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Fix inconsistent uses of row-wise and column-wise in axis param docs (#47237)
* fix corrwith docs * remove row-wise and column-wise language from all() docs
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pandas/core/frame.py

+3-3
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@@ -10159,8 +10159,8 @@ def corrwith(
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other : DataFrame, Series
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Object with which to compute correlations.
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axis : {0 or 'index', 1 or 'columns'}, default 0
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The axis to use. 0 or 'index' to compute column-wise, 1 or 'columns' for
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row-wise.
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The axis to use. 0 or 'index' to compute row-wise, 1 or 'columns' for
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column-wise.
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drop : bool, default False
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Drop missing indices from result.
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method : {'pearson', 'kendall', 'spearman'} or callable
@@ -10836,7 +10836,7 @@ def quantile(
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----------
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q : float or array-like, default 0.5 (50% quantile)
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Value between 0 <= q <= 1, the quantile(s) to compute.
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axis : {0, 1, 'index', 'columns'}, default 0
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axis : {0 or 'index', 1 or 'columns'}, default 0
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Equals 0 or 'index' for row-wise, 1 or 'columns' for column-wise.
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numeric_only : bool, default True
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If False, the quantile of datetime and timedelta data will be

pandas/core/generic.py

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@@ -11756,14 +11756,14 @@ def _doc_params(cls):
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0 True True
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1 True False
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Default behaviour checks if column-wise values all return True.
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Default behaviour checks if values in each column all return True.
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>>> df.all()
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col1 True
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col2 False
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dtype: bool
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Specify ``axis='columns'`` to check if row-wise values all return True.
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Specify ``axis='columns'`` to check if values in each row all return True.
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>>> df.all(axis='columns')
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0 True

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