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hacktober #1

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f190bd6
Fixes #72
ResidentMario Jul 16, 2018
773afba
Update README.md
ResidentMario Nov 24, 2018
ae5519b
Update README.md
ResidentMario Dec 16, 2018
5f38cbc
Provide a colorbar on the heatmap by default.
ResidentMario Feb 16, 2019
078e6b8
Minor linting
ResidentMario Feb 16, 2019
1d67f91
Make fontsize functional.
ResidentMario Feb 16, 2019
cbcc8d5
Implement columnar sorting in bar and heatap. (#87)
ResidentMario Jul 8, 2019
3008db8
Add axis param, return axis objects, and deprecate inline (#88)
ResidentMario Jul 8, 2019
6391dc4
Tweak bar subplot sizing behavior. (#89)
ResidentMario Jul 8, 2019
5b99ad5
Deprecate the geoplot function. (#90)
ResidentMario Jul 9, 2019
2d4b202
Remove deprecated function from README. (#91)
ResidentMario Jul 9, 2019
48d2f06
Pull f-strings from code to maintain py3.4 compatibility. (#92)
ResidentMario Jul 9, 2019
1c69ec9
Bump version.
ResidentMario Jul 9, 2019
a1e1120
Update badges.
ResidentMario Oct 7, 2019
024a0e2
Include additional files in sdists (#97)
toddrme2178 Nov 19, 2019
d575515
Add license to setup.py (#98)
sergiuser1 Feb 10, 2020
d523c82
fixed error 116. (#117)
armando-fandango Jul 26, 2020
40bb099
Stop pointing to old version of python since package supports 3.4+ (#…
edison12a Sep 19, 2020
1d8c590
Update Readme.md to Correct a typo in Heat Map (#121)
chacreton190 Sep 26, 2020
a0de212
feature: simple memory optimization with a numpy parameter (#124)
johnnessantos Nov 23, 2020
df0ca58
docs: fix simple typo, seperate -> separate (#125)
timgates42 Dec 28, 2020
8c31763
Correct return type when inline=False (#132)
maxmahlke Apr 27, 2021
6ad031d
Introduce orientation to bar plot (#94)
sbrugman Jul 3, 2021
5e5607c
Lint, remove deprecated features (#137)
ResidentMario Jul 3, 2021
19dc216
Remove binder. (#138)
ResidentMario Jul 3, 2021
86b52fd
Update README. (#139)
ResidentMario Jul 3, 2021
095f45f
Remove geoplot from tests. (#140)
ResidentMario Jul 3, 2021
4fec860
Download example data from GitHub (#141)
ResidentMario Jul 3, 2021
68b1b9a
Update setup.py
ResidentMario Jul 3, 2021
1f45112
Hotfix: remove import of deleted method (#143)
ResidentMario Jul 4, 2021
79feb2f
Bump the major version number.
ResidentMario Jul 4, 2021
1ea4611
Include calculations in README (#151)
ResidentMario Feb 20, 2022
a0bb989
Remove inline arg from plotters (#152)
ResidentMario Feb 20, 2022
df9ee90
Add label_rotation parameter (#153)
ResidentMario Feb 20, 2022
59bc761
Update README.md
ResidentMario Feb 27, 2022
08a4659
Bump version.
ResidentMario Feb 27, 2022
f35bd89
Update README.md
ResidentMario Feb 27, 2022
99f7954
Matplotlib deprecation warning (#162)
r-leyshon Feb 26, 2023
ead5a06
Chore: remove requirements.txt from previous commit.
ResidentMario Feb 26, 2023
570fa08
Bump version.
ResidentMario Feb 26, 2023
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Update Readme.md to Correct a typo in Heat Map (ResidentMario#121)
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chacreton190 committed Sep 26, 2020
commit 1d8c5900e687fb259802f485ebffa3b131e5a1b5
2 changes: 1 addition & 1 deletion README.md
Original file line number Diff line number Diff line change
Expand Up @@ -86,7 +86,7 @@ Nullity correlation ranges from `-1` (if one variable appears the other definite

Variables that are always full or always empty have no meaningful correlation, and so are silently removed from the visualization—in this case for instance the datetime and injury number columns, which are completely filled, are not included.

Entries marked `<1` or `>-1` are have a correlation that is close to being exactingly negative or positive, but is still not quite perfectly so. This points to a small number of records in the dataset which are erroneous. For example, in this dataset the correlation between `VEHICLE CODE TYPE 3` and `CONTRIBUTING FACTOR VEHICLE 3` is `<1`, indicating that, contrary to our expectation, there are a few records which have one or the other, but not both. These cases will require special attention.
Entries marked `<1` or `>-1` have a correlation that is close to being exactingly negative or positive, but is still not quite perfectly so. This points to a small number of records in the dataset which are erroneous. For example, in this dataset the correlation between `VEHICLE CODE TYPE 3` and `CONTRIBUTING FACTOR VEHICLE 3` is `<1`, indicating that, contrary to our expectation, there are a few records which have one or the other, but not both. These cases will require special attention.

The heatmap works great for picking out data completeness relationships between variable pairs, but its explanatory power is limited when it comes to larger relationships and it has no particular support for extremely large datasets.

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