-c-1.csv
index 2eada49..c464ee5 100755
--- a/data/indicator_3-c-1.csv
+++ b/data/indicator_3-c-1.csv
@@ -1,4 +1,5 @@
 Year,Units,Value
+2019,Total Physician and Surgeon Licenses,31328
 2018,Total Physician and Surgeon Licenses,30848
 2017,Total Physician and Surgeon Licenses,30659
 2016,Total Physician and Surgeon Licenses,30160
@@ -6,10 +7,11 @@ Year,Units,Value
 2014,Total Physician and Surgeon Licenses,29120
 2013,Total Physician and Surgeon Licenses,28672
 2012,Total Physician and Surgeon Licenses,28181
-2018,"Total Physician and Surgeon Licenses per 1,000 population",7.73
-2017,"Total Physician and Surgeon Licenses per 1,000 population",7.67
-2016,"Total Physician and Surgeon Licenses per 1,000 population",7.58
-2015,"Total Physician and Surgeon Licenses per 1,000 population",7.33
-2014,"Total Physician and Surgeon Licenses per 1,000 population",7.41
-2013,"Total Physician and Surgeon Licenses per 1,000 population",7.38
-2012,"Total Physician and Surgeon Licenses per 1,000 population",7.30
\ No newline at end of file
+2019,"Total Physician and Surgeon Licenses per 1,000 population",3.12
+2018,"Total Physician and Surgeon Licenses per 1,000 population",3.05
+2017,"Total Physician and Surgeon Licenses per 1,000 population",3.02
+2016,"Total Physician and Surgeon Licenses per 1,000 population",2.97
+2015,"Total Physician and Surgeon Licenses per 1,000 population",2.86
+2014,"Total Physician and Surgeon Licenses per 1,000 population",2.88
+2013,"Total Physician and Surgeon Licenses per 1,000 population",2.86
+2012,"Total Physician and Surgeon Licenses per 1,000 population",2.83
\ No newline at end of file
diff --git a/data/indicator_3-d-2.csv b/data/indicator_3-d-2.csv
new file mode 100644
index 0000000..9bb1a6e
--- /dev/null
+++ b/data/indicator_3-d-2.csv
@@ -0,0 +1,106 @@
+Year,Grade,Planet,Fruit,Value
+2010,,,,15.1591
+2011,,,,16.3583
+2012,,,,16.2244
+2013,,,,14.3392
+2014,,,,15.79
+2015,,,,14.0988
+2016,,,,15.5934
+2010,A,,,14.1695
+2010,B,,,16.1488
+2011,A,,,15.5065
+2011,B,,,17.2102
+2012,A,,,16.6152
+2012,B,,,15.8335
+2013,A,,,14.3857
+2013,B,,,14.2927
+2014,A,,,14.6857
+2014,B,,,16.8942
+2015,A,,,14.8525
+2015,B,,,13.3451
+2016,A,,,16.5992
+2016,B,,,14.5875
+2010,A,Mercury,,17.3458
+2010,A,Venus,,13.3825
+2010,A,Earth,,11.7802
+2010,B,Mercury,,16.4394
+2010,B,Venus,,16.5942
+2010,B,Earth,,15.4127
+2011,A,Mercury,,15.669
+2011,A,Venus,,16.9856
+2011,A,Earth,,13.8649
+2011,B,Mercury,,13.2586
+2011,B,Venus,,19.4585
+2011,B,Earth,,18.9134
+2012,A,Mercury,,16.2654
+2012,A,Venus,,18.3479
+2012,A,Earth,,15.2324
+2012,B,Mercury,,15.6618
+2012,B,Venus,,13.9548
+2012,B,Earth,,17.8839
+2013,A,Mercury,,11.8379
+2013,A,Venus,,16.8824
+2013,A,Earth,,14.4367
+2013,B,Mercury,,11.1883
+2013,B,Venus,,16.0526
+2013,B,Earth,,15.6371
+2014,A,Mercury,,16.2951
+2014,A,Venus,,10.9936
+2014,A,Earth,,16.7684
+2014,B,Mercury,,14.5468
+2014,B,Venus,,19.9637
+2014,B,Earth,,16.1722
+2015,A,Mercury,,13.309
+2015,A,Venus,,16.5238
+2015,A,Earth,,14.7246
+2015,B,Mercury,,11.8639
+2015,B,Venus,,14.424
+2015,B,Earth,,13.7473
+2016,A,Mercury,,16.5154
+2016,A,Venus,,14.8001
+2016,A,Earth,,18.4822
+2016,B,Mercury,,12.4133
+2016,B,Venus,,15.1595
+2016,B,Earth,,16.1897
+2010,,Mercury,,16.8926
+2010,,Venus,,14.9884
+2010,,Earth,,13.5965
+2011,,Mercury,,14.4638
+2011,,Venus,,18.222
+2011,,Earth,,16.3891
+2012,,Mercury,,15.9636
+2012,,Venus,,16.1514
+2012,,Earth,,16.5582
+2013,,Mercury,,11.5131
+2013,,Venus,,16.4675
+2013,,Earth,,15.0369
+2014,,Mercury,,15.4209
+2014,,Venus,,15.4786
+2014,,Earth,,16.4703
+2015,,Mercury,,12.5865
+2015,,Venus,,15.4739
+2015,,Earth,,14.236
+2016,,Mercury,,14.4644
+2016,,Venus,,14.9798
+2016,,Earth,,17.336
+2010,,,Apples,14.8497
+2010,,,Oranges,14.6733
+2010,,,Lemons,15.9544
+2011,,,Apples,13.4712
+2011,,,Oranges,18.2388
+2011,,,Lemons,17.365
+2012,,,Apples,16.4877
+2012,,,Oranges,16.0224
+2012,,,Lemons,16.163
+2013,,,Apples,14.3664
+2013,,,Oranges,13.5446
+2013,,,Lemons,15.1066
+2014,,,Apples,14.7726
+2014,,,Oranges,14.6493
+2014,,,Lemons,17.948
+2015,,,Apples,13.0809
+2015,,,Oranges,13.7446
+2015,,,Lemons,15.4709
+2016,,,Apples,13.7839
+2016,,,Oranges,15.0604
+2016,,,Lemons,17.9358
diff --git a/data/indicator_4-1-1.csv b/data/indicator_4-1-1.csv
index da167ea..7f97fb1 100644
--- a/data/indicator_4-1-1.csv
+++ b/data/indicator_4-1-1.csv
@@ -1,22 +1,56 @@
 Year,Grade Level,Gender,Poverty Level,Units,Value
-2016,Grade 3,,,Percentage by Grade,34.5
-2016,Grade 6,,,Percentage by Grade,36.3
-2016,Grade 11,,,Percentage by Grade,54.5
-2017,Grade 3,,,Percentage by Grade,36.4
-2017,Grade 6,,,Percentage by Grade,37.3
-2017,Grade 11,,,Percentage by Grade,54.6
-2018,Grade 3,,,Percentage by Grade,42.3
-2018,Grade 6,,,Percentage by Grade,39.5
-2018,Grade 11,,,Percentage by Grade,51
-2016,,Male,,Percentage by Gender,33.6
-2016,,Female,,Percentage by Gender,43.9
-2017,,Male,,Percentage by Gender,34.4
-2017,,Female,,Percentage by Gender,44.9
-2018,,Male,,Percentage by Gender,37
-2018,,Female,,Percentage by Gender,47.8
-2016,,,Economically Disadvantaged,Percentage by Poverty Level,32.9
-2016,,,Not Economically Disadvantaged,Percentage by Poverty Level,61.5
-2017,,,Economically Disadvantaged,Percentage by Poverty Level,34
-2017,,,Not Economically Disadvantaged,Percentage by Poverty Level,63.2
-2018,,,Economically Disadvantaged,Percentage by Poverty Level,36.5
-2018,,,Not Economically Disadvantaged,Percentage by Poverty Level,68.1
+2017,,,,English Language Arts,39.6
+2018,,,,English Language Arts,42.3
+2019,,,,English Language Arts,44.1
+2016,Grade 3,,,English Language Arts,34.5
+2016,Grade 6,,,English Language Arts,36.3
+2016,Grade 11,,,English Language Arts,54.5
+2017,Grade 3,,,English Language Arts,36.4
+2017,Grade 6,,,English Language Arts,37.3
+2017,Grade 11,,,English Language Arts,54.6
+2018,Grade 3,,,English Language Arts,42.3
+2018,Grade 6,,,English Language Arts,39.5
+2018,Grade 11,,,English Language Arts,51
+2019,Grade 3,,,English Language Arts,42.9
+2019,Grade 6,,,English Language Arts,42.8
+2019,Grade 11,,,English Language Arts,51.7
+2016,,Male,,English Language Arts,33.6
+2016,,Female,,English Language Arts,43.9
+2017,,Male,,English Language Arts,34.4
+2017,,Female,,English Language Arts,44.9
+2018,,Male,,English Language Arts,37
+2018,,Female,,English Language Arts,47.8
+2019,,Male,,English Language Arts,39.3
+2019,,Female,,English Language Arts,49.1
+2016,,,Economically Disadvantaged,English Language Arts,32.9
+2016,,,Not Economically Disadvantaged,English Language Arts,61.5
+2017,,,Economically Disadvantaged,English Language Arts,34
+2017,,,Not Economically Disadvantaged,English Language Arts,63.2
+2018,,,Economically Disadvantaged,English Language Arts,36.5
+2018,,,Not Economically Disadvantaged,English Language Arts,68.1
+2019,,,Economically Disadvantaged,English Language Arts,38.2
+2019,,,Not Economically Disadvantaged,English Language Arts,67.4
+2017,,,,Math,29.9
+2018,,,,Math,31.6
+2019,,,,Math,33.5
+2017,Grade 3,,,Math,40.3
+2017,Grade 6,,,Math,28.4
+2017,Grade 11,,,Math,23.9
+2018,Grade 3,,,Math,42.3
+2018,Grade 6,,,Math,30.2
+2018,Grade 11,,,Math,23.3
+2019,Grade 3,,,Math,44.4
+2019,Grade 6,,,Math,32.5
+2019,Grade 11,,,Math,25.4
+2017,,Male,,Math,29.8
+2017,,Female,,Math,29.9
+2018,,Male,,Math,31.6
+2018,,Female,,Math,31.6
+2019,,Male,,Math,33.7
+2019,,Female,,Math,33.3
+2017,,,Economically Disadvantaged,Math,24.5
+2017,,,Not Economically Disadvantaged,Math,52.3
+2018,,,Economically Disadvantaged,Math,25.8
+2018,,,Not Economically Disadvantaged,Math,57.2
+2019,,,Economically Disadvantaged,Math,27.6
+2019,,,Not Economically Disadvantaged,Math,56.5
\ No newline at end of file
diff --git a/data/indicator_4-2-1.csv b/data/indicator_4-2-1.csv
index a656d78..c552040 100644
--- a/data/indicator_4-2-1.csv
+++ b/data/indicator_4-2-1.csv
@@ -6,4 +6,6 @@ Year,Value
 2015,96.5
 2016,96.1
 2017,97.5
-2018,92.6
\ No newline at end of file
+2018,92.6
+2019,93.3
+2020,92.5
\ No newline at end of file
diff --git a/data/indicator_4-2-2.csv b/data/indicator_4-2-2.csv
index 06c5ea7..6b2f799 100755
--- a/data/indicator_4-2-2.csv
+++ b/data/indicator_4-2-2.csv
@@ -1,10 +1,12 @@
-Year,Value
-2009,55.7
-2010,56.6
-2011,57.4
-2012,56.3
-2013,56.2
-2014,55.5
-2015,55.6
-2016,55.9
-2017,56.9
+Year,Value
+2009,55.7
+2010,56.6
+2011,57.4
+2012,56.3
+2013,56.2
+2014,55.5
+2015,55.6
+2016,55.9
+2017,56.9
+2018,56.9
+2019,57.1
\ No newline at end of file
diff --git a/data/indicator_4-3-1.csv b/data/indicator_4-3-1.csv
index 9a4ccef..16e368a 100644
--- a/data/indicator_4-3-1.csv
+++ b/data/indicator_4-3-1.csv
@@ -1,31 +1,25 @@
 Year,Age Group,Value
+2019,15-17,97
+2019,18-19,80.4
+2019,20-24,48.5
+2018,15-17,97.1
+2018,18-19,79.7
+2018,20-24,48.6
 2017,15-17,97.1
 2017,18-19,79.7
 2017,20-24,48.6
-2017,25-34,13.6
-2017,35 and over,2.8
 2016,15-17,97.2
 2016,18-19,79.4
 2016,20-24,48.1
-2016,25-34,13.5
-2016,35 and over,2.9
 2015,15-17,97.3
 2015,18-19,78.8
 2015,20-24,47.5
-2015,25-34,13.7
-2015,35 and over,3
 2014,15-17,97
 2014,18-19,78.4
 2014,20-24,46.5
-2014,25-34,13.7
-2014,35 and over,3
 2013,15-17,96.7
 2013,18-19,77.5
 2013,20-24,46.2
-2013,25-34,13.7
-2013,35 and over,3.1
 2012,15-17,96.5
 2012,18-19,76.4
-2012,20-24,45
-2012,25-34,13.7
-2012,35 and over,3.3
\ No newline at end of file
+2012,20-24,45
\ No newline at end of file
diff --git a/data/indicator_4-a-2.csv b/data/indicator_4-a-2.csv
index 42b1c63..0b435a5 100644
--- a/data/indicator_4-a-2.csv
+++ b/data/indicator_4-a-2.csv
@@ -14,4 +14,6 @@ Year,Units,Value
 2018,safe on school grounds,85
 2018,safe in the neighborhood outside the school,79
 2019,safe on school grounds,64
-2019,safe in the neighborhood outside the school,61
\ No newline at end of file
+2019,safe in the neighborhood outside the school,61
+2020,safe on school grounds,60
+2020,safe in the neighborhood outside the school,58
\ No newline at end of file
diff --git a/data/indicator_4-b-2.csv b/data/indicator_4-b-2.csv
new file mode 100644
index 0000000..883c343
--- /dev/null
+++ b/data/indicator_4-b-2.csv
@@ -0,0 +1,13 @@
+Year,Gender,Value
+2017,,4067
+2017,Male,1896
+2017,Female,2170
+2018,,5416
+2018,Male,2594
+2018,Female,2821
+2019,,5884
+2019,Male,2766
+2019,Female,3117
+2020,,4622
+2020,Male,2069
+2020,Female,2544
\ No newline at end of file
diff --git a/data/indicator_4-c-1.csv b/data/indicator_4-c-1.csv
new file mode 100644
index 0000000..ee906e4
--- /dev/null
+++ b/data/indicator_4-c-1.csv
@@ -0,0 +1,7 @@
+Year,Group,Value
+2015,A,1
+2015,B,3
+2015,,2
+2016,A,1
+2016,B,3
+2016,,2
diff --git a/data/indicator_5-2-1.csv b/data/indicator_5-2-1.csv
index 9aa7039..532e2d7 100644
--- a/data/indicator_5-2-1.csv
+++ b/data/indicator_5-2-1.csv
@@ -1,10 +1,34 @@
-Year,Value
-2010,8548
-2011,8300
-2012,8457
-2013,8188
-2014,10165
-2015,11924
-2016,11811
-2017,11925
-2018,11735
\ No newline at end of file
+Year,Crime Type,Value
+2010,,10649
+2010,Intimate Partner - Aggravated Assault,232
+2010,Intimate Partner - Simple Assault,10417
+2011,,10285
+2011,Intimate Partner - Aggravated Assault,220
+2011,Intimate Partner - Simple Assault,10065
+2012,,10547
+2012,Intimate Partner - Aggravated Assault,263
+2012,Intimate Partner - Simple Assault,10284
+2013,,10237
+2013,Intimate Partner - Aggravated Assault,394
+2013,Intimate Partner - Simple Assault,9843
+2014,,12692
+2014,Intimate Partner - Aggravated Assault,1032
+2014,Intimate Partner - Simple Assault,11660
+2015,,14963
+2015,Intimate Partner - Aggravated Assault,2234
+2015,Intimate Partner - Simple Assault,12729
+2016,,14889
+2016,Intimate Partner - Aggravated Assault,2472
+2016,Intimate Partner - Simple Assault,12417
+2017,,15413
+2017,Intimate Partner - Aggravated Assault,2794
+2017,Intimate Partner - Simple Assault,12619
+2018,,15312
+2018,Intimate Partner - Aggravated Assault,2867
+2018,Intimate Partner - Simple Assault,12445
+2019,,15006
+2019,Intimate Partner - Aggravated Assault,2918
+2019,Intimate Partner - Simple Assault,12088
+2020,,13647
+2020,Intimate Partner - Aggravated Assault,2859
+2020,Intimate Partner - Simple Assault,10788
\ No newline at end of file
diff --git a/data/indicator_5-5-2.csv b/data/indicator_5-5-2.csv
index 43de08e..279a127 100755
--- a/data/indicator_5-5-2.csv
+++ b/data/indicator_5-5-2.csv
@@ -1,33 +1,9 @@
-Year,Gender,Units,Value
-2019,,Percent Female in Management Occupations,45.5
-2018,,Percent Female in Management Occupations,44.5
-2017,,Percent Female in Management Occupations,44.2
-2016,,Percent Female in Management Occupations,43.8
-2015,,Percent Female in Management Occupations,41.7
-2014,,Percent Female in Management Occupations,41.0
-2013,,Percent Female in Management Occupations,41.2
-2012,,Percent Female in Management Occupations,41.3
-2019,,(subindicator) Median Earnings,72359
-2019,Male,(subindicator) Median Earnings,80321
-2019,Female,(subindicator) Median Earnings,66552
-2018,,(subindicator) Median Earnings,71171
-2018,Male,(subindicator) Median Earnings,77251
-2018,Female,(subindicator) Median Earnings,62196
-2017,,(subindicator) Median Earnings,70407
-2017,Male,(subindicator) Median Earnings,80530
-2017,Female,(subindicator) Median Earnings,60076
-2016,,(subindicator) Median Earnings,65378
-2016,Male,(subindicator) Median Earnings,70024
-2016,Female,(subindicator) Median Earnings,61299
-2015,,(subindicator) Median Earnings,62353
-2015,Male,(subindicator) Median Earnings,67855
-2015,Female,(subindicator) Median Earnings,57486
-2014,,(subindicator) Median Earnings,61487
-2014,Male,(subindicator) Median Earnings,70225
-2014,Female,(subindicator) Median Earnings,55692
-2013,,(subindicator) Median Earnings,61927
-2013,Male,(subindicator) Median Earnings,66106
-2013,Female,(subindicator) Median Earnings,60395
-2012,,(subindicator) Median Earnings,58705
-2012,Male,(subindicator) Median Earnings,61260
-2012,Female,(subindicator) Median Earnings,52481
\ No newline at end of file
+Year,Value
+2019,45.5
+2018,44.5
+2017,44.2
+2016,43.8
+2015,41.7
+2014,41.0
+2013,41.2
+2012,41.3
\ No newline at end of file
diff --git a/data/indicator_5-5-2a.csv b/data/indicator_5-5-2a.csv
new file mode 100644
index 0000000..9e25518
--- /dev/null
+++ b/data/indicator_5-5-2a.csv
@@ -0,0 +1,25 @@
+Year,Gender,Value
+2019,,72359
+2019,Male,80321
+2019,Female,66552
+2018,,71171
+2018,Male,77251
+2018,Female,62196
+2017,,70407
+2017,Male,80530
+2017,Female,60076
+2016,,65378
+2016,Male,70024
+2016,Female,61299
+2015,,62353
+2015,Male,67855
+2015,Female,57486
+2014,,61487
+2014,Male,70225
+2014,Female,55692
+2013,,61927
+2013,Male,66106
+2013,Female,60395
+2012,,58705
+2012,Male,61260
+2012,Female,52481
\ No newline at end of file
diff --git a/data/indicator_5-6-1.csv b/data/indicator_5-6-1.csv
index ee906e4..a40ef0a 100644
--- a/data/indicator_5-6-1.csv
+++ b/data/indicator_5-6-1.csv
@@ -1,7 +1,19 @@
-Year,Group,Value
-2015,A,1
-2015,B,3
-2015,,2
-2016,A,1
-2016,B,3
-2016,,2
+Year,Use of Birth Control,Value
+2015,Uses birth control to prevent pregnancy,46.7
+2015,Does not use birth control to prevent pregnancy,48.4
+2015,No male sexual partner,4.9
+2016,Uses birth control to prevent pregnancy,47.1
+2016,Does not use birth control to prevent pregnancy,47.3
+2016,No male sexual partner,5.6
+2017,Uses birth control to prevent pregnancy,62.4
+2017,Does not use birth control to prevent pregnancy,32.7
+2017,No male sexual partner,4.9
+2018,Uses birth control to prevent pregnancy,61.5
+2018,Does not use birth control to prevent pregnancy,31.5
+2018,No male sexual partner,7
+2019,Uses birth control to prevent pregnancy,58.4
+2019,Does not use birth control to prevent pregnancy,34.1
+2019,No male sexual partner,7.4
+2020,Uses birth control to prevent pregnancy,59.4
+2020,Does not use birth control to prevent pregnancy,32
+2020,No male sexual partner,8.6
\ No newline at end of file
diff --git a/data/indicator_6-2-1.csv b/data/indicator_6-2-1.csv
index 0d2db5c..3b6a51e 100644
--- a/data/indicator_6-2-1.csv
+++ b/data/indicator_6-2-1.csv
@@ -1,4 +1,5 @@
 Year,Value
+2019,99.6
 2018,99.4
 2017,99.4
 2016,99.3
diff --git a/data/indicator_6-4-1.csv b/data/indicator_6-4-1.csv
index f47922f..908f74d 100644
--- a/data/indicator_6-4-1.csv
+++ b/data/indicator_6-4-1.csv
@@ -1,8 +1,14 @@
 Year,Sector,Units,Value
+2020,,average daily use per capita (gallons),106
+2019,,average daily use per capita (gallons),105
 2018,,average daily use per capita (gallons),112
 2017,,average daily use per capita (gallons),104
 2016,,average daily use per capita (gallons),113
 2015,,average daily use per capita (gallons),131
+2020,residential,million GPD by sector,283
+2020,commercial/ industrial/ institutional,million GPD by sector,121
+2019,residential,million GPD by sector,275
+2019,commercial/ industrial/ institutional,million GPD by sector,126
 2018,residential,million GPD by sector,289
 2018,commercial/ industrial/ institutional,million GPD by sector,132
 2017,residential,million GPD by sector,275
diff --git a/data/indicator_6-4-2.csv b/data/indicator_6-4-2.csv
index 2cdf7f9..9ba2129 100644
--- a/data/indicator_6-4-2.csv
+++ b/data/indicator_6-4-2.csv
@@ -1,4 +1,14 @@
 Year,By Source,Value
+2020,L.A. aqueduct,48
+2020,purchased water - Bay Delta,35
+2020,purchased water - Colorado River,6
+2020,groundwater,9
+2020,recycled water,2
+2019,L.A. aqueduct,38
+2019,purchased water - Bay Delta,41
+2019,purchased water - Colorado River,8
+2019,groundwater,11
+2019,recycled water,2
 2018,L.A. aqueduct,27
 2018,purchased water - Bay Delta,50
 2018,purchased water - Colorado River,9
diff --git a/data/indicator_7-1-2.csv b/data/indicator_7-1-2.csv
index c63e1a7..cf149c2 100755
--- a/data/indicator_7-1-2.csv
+++ b/data/indicator_7-1-2.csv
@@ -1,65 +1,58 @@
-Year,Fuel Type,Value
-2010,Utility Gas,67.5
-2010,Bottled Gas,0.8
-2010,Electricity,25.3
-2010,Fuel oil,0.1
-2010,Wood,0.2
-2010,Solar,0.1
-2010,Other,0.1
-2010,No Fuel Used,6
-2011,Utility Gas,66.8
-2011,Bottled Gas,0.8
-2011,Electricity,26.1
-2011,Fuel oil,0.1
-2011,Wood,0.2
-2011,Solar,0
-2011,Other,0.1
-2011,No Fuel Used,5.9
-2012,Utility Gas,66
-2012,Bottled Gas,0.8
-2012,Electricity,27
-2012,Fuel oil,0.1
-2012,Wood,0.2
-2012,Solar,0.1
-2012,Other,0.1
-2012,No Fuel Used,5.8
-2013,Utility Gas,65
-2013,Bottled Gas,0.9
-2013,Electricity,28.1
-2013,Fuel oil,0.1
-2013,Wood,0.1
-2013,Solar,0.1
-2013,Other,0.1
-2013,No Fuel Used,5.7
-2014,Utility Gas,64.1
-2014,Bottled Gas,0.9
-2014,Electricity,28.6
-2014,Fuel oil,0.1
-2014,Wood,0.1
-2014,Solar,0.1
-2014,Other,0.1
-2014,No Fuel Used,5.9
-2015,Utility Gas,62.9
-2015,Bottled Gas,0.9
-2015,Electricity,29.6
-2015,Fuel oil,0.1
-2015,Wood,0.1
-2015,Solar,0.1
-2015,Other,0.1
-2015,No Fuel Used,6.2
-2016,Utility Gas,62.3
-2016,Bottled Gas,1
-2016,Electricity,29.7
-2016,Fuel oil,0.1
-2016,Wood,0.1
-2016,Solar,0.1
-2016,Other,0.1
-2016,No Fuel Used,6.5
-2017,Utility Gas,61.8
-2017,Bottled Gas,1
-2017,Electricity,29.9
-2017,Fuel oil,0.1
-2017,Wood,0.1
-2017,Solar,0.2
-2017,Other,0.1
-2017,No Fuel Used,6.8
\ No newline at end of file
+Year,Fuel Type,Units,Value
+2012,No Fuel Used,By Heating Fuel Type,5.8
+2013,Utility Gas,By Heating Fuel Type,65
+2013,Bottled Gas,By Heating Fuel Type,0.9
+2013,Electricity,By Heating Fuel Type,28.1
+2013,Fuel oil,By Heating Fuel Type,0.1
+2013,Wood,By Heating Fuel Type,0.1
+2013,Solar,By Heating Fuel Type,0.1
+2013,Other,By Heating Fuel Type,0.1
+2013,No Fuel Used,By Heating Fuel Type,5.7
+2014,Utility Gas,By Heating Fuel Type,64.1
+2014,Bottled Gas,By Heating Fuel Type,0.9
+2014,Electricity,By Heating Fuel Type,28.6
+2014,Fuel oil,By Heating Fuel Type,0.1
+2014,Wood,By Heating Fuel Type,0.1
+2014,Solar,By Heating Fuel Type,0.1
+2014,Other,By Heating Fuel Type,0.1
+2014,No Fuel Used,By Heating Fuel Type,5.9
+2015,Utility Gas,By Heating Fuel Type,62.9
+2015,Bottled Gas,By Heating Fuel Type,0.9
+2015,Electricity,By Heating Fuel Type,29.6
+2015,Fuel oil,By Heating Fuel Type,0.1
+2015,Wood,By Heating Fuel Type,0.1
+2015,Solar,By Heating Fuel Type,0.1
+2015,Other,By Heating Fuel Type,0.1
+2015,No Fuel Used,By Heating Fuel Type,6.2
+2016,Utility Gas,By Heating Fuel Type,62.3
+2016,Bottled Gas,By Heating Fuel Type,1
+2016,Electricity,By Heating Fuel Type,29.7
+2016,Fuel oil,By Heating Fuel Type,0.1
+2016,Wood,By Heating Fuel Type,0.1
+2016,Solar,By Heating Fuel Type,0.1
+2016,Other,By Heating Fuel Type,0.1
+2016,No Fuel Used,By Heating Fuel Type,6.5
+2017,Utility Gas,By Heating Fuel Type,61.8
+2017,Bottled Gas,By Heating Fuel Type,1
+2017,Electricity,By Heating Fuel Type,29.9
+2017,Fuel oil,By Heating Fuel Type,0.1
+2017,Wood,By Heating Fuel Type,0.1
+2017,Solar,By Heating Fuel Type,0.2
+2017,Other,By Heating Fuel Type,0.1
+2017,No Fuel Used,By Heating Fuel Type,6.8
+2018,Utility Gas,By Heating Fuel Type,61.4
+2018,Bottled Gas,By Heating Fuel Type,1.1
+2018,Electricity,By Heating Fuel Type,29.9
+2018,Fuel oil,By Heating Fuel Type,0.1
+2018,Wood,By Heating Fuel Type,0.1
+2018,Solar,By Heating Fuel Type,0.2
+2018,Other,By Heating Fuel Type,0.1
+2018,No Fuel Used,By Heating Fuel Type,7.2
+2019,Utility Gas,By Heating Fuel Type,60.7
+2019,Bottled Gas,By Heating Fuel Type,1.1
+2019,Electricity,By Heating Fuel Type,30.4
+2019,Fuel oil,By Heating Fuel Type,0.1
+2019,Wood,By Heating Fuel Type,0.1
+2019,Solar,By Heating Fuel Type,0.3
+2019,Other,By Heating Fuel Type,0.1
+2019,No Fuel Used,By Heating Fuel Type,7.3
\ No newline at end of file
diff --git a/data/indicator_7-2-1.csv b/data/indicator_7-2-1.csv
index 64289cd..dc2238d 100755
--- a/data/indicator_7-2-1.csv
+++ b/data/indicator_7-2-1.csv
@@ -18,4 +18,19 @@ Year,Energy Source,Value
 2017,Coal,18
 2017,Large Hydroelectric,4
 2017,Natural Gas,31
-2017,Nuclear,10
\ No newline at end of file
+2017,Nuclear,10
+2018,Renewable,32
+2018,Coal,18
+2018,Large Hydroelectric,3
+2018,Natural Gas,30
+2018,Nuclear,10
+2019,Renewable,34
+2019,Coal,21
+2019,Large Hydroelectric,4
+2019,Natural Gas,27
+2019,Nuclear,14
+2020,Renewable,37
+2020,Coal,21
+2020,Large Hydroelectric,4
+2020,Natural Gas,24
+2020,Nuclear,14
\ No newline at end of file
diff --git a/data/indicator_7-3-1.csv b/data/indicator_7-3-1.csv
index 41d6eae..ce646fb 100755
--- a/data/indicator_7-3-1.csv
+++ b/data/indicator_7-3-1.csv
@@ -1,88 +1,94 @@
-Year,"Residential, Non-Residential",Value
-1990,,64746.17602
-1991,,62713.13433
-1992,,63272.19404
-1993,,62199.03509
-1994,,62779.74459
-1995,,62464.10018
-1996,,64178.80708
-1997,,65862.29617
-1998,,65704.4068
-1999,,66711.395
-2000,,69442.15761
-2001,,69743.63613
-2002,,67711.41408
-2003,,68515.73422
-2004,,69214.89469
-2005,,69993.61007
-2006,,70939.03277
-2007,,71264.11872
-2008,,72094.82404
-2009,,69965.43464
-2010,,68272.30209
-2011,,68209.2133
-2012,,69274.86658
-2013,,68366.42789
-2014,,69946.07105
-2015,,69690.51091
-2016,,68779.25003
-2017,,68800.94671
-2018,,67856.28125
-1990,Residential,16960.72006
-1991,Residential,16310.88407
-1992,Residential,16377.79499
-1993,Residential,15759.08304
-1994,Residential,16065.5834
-1995,Residential,16823.63593
-1996,Residential,16322.05687
-1997,Residential,17578.67224
-1998,Residential,17234.64818
-1999,Residential,17665.18361
-2000,Residential,18891.73387
-2001,Residential,18212.69867
-2002,Residential,17917.92881
-2003,Residential,19056.85228
-2004,Residential,19507.88669
-2005,Residential,19711.89407
-2006,Residential,20378.138
-2007,Residential,20537.01783
-2008,Residential,21118.10089
-2009,Residential,20594.68006
-2010,Residential,19726.42373
-2011,Residential,20069.35877
-2012,Residential,21082.23629
-2013,Residential,20620.15513
-2014,Residential,20752.65642
-2015,Residential,19998.14919
-2016,Residential,20019.33349
-2017,Residential,20711.25885
-2018,Residential,20589.17311
-1990,Non-Residential,47785.45597
-1991,Non-Residential,46402.25026
-1992,Non-Residential,46894.39905
-1993,Non-Residential,46439.95205
-1994,Non-Residential,46714.1612
-1995,Non-Residential,45640.46425
-1996,Non-Residential,47856.75021
-1997,Non-Residential,48283.62392
-1998,Non-Residential,48469.75862
-1999,Non-Residential,49046.21139
-2000,Non-Residential,50550.42374
-2001,Non-Residential,51530.93746
-2002,Non-Residential,49793.48527
-2003,Non-Residential,49458.88193
-2004,Non-Residential,49707.008
-2005,Non-Residential,50281.71599
-2006,Non-Residential,50560.89477
-2007,Non-Residential,50727.1009
-2008,Non-Residential,50976.72315
-2009,Non-Residential,49370.75458
-2010,Non-Residential,48545.87837
-2011,Non-Residential,48139.85453
-2012,Non-Residential,48192.63029
-2013,Non-Residential,47746.27276
-2014,Non-Residential,49193.41462
-2015,Non-Residential,49692.36172
-2016,Non-Residential,48759.91654
-2017,Non-Residential,48089.68786
-2018,Non-Residential,47267.10814
+Year,"Residential, Non-Residential",Value
+1990,,64746.17602
+1991,,62713.13433
+1992,,63272.19404
+1993,,62199.03509
+1994,,62779.74459
+1995,,62464.10018
+1996,,64178.80708
+1997,,65862.29617
+1998,,65704.4068
+1999,,66711.395
+2000,,69442.15761
+2001,,69743.63613
+2002,,67711.41408
+2003,,68515.73422
+2004,,69214.89469
+2005,,69993.61007
+2006,,70939.03277
+2007,,71264.11872
+2008,,72094.82404
+2009,,69965.43464
+2010,,68272.30209
+2011,,68209.2133
+2012,,69274.86658
+2013,,68366.42789
+2014,,69946.07105
+2015,,69690.51091
+2016,,68779.25003
+2017,,68800.94671
+2018,,67856.28125
+2019,,66805.01
+2020,,65649.87
+1990,Residential,16960.72006
+1991,Residential,16310.88407
+1992,Residential,16377.79499
+1993,Residential,15759.08304
+1994,Residential,16065.5834
+1995,Residential,16823.63593
+1996,Residential,16322.05687
+1997,Residential,17578.67224
+1998,Residential,17234.64818
+1999,Residential,17665.18361
+2000,Residential,18891.73387
+2001,Residential,18212.69867
+2002,Residential,17917.92881
+2003,Residential,19056.85228
+2004,Residential,19507.88669
+2005,Residential,19711.89407
+2006,Residential,20378.138
+2007,Residential,20537.01783
+2008,Residential,21118.10089
+2009,Residential,20594.68006
+2010,Residential,19726.42373
+2011,Residential,20069.35877
+2012,Residential,21082.23629
+2013,Residential,20620.15513
+2014,Residential,20752.65642
+2015,Residential,19998.14919
+2016,Residential,20019.33349
+2017,Residential,20711.25885
+2018,Residential,20589.17311
+2019,Residential,20699.46
+2020,Residential,22913.10
+1990,Non-Residential,47785.45597
+1991,Non-Residential,46402.25026
+1992,Non-Residential,46894.39905
+1993,Non-Residential,46439.95205
+1994,Non-Residential,46714.1612
+1995,Non-Residential,45640.46425
+1996,Non-Residential,47856.75021
+1997,Non-Residential,48283.62392
+1998,Non-Residential,48469.75862
+1999,Non-Residential,49046.21139
+2000,Non-Residential,50550.42374
+2001,Non-Residential,51530.93746
+2002,Non-Residential,49793.48527
+2003,Non-Residential,49458.88193
+2004,Non-Residential,49707.008
+2005,Non-Residential,50281.71599
+2006,Non-Residential,50560.89477
+2007,Non-Residential,50727.1009
+2008,Non-Residential,50976.72315
+2009,Non-Residential,49370.75458
+2010,Non-Residential,48545.87837
+2011,Non-Residential,48139.85453
+2012,Non-Residential,48192.63029
+2013,Non-Residential,47746.27276
+2014,Non-Residential,49193.41462
+2015,Non-Residential,49692.36172
+2016,Non-Residential,48759.91654
+2017,Non-Residential,48089.68786
+2018,Non-Residential,47267.10814
+2019,Non-Residential,46105.55
+2020,Non-Residential,42736.77
\ No newline at end of file
diff --git a/data/indicator_7-b-2.csv b/data/indicator_7-b-2.csv
new file mode 100644
index 0000000..ebcd24b
--- /dev/null
+++ b/data/indicator_7-b-2.csv
@@ -0,0 +1,11 @@
+Year,Value
+2012,95
+2013,149
+2014,267
+2015,417
+2016,644
+2017,936
+2018,1390
+2019,2139
+2020,9224
+2021,11083
\ No newline at end of file
diff --git a/data/indicator_8-1-1.csv b/data/indicator_8-1-1.csv
index 25e0493..7cde7c9 100755
--- a/data/indicator_8-1-1.csv
+++ b/data/indicator_8-1-1.csv
@@ -1,17 +1,15 @@
 Year,Units,Value
-2010,Per capita real GDP growth rate,1.2
-2011,Per capita real GDP growth rate,0
-2012,Per capita real GDP growth rate,2
-2013,Per capita real GDP growth rate,1.2
-2014,Per capita real GDP growth rate,3.2
-2015,Per capita real GDP growth rate,4.5
-2016,Per capita real GDP growth rate,1
-2017,Per capita real GDP growth rate,2.6
-2010,GDP in millions of current dollars,763976
-2011,GDP in millions of current dollars,782565
-2012,GDP in millions of current dollars,820863
-2013,GDP in millions of current dollars,852034
-2014,GDP in millions of current dollars,901980
-2015,GDP in millions of current dollars,967100
-2016,GDP in millions of current dollars,996432
-2017,GDP in millions of current dollars,1043735
\ No newline at end of file
+2013,GDP per capita,61661.26
+2014,GDP per capita,64339.13
+2015,GDP per capita,68206.20
+2016,GDP per capita,70946.94
+2017,GDP per capita,74346.09
+2018,GDP per capita,77651.54
+2019,GDP per capita,81625.39
+2013,GDP in millions of current dollars,617665
+2014,GDP in millions of current dollars,650900
+2015,GDP in millions of current dollars,693677
+2016,GDP in millions of current dollars,719254
+2017,GDP in millions of current dollars,755617
+2018,GDP in millions of current dollars,784709
+2019,GDP in millions of current dollars,819446
\ No newline at end of file
diff --git a/data/indicator_8-2-1.csv b/data/indicator_8-2-1.csv
index 8461d04..30ec94d 100644
--- a/data/indicator_8-2-1.csv
+++ b/data/indicator_8-2-1.csv
@@ -1,5 +1,8 @@
 Year,Value
-2014,3.1
-2015,5.5
-2016,1.7
-2017,3
\ No newline at end of file
+2013,133847.44
+2014,137191.01
+2015,143578.00
+2016,147178.08
+2017,151890.23
+2018,156898.84
+2019,162659.01
\ No newline at end of file
diff --git a/data/indicator_5-1-2.csv b/data/indicator_8-5-1a.csv
similarity index 97%
rename from data/indicator_5-1-2.csv
rename to data/indicator_8-5-1a.csv
index 6129ea4..221ed91 100644
--- a/data/indicator_5-1-2.csv
+++ b/data/indicator_8-5-1a.csv
@@ -43,4 +43,4 @@ Year,Gender,Occupation,Units,Value
 2015,,Service,women's earnings as a percentage of men's earnings,77.7
 2015,,Sales and office,women's earnings as a percentage of men's earnings,84.4
 2015,,"Natural resources, construction, and maintenance",women's earnings as a percentage of men's earnings,81.1
-2015,,"Production, transportation, and material moving",women's earnings as a percentage of men's earnings,76.1
\ No newline at end of file
+2015,,"Production, transportation, and material moving",women's earnings as a percentage of men's earnings,76.1
diff --git a/data/indicator_8-5-2.csv b/data/indicator_8-5-2.csv
index 63803cd..6685688 100755
--- a/data/indicator_8-5-2.csv
+++ b/data/indicator_8-5-2.csv
@@ -5,6 +5,11 @@ Year,Race/Ethnicity,Gender,Disability Status,Units,Value
 2019,American Indian and Alaska Native,,,Percent by Race/Ethnicity,4.4
 2019,Asian,,,Percent by Race/Ethnicity,3.7
 2019,Hispanic or Latino,,,Percent by Race/Ethnicity,5.4
+2019,,,,Percent by Gender,5.3
+2019,,Male,,Percent by Gender,4.6
+2019,,Female,,Percent by Gender,5.2
+2019,,,,Percent by Disability Status,5.3
+2019,,,With any disability,Percent by Disability Status,12.5
 2018,,,,Percent by Race/Ethnicity,6
 2018,White,,,Percent by Race/Ethnicity,5.5
 2018,Black or African American,,,Percent by Race/Ethnicity,9.5
diff --git a/data/indicator_8-8-1.csv b/data/indicator_8-8-1.csv
index cd99fa1..3ee9946 100644
--- a/data/indicator_8-8-1.csv
+++ b/data/indicator_8-8-1.csv
@@ -1,130 +1,16 @@
-Year,Injury Type,Industry,Value
-2017,Fatal,,2.2
-2017,Fatal,"Agriculture, Forestry, Fishing & Hunting",10
-2017,Fatal,Construction,6.1
-2017,Fatal,Manufacturing,1.4
-2017,Fatal,Wholesale & Retail Trade,2
-2017,Fatal,Transportation & Utilities,5.9
-2017,Fatal,"Finance, Insurance & Real Estate",0.5
-2017,Fatal,Professional & Business Services,2.6
-2017,Fatal,Education & Health Services,0.5
-2017,Fatal,"Leisure, Entertainment & Hospitality",0.9
-2017,Fatal,Other Services (Except Public Administration),1.1
-2017,Fatal,Public Administration,1.6
-2016,Fatal,,2.2
-2016,Fatal,"Agriculture, Forestry, Fishing & Hunting",10.4
-2016,Fatal,Construction,5.2
-2016,Fatal,Manufacturing,1.1
-2016,Fatal,Wholesale & Retail Trade,1.9
-2016,Fatal,Transportation & Utilities,7.4
-2016,Fatal,"Finance, Insurance & Real Estate",1
-2016,Fatal,Professional & Business Services,1.5
-2016,Fatal,Education & Health Services,0.5
-2016,Fatal,"Leisure, Entertainment & Hospitality",1.7
-2016,Fatal,Other Services (Except Public Administration),2.5
-2016,Fatal,Public Administration,2.3
-2015,Fatal,,2
-2015,Fatal,"Agriculture, Forestry, Fishing & Hunting",17.1
-2015,Fatal,Construction,6.8
-2015,Fatal,Manufacturing,1
-2015,Fatal,Wholesale & Retail Trade,1.4
-2015,Fatal,Transportation & Utilities,4.9
-2015,Fatal,Professional & Business Services,2.3
-2015,Fatal,Education & Health Services,0.7
-2015,Fatal,"Leisure, Entertainment & Hospitality",1.5
-2015,Fatal,Other Services (Except Public Administration),1.6
-2015,Fatal,Public Administration,3
-2014,Fatal,,2
-2014,Fatal,"Agriculture, Forestry, Fishing & Hunting",8.2
-2014,Fatal,Construction,4.5
-2014,Fatal,Manufacturing,1.2
-2014,Fatal,Wholesale & Retail Trade,1.1
-2014,Fatal,Transportation & Utilities,7.9
-2014,Fatal,"Finance, Insurance & Real Estate",1
-2014,Fatal,Professional & Business Services,2.4
-2014,Fatal,Education & Health Services,0.7
-2014,Fatal,"Leisure, Entertainment & Hospitality",1.1
-2014,Fatal,Other Services (Except Public Administration),2.2
-2014,Fatal,Public Administration,2.2
-2013,Fatal,,2.4
-2013,Fatal,"Agriculture, Forestry, Fishing & Hunting",9.2
-2013,Fatal,Construction,6.2
-2013,Fatal,Manufacturing,2
-2013,Fatal,Wholesale & Retail Trade,2.4
-2013,Fatal,Transportation & Utilities,9.1
-2013,Fatal,Information,1.1
-2013,Fatal,Professional & Business Services,2.2
-2013,Fatal,Education & Health Services,0.6
-2013,Fatal,"Leisure, Entertainment & Hospitality",1.5
-2013,Fatal,Other Services (Except Public Administration),1.5
-2013,Fatal,Public Administration,1.5
-2017,Non-Fatal,,3.6
-2017,Non-Fatal,"Agriculture, Forestry, Fishing & Hunting",5.3
-2017,Non-Fatal,"Mining, Quarrying, Oil & Gas Extraction",0.7
-2017,Non-Fatal,Construction,4.3
-2017,Non-Fatal,Manufacturing,3.1
-2017,Non-Fatal,Wholesale & Retail Trade,3.4
-2017,Non-Fatal,Transportation & Utilities,3.4
-2017,Non-Fatal,Information,1.2
-2017,Non-Fatal,"Finance, Insurance & Real Estate",1.5
-2017,Non-Fatal,Professional & Business Services,1.6
-2017,Non-Fatal,Education & Health Services,4.3
-2017,Non-Fatal,"Leisure, Entertainment & Hospitality",4.3
-2017,Non-Fatal,Other Services (Except Public Administration),2.4
-2017,Non-Fatal,Public Administration,6
-2016,Non-Fatal,,3.7
-2016,Non-Fatal,"Agriculture, Forestry, Fishing & Hunting",5.8
-2016,Non-Fatal,"Mining, Quarrying, Oil & Gas Extraction",1.5
-2016,Non-Fatal,Construction,3.8
-2016,Non-Fatal,Manufacturing,3.2
-2016,Non-Fatal,Wholesale & Retail Trade,3.3
-2016,Non-Fatal,Transportation & Utilities,4
-2016,Non-Fatal,Information,1.5
-2016,Non-Fatal,"Finance, Insurance & Real Estate",1.8
-2016,Non-Fatal,Professional & Business Services,1.8
-2016,Non-Fatal,Education & Health Services,4.3
-2016,Non-Fatal,"Leisure, Entertainment & Hospitality",4.1
-2016,Non-Fatal,Other Services (Except Public Administration),3.2
-2016,Non-Fatal,Public Administration,6.8
-2015,Non-Fatal,,3.8
-2015,Non-Fatal,"Agriculture, Forestry, Fishing & Hunting",5.6
-2015,Non-Fatal,"Mining, Quarrying, Oil & Gas Extraction",0.7
-2015,Non-Fatal,Construction,3.3
-2015,Non-Fatal,Manufacturing,3.2
-2015,Non-Fatal,Wholesale & Retail Trade,3.7
-2015,Non-Fatal,Transportation & Utilities,3.75
-2015,Non-Fatal,Information,1.4
-2015,Non-Fatal,"Finance, Insurance & Real Estate",1.7
-2015,Non-Fatal,Professional & Business Services,1.7
-2015,Non-Fatal,Education & Health Services,4.3
-2015,Non-Fatal,"Leisure, Entertainment & Hospitality",4.3
-2015,Non-Fatal,Other Services (Except Public Administration),2.5
-2015,Non-Fatal,Public Administration,6.4
-2014,Non-Fatal,,3.8
-2014,Non-Fatal,"Agriculture, Forestry, Fishing & Hunting",5.2
-2014,Non-Fatal,"Mining, Quarrying, Oil & Gas Extraction",1
-2014,Non-Fatal,Construction,4.8
-2014,Non-Fatal,Manufacturing,3.2
-2014,Non-Fatal,Wholesale & Retail Trade,3.35
-2014,Non-Fatal,Transportation & Utilities,3.9
-2014,Non-Fatal,Information,1.5
-2014,Non-Fatal,"Finance, Insurance & Real Estate",1.8
-2014,Non-Fatal,Professional & Business Services,2
-2014,Non-Fatal,Education & Health Services,4.3
-2014,Non-Fatal,"Leisure, Entertainment & Hospitality",4.4
-2014,Non-Fatal,Other Services (Except Public Administration),2.7
-2014,Non-Fatal,Public Administration,6.9
-2013,Non-Fatal,,4
-2013,Non-Fatal,"Agriculture, Forestry, Fishing & Hunting",5.4
-2013,Non-Fatal,"Mining, Quarrying, Oil & Gas Extraction",1.6
-2013,Non-Fatal,Construction,4
-2013,Non-Fatal,Manufacturing,3.2
-2013,Non-Fatal,Wholesale & Retail Trade,3.7
-2013,Non-Fatal,Transportation & Utilities,3.95
-2013,Non-Fatal,Information,2
-2013,Non-Fatal,"Finance, Insurance & Real Estate",1.5
-2013,Non-Fatal,Professional & Business Services,1.9
-2013,Non-Fatal,Education & Health Services,4.4
-2013,Non-Fatal,"Leisure, Entertainment & Hospitality",5.2
-2013,Non-Fatal,Other Services (Except Public Administration),3
-2013,Non-Fatal,Public Administration,7.2
+Year,Injury Type,Value
+2013,Fatal Injury,396
+2014,Fatal Injury,344
+2015,Fatal Injury,388
+2016,Fatal Injury,376
+2017,Fatal Injury,376
+2018,Fatal Injury,422
+2019,Fatal Injury,451
+2013,Non-Fatal Injury and Illness,468400
+2014,Non-Fatal Injury and Illness,460700
+2015,Non-Fatal Injury and Illness,470600
+2016,Non-Fatal Injury and Illness,466600
+2017,Non-Fatal Injury and Illness,466600
+2018,Non-Fatal Injury and Illness,466500
+2019,Non-Fatal Injury and Illness,483300
+2020,Non-Fatal Injury and Illness,448300
\ No newline at end of file
diff --git a/data/indicator_8-9-2.csv b/data/indicator_8-9-2.csv
deleted file mode 100644
index 31feb0d..0000000
--- a/data/indicator_8-9-2.csv
+++ /dev/null
@@ -1,16 +0,0 @@
-Year,Units,Value
-2016-2017,Tourism Jobs as Percentage of Total Jobs,11.7
-2016,Tourism Jobs as Percentage of Total Jobs,11.6
-2015,Tourism Jobs as Percentage of Total Jobs,11.4
-2013-2014,Tourism Jobs as Percentage of Total Jobs,10.1
-2012-2013,Tourism Jobs as Percentage of Total Jobs,10.9
-2016-2017,Number of Jobs,515992
-2016,Number of Jobs,505492
-2015,Number of Jobs,466608
-2013-2014,Number of Jobs,453600
-2012-2013,Number of Jobs,423358
-2016-2017,Year Over Year Jobs Growth Rate (%),2
-2016,Year Over Year Jobs Growth Rate (%),8
-2015,Year Over Year Jobs Growth Rate (%),3
-2013-2014,Year Over Year Jobs Growth Rate (%),7
-2012-2013,Year Over Year Jobs Growth Rate (%),5
diff --git a/data/indicator_9-1-2.csv b/data/indicator_9-1-2.csv
index 318a06a..c6ff687 100755
--- a/data/indicator_9-1-2.csv
+++ b/data/indicator_9-1-2.csv
@@ -33,4 +33,14 @@ Year,LAX passengers and cargo,POLA cargo,Units,Value
 2018,LAX total air cargo (tons),,Los Angeles International Airport,2446137
 2018,,POLA total imports,Port of Los Angeles,5035294
 2018,,POLA total exports,Port of Los Angeles,4423455
-2018,,POLA total TEUs,Port of Los Angeles,9458749
\ No newline at end of file
+2018,,POLA total TEUs,Port of Los Angeles,9458749
+2019,LAX international passengers,,Los Angeles International Airport,25696322
+2019,LAX total air cargo (tons),,Los Angeles International Airport,2313247
+2019,,POLA total imports,Port of Los Angeles,4863844
+2019,,POLA total exports,Port of Los Angeles,4473787
+2019,,POLA total TEUs,Port of Los Angeles,9337632
+2020,LAX international passengers,,Los Angeles International Airport,6421742
+2020,LAX total air cargo (tons),,Los Angeles International Airport,2464845
+2020,,POLA total imports,Port of Los Angeles,4876351
+2020,,POLA total exports,Port of Los Angeles,4337044
+2020,,POLA total TEUs,Port of Los Angeles,9213395
\ No newline at end of file
diff --git a/data/indicator_9-2-1.csv b/data/indicator_9-2-1.csv
index 1dafaa8..0067a48 100755
--- a/data/indicator_9-2-1.csv
+++ b/data/indicator_9-2-1.csv
@@ -1,8 +1,15 @@
-Year,Value
-2011,9.34
-2012,9.35
-2013,9.38
-2014,9.23
-2015,8.87
-2016,8.78
-2017,8.55
\ No newline at end of file
+Year,Units,Value
+2013,Manufacturing total GDP in millions of current dollars,78222
+2014,Manufacturing total GDP in millions of current dollars,82889
+2015,Manufacturing total GDP in millions of current dollars,88260
+2016,Manufacturing total GDP in millions of current dollars,90636
+2017,Manufacturing total GDP in millions of current dollars,97606
+2018,Manufacturing total GDP in millions of current dollars,103768
+2019,Manufacturing total GDP in millions of current dollars,103351
+2013,Manufacturing as proportion of all industry GDP (%),9.55
+2014,Manufacturing as proportion of all industry GDP (%),9.62
+2015,Manufacturing as proportion of all industry GDP (%),9.61
+2016,Manufacturing as proportion of all industry GDP (%),9.51
+2017,Manufacturing as proportion of all industry GDP (%),9.73
+2018,Manufacturing as proportion of all industry GDP (%),9.96
+2019,Manufacturing as proportion of all industry GDP (%),9.49
\ No newline at end of file
diff --git a/data/indicator_9-2-2.csv b/data/indicator_9-2-2.csv
index 22596e9..0c2be62 100755
--- a/data/indicator_9-2-2.csv
+++ b/data/indicator_9-2-2.csv
@@ -1,7 +1,15 @@
 Year,Units,Value
-2015,total,162224
-2016,total,161733
-2017,total,163169
-2015,as a proportion of total employment,8.68
-2016,as a proportion of total employment,8.49
-2017,as a proportion of total employment,8.35
+2013,total manufacturing employed,130209
+2014,total manufacturing employed,135865
+2015,total manufacturing employed,131430
+2016,total manufacturing employed,131600
+2017,total manufacturing employed,130183
+2018,total manufacturing employed,129966
+2019,total manufacturing employed,118771
+2013,manufacturing as a proportion of total employment,10.65
+2014,manufacturing as a proportion of total employment,10.66
+2015,manufacturing as a proportion of total employment,9.90
+2016,manufacturing as a proportion of total employment,9.77
+2017,manufacturing as a proportion of total employment,9.30
+2018,manufacturing as a proportion of total employment,9.25
+2019,manufacturing as a proportion of total employment,8.25
\ No newline at end of file
diff --git a/meta/1-1-1.md b/meta/1-1-1.md
index c770e92..d6f82c8 100644
--- a/meta/1-1-1.md
+++ b/meta/1-1-1.md
@@ -48,6 +48,4 @@ source_organisation_1: United States Census Bureau
 source_url_1: 'https://factfinder.census.gov'
 source_geographical_coverage_1: City of Los Angeles
 ---
-**Proxy indicator:**
-
 In the United States, the proportion of population below the international poverty line of $1.90 is extremely low (less than 1% of the total population). In Los Angeles, we report a proxy indicator to measure extreme poverty (proportion of population earning less than 50% of the poverty level). The poverty level is set by the Federal Government each year in accordance to household size. For context, the 2020 poverty level for a household of 4 was $26,200 in annual earnings (50% of the poverty level was $13,100).
diff --git a/meta/1-2-2.md b/meta/1-2-2.md
index c998dc9..acd0ea7 100644
--- a/meta/1-2-2.md
+++ b/meta/1-2-2.md
@@ -24,16 +24,14 @@ target: >-
   all ages living in poverty in all its dimensions according to national
   definitions
 target_id: '1.2'
-graph_title: People at Specific Levels of Poverty in the Past 12 Months
+graph_title: Percentage of households below Real Cost Measure
 un_custodian_agency: >-
   United Nations Children's Fund (UNICEFF) World Bank (WB) United Nations
   Development Programme (UNDP)
 un_designated_tier: '1'
 data_show_map: false
 source_active_1: true
-source_url_text_1: >-
-  American Community Survey 5-Year Estimates: People at Specific Levels of
-  Poverty in the Past 12 Months (S1703)
+source_url_text_1: The Real Cost Measure in California Dashboard
 source_active_2: false
 source_url_text_2: Link to Source
 source_active_3: false
@@ -45,15 +43,23 @@ source_url_text_5: Link to source
 source_active_6: false
 source_url_text_6: Link to source
 title: Untitled
-national_indicator_available: People at Specific Levels of Poverty in the Past 12 Months
-national_geographical_coverage: City of Los Angeles
+national_indicator_available: Percentage of households below Real Cost Measure
+national_geographical_coverage: Los Angeles County
 computation_units: Percentage
-data_disaggregation_information: 'gender, age'
-source_organisation_1: U.S. Census Bureau
-source_url_1: 'https://factfinder.census.gov'
+data_disaggregation_information: 'education level, race/ ethnicity'
+source_organisation_1: United Ways of California
+source_url_1: >-
+  https://public.tableau.com/app/profile/hgascon/viz/TheRealCostMeasureinCalifornia2021/RealCostDashboard
 wccd_iso_37120_alignment: 'Aligns to WCCD 5.3- Percentage of city population living in poverty '
-source_geographical_coverage_1: City of Los Angeles
+source_geographical_coverage_1: Los Angeles County
 tags:
   - Revised
+computation_definitions: >-
+  The Real Cost Measure is a self-sufficiency measure designed by United Ways of
+  California. Unlike the official poverty measure which does not account for
+  local costs of living, the Real Cost Measure incorporates the costs of
+  housing, food, health care, child care, transportation and other basic needs
+  for a more accurate measure of financial security. To read the methodology,
+  visit https://www.unitedwaysca.org/realcost.
 ---
 **Revised indicator:** All instances of "men and women" is revised to people and all instances of "boys and girls" is revised to "all children". This indicator has been revised for inclusivity from the original text: "Proportion of men, women and children of all ages living in poverty in all its dimensions according to national definitions."
diff --git a/meta/1-3-1.md b/meta/1-3-1.md
index a346db8..076b692 100644
--- a/meta/1-3-1.md
+++ b/meta/1-3-1.md
@@ -64,3 +64,4 @@ national_indicator_description: >-
   Health Insurance Program); and other safety net programs that provide aid to
   individuals and families facing hardship.
 ---
+Social security in the United States is overseen by the federal Social Security Administration. Social security benefit programs include retirement, disabiity, medicare, survivors, and supplemental security income (SSI). These federal programs are often administered by State authorities. 
\ No newline at end of file
diff --git a/meta/1-4-1.md b/meta/1-4-1.md
index de71958..08a6aa7 100644
--- a/meta/1-4-1.md
+++ b/meta/1-4-1.md
@@ -18,7 +18,7 @@ target: >-
   inheritance, natural resources, appropriate new technology and financial
   services, including microfinance.
 target_id: '1.4'
-graph_title: Proportion of population living in households with access to basic services
+graph_title: Percent of occupied housing units with access to basic services
 un_custodian_agency: UN-Habitat
 un_designated_tier: '3'
 data_show_map: false
@@ -38,9 +38,12 @@ source_active_6: false
 source_url_text_6: Link to source
 title: Untitled
 national_geographical_coverage: City of Los Angeles
-computation_units: Percentage of occupied housing units and total occupied housing units
+computation_units: Percentage
 source_organisation_1: United States Census Bureau
 source_geographical_coverage_1: City of Los Angeles
 source_url_1: data.census.gov
+national_indicator_available: >-
+  Households with complete kitchen facilities, complete plumbing facilities,
+  telephone service, and at least one car.
 ---
-**Proxy indicator:** By international standards, this indicator has been achieved in Los Angeles already as more than 99.7% of all households in urban areas of the United States have access to basic drinking water and sanitation services. In Los Angeles we report the following proxy indicators: households with complete kitchen facilities, households with complete plumbing facilities, and households with telephone service.
+By international standards, this indicator has been achieved in Los Angeles already as more than 99.7% of all households in urban areas of the United States have access to basic drinking water and sanitation services. In Los Angeles we report the following proxy indicators: households with complete kitchen facilities, households with complete plumbing facilities, and households with telephone service.
diff --git a/meta/1-a-2.md b/meta/1-a-2.md
index f217fe3..a968382 100644
--- a/meta/1-a-2.md
+++ b/meta/1-a-2.md
@@ -1,27 +1,62 @@
 ---
-data_non_statistical: false
-goal_meta_link: https://unstats.un.org/sdgs/files/metadata-compilation/Metadata-Goal-1.pdf
-goal_meta_link_text: TIER III - NO WORK PLAN
-graph_type: line
 indicator: 1.a.2
-indicator_name: Proportion of total government spending on essential services (education,
-  health and social protection)
-indicator_sort_order: 01-aa-02
 layout: indicator
 permalink: /1-a-2/
-published: true
-reporting_status: notstarted
 sdg_goal: '1'
-target: Ensure significant mobilization of resources from a variety of sources, including
-  through enhanced development cooperation, in order to provide adequate and predictable
-  means for developing countries, in particular least developed countries, to implement
-  programmes and policies to end poverty in all its dimensions
+data_non_statistical: false
+goal_meta_link: 'https://unstats.un.org/sdgs/metadata/files/Metadata-01-0a-02.pdf'
+goal_meta_link_text: United Nations Sustainable Development Goals Metadata
+graph_type: bar
+indicator_name: >-
+  Proportion of total government spending on essential services (education,
+  health and social protection)
+indicator_sort_order: 01-aa-02
+published: true
+reporting_status: complete
+target: >-
+  Ensure significant mobilization of resources from a variety of sources,
+  including through enhanced development cooperation, in order to provide
+  adequate and predictable means for developing countries, in particular least
+  developed countries, to implement programmes and policies to end poverty in
+  all its dimensions
 target_id: 1.a
-graph_title: Proportion of total government spending on essential services (education, health
-  and social protection)
-un_custodian_agency: Discussions are occurring between the following organisations
-  International Labour Organization (ILO) United Nations Educational Scientific and
-  Cultural Organization - Institute for Statistics (UNESCO-UIS) and World Health Organization
-  (WHO)
+graph_title: >-
+  Total government spending on essential services (education, health and social
+  protection) in billion dollars
+un_custodian_agency: >-
+  Discussions are occurring between the following organisations International
+  Labour Organization (ILO) United Nations Educational Scientific and Cultural
+  Organization - Institute for Statistics (UNESCO-UIS) and World Health
+  Organization (WHO)
 un_designated_tier: '3'
+data_show_map: false
+source_active_1: true
+source_url_text_1: Los Angeles Unified School District Budget Documents
+source_active_2: true
+source_url_text_2: County of Los Angeles Open Budget
+source_active_3: false
+source_url_3: Link to source
+source_active_4: false
+source_url_text_4: Link to source
+source_active_5: false
+source_url_text_5: Link to source
+source_active_6: false
+source_url_text_6: Link to source
+title: Untitled
+source_organisation_1: Los Angeles Unified School District
+source_geographical_coverage_1: Los Angeles County
+source_url_1: 'https://achieve.lausd.net/Page/1327'
+national_indicator_available: >-
+  Total government spending on essential services (education, health and social
+  protection)
+national_geographical_coverage: Los Angeles County
+source_organisation_2: Los Angeles County
+source_geographical_coverage_2: Los Angeles County
+source_url_2: 'http://budget.lacounty.gov/#!/year/2020/operating/0/department'
+computation_definitions: >-
+  Total budgets for the Los Angeles Unified School District, and the Los Angeles
+  County Departments of Public Social Services, Mental Health, Public Health,
+  and Health Services.
+computation_units: $ Billions
 ---
+K-12 education policy and services are administered through the [Los Angeles Unified School District (LAUSD)](https://achieve.lausd.net/domain/4), hte second-largest school district in the United States, which is overseen by an independently elected Board of Education. Los Angeles County oversees [public health](http://www.publichealth.lacounty.gov/) and [social services](https://dpss.lacounty.gov/en.html) programs for the 88 cities within the County, including the City of Los Angeles.
diff --git a/meta/10-2-1.md b/meta/10-2-1.md
index b62f024..0451497 100644
--- a/meta/10-2-1.md
+++ b/meta/10-2-1.md
@@ -26,9 +26,7 @@ target: >-
   all, irrespective of age, sex, disability, race, ethnicity, origin, religion
   or economic or other status
 target_id: '10.2'
-graph_title: >-
-  Proportion of people living below 50 percent of median income, by sex, age and
-  persons with disabilities
+graph_title: 'Percentage of full-time workers earning less than $25,000 a year'
 un_custodian_agency: United Nations Children's Fund (UNICEF) World Bank (WB)
 un_designated_tier: '2'
 data_show_map: false
@@ -47,20 +45,17 @@ source_url_text_5: Link to source
 source_active_6: false
 source_url_text_6: Link to source
 title: Untitled
-national_indicator_available: >-
-  Earnings in the past 12 months by earning category (percentage of full-time,
-  year-round workers with earnings)
+national_indicator_available: 'Percentage of full-time workers earning less than $25,000 a year'
 national_indicator_description: >-
-  This indicator shows the percentage of full-time, year-round workers with
-  earnings in each earning category (less than $25,000, between $25,000 and
-  $50,000, between $50,000 and $75,000, and above $75,000. Median income in the
-  City of LA has changed in the years 2009-2017 but has stayed around $35,000 -
-  $40,000.  
+  Median earnings in the City of LA has changed in the years 2009-2017 but has
+  stayed around $35,000 - $46,000.  The Census Bureau reports a data table on
+  earnings by income brackets. This data shows the percentage of population
+  earning less than $25,000 a year.
 national_geographical_coverage: City of Los Angeles
 computation_units: Percentage
 computation_calculations: >-
-  The values were calculated from the Census earnings categories which are finer
-  than our categories. 
+  Proportion earning less than $25,000: Total earning less than $25,000/ total
+  full-time workers with earnings
 data_disaggregation_information: gender
 source_organisation_1: United States Census Bureau
 source_periodicity_1: Annual
@@ -68,4 +63,12 @@ source_earliest_available_1: '2009'
 source_geographical_coverage_1: 'City of Los Angeles '
 source_url_1: 'https://factfinder.census.gov'
 wccd_iso_37120_alignment: Aligns to WCCD - Income distribution (Gini Coefficient)
+computation_definitions: >-
+  Every year, the Census Bureau collects data on how much money households
+  obtain from 50 different sources, all of which we label “income.” Earnings,
+  primarily wages and salary from a job, are usually a big source of income.
+  Other sources of income include Social Security payments, pensions, child
+  support, public assistance, annuities, money derived from rental properties,
+  interest and dividends. Only full-time, year-round workers with earnings are
+  included.
 ---
diff --git a/meta/10-4-2.md b/meta/10-4-2.md
index 9039f85..d86aa17 100644
--- a/meta/10-4-2.md
+++ b/meta/10-4-2.md
@@ -8,7 +8,7 @@ goal_meta_link: 'https://unstats.un.org/sdgs/metadata/files/Metadata-10-04-02.pd
 goal_meta_link_text: United Nations Sustainable Development Goals Metadata (PDF 190 KB)
 graph_type: bar
 indicator_name: Redistributive impact of fiscal policy
-indicator_sort_order: 10-04-01
+indicator_sort_order: 10-04-02
 published: true
 reporting_status: complete
 target: >-
diff --git a/meta/10-7-4.md b/meta/10-7-4.md
index 60ffbfd..1131ff7 100644
--- a/meta/10-7-4.md
+++ b/meta/10-7-4.md
@@ -6,24 +6,24 @@ sdg_goal: '10'
 data_non_statistical: false
 goal_meta_link: 'https://unstats.un.org/sdgs/metadata/files/Metadata-10-07-03.pdf'
 goal_meta_link_text: United Nations Sustainable Development Goals Metadata (pdf 564kB)
-graph_type: line
-indicator_name: >-
-  Proportion of the population who are refugees, by country of origin
+graph_type: bar
+indicator_name: 'Proportion of the population who are refugees, by country of origin'
 indicator_sort_order: 10-07-04
 published: true
-reporting_status: notstarted
+reporting_status: complete
 target: >-
   Facilitate orderly, safe, regular and responsible migration and mobility of
   people, including through the implementation of planned and well-managed
   migration policies
 target_id: '10.7'
-graph_title: >-
-  Proportion of the population who are refugees, by country of origin
+graph_title: Foreign born population by region of birth
 un_custodian_agency: UNHCR
 un_designated_tier: '2'
 data_show_map: false
 source_active_1: true
-source_url_text_1: Link to source
+source_url_text_1: >-
+  American Community Survey 1-Year Estimates: Selected Social Characteristics in
+  the United States (DP02)
 source_active_2: false
 source_url_text_2: Link to Source
 source_active_3: false
@@ -35,4 +35,9 @@ source_url_text_5: Link to source
 source_active_6: false
 source_url_text_6: Link to source
 title: Untitled
+national_indicator_available: Foreign born population by region of birth
+source_organisation_1: U.S. Census Bureau
+source_geographical_coverage_1: City of Los Angeles
+source_url_1: 'https://data.census.gov'
+national_geographical_coverage: City of Los Angeles
 ---
diff --git a/meta/10-c-1.md b/meta/10-c-1.md
new file mode 100644
index 0000000..3e9b86a
--- /dev/null
+++ b/meta/10-c-1.md
@@ -0,0 +1,19 @@
+---
+data_non_statistical: false
+goal_meta_link: https://unstats.un.org/sdgs/metadata/files/Metadata-10-0C-01.pdf
+goal_meta_link_text: United Nations Sustainable Development Goals Metadata (pdf 865kB)
+graph_type: line
+indicator: 10.c.1
+indicator_name: Remittance costs as a proportion of the amount remitted
+indicator_sort_order: 10-cc-01
+layout: indicator
+permalink: /10-c-1/
+published: true
+reporting_status: notstarted
+sdg_goal: '10'
+target: By 2030, reduce to less than 3 per cent the transaction costs of migrant remittances and eliminate remittance corridors with costs higher than 5 per cent
+target_id: '10.c'
+graph_title: Remittance costs as a proportion of the amount remitted
+un_custodian_agency: World Bank
+un_designated_tier: '10'
+---
diff --git a/meta/10-x-2.md b/meta/10-x-2.md
index 4a2e943..a022075 100644
--- a/meta/10-x-2.md
+++ b/meta/10-x-2.md
@@ -21,7 +21,7 @@ graph_title: >-
 tags:
   - New
 data_show_map: false
-source_active_1: false
+source_active_1: true
 source_url_text_1: LAUSD School Experience Survey Data Files
 source_active_2: false
 source_url_text_2: AB 1400 Civil Rights Act
@@ -47,4 +47,5 @@ national_indicator_description: >-
   Proportions of students in LAUSD high schools who agree or strongly agree with
   the statement "LGBTQ (lesbian, gay, bisexual, transgender, and/or queer)
   students at my school are accepted."
+goal_meta_link_text: UN metadata
 ---
diff --git a/meta/11-1-1.md b/meta/11-1-1.md
index 1cac562..f3c7ba3 100644
--- a/meta/11-1-1.md
+++ b/meta/11-1-1.md
@@ -47,5 +47,11 @@ wccd_iso_37120_alignment: >-
   Aligns to WCCD 15.2- Number of Homeless per 100k population; and WCCD 19.3-
   Areal size of informal settlements as a percentage of city area
 source_url_text_2: Link to Source
-data_disaggregation_information: 'age, gender, disability, race, sexula orientation'
+data_disaggregation_information: 'age, gender, disability, race, sexual orientation, domestic violence history'
+national_indicator_description: >-
+  The Shelter Count & Housing Inventory Count (HIC) is a component of the
+  Greater Los Angeles Homeless Count. The HIC is a point-in-time inventory of
+  projects/programs or sites within the Los Angeles Continuum of Care (LA CoC)
+  that provide beds and units dedicated to serve people experiencing
+  homelessness or people who have experienced homelessness.
 ---
diff --git a/meta/11-2-1.md b/meta/11-2-1.md
index 0ee0a2b..3116f2e 100644
--- a/meta/11-2-1.md
+++ b/meta/11-2-1.md
@@ -19,20 +19,24 @@ target: >-
   transport, with special attention to the needs of those in vulnerable
   situations, women, children, persons with disabilities and older persons
 target_id: '11.2'
-graph_title: Proportion of population that has convenient access to public transportation
+graph_title: LA Metro bus and rail ridership
 un_custodian_agency: UN-Habitat
 un_designated_tier: '2'
 data_show_map: false
 source_active_1: true
 source_active_2: false
-source_active_3: true
-source_url_3: 'http://open.dataforcities.org/'
+source_active_3: false
 source_active_4: false
 source_url_text_4: Link to source
 source_active_5: false
 source_url_text_5: Link to source
 source_active_6: false
 source_url_text_6: Link to source
+national_target_line: >-
+  Increase the percentage of all trips made by walking, biking, micro-mobility,
+  matched rides or transit to at least 35% by 2025 - <a
+  href="https://plan.lamayor.org/sites/default/files/pLAn_2019_final.pdf"
+  target="_blank">L.A.'s Green New Deal Sustainable City pLAn</a>
 title: Untitled
 national_geographical_coverage: 'City of Los Angeles, County of Los Angeles'
 wccd_iso_37120_alignment: >-
@@ -41,17 +45,10 @@ wccd_iso_37120_alignment: >-
   number of public transport trips per capita; WCCD 18.5-Percentage of Commuters
   using a travel mode to work other than a personal vehicle
 source_organisation_3: World Council on City Data
-source_url_text_3: >-
-  WCCD 18.1- km of High Capacity Public Transport per 100k population; 18.2- km
-  of Light Passenger Public Transport per 100k; 18.3-Annual number of public
-  transport trips per capita; 18.5-Percentage of Commuters using a travel mode
-  to work other than a personal vehicle
 source_organisation_1: LA Metro
 source_geographical_coverage_1: Los Angeles County
 source_url_1: 'http://isotp.metro.net/MetroRidership/'
 source_url_text_1: LA Metro Ridership Statistics
 source_url_text_2: Link to Source
-national_indicator_available: >-
-  While access to public transportation is calculated, this indicator reports LA
-  Metro bus and ridership data
+national_indicator_available: LA Metro bus and rail ridership
 ---
diff --git a/meta/11-2-2.md b/meta/11-2-2.md
new file mode 100644
index 0000000..aca05d5
--- /dev/null
+++ b/meta/11-2-2.md
@@ -0,0 +1,47 @@
+---
+indicator: 11.2.2
+layout: indicator
+permalink: /11-2-2/
+sdg_goal: '11'
+data_non_statistical: false
+graph_type: bar
+indicator_name: Proportion of workers who commute to work by public transportation
+indicator_sort_order: 11-02-02
+published: true
+reporting_status: complete
+target: >-
+  By 2030, provide access to safe, affordable, accessible and sustainable
+  transport systems for all, improving road safety, notably by expanding public
+  transport, with special attention to the needs of those in vulnerable
+  situations, women, children, persons with disabilities and older persons
+target_id: '11.2'
+graph_title: Proportion of workers who commute to work by public transportation
+data_show_map: false
+source_active_1: true
+source_active_2: false
+source_active_3: false
+source_active_4: false
+source_url_text_4: Link to source
+source_active_5: false
+source_url_text_5: Link to source
+source_active_6: false
+source_url_text_6: Link to source
+national_target_line: >-
+  Increase the percentage of all trips made by walking, biking, micro-mobility,
+  matched rides or transit to at least 35% by 2025 - <a
+  href="https://plan.lamayor.org/sites/default/files/pLAn_2019_final.pdf"
+  target="_blank">L.A.'s Green New Deal Sustainable City pLAn</a>
+title: Untitled
+national_geographical_coverage: City of Los Angeles
+source_organisation_1: U.S. Census Bureau
+source_geographical_coverage_1: City of Los Angeles
+source_url_1: 'https://data.census.gov'
+source_url_text_1: >-
+  American Community Survey 1-Year Estimates: Commuting Characteristics by Sex
+  (S0801)
+source_url_text_2: Link to Source
+tags:
+  - New
+data_disaggregation_information: gender
+computation_units: Percentage
+---
diff --git a/meta/11-6-1.md b/meta/11-6-1.md
index 5fad275..c670fa5 100644
--- a/meta/11-6-1.md
+++ b/meta/11-6-1.md
@@ -18,12 +18,13 @@ target: >-
   including by paying special attention to air quality and municipal and other
   waste management
 target_id: '11.6'
-graph_title: Annual tonnages reported by district yards
+graph_title: >-
+  Proportion of urban solid waste regularly collected and with adequate final
+  discharge out of total urban solid waste generated, by cities
 un_custodian_agency: 'UN-Habitat, United Nations Statistics Division (UNSD)'
 un_designated_tier: '2'
 data_show_map: false
-source_active_1: true
-source_url_text_1: 'LASAN Solid Resources Tonnages, Bulky Item E-Waste'
+source_active_1: false
 source_active_2: false
 source_active_3: false
 source_url_3: Link to source
@@ -35,12 +36,7 @@ source_active_6: false
 source_url_text_6: Link to source
 title: Untitled
 national_geographical_coverage: City of Los Angeles
-computation_units: Tons
-source_organisation_1: 'City of Los Angeles Bureau of Sanitation and Environment '
-source_geographical_coverage_1: City of Los Angeles
-source_url_1: >-
-  https://data.lacity.org/A-Livable-and-Sustainable-City/LASAN-Solid-Resources-Tonnages-Bulky-Item-E-Waste-/qwh3-ax8z/data
+computation_units: Percentage
 wccd_iso_37120_alignment: Aligns to WCCD 16.2 - Total Collected Municipal Solid Waste per Capita
+source_url_text_2: Link to Source
 ---
-**Proxy indicator:**
-The City of Los Angeles has reached 100% waste collection. This proxy indicator shows the annual tonnages reported by district yards along the following categories: bulky, recycling, refuse, and yard trimmings.
diff --git a/meta/11-6-2.md b/meta/11-6-2.md
index d28909f..3d0a773 100644
--- a/meta/11-6-2.md
+++ b/meta/11-6-2.md
@@ -26,10 +26,7 @@ un_designated_tier: '1'
 data_show_map: false
 source_active_1: true
 source_url_text_1: South Coast Air Quality Management District (AQMD)
-source_active_2: true
-source_url_text_2: >-
-  WCCD 8.1-Fine Particulate Matter (PM2.5) Concentration; WCCD 8.2-Particulate
-  Matter (PM10) Concentration
+source_active_2: false
 source_active_3: false
 source_url_3: Link to source
 source_active_4: false
@@ -48,9 +45,6 @@ source_url_1: >-
 wccd_iso_37120_alignment: >-
   Aligns to WCCD 8.1-Fine Particulate Matter (PM2.5) Concentration; WCCD
   8.2-Particulate Matter (PM10) Concentration
-source_organisation_2: World Council on City Data
-source_url_2: 'http://open.dataforcities.org/'
-source_geographical_coverage_2: City of Los Angeles
 computation_units: Annual Average Concentration in µg/m^3
 national_indicator_description: >-
   South Coast Air Quality Management District (AQMD) Historical Data at the
diff --git a/meta/12-c-2.md b/meta/12-c-2.md
new file mode 100644
index 0000000..85e3451
--- /dev/null
+++ b/meta/12-c-2.md
@@ -0,0 +1,59 @@
+---
+indicator: 12.c.2
+layout: indicator
+permalink: /12-c-2/
+sdg_goal: '12'
+data_non_statistical: false
+graph_type: bar
+indicator_name: Motor vehicle fuel (gasolie) tax rates
+indicator_sort_order: 12-cc-02
+published: true
+reporting_status: complete
+target: >-
+  Rationalize inefficient fossil-fuel subsidies that encourage wasteful
+  consumption by removing market distortions, in accordance with national
+  circumstances, including by restructuring taxation and phasing out those
+  harmful subsidies, where they exist, to reflect their environmental impacts,
+  taking fully into account the specific needs and conditions of developing
+  countries and minimizing the possible adverse impacts on their development in
+  a manner that protects the poor and the affected communities
+target_id: 12.c
+graph_title: Motor vehicle fuel (gasolie) tax rates
+data_show_map: false
+source_active_1: true
+source_url_text_1: Sales Tax Rates for Fuels
+source_active_2: true
+source_url_text_2: California Road Repair and Accountability Act of 2017
+source_active_3: false
+source_url_3: Link to source
+source_active_4: false
+source_url_text_4: Link to source
+source_active_5: false
+source_url_text_5: Link to source
+source_active_6: false
+source_url_text_6: Link to source
+title: Untitled
+national_geographical_coverage: State of California
+computation_units: Dollars per gallon
+computation_definitions: >-
+  Excise taxes are taxes that are imposed on various goods, services and
+  activities. Such taxes may be imposed on the manufacturer, retailer or
+  consumer, depending on the specific tax.
+tags:
+  - New
+source_organisation_1: California Department of Tax and Fee Administration
+source_geographical_coverage_1: State of California
+source_url_1: 'https://www.cdtfa.ca.gov/taxes-and-fees/sales-tax-rates-for-fuels.htm'
+national_indicator_description: >-
+  The California Road Repair and Accountability Act of 2017 (RRAA), also known
+  as Senate Bill 1 (SB 1), was enacted into law on April 28, 2017. The RRAA
+  increased transportation-related taxes and fees, including the gas excise tax,
+  diesel excise tax, and diesel sales tax, and was designed to dedicate the
+  revenue to transportation infrastructure. The increased taxes went into effect
+  on November 1, 2017.
+source_organisation_2: Ballotpedia
+source_geographical_coverage_2: State of California
+source_url_2: 'https://ballotpedia.org/California_Road_Repair_and_Accountability_Act_of_2017'
+goal_meta_link_text: UN metadata
+national_indicator_available: Excise tax rates on gas and diesel in dollars per gallon
+---
diff --git a/meta/13-2-2.md b/meta/13-2-2.md
index 7c341a5..145ca5b 100644
--- a/meta/13-2-2.md
+++ b/meta/13-2-2.md
@@ -30,6 +30,9 @@ source_active_5: false
 source_url_text_5: Link to source
 source_active_6: false
 source_url_text_6: Link to source
+national_target_line: >-
+  Reduce industrial emissions by 38% by 2035 <br />  Reduce municipal greenhouse
+  gas emissions 55% by 2025
 title: Untitled
 wccd_iso_37120_alignment: >-
   Aligns to WCCD 8.3 – Greenhouse Gas Emissions; WCCD 7.3 – Energy Consumption
diff --git a/meta/14-7-1.md b/meta/14-7-1.md
index 7fc7498..91f267b 100644
--- a/meta/14-7-1.md
+++ b/meta/14-7-1.md
@@ -7,9 +7,7 @@ data_non_statistical: false
 goal_meta_link: 'https://unstats.un.org/sdgs/metadata/files/Metadata-14-07-01.pdf'
 goal_meta_link_text: United Nations Sustainable Development Goals Metadata (pdf 288kB)
 graph_type: bar
-indicator_name: >-
-  Sustainable fisheries as a proportion of GDP in small island developing
-  States, least developed countries and all countries
+indicator_name: Sustainable fisheries as a proportion of GDP
 indicator_sort_order: 14-07-01
 published: true
 reporting_status: complete
@@ -54,9 +52,12 @@ computation_definitions: >-
   Terminal Island, San Pedro, Dana Point, Newport Beach, Redondo Beach, Marind
   del Rey, Avalon, Hermosa Beach, Santa Monica, Huntington Beach, Los Angeles,
   and Wilmington.
+tags:
+  - Revised
 ---
-**Not Applicable in the local context**
+**Revised**
+Revised from original indicator language:"Sustainable fisheries as a proportion of GDP in small island developing States, least developed countries and all countries"
 
 Local governments do not have jurisdiction over marine areas and therefore cannot pass regulations on sustainable fisheries. In California, the tidelands up to 3 nautical miles from shore are managed by the [California State Lands Commission](https://www.slc.ca.gov/water-boundaries/). The Territorial Sea, Contiguous Zone and, Exclusive Economic Zone are regulated by the [federal government](https://nauticalcharts.noaa.gov/data/us-maritime-limits-and-boundaries.html#general-information). The [Magnuson-Stevens Act](https://www.fisheries.noaa.gov/resource/document/magnuson-stevens-fishery-conservation-and-management-act) is the primary law governing marine fisheries management in U.S. federal waters.
 
-An approximation would be the GDP from agriculture, forestry, fishing and hunting as a proportion of total regional GDP. The California Department of Fish and Wildlife also reports Final California Commercial Landings by regions. 
+An approximation would be the GDP from agriculture, forestry, fishing and hunting as a proportion of total regional GDP. The California Department of Fish and Wildlife also reports Final California Commercial Landings by regions.
diff --git a/meta/16-1-2.md b/meta/16-1-2.md
index bb280fa..87ecc51 100644
--- a/meta/16-1-2.md
+++ b/meta/16-1-2.md
@@ -40,5 +40,7 @@ source_url_1: >-
   http://assets.lapdonline.org/assets/pdf/2017%20LAPD%20Crime%20&%20Initiatives.pdf
 computation_units: Number
 wccd_iso_37120_alignment: 'Aligns to WCCD 14.2- Number of homicides per 100,000 population'
+tags:
+  - Proxy
 ---
-**Proxy indicator:** There is currently no active armed conflict in the City of Los Angeles as defined by in International Humanitarian Law (IHL). Indicator 16.1.1 already reports all homicides in the City. This proxy indicator reports the numbers of victims that have been shot by a firearm in the city.
\ No newline at end of file
+**Proxy indicator:** There is currently no active armed conflict in the City of Los Angeles as defined by in International Humanitarian Law (IHL). Indicator 16.1.1 already reports all homicides in the City. This proxy indicator reports the numbers of victims that have been shot by a firearm in the city.
diff --git a/meta/16-1-4.md b/meta/16-1-4.md
index 8f7055a..3a3e861 100644
--- a/meta/16-1-4.md
+++ b/meta/16-1-4.md
@@ -17,9 +17,7 @@ target: >-
   16.1 Significantly reduce all forms of violence and related death rates
   everywhere
 target_id: '16.1'
-graph_title: >-
-  Proportion of population that feel safe walking alone around the area they
-  live
+graph_title: Proportion of population that always feels safe in neighborhood
 un_custodian_agency: United Nations Office on Drugs and Crime (UNODC)
 un_designated_tier: '2'
 data_show_map: false
@@ -36,12 +34,13 @@ source_url_text_5: Link to source
 source_active_6: false
 source_url_text_6: Link to source
 title: Untitled
-wccd_iso_37120_alignment: 'Aligns to WCCD 14.2- Number of homicides per 100,000 population'
-national_indicator_available: >-
-  Proportion of population who agree or strongly agree with the statement
-  "Nearby park or playground safe during the day"
 national_geographical_coverage: Los Angeles County
 computation_units: Percentage
 source_organisation_1: UCLA Center for Health Policy Research
 source_url_1: 'http://ask.chis.ucla.edu/AskCHIS/tools/_layouts/AskChisTool/home.aspx#/results'
+national_indicator_description: >-
+  Proportion of population who answered "Feels safe all of the time" to the
+  question "Do you feel safe in your neighborhood all of the time, most of the
+  time, some of the time, or none of the time?"
+data_disaggregation_information: gender
 ---
diff --git a/meta/2-2-1.md b/meta/2-2-1.md
index 9b14638..adea5e5 100644
--- a/meta/2-2-1.md
+++ b/meta/2-2-1.md
@@ -27,7 +27,7 @@ data_show_map: false
 source_active_1: true
 source_url_text_1: >-
   Prevalence of Underweight Among Children and Adolescents Aged 2–19 Years:
-  United States, 1963–1965 Through 2015–2016
+  United States, 1963–1965 Through 2017–2018
 source_active_2: false
 source_url_text_2: Link to Source
 source_active_3: false
@@ -52,5 +52,5 @@ computation_units: Percentage
 source_organisation_1: Centers for Disease Control and Prevention (CDC)
 source_geographical_coverage_1: United States of America
 source_url_1: >-
-  https://www.cdc.gov/nchs/data/hestat/underweight_child_15_16/underweight_child_15_16.pdf
+  https://www.cdc.gov/nchs/data/hestat/underweight-child-17-18/underweight-child.htm
 ---
diff --git a/meta/2-3-2.md b/meta/2-3-2.md
index 4ba2436..33356ea 100644
--- a/meta/2-3-2.md
+++ b/meta/2-3-2.md
@@ -50,3 +50,4 @@ source_geographical_coverage_1: City of Los Angeles
 source_url_1: 'https://factfinder.census.gov'
 data_disaggregation_information: gender
 ---
+The agriculture, forestry, fishing, and hunting industries on average employ less than 8,000 workers out of the approximately 2 million civilian employed population 16 years and over.
\ No newline at end of file
diff --git a/meta/3-2-2.md b/meta/3-2-2.md
index 160cdf7..fba52bb 100644
--- a/meta/3-2-2.md
+++ b/meta/3-2-2.md
@@ -46,4 +46,6 @@ national_geographical_coverage: Los Angeles County
 source_organisation_1: Centers for Disease Control and Prevention (CDC)
 source_geographical_coverage_1: Los Angeles County
 source_url_1: 'https://wonder.cdc.gov/lbd.html'
+data_disaggregation_information: race
+national_indicator_description: Infant deaths from birth to 364 days.
 ---
diff --git a/meta/3-4-3.md b/meta/3-4-3.md
index 08cc128..d7c77a8 100644
--- a/meta/3-4-3.md
+++ b/meta/3-4-3.md
@@ -5,25 +5,22 @@ permalink: /3-4-3/
 sdg_goal: '3'
 data_non_statistical: false
 graph_type: bar
-indicator_name: >-
-  Proportion of adults (ages 18 years and older) with current depression who are
-  receiving counseling from a mental health professional for the disorder
+indicator_definition: NA
+indicator_name: Attempted youth suicide
 indicator_sort_order: 03-04-03
 published: true
 reporting_status: complete
 target: >-
-  By 2030, reduce premature mortality from non-communicable diseases through
-  prevention and treatment and promote mental health and well-being
+  By 2030, reduce by one third premature mortality from non-communicable
+  diseases through prevention and treatment and promote mental health and
+  well-being
 target_id: '3.4'
-graph_title: >-
-  Proportion of adults (ages 18 years and older) with current depression who are
-  receiving counseling from a mental health professional for the disorder
+graph_title: Attempted youth suicide
+un_custodian_agency: NA
+un_designated_tier: NA
 data_show_map: false
 source_active_1: true
-source_url_text_1: >-
-  2018 LA County Health Survey: Percent of Adults (Ages 18 Years and Older) with
-  Current Depression Who Are Receiving Counseling from a Mental Health
-  Professional for the Disorder (M6 - Medical Conditions)
+source_url_text_1: 'Youth Risk Behaviour Surveillance System '
 source_active_2: false
 source_url_text_2: Link to Source
 source_active_3: false
@@ -35,20 +32,20 @@ source_url_text_5: Link to source
 source_active_6: false
 source_url_text_6: Link to source
 title: Untitled
+national_geographical_coverage: Los Angeles County
+computation_units: Total attempted youth suicides
+computation_definitions: >-
+  Actually Attempted Suicide (one or more times during the 12 months before the
+  survey) for high school students between 15 and 18 years old in Los Angeles
+  county disaggregated by sexual orientation categories "Heterosexual", "Gay,
+  Lesbian or Bisexual", and "Not sure".
+source_organisation_1: Center for Disease Control and Prevention
+source_geographical_coverage_1: City of Los Angeles
+source_url_1: >-
+  https://nccd.cdc.gov/youthonline/App/Results.aspx?TT=B&OUT=0&SID=HS&QID=H28&LID=LL&YID=RY&LID2=&YID2=&COL=&ROW1=&ROW2=&HT=&LCT=&FS=&FR=&FG=&FA=&FI=&FP=&FSL=&FRL=&FGL=&FAL=&FIL=&FPL=&PV=&TST=&C1=&C2=&QP=&DP=&VA=CI&CS=Y&SYID=&EYID=&SC=&SO=
+data_disaggregation_information: sexual orientation
+national_indicator_available: Attempted youth suicide
 tags:
   - New
-national_indicator_available: >-
-  Proportion of adults (ages 18 years and older) with current depression who are
-  receiving counseling from a mental health professional for the disorder
-national_indicator_description: >-
-  Conducted every 2-3 years, the Los Angeles County Health Survey is a
-  population based telephone survey that provides information concerning the
-  health of Los Angeles County residents. 
-national_geographical_coverage: Los Angeles County
-computation_units: Percentage
-source_organisation_1: Los Angeles County Department of Public Health (DPH)
-source_geographical_coverage_1: Los Angeles County
-source_url_1: 'http://www.publichealth.lacounty.gov/ha/hasurveyintro.htm'
 goal_meta_link_text: UN metadata
-data_disaggregation_information: 'education, gender, race'
 ---
diff --git a/meta/3-4-4.md b/meta/3-4-4.md
new file mode 100644
index 0000000..81128c6
--- /dev/null
+++ b/meta/3-4-4.md
@@ -0,0 +1,54 @@
+---
+indicator: 3.4.4
+layout: indicator
+permalink: /3-4-4/
+sdg_goal: '3'
+data_non_statistical: false
+graph_type: bar
+indicator_name: >-
+  Proportion of adults (ages 18 years and older) with current depression who are
+  receiving counseling from a mental health professional for the disorder
+indicator_sort_order: 03-04-04
+published: true
+reporting_status: complete
+target: >-
+  By 2030, reduce premature mortality from non-communicable diseases through
+  prevention and treatment and promote mental health and well-being
+target_id: '3.4'
+graph_title: >-
+  Proportion of adults (ages 18 years and older) with current depression who are
+  receiving counseling from a mental health professional for the disorder
+data_show_map: false
+source_active_1: true
+source_url_text_1: >-
+  2018 LA County Health Survey: Percent of Adults (Ages 18 Years and Older) with
+  Current Depression Who Are Receiving Counseling from a Mental Health
+  Professional for the Disorder (M6 - Medical Conditions)
+source_active_2: false
+source_url_text_2: Link to Source
+source_active_3: false
+source_url_3: Link to source
+source_active_4: false
+source_url_text_4: Link to source
+source_active_5: false
+source_url_text_5: Link to source
+source_active_6: false
+source_url_text_6: Link to source
+title: Untitled
+tags:
+  - New
+national_indicator_available: >-
+  Proportion of adults (ages 18 years and older) with current depression who are
+  receiving counseling from a mental health professional for the disorder
+national_indicator_description: >-
+  Conducted every 2-3 years, the Los Angeles County Health Survey is a
+  population based telephone survey that provides information concerning the
+  health of Los Angeles County residents. 
+national_geographical_coverage: Los Angeles County
+computation_units: Percentage
+source_organisation_1: Los Angeles County Department of Public Health (DPH)
+source_geographical_coverage_1: Los Angeles County
+source_url_1: 'http://www.publichealth.lacounty.gov/ha/hasurveyintro.htm'
+goal_meta_link_text: UN metadata
+data_disaggregation_information: 'education, gender, race'
+---
diff --git a/meta/3-5-2.md b/meta/3-5-2.md
index 1c25ff1..444fc37 100644
--- a/meta/3-5-2.md
+++ b/meta/3-5-2.md
@@ -52,3 +52,4 @@ computation_definitions: >-
   Binge drinking is defined as drinking 4 or more drinks for females and 5 or
   more drinks for males on one occasion at least one time in the past month.
 ---
+The data available at the local level is "Percent of adults (ages 18 years and older) who reported binge drinking in the past month".
diff --git a/meta/3-6-1.md b/meta/3-6-1.md
index 5d9a7ef..059da03 100644
--- a/meta/3-6-1.md
+++ b/meta/3-6-1.md
@@ -21,8 +21,8 @@ un_designated_tier: '1'
 data_show_map: false
 source_active_1: true
 source_url_text_1: City Of Los Angeles 2018 Vision Zero Action Plan and Progress Report
-source_active_2: false
-source_url_text_2: Link to Source
+source_active_2: true
+source_url_text_2: 'CDC WONDER 1999-2019: Underlying Cause of Death by Bridged-Race Categories'
 source_active_3: false
 source_url_3: Link to source
 source_active_4: false
@@ -31,12 +31,24 @@ source_active_5: false
 source_url_text_5: Link to source
 source_active_6: false
 source_url_text_6: Link to source
+national_target_line: >-
+  Eliminate traffic deaths in Los Angeles by 2025 - <a
+  href="https://view.joomag.com/vision-zero-los-angeles/0915902001459876247?short"
+  target="_blank">Vision Zero Los Angeles</a>
 title: Untitled
 national_indicator_available: Los Angeles Traffic Fatalities
 computation_units: Number of People
-national_geographical_coverage: City of Los Angeles
+national_geographical_coverage: City of Los Angeles and Los Angeles County
 source_organisation_1: Vision Zero Los Angeles
 source_url_1: 'https://indd.adobe.com/view/a0e9f83f-4c36-4d55-bdfe-0c8597fa72c3'
 wccd_iso_37120_alignment: 'Aligns to WCCD 18.8 - Transportation fatalities per 100,000 population'
 source_geographical_coverage_1: City of Los Angeles
+computation_definitions: >-
+  Los Angeles County data comes from the Centers for Disease Control and
+  Prevention, National Center for Health Statistics. Reported deaths fall under
+  ICD-10 Code V01-V99 (Transport accidents).
+source_organisation_2: Centers for Disease Control and Prevention
+source_geographical_coverage_2: Los Angeles County
+source_url_2: 'https://wonder.cdc.gov/ucd-icd10.html'
+data_disaggregation_information: race
 ---
diff --git a/meta/3-7-1.md b/meta/3-7-1.md
index 1765e46..d1ac061 100644
--- a/meta/3-7-1.md
+++ b/meta/3-7-1.md
@@ -18,12 +18,12 @@ target: >-
   services, including for family planning, information and education, and the
   integration of reproductive health into national strategies and programmes
 target_id: '3.7'
-graph_title: Proportion of women who use birth control to prevent pregnancy
+graph_title: Birth control use to prevent pregnancy among sexually active females
 un_custodian_agency: DESA Population Division
 un_designated_tier: '1'
 data_show_map: false
 source_active_1: true
-source_url_text_1: AskCHIS
+source_url_text_1: California Health Interview Survey
 source_active_2: false
 source_url_text_2: Link to Source
 source_active_3: false
@@ -35,15 +35,15 @@ source_url_text_5: Link to source
 source_active_6: false
 source_url_text_6: Link to source
 title: Untitled
-national_indicator_available: Use of birth control to prevent pregnancy
+national_indicator_available: Birth control use to prevent pregnancy among sexually active females
 national_geographical_coverage: Los Angeles County
 computation_units: Percentage
 source_organisation_1: UCLA Center for Health Policy Research
 source_geographical_coverage_1: Los Angeles County
 source_url_1: 'http://ask.chis.ucla.edu/AskCHIS/tools/_layouts/AskChisTool/home.aspx#/results'
-computation_definitions: >-
-  The percentage of women of reproductive age (15-49 years) who desire either to
-  have no (additional) children or to postpone the next child and who are
-  currently using a modern method of contraception. The indicator is also
-  referred to as the demand for family planning satisfied with modern methods.
+national_indicator_description: >-
+  Respondents were asked: "Are you or your male sex partner currently using a
+  birth control method to prevent pregnancy? This includes male or female
+  sterilization." Asked of sexually active heterosexual women 18-44 years who
+  are not currently pregnant.
 ---
diff --git a/meta/3-9-4.md b/meta/3-9-4.md
index a990b31..0b39ae3 100644
--- a/meta/3-9-4.md
+++ b/meta/3-9-4.md
@@ -5,7 +5,7 @@ permalink: /3-9-4/
 sdg_goal: '3'
 data_non_statistical: false
 graph_type: bar
-indicator_name: Proportion of population with asthma
+indicator_name: Childhood asthma emergency department visits
 indicator_sort_order: 03-09-04
 published: true
 reporting_status: complete
@@ -13,10 +13,10 @@ target: >-
   By 2030, substantially reduce the number of deaths and illnesses from
   hazardous chemicals and air, water and soil pollution and contamination
 target_id: '3.9'
-graph_title: Proportion of population with asthma
+graph_title: Childhood asthma emergency department visits
 data_show_map: false
 source_active_1: true
-source_url_text_1: '2015, 2018 Los Angeles County Health Survey'
+source_url_text_1: California Health and Human Services Open Data Portal
 source_active_2: false
 source_url_text_2: Link to Source
 source_active_3: false
@@ -28,22 +28,23 @@ source_url_text_5: Link to source
 source_active_6: false
 source_url_text_6: Link to source
 title: Untitled
-national_indicator_available: Proportion of population currently with asthma
+national_indicator_available: Childhood asthma emergency department visits
 national_geographical_coverage: Los Angeles County
-computation_units: Percentage
+computation_units: 'Rate per 10,000'
 tags:
   - New
-source_organisation_1: Los Angeles County Department of Public Health (DPH)
+source_organisation_1: California Health and Human Services (CHHS)
 source_geographical_coverage_1: Los Angeles County
-source_url_1: 'http://www.publichealth.lacounty.gov/ha/hasurveyintro.htm'
+source_url_1: >-
+  https://data.chhs.ca.gov/dataset/asthma-ed-visit-rates-lghc-indicator-07/resource/781708cb-7b25-4967-b760-54b2a4b8cfed?filters=Geography%3ALos+Angeles%7CStrata%3ATotal+Population%7CAge+Group%3AUnder+18
 goal_meta_link_text: UN metadata
 computation_definitions: >-
-  The Los Angeles County Health Survey is a population based telephone survey
-  that provides information concerning the health of Los Angeles County
-  residents. The data are used for assessing health-related needs of the
-  population, for program planning and policy development, and for program
-  evaluation. The relatively large sample size allows users to obtain health
-  indicator data for large demographic subgroups and across geographic regions
-  of the County, including Service Planning Areas and Health Districts.
-data_disaggregation_information: 'disability, gender, race'
+  This dataset contains counts and rates (per 10,000 residents) of asthma
+  (ICD9-CM, 493.0-493.9) emergency department visits among Los Angeles County
+  residents ages 0-17. The data are derived from the Office of Statewide Health
+  Planning and Development emergency department databases. These data include
+  emergency department visits from all licensed hospitals in California. These
+  data are based only on primary discharge diagnosis codes (ICD9-CM).
+data_disaggregation_information: 'gender, race'
+national_target_line: '28 per 10,000 (Let''s Get Healthy California)'
 ---
diff --git a/meta/3-a-1.md b/meta/3-a-1.md
index 16c71c3..460771e 100644
--- a/meta/3-a-1.md
+++ b/meta/3-a-1.md
@@ -17,14 +17,14 @@ target: >-
   3.a Strengthen the implementation of the World Health Organization Framework
   Convention on Tobacco Control in all countries, as appropriate
 target_id: 3.a
-graph_title: Prevalence of current tobacco use among persons aged 18 years and older
+graph_title: Percentage of adults who are current smokers
 un_custodian_agency: >-
   World Health Organization (WHO), Framework Convention on Tobacco Control
   (FCTC)
 un_designated_tier: '1'
 data_show_map: false
 source_active_1: true
-source_url_text_1: 'http://www.publichealth.lacounty.gov/ha/hasurveyintro.htm'
+source_url_text_1: California Health Interview Survey
 source_active_2: false
 source_url_text_2: Link to Source
 source_active_3: false
@@ -36,19 +36,13 @@ source_url_text_5: Link to source
 source_active_6: false
 source_url_text_6: Link to source
 title: Untitled
-national_indicator_available: >-
-  Percent of adults (18+ years old) who reported using an electronic cigarette
-  in the past month and percent of adults (18+ years old) who are cigarette
-  smokers. 
 national_geographical_coverage: Los Angeles County
 computation_units: Percentage
-computation_definitions: >-
-  Cigarette smokers are those who have reported smoking at least 100 lifetime
-  cigarettes and currently smoke.
-data_disaggregation_information: 'age, eduation, gender, race'
-source_organisation_1: Los Angeles County Department of Public Health (DPH)
+data_disaggregation_information: 'gender, race'
 source_geographical_coverage_1: Los Angeles County
 source_url_1: >-
-  2015, 2018 Los Angeles County Health Survey: Smoking Status and E-cigarette
-  Use
+  https://ask.chis.ucla.edu/AskCHIS/tools/_layouts/AskChisTool/home.aspx#/results
+national_indicator_available: Percentage of adults who are current smokers
+computation_definitions: 'Smoking status - current, former, and never.'
+source_organisation_1: UCLA Center for Health Policy Research
 ---
diff --git a/meta/3-b-3.md b/meta/3-b-3.md
index acdbfa8..b55e08c 100644
--- a/meta/3-b-3.md
+++ b/meta/3-b-3.md
@@ -50,10 +50,10 @@ source_geographical_coverage_1: City of Los Angeles
 source_url_1: >-
   https://data.lacounty.gov/Parcel-/Assessor-Parcels-Data-2006-thru-2019/9trm-uz8i
 ---
-**Proxy indicator:** Hospitals in the United States are heavily regulated by various national and state agencies. All hospitals in Los Angeles must abide by these rules. This proxy indicator reports the number of hospitals in Los Angeles, all meeting the necessary standards. 
+Hospitals in the United States are heavily regulated by various national and state agencies. All hospitals in Los Angeles must abide by these rules. This proxy indicator reports the number of hospitals in Los Angeles, all meeting the necessary standards. 
 
 ## Relevant Policies
 
 At the national level, [four federal agencies](https://www.aha.org/system/files/2018-01/info-regulatory-burden-federal-agencies.pdf) account for 629 regulatory requirements that health systems, hospitals and post-acute care providers must comply with, yet providers are subject to regulation and oversight from many other sources. These are the [Centers for Medicare and Medicaid Services](https://www.cms.gov/Regulations-and-Guidance/Regulations-and-Guidance), the [Office of Inspector General](https://oig.hhs.gov/compliance/), the [Office for Civil Rights](https://www.hhs.gov/civil-rights/for-providers/laws-regulations-guidance/laws/index.html), and the Office for the [National Coordination for Health IT](https://www.healthit.gov/). 
 
-The [California Department of Public Health’s (CDPH) Licensing and Certification Division (L&C)](https://www.cdph.ca.gov/Programs/CHCQ/LCP/Pages/LandCProgramHome.aspx) is responsible for the licensure, regulation, inspection, and certification of health care facilities and certain health care professionals in California.
\ No newline at end of file
+The [California Department of Public Health’s (CDPH) Licensing and Certification Division (L&C)](https://www.cdph.ca.gov/Programs/CHCQ/LCP/Pages/LandCProgramHome.aspx) is responsible for the licensure, regulation, inspection, and certification of health care facilities and certain health care professionals in California.
diff --git a/meta/3-d-2.md b/meta/3-d-2.md
new file mode 100644
index 0000000..5078d90
--- /dev/null
+++ b/meta/3-d-2.md
@@ -0,0 +1,40 @@
+---
+indicator: 3.d.2
+layout: indicator
+permalink: /3-d-2/
+sdg_goal: '3'
+data_non_statistical: true
+goal_meta_link: 'https://unstats.un.org/sdgs/metadata/files/Metadata-03-0D-01.pdf'
+goal_meta_link_text: United Nations Sustainable Development Goals Metadata (pdf 865kB)
+graph_type: line
+indicator_name: >-
+  Percentage of bloodstream infections due to selected antimicrobial-resistant organisms
+indicator_sort_order: 03-dd-02
+published: true
+reporting_status: notstarted
+target: >-
+  Strengthen the capacity of all countries, in particular developing countries,
+  for early warning, risk reduction and management of national and global health
+  risks
+target_id: 3.d
+un_custodian_agency: WHO
+un_designated_tier: '1'
+data_show_map: false
+source_active_1: true
+source_url_text_1: Public Health Emergency Preparedness Cooperative Agreement (PHEP) Program
+source_active_2: false
+source_url_text_2: Link to Source
+source_active_3: false
+source_url_3: Link to source
+source_active_4: false
+source_url_text_4: Link to source
+source_active_5: false
+source_url_text_5: Link to source
+source_active_6: false
+source_url_text_6: Link to source
+title: Untitled
+source_organisation_1: Los Angeles County Department of Public Health (DPH)
+source_geographical_coverage_1: County of Los Angeles
+source_url_1: 'https://www.cdc.gov/cpr/pubs-links/2018/documents/LAC2018.pdf'
+tags:
+---
diff --git a/meta/4-1-1.md b/meta/4-1-1.md
index e43ea6b..207a177 100644
--- a/meta/4-1-1.md
+++ b/meta/4-1-1.md
@@ -18,7 +18,9 @@ target: >-
   By 2030, ensure that all children complete free, equitable and quality primary
   and secondary education leading to relevant and effective learning outcomes
 target_id: '4.1'
-graph_title: 'Smarter Balanced English Language Arts: Percent Met or Exceeded Standards'
+graph_title: >-
+  Smarter Balanced English Language Arts and Math: Percent Met or Exceeded
+  Standards
 un_custodian_agency: UNESCO Institute for Statistics
 un_designated_tier: '2'
 data_show_map: false
@@ -35,22 +37,24 @@ source_url_text_5: Link to source
 source_active_6: false
 source_url_text_6: Link to source
 title: Untitled
-national_indicator_available: 'Smarter Balanced English Language Arts: Percent Met or Exceeded Standards'
+national_indicator_available: >-
+  "Smarter Balanced English Language Arts: Percent Met or Exceeded Standards"
+  and "Smarter Balanced Math: Percent Met or Exceeded Standards"
 national_indicator_description: >-
   The California Assessment of Student Performance and Progress (CAASPP)
   administration consists of the Smarter Balanced English-language arts/literacy
   (ELA) and mathematics tests and the California Alternative Assessment (CAA)
   English Language Arts (ELA) and mathematics tests. The indicator displays the
   percentage of students that met or exceed standards on the Smarter Balanced
-  English Language Arts test.
-national_geographical_coverage: >-
-  Los Angeles Unified School District's (LAUSD) boundaries stretch across 720
-  square miles and include the City of Los Angeles as well as all or parts of 31
-  municipalities and several unincorporated regions of Southern California.
+  English Language Arts test and the Smarter Balanced Math test.
 computation_units: Percentage
 source_organisation_1: Los Angeles Unified School District (LAUSD)
 source_url_1: 'https://my.lausd.net/opendata/dashboard'
 source_geographical_coverage_1: Los Angeles Unified School District
-wccd_iso_37120_alignment: Aligns to WCCD 6.6- Percentage of school-aged population enrolled in schools
 data_disaggregation_information: 'gender, grade level, poverty status'
+computation_definitions: >-
+  Los Angeles Unified School District's (LAUSD) boundaries stretch across 720
+  square miles and include the City of Los Angeles as well as all or parts of 31
+  municipalities and several unincorporated regions of Southern California.
+national_geographical_coverage: Los Angeles Unified School District
 ---
diff --git a/meta/4-5-1.md b/meta/4-5-1.md
index 43fb3b5..5883edf 100644
--- a/meta/4-5-1.md
+++ b/meta/4-5-1.md
@@ -1,27 +1,46 @@
 ---
-data_non_statistical: false
-goal_meta_link: https://unstats.un.org/sdgs/metadata/files/Metadata-04-05-01.pdf
+indicator: 4.5.1
+layout: indicator
+permalink: /4-5-1/
+sdg_goal: '4'
+data_non_statistical: true
+goal_meta_link: 'https://unstats.un.org/sdgs/metadata/files/Metadata-04-05-01.pdf'
 goal_meta_link_text: United Nations Sustainable Development Goals Metadata (pdf 210kB)
 graph_type: line
-indicator: 4.5.1
-indicator_name: Parity indices (female/male, rural/urban, bottom/top wealth quintile
-  and others such as disability status, indigenous peoples and conflict-affected,
-  as data become available) for all education indicators on this list that can be
+indicator_name: >-
+  Parity indices (female/male, rural/urban, bottom/top wealth quintile and
+  others such as disability status, indigenous peoples and conflict-affected, as
+  data become available) for all education indicators on this list that can be
   disaggregated
 indicator_sort_order: 04-05-01
-layout: indicator
-permalink: /4-5-1/
 published: true
-reporting_status: notstarted
-sdg_goal: '4'
-target: By 2030, eliminate gender disparities in education and ensure equal access
-  to all levels of education and vocational training for the vulnerable, including
-  persons with disabilities, indigenous peoples and children in vulnerable situations
+reporting_status: complete
+target: >-
+  By 2030, eliminate gender disparities in education and ensure equal access to
+  all levels of education and vocational training for the vulnerable, including
+  persons with disabilities, indigenous peoples and children in vulnerable
+  situations
 target_id: '4.5'
-graph_title: Parity indices (female/male, rural/urban, bottom/top wealth quintile and others
-  such as disability status, indigenous peoples and conflict-affected, as data become
-  available) for all education indicators on this list that can be disaggregated
-un_custodian_agency: United Nations Educational, Scientific and Cultural Organization
-  (UNESCO)
+graph_title: >-
+  Parity indices (female/male, rural/urban, bottom/top wealth quintile and
+  others such as disability status, indigenous peoples and conflict-affected, as
+  data become available) for all education indicators on this list that can be
+  disaggregated
+un_custodian_agency: 'United Nations Educational, Scientific and Cultural Organization (UNESCO)'
 un_designated_tier: 1/2/3
+data_show_map: false
+source_active_1: true
+source_url_text_1: Link to source
+source_active_2: false
+source_url_text_2: Link to Source
+source_active_3: false
+source_url_3: Link to source
+source_active_4: false
+source_url_text_4: Link to source
+source_active_5: false
+source_url_text_5: Link to source
+source_active_6: false
+source_url_text_6: Link to source
+title: Untitled
 ---
+Where data is available, disaggregation by gender, race/ethnicity, poverty status are added directly in the indicator reporting. We will continue to explore data sources that allow for disaggregation and parity reporting.
\ No newline at end of file
diff --git a/meta/4-b-2.md b/meta/4-b-2.md
new file mode 100644
index 0000000..4b34bd2
--- /dev/null
+++ b/meta/4-b-2.md
@@ -0,0 +1,43 @@
+---
+indicator: 4.b.2
+layout: indicator
+permalink: /4-b-2/
+sdg_goal: '4'
+data_non_statistical: false
+graph_type: bar
+indicator_name: Number of students participating in the Los Angeles College Promise program
+indicator_sort_order: 04-bb-02
+published: true
+reporting_status: complete
+target: >-
+  By 2020, substantially expand globally the number of scholarships available to
+  developing countries, in particular least developed countries, small island
+  developing States and African countries, for enrolment in higher education,
+  including vocational training and information and communications technology,
+  technical, engineering and scientific programmes, in developed countries and
+  other developing countries
+target_id: 4.b
+un_designated_tier: '1'
+data_show_map: false
+source_active_1: true
+source_url_text_1: Los Angeles College Promise Dashboard
+source_active_2: false
+source_url_text_2: Link to Source
+source_active_3: false
+source_url_3: Link to source
+source_active_4: false
+source_url_text_4: Link to source
+source_active_5: false
+source_url_text_5: Link to source
+source_active_6: false
+source_url_text_6: Link to source
+title: Untitled
+national_indicator_available: Number of students participating in the Los Angeles College Promise program
+graph_title: Number of students participating in the Los Angeles College Promise program
+source_organisation_1: Los Angeles Community College District
+source_geographical_coverage_1: City of Los Angeles
+source_url_1: >-
+  https://app.powerbi.com/view?r=eyJrIjoiYWQwMDhjMDItYzA1My00NTYzLWE4ODUtNTc5ZTE1NjFmZDFhIiwidCI6IjBiNzEyNjFhLTQ5NWYtNGVhOS05OTExLWRhODQ0Yjk0MDJlZiIsImMiOjZ9
+goal_meta_link_text: UN metadata
+---
+The [Los Angeles College Promise](http://lacollegepromise.org/about.html) (LACP) serves first-time college students with a comprehensive strategy designed to support students to complete a higher education degree and/or a workforce certificate. LACP students receive waived tuition for two years of full-time college, priority enrollment at any of Los Angeles Community College District's nine college, and a dedicated support team providing an array of academic and student support services.
diff --git a/meta/4-c-1.md b/meta/4-c-1.md
new file mode 100644
index 0000000..42101a3
--- /dev/null
+++ b/meta/4-c-1.md
@@ -0,0 +1,37 @@
+---
+indicator: 4.c.1
+layout: indicator
+permalink: /4-c-1/
+sdg_goal: '4'
+data_non_statistical: true
+goal_meta_link: 'https://unstats.un.org/sdgs/metadata/files/Metadata-04-0C-01.pdf'
+goal_meta_link_text: United Nations Sustainable Development Goals Metadata (PDF 211 KB)
+graph_type: line
+indicator_definition: >-
+  Proportion of teachers with the minimum required qualifications, by education level
+indicator_name: >-
+  Proportion of teachers with the minimum required qualifications, by education level
+indicator_sort_order: 04-cc-01
+published: true
+reporting_status: notstarted
+target: >-
+  By 2030, substantially increase the supply of qualified teachers
+target_id: 4.c
+un_custodian_agency: UNESCO Institute for Statistics (UNESCO-UIS)
+un_designated_tier: '1'
+data_show_map: false
+source_active_1: true
+source_url_text_1: Link to source
+source_active_2: false
+source_url_text_2: Link to Source
+source_active_3: false
+source_url_3: Link to source
+source_active_4: false
+source_url_text_4: Link to source
+source_active_5: false
+source_url_text_5: Link to source
+source_active_6: false
+source_url_text_6: Link to source
+title: Untitled
+---
+
diff --git a/meta/5-2-1.md b/meta/5-2-1.md
index 5e4f02d..b37147e 100644
--- a/meta/5-2-1.md
+++ b/meta/5-2-1.md
@@ -32,8 +32,8 @@ un_custodian_agency: >-
 un_designated_tier: '2'
 data_show_map: false
 source_active_1: true
-source_url_text_1: Crime Data from 2010 to Present
-source_active_2: false
+source_url_text_1: Crime Data from 2010 to 2019
+source_active_2: true
 source_url_text_2: Link to Source
 source_active_3: false
 source_url_3: Link to source
@@ -44,11 +44,26 @@ source_url_text_5: Link to source
 source_active_6: false
 source_url_text_6: Link to source
 title: Untitled
-national_indicator_available: Cases of Intimate Partner Violence in Los Angeles County
+national_indicator_available: >-
+  Incidents of reported intimate partner crime recorded by the Los Angeles
+  Police Department in the City of Los Angeles.
 national_indicator_description: Total number of intimate partner assaults reported
 national_geographical_coverage: City of Los Angeles
 source_url_1: 'https://data.lacity.org/A-Safe-City/Crime-Data-from-2010-to-Present/63jg-8b9z'
 source_geographical_coverage_1: City of Los Angeles
 computation_units: Total number
 source_organisation_1: Los Angeles Police Department (LAPD)
+computation_definitions: >-
+  This dataset reflects incidents of crime in the City of Los Angeles dating
+  back to 2010. This data is transcribed from original crime reports that are
+  typed on paper and therefore there may be some inaccuracies within the data.
+  Data reported here was filtered from the data source for all crime reports
+  wiht Crime Code "Intimate Partner - Aggravated Assault" and "Intimate Partner
+  - Simple Assault".
+data_disaggregation_information: Crime type
+source_organisation_2: Los Angeles Police Department
+source_geographical_coverage_2: City of Los Angeles
+source_url_2: >-
+  https://data.lacity.org/Public-Safety/Crime-Data-from-2020-to-Present/2nrs-mtv8
+source_release_date_2: Crime Data from 2020 to Present
 ---
diff --git a/meta/5-3-1.md b/meta/5-3-1.md
index 0474728..4313ba3 100644
--- a/meta/5-3-1.md
+++ b/meta/5-3-1.md
@@ -3,7 +3,7 @@ indicator: 5.3.1
 layout: indicator
 permalink: /5-3-1/
 sdg_goal: '5'
-data_non_statistical: false
+data_non_statistical: true
 goal_meta_link_text: United Nations Sustainable Development Goals Metadata (PDF 207 KB)
 graph_type: line
 indicator_name: >-
@@ -11,19 +11,16 @@ indicator_name: >-
   15 and before age 18
 indicator_sort_order: 05-03-01
 published: true
-reporting_status: notstarted
+reporting_status: complete
 target: >-
   Eliminate all harmful practices, such as child, early and forced marriage and
   female genital mutilation
 target_id: '5.3'
-graph_title: >-
-  Proportion of women aged 20-24 years who were married or in a union before age
-  15 and before age 18
 un_custodian_agency: United Nations Children's Fund (UNICEFF)
 un_designated_tier: '1'
 data_show_map: false
 source_active_1: true
-source_url_text_1: Link to source
+source_url_text_1: Types of Marriage Licenses
 source_active_2: false
 source_url_text_2: Link to Source
 source_active_3: false
@@ -36,4 +33,13 @@ source_active_6: false
 source_url_text_6: Link to source
 title: Untitled
 goal_meta_link: 'https://unstats.un.org/sdgs/metadata/files/Metadata-05-03-01.pdf'
+tags:
+  - Non-Statistical
+source_organisation_1: California Department of Public Health
+source_geographical_coverage_1: California
+source_url_1: 'https://www.cdph.ca.gov/Programs/CHSI/Pages/Types-of-Marriage-Licenses-.aspx'
 ---
+**Non-Statistical Indicator**
+
+## Relevant Policies
+Los Angeles County and the State of California have no minimum age requirement for marriage. Persons under 18 may get a marriage license with written consent from a parent or legal guardian and permission from a California Superior Court Judge. In 2021, State Assemblymember Cottie Petrie-Norris introduced a bill ([AB 1286](https://leginfo.legislature.ca.gov/faces/billNavClient.xhtml?bill_id=202120220AB1286)) requiring counties to report the number of child marriages to the state on a quarterly basis.
diff --git a/meta/5-5-2.md b/meta/5-5-2.md
index 7a0f843..7d36a2a 100644
--- a/meta/5-5-2.md
+++ b/meta/5-5-2.md
@@ -35,19 +35,17 @@ source_url_text_6: Link to source
 title: Untitled
 national_geographical_coverage: City of Los Angeles
 source_geographical_coverage_1: City of Los Angeles
-source_url_1: data.census.gov
+source_url_1: 'https://data.census.gov'
 source_url_2: >-
   https://www2.census.gov/programs-surveys/acs/tech_docs/code_lists/2019_ACS_Code_Lists.pdf
 source_geographical_coverage_2: United States
 source_periodicity_3: Annual
-computation_units: Percentage and median income (in 2019 inflation-adjusted dollars)
+computation_units: Percentage
 source_organisation_1: United States Census Bureau
 source_organisation_2: United States Census Bureau
 wccd_iso_37120_alignment: Aligns to WCCD 11.3 - Percentage of Women Employed in the City Gov’t Workforce
 graph_title: Proportion of women in managerial positions
-national_indicator_description: >-
-  Proportion of women in management occupations and median earnings in
-  management occupations by gender.
+national_indicator_description: Proportion of women in management occupations
 computation_definitions: >-
   Management Occupations include: chief executives; general and operations
   managers; legislators; advertising and promotions managers; marketing
@@ -63,5 +61,5 @@ computation_definitions: >-
   superintendents; property, real estate, and community association managers;
   social and community service managers; emergency management directors;
   personal service managers, all others; managers, all others.
-data_disaggregation_information: gender
+source_url_3: Link to source
 ---
diff --git a/meta/5-5-2a.md b/meta/5-5-2a.md
new file mode 100644
index 0000000..f885440
--- /dev/null
+++ b/meta/5-5-2a.md
@@ -0,0 +1,65 @@
+---
+indicator: 5.5.2a
+layout: indicator
+permalink: /5-5-2a/
+sdg_goal: '5'
+data_non_statistical: false
+graph_type: bar
+indicator_name: Median earnings in management occupations by gender
+indicator_sort_order: 05-05-2a
+published: true
+reporting_status: complete
+target: >-
+  Ensure women’s full and effective participation and equal opportunities for
+  leadership at all levels of decision-making in political, economic and public
+  life
+target_id: '5.5'
+un_designated_tier: '1'
+data_show_map: false
+source_active_1: true
+source_url_text_1: >-
+  American Community Survey 1-Year Estimates 2012-2019: Occupation and Sex for
+  the Civilian Employed Population 16 Years and Over (S2401)
+source_active_2: true
+source_url_text_2: American Community Survey and Puerto Rico Community Survey 2019 Code List
+source_active_3: false
+source_active_4: false
+source_url_text_4: Link to source
+source_active_5: false
+source_url_text_5: Link to source
+source_active_6: false
+source_url_text_6: Link to source
+title: Untitled
+national_geographical_coverage: City of Los Angeles
+source_geographical_coverage_1: City of Los Angeles
+source_url_1: 'https://data.census.gov'
+source_url_2: >-
+  https://www2.census.gov/programs-surveys/acs/tech_docs/code_lists/2019_ACS_Code_Lists.pdf
+source_geographical_coverage_2: United States
+source_periodicity_3: Annual
+computation_units: Median income (in 2019 inflation-adjusted dollars)
+source_organisation_1: United States Census Bureau
+source_organisation_2: United States Census Bureau
+wccd_iso_37120_alignment: Aligns to WCCD 11.3 - Percentage of Women Employed in the City Gov’t Workforce
+graph_title: Proportion of women in managerial positions
+national_indicator_description: Median earnings in management occupations by gender
+computation_definitions: >-
+  Management Occupations include: chief executives; general and operations
+  managers; legislators; advertising and promotions managers; marketing
+  managers; sales managers; public relations and fundraising managers;
+  administrative services managers; financial managers; compensation and
+  benefits managers; human resources managers; training and development
+  managers; industrial production managers; puchasing managers; transportation,
+  storage, and distribution managers; farmers, ranchers, and other agricultural
+  managers; construction managers; education and childcare administrators;
+  architectural and engineering managers; food service managers; funeral home
+  managers; entertainment and recreation managers; lodging managers; medical and
+  health services managers; natural sciences managers; postmasters and mail
+  superintendents; property, real estate, and community association managers;
+  social and community service managers; emergency management directors;
+  personal service managers, all others; managers, all others.
+data_disaggregation_information: gender
+source_url_3: Link to source
+tags:
+  - New
+---
diff --git a/meta/5-6-1.md b/meta/5-6-1.md
index 64f47b3..e88bdf3 100644
--- a/meta/5-6-1.md
+++ b/meta/5-6-1.md
@@ -6,27 +6,25 @@ sdg_goal: '5'
 data_non_statistical: false
 goal_meta_link: 'https://unstats.un.org/sdgs/metadata/files/Metadata-05-06-01.pdf'
 goal_meta_link_text: United Nations Sustainable Development Goals Metadata (pdf 634kB)
-graph_type: line
+graph_type: bar
 indicator_name: >-
   Proportion of women aged 15-49 years who make their own informed decisions
   regarding sexual relations, contraceptive use and reproductive health care
 indicator_sort_order: 05-06-01
 published: true
-reporting_status: notstarted
+reporting_status: complete
 target: >-
   Ensure universal access to sexual and reproductive health and reproductive
   rights as agreed in accordance with the Programme of Action of the
   International Conference on Population and Development and the Beijing
   Platform for Action and the outcome documents of their review conferences
 target_id: '5.6'
-graph_title: >-
-  Proportion of women aged 15-49 years who make their own informed decisions
-  regarding sexual relations, contraceptive use and reproductive health care
+graph_title: Birth control use to prevent pregnancy among sexually active females
 un_custodian_agency: UNFPA
 un_designated_tier: '2'
 data_show_map: false
 source_active_1: true
-source_url_text_1: WCCD 12.3 - Number of physicians per 100k pop
+source_url_text_1: California Health Interview Survey
 source_active_2: false
 source_url_text_2: Link to Source
 source_active_3: false
@@ -39,8 +37,15 @@ source_active_6: false
 source_url_text_6: Link to source
 title: Untitled
 WCCD / International Organization for Standardization (ISO) 37120 Alignment: Aligns to WCCD 12.3 - Number of Physicians per 100k population
-source_organisation_1: World Council on City Data
-source_geographical_coverage_1: City of Los Angeles
-source_url_1: open.dataforcities.org
-wccd_iso_37120_alignment: Aligns to WCCD 12.3 - Number of Physicians per 100k population
+source_organisation_1: UCLA Center for Health Policy Research
+source_geographical_coverage_1: Los Angeles County
+source_url_1: 'http://ask.chis.ucla.edu/AskCHIS/tools/_layouts/AskChisTool/home.aspx#/results'
+national_indicator_available: Birth control use to prevent pregnancy among sexually active females
+national_geographical_coverage: Los Angeles County
+computation_units: percentage
+national_indicator_description: >-
+  Respondents were asked: "Are you or your male sex partner currently using a
+  birth control method to prevent pregnancy? This includes male or female
+  sterilization." Asked of sexually active heterosexual women 18-44 years who
+  are not currently pregnant.
 ---
diff --git a/meta/6-2-1.md b/meta/6-2-1.md
index 81e0693..479bb62 100644
--- a/meta/6-2-1.md
+++ b/meta/6-2-1.md
@@ -41,7 +41,7 @@ source_url_text_6: Link to source
 title: Untitled
 source_organisation_1: United States Census Bureau
 source_geographical_coverage_1: City of Los Angeles
-source_url_1: data.census.gov
+source_url_1: 'https://data.census.gov'
 national_geographical_coverage: City of Los Angeles
 computation_units: Percentage
 national_indicator_available: Proportion of households with complete plumbing facilities
diff --git a/meta/6-4-1.md b/meta/6-4-1.md
index b3551ef..0555d86 100644
--- a/meta/6-4-1.md
+++ b/meta/6-4-1.md
@@ -22,7 +22,7 @@ un_custodian_agency: FAO
 un_designated_tier: '2'
 data_show_map: false
 source_active_1: true
-source_url_text_1: 2015-2018 LADWP Briefing Book
+source_url_text_1: 2015-2021 LADWP Briefing Books
 source_active_2: false
 source_url_text_2: Link to Source
 source_active_3: false
@@ -42,5 +42,5 @@ national_geographical_coverage: City of Los Angeles
 computation_units: Gallons per capita per day and Million gallons per day
 source_organisation_1: Los Angeles Department of Water and Power (LADWP)
 source_geographical_coverage_1: City of Los Angeles
-source_url_1: 'https://ladwp.response.news/category/publications-briefing-book-irp/page/2/'
+source_url_1: 'https://www.ladwpnews.com/category/briefing-book/'
 ---
diff --git a/meta/6-4-2.md b/meta/6-4-2.md
index d094bbf..46e82d8 100644
--- a/meta/6-4-2.md
+++ b/meta/6-4-2.md
@@ -24,7 +24,7 @@ un_custodian_agency: FAO
 un_designated_tier: '1'
 data_show_map: false
 source_active_1: true
-source_url_text_1: 2015-2018 LADWP Briefing Book
+source_url_text_1: 2015-2020 LADWP Briefing Books
 source_active_2: false
 source_url_text_2: Link to Source
 source_active_3: false
@@ -35,12 +35,20 @@ source_active_5: false
 source_url_text_5: Link to source
 source_active_6: false
 source_url_text_6: Link to source
+national_target_line: >-
+  Source 70% of L.A.’s water locally and capture 150,000 acre ft/yr of
+  stormwater by 2035  Recycle 100% of all wastewater for beneficial reuse by
+  2035 - <a
+  href="https://plan.lamayor.org/sites/default/files/pLAn_2019_final.pdf"
+  target="_blank">L.A.'s Green New Deal Sustainable City pLAn</a>
 title: Untitled
 national_indicator_available: Water supply sources
 national_geographical_coverage: City of Los Angeles
 source_organisation_1: Los Angeles Department of Water and Power (LADWP)
 source_geographical_coverage_1: City of Los Angeles
-source_url_1: 'https://ladwp.response.news/category/publications-briefing-book-irp/page/2/'
+source_url_1: 'https://www.ladwpnews.com/category/briefing-book/'
+tags:
+  - Proxy
 ---
 **Proxy indicator:**
-The City of Los Angeles has very little available freshwater resources within City boundaries. This proxy indicator shows the distribution of L.A.'s water supply sources.
\ No newline at end of file
+The City of Los Angeles has very little available freshwater resources within City boundaries. This proxy indicator shows the distribution of L.A.'s water supply sources.
diff --git a/meta/6-5-1.md b/meta/6-5-1.md
index 7e4f590..a924e7e 100644
--- a/meta/6-5-1.md
+++ b/meta/6-5-1.md
@@ -43,4 +43,4 @@ tags:
 ---
 **Non-Statistical Indicator**
 
-The City of Los Angeles is required to adopt an Urban Water Management Plan (UWMP) every five years to comply with California’s Urban Water Management Planning Act (Act). The Act is codified in Sections 10610 through 10656 of the California Water Code (CWC). The 2015 UWMP builds upon the goals and progress made in the 2010 UWMP and continues to serve as the City’s master plan for reliable water supply and resources management. The 2015 UWMP is based on a 25 year planning horizon through 2040.
+The City of Los Angeles is required to adopt an [Urban Water Management Plan](https://www.ladwp.com/ladwp/faces/ladwp/aboutus/a-water/a-w-sourcesofsupply/a-w-sos-uwmpln?_afrLoop=389979723489671&_afrWindowMode=0&_afrWindowId=null#%40%3F_afrWindowId%3Dnull%26_afrLoop%3D389979723489671%26_afrWindowMode%3D0%26_adf.ctrl-state%3Drl49xxjl2_46) (UWMP) every five years to comply with California’s Urban Water Management Planning Act (Act). The Act is codified in Sections 10610 through 10656 of the California Water Code (CWC). The 2015 UWMP builds upon the goals and progress made in the 2010 UWMP and continues to serve as the City’s master plan for reliable water supply and resources management. The 2015 UWMP is based on a 25 year planning horizon through 2040.
diff --git a/meta/6-5-2.md b/meta/6-5-2.md
index 26a7fff..178aa76 100644
--- a/meta/6-5-2.md
+++ b/meta/6-5-2.md
@@ -3,7 +3,7 @@ indicator: 6.5.2
 layout: indicator
 permalink: /6-5-2/
 sdg_goal: '6'
-data_non_statistical: false
+data_non_statistical: true
 goal_meta_link: 'https://unstats.un.org/sdgs/metadata/files/Metadata-06-05-02.pdf'
 goal_meta_link_text: United Nations Sustainable Development Goals Metadata (PDF 4.0 MB)
 graph_type: line
@@ -12,20 +12,17 @@ indicator_name: >-
   water cooperation
 indicator_sort_order: 06-05-02
 published: true
-reporting_status: notstarted
+reporting_status: complete
 target: >-
   By 2030, implement integrated water resources management at all levels,
   including through transboundary cooperation as appropriate
 target_id: '6.5'
-graph_title: >-
-  Proportion of transboundary basin area with an operational arrangement for
-  water cooperation
 un_custodian_agency: >-
   United Nations Education and Scientific Cultural Organisation - Institute for
   Statistics (UNESCO-UIS) United Nations Economic Commission for Europe (UNECE)
 un_designated_tier: '1'
 data_show_map: false
-source_active_1: true
+source_active_1: false
 source_url_text_1: Link to source
 source_active_2: false
 source_url_text_2: Link to Source
@@ -40,3 +37,10 @@ source_url_text_6: Link to source
 title: Untitled
 wccd_iso_37120_alignment: Aligns to WCCD- Percentage of water loss (unaccounted for water)
 ---
+**Non-Statistical Indicator**
+
+**Water Supply**
+The Los Angeles Aqueducts, local groundwater, and supplemental water purchased from the Metropolitan Water District of Southern California (MWD) are the [primary sources of water supply](https://www.ladwp.com/ladwp/faces/ladwp/aboutus/a-water/a-w-sourcesofsupply?_adf.ctrl-state=rl49xxjl2_71&_afrLoop=390821859248607) for the City of Los Angeles (City). The water from the MWD is delivered through the Colorado River Aqueduct and the State Water Project’s California Aqueduct. The LADWP [Urban Water Management Plan](https://www.ladwp.com/cs/groups/ladwp/documents/pdf/mdaw/nzyy/~edisp/opladwpccb762836.pdf) (UWMP) serves as the Water System’s primary resource planning document for achieving compliance with the requirements of California’s Urban Water Management Planning Act.
+
+**Local Watersheds**
+There are five watersheds in Los Angeles: Ballona Creek, Dominguez Channel, Marina Del Rey, Santa Monica Bay, and Upper Los Angeles River. Each of the five watersheds has a a Watershed Management Group that meets on a regular basis to develop an [Enhanced Watershed Management Plan](https://www.lacitysan.org/san/faces/home/portal/s-lsh-wwd/s-lsh-wwd-wp/s-lsh-wwd-wp-ewmp?_afrLoop=10496034447815350&_afrWindowMode=0&_afrWindowId=c8ipmouxn&_adf.ctrl-state=75wbrlfe7_78#!%40%40%3F_afrWindowId%3Dc8ipmouxn%26_afrLoop%3D10496034447815350%26_afrWindowMode%3D0%26_adf.ctrl-state%3D75wbrlfe7_82) (EWMP) for their specific watershed.
\ No newline at end of file
diff --git a/meta/6-a-1.md b/meta/6-a-1.md
index 5b56de9..eb7257f 100644
--- a/meta/6-a-1.md
+++ b/meta/6-a-1.md
@@ -16,11 +16,11 @@ indicator_definition: >-
   with national governments while highlighting total water and sanitation ODA
   disbursements to developing countries over time.
 indicator_name: >-
-  Amount of water- and sanitation-related official development assistance that
-  is part of a government-coordinated spending plan
+  Amount of water- and sanitation-related support for the most underserved
+  communities as part of a government-coordinated spending plan
 indicator_sort_order: 06-aa-01
 published: true
-reporting_status: notapplicable
+reporting_status: complete
 target: >-
   By 2030, expand international cooperation and capacity-building support to
   developing countries in water- and sanitation-related activities and
@@ -32,7 +32,7 @@ un_custodian_agency: >-
   Organisation for Economic Co-operation and Development (OECD)
 un_designated_tier: '1'
 data_show_map: false
-source_active_1: true
+source_active_1: false
 source_url_text_1: Link to source
 source_active_2: false
 source_url_text_2: Link to Source
@@ -45,7 +45,16 @@ source_url_text_5: Link to source
 source_active_6: false
 source_url_text_6: Link to source
 title: Untitled
+tags:
+  - Revised
+  - Non-Statistical
 ---
-**Not Applicable in the local context**
+**revised indicator:** Revised to the local context from the original text: "Amount of water- and sanitation-related official development assistance that is part of a government-coordinated spending plan”
 
-Foreign policy, including official foreign aid, in the United States, is under the purview of the federal government.
+**Non-Statistical Indicator**
+
+**Sanitation Services**
+On October 1, 2019, LASAN’s [Livability Services Division](https://www.lacitysan.org/san/faces/home/portal/s-lsh-wwd/s-lsh-wwd-s/s-lsh-wwd-s-l?_afrLoop=10502278079338666&_afrWindowMode=0&_afrWindowId=null&_adf.ctrl-state=12fnnvbvbp_1#!%40%40%3F_afrWindowId%3Dnull%26_afrLoop%3D10502278079338666%26_afrWindowMode%3D0%26_adf.ctrl-state%3D12fnnvbvbp_5) (LSD) launched the Comprehensive Cleaning and Rapid Engagement (CARE/CARE+) program providing CARE and CARE+ teams for immediate, dedicated service deployed regionally to ensure the highest level of service. These teams conduct citywide encampment clean-ups along with trash, litter/debris, and health hazard and/or safety hazard removal on the City's public rights-of-way. The primary mission of the CARE and CARE+ teams is to deliver services to the individuals experiencing homelessness within their service areas. The Mobile Hygiene Unit (MHU) program launched as part of the redeveloped CARE/CARE+ program model. Starting with three trailer units and quickly growing to six units operating citywide Monday through Friday. The MHU provides restrooms and showers for unsheltered Angelenos. Each client is provided with hygiene products, clean towels, and a clean change of clothes. Additionally, clients receive a hygiene kit with essentials that they can keep with them. Since inception, the MHU program has serviced more than 23,000 guests.
+
+**Water Services**
+The Los Angeles Department of Water and Power has a series of [assistance programs](https://www.ladwp.com/ladwp/faces/wcnav_externalId/r-fa-assist-prog?_adf.ctrl-state=q97ixpmym_4&_afrLoop=396972262145418) including support for income-qualified residental customers and seniors.
diff --git a/meta/6-b-1.md b/meta/6-b-1.md
index 49b9acd..886346a 100644
--- a/meta/6-b-1.md
+++ b/meta/6-b-1.md
@@ -1,23 +1,42 @@
 ---
-data_non_statistical: false
-goal_meta_link: https://unstats.un.org/sdgs/metadata/files/Metadata-06-0B-01.pdf
-goal_meta_link_text: United Nations Sustainable Development Goals Metadata (pdf 428kB)
-graph_type: line
 indicator: 6.b.1
-indicator_name: Proportion of local administrative units with established and operational
-  policies and procedures for participation of local communities in water and sanitation
-  management
-indicator_sort_order: 06-bb-01
 layout: indicator
 permalink: /6-b-1/
-published: true
-reporting_status: notstarted
 sdg_goal: '6'
-target: Support and strengthen the participation of local communities in improving
+data_non_statistical: true
+goal_meta_link: 'https://unstats.un.org/sdgs/metadata/files/Metadata-06-0B-01.pdf'
+goal_meta_link_text: United Nations Sustainable Development Goals Metadata (pdf 428kB)
+graph_type: line
+indicator_name: >-
+  Proportion of local administrative units with established and operational
+  policies and procedures for participation of local communities in water and
+  sanitation management
+indicator_sort_order: 06-bb-01
+published: true
+reporting_status: complete
+target: >-
+  Support and strengthen the participation of local communities in improving
   water and sanitation management
 target_id: 6.b
-graph_title: Proportion of local administrative units with established and operational policies
-  and procedures for participation of local communities in water and sanitation management
-un_custodian_agency: WHO,UNEP, OECD
+un_custodian_agency: 'WHO,UNEP, OECD'
 un_designated_tier: '1'
+data_show_map: false
+source_active_1: false
+source_url_text_1: Link to source
+source_active_2: false
+source_url_text_2: Link to Source
+source_active_3: false
+source_url_3: Link to source
+source_active_4: false
+source_url_text_4: Link to source
+source_active_5: false
+source_url_text_5: Link to source
+source_active_6: false
+source_url_text_6: Link to source
+title: Untitled
+tags:
+  - Non-Statistical
 ---
+**Non-Statistical Indicator**
+
+The Los Angeles Department of Water and Power has a formal [Memorandum of Understanding with Neighborhood Councils](https://www.ladwp.com/ladwp/faces/ladwp/aboutus/a-inourcommunity/a-ioc-neighborhoodcouncils?_adf.ctrl-state=q97ixpmym_38&_afrLoop=397358801318631), committing to regular and ongoing communication about our programs and policies. The DWP-NC MOU Oversight and Advocacy Committees meet every month to share information on the latest on operations, programs and policies.
\ No newline at end of file
diff --git a/meta/7-2-1.md b/meta/7-2-1.md
index 5fe02bd..54052f3 100644
--- a/meta/7-2-1.md
+++ b/meta/7-2-1.md
@@ -23,7 +23,7 @@ un_custodian_agency: >-
 un_designated_tier: '1'
 data_show_map: false
 source_active_1: true
-source_url_text_1: 2015-2018 LADWP Briefing Book
+source_url_text_1: 2015-2020 LADWP Briefing Books
 source_active_2: false
 source_url_text_2: Link to Source
 source_active_3: false
@@ -34,6 +34,10 @@ source_active_5: false
 source_url_text_5: Link to source
 source_active_6: false
 source_url_text_6: Link to source
+national_target_line: >-
+  100% Renewable Energy by 2035 - <a
+  href="https://plan.lamayor.org/sites/default/files/pLAn_2019_final.pdf"
+  target="_blank">L.A.'s Green New Deal Sustainable City pLAn</a>
 title: Untitled
 national_indicator_available: LADWP Power Supply Since 2003
 national_indicator_description: 'LADWP power supply by category '
@@ -47,5 +51,5 @@ wccd_iso_37120_alignment: >-
   share of the city's total energy consumption.
 source_organisation_1: Los Angeles Department of Water and Power (LADWP)
 source_geographical_coverage_1: City of Los Angeles
-source_url_1: 'https://ladwp.response.news/category/publications-briefing-book-irp/page/2/'
+source_url_1: 'https://www.ladwpnews.com/category/briefing-book/'
 ---
diff --git a/meta/7-3-1.md b/meta/7-3-1.md
index 92e2cd6..ec2e4c8 100644
--- a/meta/7-3-1.md
+++ b/meta/7-3-1.md
@@ -13,7 +13,7 @@ published: true
 reporting_status: complete
 target: 'By 2030, double the global rate of improvement in energy efficiency'
 target_id: '7.3'
-graph_title: Energy intensity measured in terms of primary energy and GDP
+graph_title: Total electricity consumption in Millions of kWh (GWh)
 un_custodian_agency: >-
   International Energy Agency (IEA) United Nations Statistics Division (UNSD)
   United Nations' inter-agency mechanism on energy (UN Energy) and the SE4ALL
diff --git a/meta/7-b-1.md b/meta/7-b-1.md
index 5514e29..f53289d 100644
--- a/meta/7-b-1.md
+++ b/meta/7-b-1.md
@@ -38,9 +38,10 @@ source_active_5: false
 source_url_text_5: Link to source
 source_active_6: false
 source_url_text_6: Link to source
+national_target_line: Increase cumulative megawatts of local solar to 900-1,500 MW by 2025 - <a href="https://plan.lamayor.org/sites/default/files/pLAn_2019_final.pdf" target="_blank">L.A.'s Green New Deal Sustainable City pLAn</a>
 title: Untitled
 tags:
   - Revised
 ---
 **Revised indicator:**
-Revised from original indicator language: "Installed renewable energy-generating capacity in developing countries (in watts per capita)". 
\ No newline at end of file
+Revised from original indicator language: "Installed renewable energy-generating capacity in developing countries (in watts per capita)". 
diff --git a/meta/7-b-2.md b/meta/7-b-2.md
new file mode 100644
index 0000000..d2ed5a9
--- /dev/null
+++ b/meta/7-b-2.md
@@ -0,0 +1,44 @@
+---
+indicator: 7.b.2
+layout: indicator
+permalink: /7-b-2/
+sdg_goal: '7'
+data_non_statistical: false
+graph_type: bar
+indicator_name: Number of electric vehicle charging stations installed
+indicator_sort_order: 07-bb-02
+published: true
+reporting_status: complete
+target: >-
+  By 2030, expand infrastructure and upgrade technology for supplying modern and
+  sustainable energy services for all in developing countries, in particular
+  least developed countries, small island developing States and landlocked
+  developing countries, in accordance with their respective programmes of
+  support
+target_id: 7.b
+graph_title: Number of electric vehicle charging stations installed
+data_show_map: false
+source_active_1: true
+source_url_text_1: Link to source
+source_active_2: false
+source_url_text_2: Link to Source
+source_active_3: false
+source_url_3: Link to source
+source_active_4: false
+source_url_text_4: Link to source
+source_active_5: false
+source_url_text_5: Link to source
+source_active_6: false
+source_url_text_6: Link to source
+title: Untitled
+tags:
+  - New
+source_organisation_1: Los Angeles Department of Water and Power
+national_indicator_description: >-
+  Cumulative EV charging stations supported by the City of Los Angeles
+  Department of Water and Power by year of installation
+national_geographical_coverage: City of Los Angeles
+source_geographical_coverage_1: City of Los Angeles
+source_url_1: Data provided by department
+goal_meta_link_text: UN metadata
+---
diff --git a/meta/8-1-1.md b/meta/8-1-1.md
index 58dfe8b..bcea012 100644
--- a/meta/8-1-1.md
+++ b/meta/8-1-1.md
@@ -21,7 +21,7 @@ un_designated_tier: '1'
 data_show_map: false
 source_active_1: true
 source_url_text_1: 'Regional Data: GDP and Personal Income'
-source_active_2: false
+source_active_2: true
 source_active_3: false
 source_active_4: true
 source_url_text_4: >-
@@ -34,8 +34,8 @@ source_url_text_6: Link to source
 title: Untitled
 national_indicator_available: >-
   Gross Domestic Product (GDP) is in millions of current dollars (not adjusted
-  for inflation); annual growth rate of real GDP per capita
-national_geographical_coverage: 'Los Angeles, Long Beach, Anaheim Metropolitan Statistical Area'
+  for inflation); total GDP per capita
+national_geographical_coverage: Los Angeles County
 computation_units: Percent Change
 wccd_iso_37120_alignment: >-
   Aligns to WCCD 4.4 - County Gross Domestic Product (GDP); and WCCD 4.37 -
@@ -43,11 +43,17 @@ wccd_iso_37120_alignment: >-
 source_organisation_1: US Department of Commerce Bureau of Economic Analysis
 source_url_1: >-
   https://apps.bea.gov/iTable/iTable.cfm?isuri=1&reqid=70&step=1#isuri=1&reqid=70&step=1
-source_geographical_coverage_1: 'Los Angeles, Long Beach, Anaheim Metropolitan Statistical Area'
+source_geographical_coverage_1: Los Angeles County
 source_organisation_4: World Council on City Data
 source_url_4: 'http://open.dataforcities.org/'
 source_geographical_coverage_4: City of Los Angeles
-source_url_text_2: Link to Source
-graph_title: Annual growth rate of real GDP per capita
+source_url_text_2: >-
+  American Community Survey 1-Year Estimates: ACS Demographic and Housing
+  Estimates (DP05)
+graph_title: GDP in millions of current dollars and total GDP per capita
 source_url_3: Link to source
+source_organisation_2: U.S. Census Bureau
+source_geographical_coverage_2: Los Angeles County
+source_url_2: 'https://data.census.gov'
+computation_calculations: 'For GDP per capita: total GDP in current dollars/ total population'
 ---
diff --git a/meta/8-2-1.md b/meta/8-2-1.md
index 7d35292..0694cda 100644
--- a/meta/8-2-1.md
+++ b/meta/8-2-1.md
@@ -16,12 +16,12 @@ target: >-
   technological upgrading and innovation, including through a focus on
   high-value added and labour-intensive sectors
 target_id: '8.2'
-graph_title: Annual growth rate of real GDP per employed person (%)
+graph_title: GDP per employed person
 un_custodian_agency: International Labour Organization (ILO)
 un_designated_tier: '1'
 data_show_map: false
 source_active_1: true
-source_url_text_1: GDP of the Los Angeles metro area from 2001 to 2017 (in billion U.S. dollars)
+source_url_text_1: 'Regional Data: GDP and Personal Income'
 source_active_2: true
 source_active_3: false
 source_url_3: Link to source
@@ -32,18 +32,20 @@ source_url_text_5: Link to source
 source_active_6: false
 source_url_text_6: Link to source
 title: Untitled
-computation_definitions: Calculated growth rate of GDP$ per employed person for LA Metro Area
-national_geographical_coverage: 'Los Angeles, Long Beach, Anaheim Metropolitan Statistical Area'
-source_geographical_coverage_1: LA Metro Area
-source_url_1: 'https://www.statista.com/statistics/183822/gdp-of-the-los-angeles-metro-area/'
-source_geographical_coverage_2: LA Metro Area
-source_url_2: >-
-  https://factfinder.census.gov/faces/tableservices/jsf/pages/productview.xhtml?pid=ACS_16_1YR_B24050&prodType=table
+national_geographical_coverage: Los Angeles County
+source_geographical_coverage_1: Los Angeles County
+source_url_1: >-
+  https://apps.bea.gov/iTable/iTable.cfm?isuri=1&reqid=70&step=1#isuri=1&reqid=70&step=1
+source_geographical_coverage_2: Los Angeles County
+source_url_2: 'https://data.census.gov'
 source_organisation_2: United States Census Bureau
 source_url_text_2: >-
-  Industry by Occupation for the Civilian employed population 16 years and
-  over,  Table B24050
+  American Community Survey 1-Year Estimates: Selected Economic Characteristics
+  (DP03)
 computation_units: Percent Change
-source_organisation_1: Statista
+source_organisation_1: US Department of Commerce Bureau of Economic Analysis
 wccd_iso_37120_alignment: Aligns to WCCD- City Product per capita (USD)
+national_indicator_available: GDP per employed person
+computation_calculations: 'GDP per employed person: total GDP in current dollars/ total employed persons'
+computation_definitions: 'Employed person: civilian population 16 years and over employed'
 ---
diff --git a/meta/8-5-1.md b/meta/8-5-1.md
index 11fc366..86865d7 100644
--- a/meta/8-5-1.md
+++ b/meta/8-5-1.md
@@ -8,8 +8,8 @@ goal_meta_link: 'https://unstats.un.org/sdgs/metadata/files/Metadata-08-05-01.pd
 goal_meta_link_text: United Nations Sustainable Development Goals Metadata (PDF 317 KB)
 graph_type: bar
 indicator_name: >-
-  Average hourly earnings of female and male employees, by occupation, age and
-  persons with disabilities
+  Average hourly earnings of employees, by sex, age, occupation and persons with
+  disabilities
 indicator_sort_order: 08-05-01
 published: true
 reporting_status: complete
@@ -19,8 +19,8 @@ target: >-
   equal pay for work of equal value
 target_id: '8.5'
 graph_title: >-
-  Average hourly earnings of female and male employees, by occupation, age and
-  persons with disabilities
+  Median annual earnings of employees, by sex, age, occupation and persons with
+  disabilities
 un_custodian_agency: International Labour Organization (ILO)
 un_designated_tier: '2'
 data_show_map: false
diff --git a/meta/5-1-2.md b/meta/8-5-1a.md
similarity index 84%
rename from meta/5-1-2.md
rename to meta/8-5-1a.md
index 92dfbbb..ebbe543 100644
--- a/meta/5-1-2.md
+++ b/meta/8-5-1a.md
@@ -1,19 +1,22 @@
 ---
-indicator: 5.1.2
+indicator: 8.5.1a
 layout: indicator
-permalink: /5-1-2/
-sdg_goal: '5'
+permalink: /8-5-1a/
+sdg_goal: '8'
 data_non_statistical: false
 graph_type: bar
 indicator_name: Women's earnings as a percentage of men's earning
 embedded_feature_tab_title: Interactive Map
 embedded_feature_title: Women's earnings as a percentage of men's earning
 embedded_feature_url: 'https://dawncomer.github.io/open-sdg-site-starter/gendertest/'
-indicator_sort_order: 05-01-02
+indicator_sort_order: 08-05-01a
 published: true
 reporting_status: complete
-target: End all forms of discrimination against all women and girls everywhere
-target_id: '5.1'
+target: >-
+  By 2030, achieve full and productive employment and decent work for all,
+  including for young people and persons with disabilities, and equal pay for
+  work of equal value
+target_id: '8.5'
 graph_title: Women's earnings as a percentage of men's earning
 data_show_map: false
 source_active_1: true
diff --git a/meta/8-5-2.md b/meta/8-5-2.md
index e46b906..96a5c6c 100644
--- a/meta/8-5-2.md
+++ b/meta/8-5-2.md
@@ -35,8 +35,7 @@ source_active_1: true
 source_url_text_1: >-
   2013-2018 American Community Survey 1-Year Estimates: Employment Status
   (S2301)
-source_active_2: true
-source_url_text_2: WCCD 5.1-City's Unemployment Rate; and 5.5 - Youth Unemployment Rate
+source_active_2: false
 source_active_3: false
 source_url_3: Link to source
 source_active_4: false
@@ -52,9 +51,6 @@ wccd_iso_37120_alignment: Aligns to WCCD 5.1-City's Unemployment Rate; and 5.5 -
 source_url_1: data.census.gov
 source_geographical_coverage_1: City of Los Angeles
 source_organisation_1: United States Census Bureau
-source_organisation_2: World Council on City Data
-source_geographical_coverage_2: City of Los Angeles
-source_url_2: 'http://open.dataforcities.org/'
 graph_title: 'Unemployment rate, by sex, age and persons with disabilities'
 data_disaggregation_information: 'disability status, gender, race'
 ---
diff --git a/meta/8-8-1.md b/meta/8-8-1.md
index 8f75395..06802ff 100644
--- a/meta/8-8-1.md
+++ b/meta/8-8-1.md
@@ -38,7 +38,6 @@ comments_limitations: >-
   Injuries and Illnesses (SOII) and the BLS Census of Fatal Occupational
   Injuries (CFOI)
 national_geographical_coverage: State of California
-computation_calculations: "Fatal injury rates depict the risk of incurring a fatal occupational injury and can be used to compare risk among worker groups with varying employment levels. Since employment data are not collected by CFOI, fatal injury rates are calculated using CPS and LAUS data. Each state rate in the table above represents the number of fatal occupational injuries per 100,000 full-time equivalent workers and was calculated as:   Fatality rate = (NS/EHS) x 200,000,000 where        NS = number of fatal work injuries in the state        EHS = total hours worked by all employees in the state during the calendar year        200,000,000 = base for 100,000 equivalent full-time workers (working 40 hours per week, 50 weeks per year)              State rates by industry were imputed by using national-level \"average hours\"\x9D and \"at work\"\x9D information from CPS to calculate the average annual number of hours for each employee, since these data are not available at the state level. EHS (total hours worked by all employees in the state during the calendar year) was calculated as:   EHS = HWN x ES where        ES = State employment (from LAUS)        HWN = average annual number of hours for each employee at the national level (from CPS)"
 national_indicator_available: >-
   Frequency of work-related injuries, illnesses, and fatal injuries - State of
   California
@@ -48,4 +47,5 @@ source_geographical_coverage_1: State of California
 source_other_info_1: >-
   The BLS Survey of Occupational Injuries and Illnesses (SOII) and the BLS
   Census of Fatal Occupational Injuries (CFOI)
+computation_units: Total injuries
 ---
diff --git a/meta/8-9-2.md b/meta/8-9-2.md
deleted file mode 100644
index 1c9602e..0000000
--- a/meta/8-9-2.md
+++ /dev/null
@@ -1,49 +0,0 @@
----
-indicator: 8.9.2
-layout: indicator
-permalink: /8-9-2/
-sdg_goal: '8'
-data_non_statistical: false
-goal_meta_link: 'https://unstats.un.org/sdgs/files/metadata-compilation/Metadata-Goal-8.pdf'
-goal_meta_link_text: United Nations Sustainable Development Goals Metadata (PDF 526 KB)
-graph_type: bar
-indicator_name: >-
-  Proportion of jobs tourism industries as proportion of total jobs across all
-  industries
-indicator_sort_order: 08-09-02
-published: true
-reporting_status: complete
-target: >-
-  By 2030, devise and implement policies to promote sustainable tourism that
-  creates jobs and promotes local culture and products
-target_id: '8.9'
-graph_title: Proportion of jobs in tourism industries as proportion of total jobs
-un_custodian_agency: World Health Organisation (WHO)
-un_designated_tier: '3'
-data_show_map: false
-source_active_1: true
-source_url_text_1: >-
-  City of Los Angeles Department of Convention and Tourism Development Annual
-  Reports
-source_active_2: false
-source_url_text_2: Link to Source
-source_active_3: false
-source_url_3: Link to source
-source_active_4: false
-source_url_text_4: Link to source
-source_active_5: false
-source_url_text_5: Link to source
-source_active_6: false
-source_url_text_6: Link to source
-title: Untitled
-data_footnote: >-
-  2015 and 2016 reported as Calendar Years; all other years reported as Fiscal
-  Years
-national_geographical_coverage: Los Angeles County
-source_organisation_1: Los Angeles Department of Convention and Tourism Development (CTD)
-source_url_1: 'https://ctd.lacity.org/publications'
-comments_limitations: >-
-  Data gathered from City of Los Angeles Department of Convention and Tourism
-  Development Annual Reports
-source_geographical_coverage_1: Los Angeles County
----
diff --git a/meta/9-2-1.md b/meta/9-2-1.md
index 288d909..a44db19 100644
--- a/meta/9-2-1.md
+++ b/meta/9-2-1.md
@@ -24,7 +24,7 @@ target: >-
   in line with national circumstances, and double its share in least developed
   countries
 target_id: '9.2'
-graph_title: Manufacturing GDP as a proportion of total industry GDP
+graph_title: Manufacturing GDP
 un_custodian_agency: United Nations Industrial Development Organization (UNIDO)
 un_designated_tier: '1'
 data_show_map: false
@@ -41,10 +41,11 @@ source_url_text_5: Link to source
 source_active_6: false
 source_url_text_6: Link to source
 title: Untitled
-national_indicator_available: Manufacturing GDP as a proportion of total industry GDP
+national_indicator_available: Manufacturing GDP in thousands of current dollars
 national_geographical_coverage: 'Los Angeles, Long Beach, Anaheim Metropolitan Statistical Area'
 computation_units: Percentage
 source_organisation_1: US Department of Commerce Bureau of Economic Analysis
 source_geographical_coverage_1: 'Los Angeles, Long Beach, Anaheim Metropolitan Statistical Area'
-source_url_1: 'https://www.bea.gov/data/gdp/gdp-metropolitan-area'
+source_url_1: >-
+  https://apps.bea.gov/iTable/iTable.cfm?isuri=1&reqid=70&step=1#isuri=1&reqid=70&step=1
 ---
diff --git a/meta/9-2-2.md b/meta/9-2-2.md
index 62ca32d..47d0b90 100644
--- a/meta/9-2-2.md
+++ b/meta/9-2-2.md
@@ -17,7 +17,9 @@ target: >-
   in line with national circumstances, and double its share in least developed
   countries
 target_id: '9.2'
-graph_title: Manufacturing employment as a proportion of total employment
+graph_title: >-
+  Total manufacturing employment and manufacturing employment as a proportion of
+  total employment
 un_custodian_agency: United Nations Industrial Development Organization (UNIDO)
 un_designated_tier: '1'
 data_show_map: false
@@ -36,15 +38,18 @@ source_url_text_5: Link to source
 source_active_6: false
 source_url_text_6: Link to source
 title: Untitled
-national_indicator_available: Total manufacturing civilian employed population
+national_indicator_available: 'Total employed in manufacturing, proportion employed in manufacturing'
 national_geographical_coverage: City of Los Angeles
 computation_units: 'Total and Percentage '
 computation_calculations: >-
-  The percent as a proportion of total employment was calculated by dividing the
-  total civilian population employed in the manufacturing industry by the total
-  employed civilian population. 
+  Proportion in management: total population employed in manufacturing/ total
+  employed population.
 source_organisation_1: United States Census Bureau
 source_url_1: >-
   https://factfinder.census.gov/faces/tableservices/jsf/pages/productview.xhtml?src=CF
 wccd_iso_37120_alignment: 'Aligns to WCCD 5.6- Number of businesses per 100,000 population'
+computation_definitions: >-
+  Employed population: full-time, year-round civilian employed population 16
+  years and over
+source_geographical_coverage_1: City of Los Angeles
 ---
diff --git a/meta/9-4-1.md b/meta/9-4-1.md
index 5c09437..f148e33 100644
--- a/meta/9-4-1.md
+++ b/meta/9-4-1.md
@@ -17,14 +17,14 @@ target: >-
   clean and environmentally sound technologies and industrial processes, with
   all countries taking action in accordance with their respective capabilities
 target_id: '9.4'
-graph_title: CO2 Emission per Unit of Value Added
+graph_title: GHG emissions and GHG efficiency
 un_custodian_agency: >-
   International Energy Agency (IEA) United Nations Industrial Development
   Organization (UNIDO)
 un_designated_tier: '1'
 data_show_map: false
 source_active_1: true
-source_url_text_1: 'Mayor''s Dashboard: LA''s Green New Deal'
+source_url_text_1: Community-Wide Greenhouse Gas Emissions
 source_active_2: false
 source_url_text_2: Link to Source
 source_active_3: false
@@ -37,9 +37,9 @@ source_active_6: false
 source_url_text_6: Link to source
 title: Untitled
 national_geographical_coverage: City of Los Angeles
-source_organisation_1: City of Los Angeles Sustainability Team
+source_organisation_1: Los Angeles Bureau of Sanitation and Environment
 source_geographical_coverage_1: City of Los Angeles
-source_url_1: 'http://dashboard.lamayor.org/pages/42'
+source_url_1: 'https://data.lacity.org/browse?q=greenhouse&sortBy=relevance'
 national_indicator_available: GHG efficiency of LA metro economy and Citywide GHG emissions
 computation_units: >-
   GHG efficiency in metric tons of CO2 per million dollars of metro area and GHG
diff --git a/meta/9-5-1.md b/meta/9-5-1.md
index f70edc6..5614a42 100644
--- a/meta/9-5-1.md
+++ b/meta/9-5-1.md
@@ -1,24 +1,44 @@
 ---
-data_non_statistical: false
-goal_meta_link: https://unstats.un.org/sdgs/metadata/files/Metadata-09-05-01.pdf
-goal_meta_link_text: United Nations Sustainable Development Goals Metadata (PDF 382
-  KB)
-graph_type: line
 indicator: 9.5.1
-indicator_name: Research and development expenditure as a proportion of GDP
-indicator_sort_order: 09-05-01
 layout: indicator
 permalink: /9-5-1/
-published: true
-reporting_status: notstarted
 sdg_goal: '9'
-target: Enhance scientific research, upgrade the technological capabilities of industrial
-  sectors in all countries, in particular developing countries, including, by 2030,
-  encouraging innovation and substantially increasing the number of research and development
-  workers per 1 million people and public and private research and development spending
+data_non_statistical: true
+goal_meta_link: 'https://unstats.un.org/sdgs/metadata/files/Metadata-09-05-01.pdf'
+goal_meta_link_text: United Nations Sustainable Development Goals Metadata (PDF 382 KB)
+graph_type: line
+indicator_name: Research and development expenditure as a proportion of GDP
+indicator_sort_order: 09-05-01
+published: true
+reporting_status: complete
+target: >-
+  Enhance scientific research, upgrade the technological capabilities of
+  industrial sectors in all countries, in particular developing countries,
+  including, by 2030, encouraging innovation and substantially increasing the
+  number of research and development workers per 1 million people and public and
+  private research and development spending
 target_id: '9.5'
-graph_title: Research and development expenditure as a proportion of GDP
-un_custodian_agency: United Nations Educational Scientific and Cultural Organization
-  (UNESCO)
+un_custodian_agency: United Nations Educational Scientific and Cultural Organization (UNESCO)
 un_designated_tier: '1'
+data_show_map: false
+source_active_1: true
+source_url_text_1: Link to source
+source_active_2: false
+source_url_text_2: Link to Source
+source_active_3: false
+source_url_3: Link to source
+source_active_4: false
+source_url_text_4: Link to source
+source_active_5: false
+source_url_text_5: Link to source
+source_active_6: false
+source_url_text_6: Link to source
+title: Untitled
+tags:
+  - Non-Statistical
 ---
+**Non-statistical Indicator:**
+
+[Los Angeles County](https://laedc.org/wtc/chooselacounty/research-development/) is home to three, world-class research universities: USC, UCLA, and Caltech. These educational institutions combined graduate more engineers than anywhere else in the country. 
+
+In 2011, the [Los Angeles cleantech Incubator](https://laincubator.org/) was founded with support from the City of Los Angeles to accelerate innovation in cleantech. 
\ No newline at end of file
diff --git a/scripts/check_invalidations.sh b/scripts/check_invalidations.sh
new file mode 100755
index 0000000..826721f
--- /dev/null
+++ b/scripts/check_invalidations.sh
@@ -0,0 +1,78 @@
+#!/usr/bin/env bash
+
+# Modified from https://github.com/swoodford/aws/blob/master/cloudfront-invalidation-status.sh
+
+# This script monitors CloudFront distributions for cache invalidation status and alerts when it has completed
+# Requires the AWS CLI and jq
+
+# Functions
+
+# Check Command Exists
+function checkCommand {
+	type -P $1 &>/dev/null || fail "Unable to find $1, please install it and run this script again."
+}
+
+# Completed Script
+function scriptExit(){
+	HorizontalRule
+	echo "Exiting Script"
+	HorizontalRule
+	echo
+	exit 0
+}
+
+# Script Failed
+function fail(){
+	echo "Failure: $*"
+	exit 1
+}
+
+# Horizontal Rule, print divider line
+function HorizontalRule(){
+	echo "============================================================"
+}
+
+# List Cloudfront Invalidations
+function listInvalidations(){
+	HorizontalRule
+	echo "Checking for Invalidations In Progress..."
+
+	# jq used to parse aws json output
+	invalidations=$(aws cloudfront list-invalidations --distribution-id $CLOUDFRONT_DIST_ID | jq '.InvalidationList | .Items | .[] | select(.Status != "Completed") | .Id' | cut -d \" -f2)
+	# Check if invalidation exists, if so output status
+	if ! [ -z "$invalidations" ]; then
+		HorizontalRule
+		echo "Invalidation in progress: $invalidations"
+		HorizontalRule
+	fi
+}
+
+# Check the Cloudfront Invalidation Status
+function checkInvalidationstatus(){
+	# Check if invalidation exists, if not exit script
+	if [ -z "$invalidations" ]; then
+		echo No CloudFront Invalidations In Progress.
+		HorizontalRule
+		return 1
+	else
+		# Loop through all invalidations
+		while IFS= read -r invalidationid
+		do
+			echo "Waiting for invalidation $invalidationid to complete..."
+			# Poll every 20 seconds (built into AWS command), Wait until invalidation has completed
+			# See https://docs.aws.amazon.com/cli/latest/reference/cloudfront/wait/invalidation-completed.html for more info
+			aws cloudfront wait invalidation-completed --distribution-id "$CLOUDFRONT_DIST_ID" --id "$invalidationid"
+			HorizontalRule
+			echo "Invalidation $invalidationid completed"
+		done <<< "$invalidations"
+		# All invalidations completed, exit script
+		scriptExit
+	fi
+}
+
+# Make sure jq exists on the system
+checkCommand "jq"
+# Grab all invalidations
+listInvalidations
+# Make sure invalidations are completed
+checkInvalidationstatus