[Term Entry] Python:Pandas built-in-functions: .concat() #4814
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Hey @Liam-Dupeyron, please sign the CLA |
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Hi Mamta,
I just signed the CLA.
Best,
Liam
…On Fri, Jun 21, 2024 at 6:09 PM Mamta Wardhani ***@***.***> wrote:
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<https://cla-assistant.io/Codecademy/docs?pullRequest=4814> Thank you for
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*Liam Dupeyron*
Data Science
University of California Berkeley | Class of 2025
***@***.*** | (909)-300-2032
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mamtawardhani
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@Liam-Dupeyron thank you for contributing to the Codecademy Docs! The entry is well written!
I've suggested a few changes, could you please review and modify those at your earliest convenience? Feel free to discuss any concerns, thank you! 😃
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| --- | ||
| 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' | ||
| 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' | ||
| --- |
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| --- | |
| 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' | |
| 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' | |
| --- | |
| --- | |
| Title: '.concat()' | |
| Description: 'Concatenates multiple DataFrames or Series along a specified axis.' | |
| Subjects: | |
| - 'Computer Science' | |
| - 'Data Science' | |
| Tags: | |
| - 'Data Structures' | |
| - 'Functions' | |
| - 'Pandas' | |
| CatalogContent: | |
| - 'learn-python-3' | |
| - 'paths/computer-science' | |
| - 'paths/data-science' | |
| - 'paths/data-science-foundations' | |
| --- |
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added relevant subjects and tags from the documents
| - 'paths/data-science' | ||
| --- | ||
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| 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. |
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| 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 specified axis. |
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The first instance of the term should be wrapped in bold
| ## Syntax | ||
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| ```pseudo | ||
| pandas.concat(objs) |
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The syntax should include all the parameters from the documentation of the .concat() method. I found out the following two:
pandas.concat(objs, axis=0, join='outer', ignore_index=False, keys=None, levels=None, names=None, verify_integrity=False, sort=False, copy=True)
pandas.concat(objs, axis, join, ignore_index, keys, levels, names, verify_integrity, sort, copy)
You can use either of them
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| 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). | ||
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| The rest of the parameters are listed below: | ||
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| | 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 | | ||
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All the parameters need to be described in the below format:
objs: A sequence or mapping ofSeriesorDataFrameobjects. Can be a list of objects or a dictionary where the keys will be used for thekeysparameter.axis: Specifies the axis along which to concatenate the objects. The default value is 0.
And so on, so in this format describe the other parameters as well.
| ## Example | ||
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| ```py | ||
| import pandas |
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| import pandas | |
| import pandas as pd |
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since you are using the abbreviation pd in the code
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The output that I'm getting is somewhat different, could you please run the code and check again? The is the output I'm getting:
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| ``` | ||
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| The example will result in a new DataFrame is returned by concatenating df1 and df2 along the rows: |
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| 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: |
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@mamtawardhani I just pushed the updated concat.md file! Let me know if I should add any other changes! |
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I just double-checked, and I need to add more changes to the Syntax section. I will be working on it |
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I have finished my last revision of the file and pushed it. Let me know if there are any further changes I should add! |
mamtawardhani
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Hey @Liam-Dupeyron, just one last change required from my side, could you please add a ##Codebyte Example block at the end, with a runnable code?
It should not have any ouput block, just the code showing the use of the .concat() method.
Let me know once you add that, thanks! 😃
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Hi @mamtawardhani! I just added the Codebyte Example. Let me know if there is anything else I should add or correct if needed :). |
minor changes
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Jun 25, 2024
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Thank you @Liam-Dupeyron for the contribution, the entry looks good for a second round of review! 🚀
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Sounds awesome! Thank you so much for your support |
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Hey @Liam-Dupeyron, I've suggested a few changes, please make them and let me know. Thank you!!
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| - 'paths/data-science' | ||
| - 'learn-python-3' | ||
| - 'paths/computer-science' | ||
| - 'paths/data-science-foundations' |
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Suggested change
| - 'paths/data-science' | |
| - 'learn-python-3' | |
| - 'paths/computer-science' | |
| - 'paths/data-science-foundations' | |
| - 'paths/data-science' | |
| - 'learn-python-3' | |
| - 'paths/computer-science' | |
| - 'paths/data-science-foundations' |
We prefer to keep 2 CatalogContent here:
- Free course
- Pro course/path
Can you modify it accordingly?
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| --- | |||
| Title: '.concat()' | |||
| Description: 'Concatenates multiple Dataframes or Series along a particular axis.' | |||
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Suggested change
| Description: 'Concatenates multiple Dataframes or Series along a particular axis.' | |
| Description: 'Concatenates multiple dataframes or series along a particular axis.' |
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| - `objs`: Denotes the objects to concatenate, which can be a sequence or mapping of pandas `Series` or `DataFrame` objects. It must be specified and can be passed as a list, tuple, dictionary, Series, or DataFrame. | ||
| - `axis`: Specifies the axis along which to concatenate the objects. The default value is 0 for rows, while 1 represents columns. | ||
| - `join`: Determines how to handle indexes on other axes. Options include "outer" (default), "inner," "left," or "right." |
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Can you recheck if the join parameter supports "left" or "right" options?
| - `levels`: Specific levels to use for constructing a MultiIndex if keys are provided. Default value is `None`. | ||
| - `names`: Names for the levels generated in the hierarchical index. Default value is `None`. | ||
| - `verify_integrity`: If `True`, checks whether the new concatenated axis contains duplicates. Default value is `False`. | ||
| - `sort`: If `True`, sorts the resulting `Series` or `Dataframe` by the keys. Default value is `False`. |
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It sorts non-concatenation axis if it is not already aligned. Please recheck this too.
| result = pd.concat([df1, df2], axis=1, keys = ['df1', 'df2']) | ||
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| print(result) | ||
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Unnecessary space.
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| - `ignore_index`: If `True`, resets the index in the resulting DataFrame. The new axis will be labeled 0, ..., n-1. Default value is `False`. | ||
| - `keys`: Constructs a hierarchical index using the provided keys as the outermost level. Default value is `None`. | ||
| - `levels`: Specific levels to use for constructing a MultiIndex if keys are provided. Default value is `None`. | ||
| - `names`: Names for the levels generated in the hierarchical index. Default value is `None`. | ||
| - `verify_integrity`: If `True`, checks whether the new concatenated axis contains duplicates. Default value is `False`. | ||
| - `sort`: If `True`, sorts the resulting `Series` or `Dataframe` by the keys. Default value is `False`. |
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Suggested change
| - `ignore_index`: If `True`, resets the index in the resulting DataFrame. The new axis will be labeled 0, ..., n-1. Default value is `False`. | |
| - `keys`: Constructs a hierarchical index using the provided keys as the outermost level. Default value is `None`. | |
| - `levels`: Specific levels to use for constructing a MultiIndex if keys are provided. Default value is `None`. | |
| - `names`: Names for the levels generated in the hierarchical index. Default value is `None`. | |
| - `verify_integrity`: If `True`, checks whether the new concatenated axis contains duplicates. Default value is `False`. | |
| - `sort`: If `True`, sorts the resulting `Series` or `Dataframe` by the keys. Default value is `False`. | |
| - `ignore_index`: If `True`, reset the index in the resulting DataFrame. The new axis will be labeled 0, ..., n-1. The default value is `False`. | |
| - `keys`: Constructs a hierarchical index using the provided keys as the outermost level. The default value is `None`. | |
| - `levels`: Specific levels to use for constructing a MultiIndex if keys are provided. The default value is `None`. | |
| - `names`: Names for the levels generated in the hierarchical index. The default value is `None`. | |
| - `verify_integrity`: If `True`, checks whether the new concatenated axis contains duplicates. The default value is `False`. | |
| - `sort`: If `True`, sorts the resulting `Series` or `Dataframe` by the keys. The default value is `False`. |
| - `names`: Names for the levels generated in the hierarchical index. Default value is `None`. | ||
| - `verify_integrity`: If `True`, checks whether the new concatenated axis contains duplicates. Default value is `False`. | ||
| - `sort`: If `True`, sorts the resulting `Series` or `Dataframe` by the keys. Default value is `False`. | ||
| - `copy`: If `False`, avoids copying data unnecessarily. Default value is `True`. |
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| - `copy`: If `False`, avoids copying data unnecessarily. Default value is `True`. | |
| - `copy`: If `False`, avoid copying data unnecessarily. The default value is `True`. |
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| - `objs`: Denotes the objects to concatenate, which can be a sequence or mapping of pandas `Series` or `DataFrame` objects. It must be specified and can be passed as a list, tuple, dictionary, Series, or DataFrame. | ||
| - `axis`: Specifies the axis along which to concatenate the objects. The default value is 0 for rows, while 1 represents columns. | ||
| - `join`: Determines how to handle indexes on other axes. Options include "outer" (default), "inner," "left," or "right." |
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Suggested change
| - `objs`: Denotes the objects to concatenate, which can be a sequence or mapping of pandas `Series` or `DataFrame` objects. It must be specified and can be passed as a list, tuple, dictionary, Series, or DataFrame. | |
| - `axis`: Specifies the axis along which to concatenate the objects. The default value is 0 for rows, while 1 represents columns. | |
| - `join`: Determines how to handle indexes on other axes. Options include "outer" (default), "inner," "left," or "right." | |
| - `objs`: Denotes the objects to concatenate, which can be a sequence or mapping of pandas `Series` or `DataFrame` objects. It must be specified and can be passed as a list, tuple, dictionary, Series, or DataFrame. | |
| - `axis`: Specifies the axis to concatenate the objects. The default value is 0 for rows, while 1 represents columns. | |
| - `join`: Determines how to handle indexes on other axes. Options include "outer" (default), "inner," "left," or "right." |
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Description
-Added the pandas.concat() function term for Python: Pandas
Issue Solved
-Closed Issue #4524
Type of Change
Checklist
mainbranch.Issues Solvedsection.