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DOC: Enforce Numpy Docstring Validation | pandas.ExcelFile through pandas.HDFStore #58067

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@jordan-d-murphy

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@jordan-d-murphy

DOC: Enforce Numpy Docstring Validation (Parent Issue) #58063

Pandas has a script for validating docstrings in code_checks.sh. Currently, some methods fail some of these checks.

pandas.ExcelFile through pandas.HDFStore

pandas/ci/code_checks.sh

Lines 168 to 181 in c468028

-i "pandas.ExcelFile PR01,SA01" \
-i "pandas.ExcelFile.parse PR01,SA01" \
-i "pandas.ExcelWriter SA01" \
-i "pandas.Float32Dtype SA01" \
-i "pandas.Float64Dtype SA01" \
-i "pandas.Grouper PR02,SA01" \
-i "pandas.HDFStore.append PR01,SA01" \
-i "pandas.HDFStore.get SA01" \
-i "pandas.HDFStore.groups SA01" \
-i "pandas.HDFStore.info RT03,SA01" \
-i "pandas.HDFStore.keys SA01" \
-i "pandas.HDFStore.put PR01,SA01" \
-i "pandas.HDFStore.select SA01" \
-i "pandas.HDFStore.walk SA01" \

The task is:

  1. take 1-5 methods

  2. run: scripts/validate_docstrings.py --format=actions <method-name>

example command: scripts/validate_docstrings.py --format=actions pandas.Categorical.__array__
example output:

################################################################################
################################## Validation ##################################
################################################################################

2 Errors found for `pandas.Categorical.__array__`:
	ES01	No extended summary found
	SA01	See Also section not found
  1. check if validation docstrings passes for those methods, and if it’s necessary fix the docstrings according to whatever error is reported. Note: We've chosen to ignore ES01 errors, these are not required to be fixed.

  2. remove those methods from code_checks.sh if all errors are cleared and the docstring is correct, otherwise, remove the specific error that was fixed from the list of errors for that method.

  3. commit, push, open pull request

Please don't comment take as multiple people can work on this issue. You also don't need to ask for permission to work on this, just comment on which methods are you going to work : )

If you're new contributor, please check the contributing guide

thanks @datapythonista for the inspiration for this issue!

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