Applied changes and suggestions

content/pandas/concepts/built-in-functions/terms/concat/concat.md

@@ -2,48 +2,50 @@
 Title: '.concat()'
 Description: 'Concatenates multiple Dataframes or Series along a particular axis'
 Subjects: # Please only use Subjects in the subjects.md file (https://github.com/Codecademy/docs/blob/main/documentation/subjects.md). If that list feels insufficient, feel free to create a new Subject and add it to subjects.md in your PR!
-  - 'A subject name'
-  - 'A second subject name'
-  - 'An nth subject name'
+  - 'Computer Science'
+  - 'Data Science'
 Tags: # Please only use Tags in the tags.md file (https://github.com/Codecademy/docs/blob/main/documentation/tags.md). If that list feels insufficient, feel free to create a new Tag and add it to tags.md in your PR!
   - 'Data Structures'
   - 'Functions'
   - 'Pandas'
-  - 'CSV'
-  - 'Data'
 CatalogContent: # Please use course/path landing page slugs, rather than linking to individual content items. If listing multiple items, please put the most relevant one first
-  - 'learn-Data-Analysis-with-Pandas'
   - 'paths/data-science'
+  - 'learn-python-3'
+  - 'paths/computer-science'
+  - 'paths/data-science-foundations'
 ---
 
-The `.concat()` function is used to concatenate and combine multiple [`DataFrames`](https://www.codecademy.com/resources/docs/pandas/dataframe) or `Series` along a particular axis.
+The **`.concat()`** function is used to concatenate and combine multiple [`DataFrames`](https://www.codecademy.com/resources/docs/pandas/dataframe) or `Series` along a particular axis.
 
 ## Syntax
 
 ```pseudo
-pandas.concat(objs)
+pandas.concat(objs, axis=0, join='outer', ignore_index=False, keys=None, levels=None, names=None, verify_integrity=False, sort=False, copy=True)
 ```
 
 The `objs` parameter is essential and must be specified. It represents the objects to be concatenated and can be a sequence or mapping of pandas Series or DataFrame objects. The objects should be passed as a sequence (like a list or tuple) or a mapping (like a dictionary).
 
 The rest of the parameters are listed below:
 
-|   Parameter Name   |                      Data Type                       | Usage                                                                                  |
-| :----------------: | :--------------------------------------------------: | -------------------------------------------------------------------------------------- |
-|       `axis`       |     int (0 for rows, 1 for columns ), default 0      | Specifies the axis along which to concatenate the objects                              |
-|       `join`       | str (“outer” (default), “inner,” “left,” or “right”) | Determines how to handle indexes on other axes                                         |
-|   `ignore_index`   |                bool, default `False`                 | If `True`, it resets the index in the resulting DataFrame                              |
-|       `keys`       |        sequence (list or tuple), default None        | Lets you construct a hierarchical index using the provided keys as the outermost level |
-|      `levels`      |           list of sequences, default None            | Specific levels to use for constructing a MultiIndex if keys are provided              |
-|      `names`       |              list of str, default None               | Names for the levels generated in the hierarchical index                               |
-| `verify_integrity` |                bool, default `False`                 | If `True`, checks whether the new concatenated axis contains duplicates                |
-|       `sort`       |                bool, default `False`                 | If `True`, it sorts the resulting Series or Dataframe by the keys                      |
-|       `copy`       |                 bool, default `True`                 | If `False`, it avoids copying data unnecessarily                                       |
+|   Parameter Name   |                      Data Type                       | Usage                                                                                                                          |
+| :----------------: | :--------------------------------------------------: | ------------------------------------------------------------------------------------------------------------------------------ |
+|       `objs`       |         list, tuple, dict, Series, DataFrame         | The primary argument where you pass the sequence or mapping of pandas Series or DataFrame objects that you want to concatenate |
+|       `axis`       |     int (0 for rows, 1 for columns ), default 0      | Specifies the axis along which to concatenate the objects                                                                      |
+|       `join`       | str (“outer” (default), “inner,” “left,” or “right”) | Determines how to handle indexes on other axes                                                                                 |
+|   `ignore_index`   |                bool, default `False`                 | If `True`, it resets the index in the resulting DataFrame                                                                      |
+|       `keys`       |        sequence (list or tuple), default None        | Lets you construct a hierarchical index using the provided keys as the outermost level                                         |
+|      `levels`      |           list of sequences, default None            | Specific levels to use for constructing a MultiIndex if keys are provided                                                      |
+|      `names`       |              list of str, default None               | Names for the levels generated in the hierarchical index                                                                       |
+| `verify_integrity` |                bool, default `False`                 | If `True`, checks whether the new concatenated axis contains duplicates                                                        |
+|       `sort`       |                bool, default `False`                 | If `True`, it sorts the resulting Series or Dataframe by the keys                                                              |
+|       `copy`       |                 bool, default `True`                 | If `False`, it avoids copying data unnecessarily                                                                               |
 
 ## Example
 
+The example below demonstrates the use of `.concat()` method:
+
 ```py
-import pandas
+import pandas as pd
 
 df1 = pd.DataFrame({'A': [1, 2], 'B': [3, 4]})
 df2 = pd.DataFrame({'A': [5, 6], 'B': [7, 8]})
@@ -53,12 +55,12 @@ print(result)
 
 ```
 
-The example will result in a new DataFrame is returned by concatenating df1 and df2 along the rows:
+The example will result in a new DataFrame created by concatenating df1 and df2 along the rows. The output is as follows:
 
 ```shell
    A   B
-0  1   2
-1  3   4
-0  5   6
-1  7   8
+0  1   3
+1  2   4
+0  5   7
+1  6   8
 ```