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issue, pandas, documentation, valuecounts, label, foo, single, testing, tpackard, sign, docs, added, algos, projects, closed, subset, implementation, member, mroeschke, good, test, navigation, pandasdev, pull, requests, actions, security, doc, dataframecountvalues, supports, mattf, labels, change, reflect, triage, reviewed, team, commented, functions, related, suite, nonarithmetic, factorize, sorting, isin, clip, shift, diff, comment, rhshadrach,

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org/docs/reference/api/pandas single label subset personal information doc test suite good single label import pandas updated value_counts documentation projects milestone 2 //pandas type projects triage issue issue type arithmetic algos docs testing documentation https documentation change value_counts documentation label github latest versions subset accepts mapping capabilities change 0 closed 100% complete relationships issue labels comment api documentation df = pd value_counts implementation good xyz value_counts df implementation pd foo sign skip jump dataframe checked exists main location pydata list

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DiscussionForumPosting:
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      headline:DOC: DataFrame.count_values supports single label
      articleBody:### Pandas version checks - [X] I have checked that the issue still exists on the latest versions of the docs on `main` [here](https://pandas.pydata.org/docs/dev/) ### Location of the documentation https://pandas.pydata.org/docs/reference/api/pandas.DataFrame.value_counts.html ### Documentation problem documentation claims the `subset` must be `list-like, optional` the [implementation](https://github.com/pandas-dev/pandas/blob/v1.5.2/pandas/core/frame.py#L7215) uses [`DataFrame.groupby`](https://pandas.pydata.org/docs/reference/api/pandas.DataFrame.groupby.html), which accepts `mapping, function, label, or list of labels` the result is `value_counts` can accept a single label ``` In [1]: import pandas as pd In [2]: pd.__version__ Out[2]: '1.5.2' In [3]: df = pd.DataFrame({"XYZ": ["foo", "foo", "foo", "foo", "foo"]}) In [4]: df.value_counts("XYZ") Out[4]: XYZ foo 5 dtype: int64 ``` ### Suggested fix for documentation 1. change the `value_counts` documentation to reflect its capabilities 2. change the `value_counts` implementation to reflect the documentation use of [groupby goes to value_count's inception](https://github.com/pandas-dev/pandas/pull/31247), and groupby's api has been [consistent since 1.0](https://pandas.pydata.org/pandas-docs/version/1.0/reference/api/pandas.DataFrame.groupby.html) +1 option (1)
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      headline:DOC: DataFrame.count_values supports single label
      articleBody:### Pandas version checks - [X] I have checked that the issue still exists on the latest versions of the docs on `main` [here](https://pandas.pydata.org/docs/dev/) ### Location of the documentation https://pandas.pydata.org/docs/reference/api/pandas.DataFrame.value_counts.html ### Documentation problem documentation claims the `subset` must be `list-like, optional` the [implementation](https://github.com/pandas-dev/pandas/blob/v1.5.2/pandas/core/frame.py#L7215) uses [`DataFrame.groupby`](https://pandas.pydata.org/docs/reference/api/pandas.DataFrame.groupby.html), which accepts `mapping, function, label, or list of labels` the result is `value_counts` can accept a single label ``` In [1]: import pandas as pd In [2]: pd.__version__ Out[2]: '1.5.2' In [3]: df = pd.DataFrame({"XYZ": ["foo", "foo", "foo", "foo", "foo"]}) In [4]: df.value_counts("XYZ") Out[4]: XYZ foo 5 dtype: int64 ``` ### Suggested fix for documentation 1. change the `value_counts` documentation to reflect its capabilities 2. change the `value_counts` implementation to reflect the documentation use of [groupby goes to value_count's inception](https://github.com/pandas-dev/pandas/pull/31247), and groupby's api has been [consistent since 1.0](https://pandas.pydata.org/pandas-docs/version/1.0/reference/api/pandas.DataFrame.groupby.html) +1 option (1)
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