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DOC: fix PR02 errors in docstring for pandas.core.groupby.DataFrameGr…
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…oupBy.hist (pandas-dev#57304)

* DOC: fix PR02 errors in docstring for pandas.core.groupby.DataFrameGroupBy.hist

* update example for df.groupby().hist()
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jordan-d-murphy authored and pmhatre1 committed May 7, 2024
1 parent 7ff9f2d commit f0ceebe
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1 change: 0 additions & 1 deletion ci/code_checks.sh
Original file line number Diff line number Diff line change
Expand Up @@ -140,7 +140,6 @@ if [[ -z "$CHECK" || "$CHECK" == "docstrings" ]]; then
pandas.core.groupby.DataFrameGroupBy.rolling\
pandas.core.groupby.SeriesGroupBy.nth\
pandas.core.groupby.SeriesGroupBy.rolling\
pandas.core.groupby.DataFrameGroupBy.hist\
pandas.core.groupby.DataFrameGroupBy.plot\
pandas.core.groupby.SeriesGroupBy.plot # There should be no backslash in the final line, please keep this comment in the last ignored function
RET=$(($RET + $?)) ; echo $MSG "DONE"
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87 changes: 86 additions & 1 deletion pandas/core/groupby/generic.py
Original file line number Diff line number Diff line change
Expand Up @@ -2595,7 +2595,6 @@ def cov(
)
return result

@doc(DataFrame.hist.__doc__)
def hist(
self,
column: IndexLabel | None = None,
Expand All @@ -2615,6 +2614,92 @@ def hist(
legend: bool = False,
**kwargs,
):
"""
Make a histogram of the DataFrame's columns.
A `histogram`_ is a representation of the distribution of data.
This function calls :meth:`matplotlib.pyplot.hist`, on each series in
the DataFrame, resulting in one histogram per column.
.. _histogram: https://en.wikipedia.org/wiki/Histogram
Parameters
----------
column : str or sequence, optional
If passed, will be used to limit data to a subset of columns.
by : object, optional
If passed, then used to form histograms for separate groups.
grid : bool, default True
Whether to show axis grid lines.
xlabelsize : int, default None
If specified changes the x-axis label size.
xrot : float, default None
Rotation of x axis labels. For example, a value of 90 displays the
x labels rotated 90 degrees clockwise.
ylabelsize : int, default None
If specified changes the y-axis label size.
yrot : float, default None
Rotation of y axis labels. For example, a value of 90 displays the
y labels rotated 90 degrees clockwise.
ax : Matplotlib axes object, default None
The axes to plot the histogram on.
sharex : bool, default True if ax is None else False
In case subplots=True, share x axis and set some x axis labels to
invisible; defaults to True if ax is None otherwise False if an ax
is passed in.
Note that passing in both an ax and sharex=True will alter all x axis
labels for all subplots in a figure.
sharey : bool, default False
In case subplots=True, share y axis and set some y axis labels to
invisible.
figsize : tuple, optional
The size in inches of the figure to create. Uses the value in
`matplotlib.rcParams` by default.
layout : tuple, optional
Tuple of (rows, columns) for the layout of the histograms.
bins : int or sequence, default 10
Number of histogram bins to be used. If an integer is given, bins + 1
bin edges are calculated and returned. If bins is a sequence, gives
bin edges, including left edge of first bin and right edge of last
bin. In this case, bins is returned unmodified.
backend : str, default None
Backend to use instead of the backend specified in the option
``plotting.backend``. For instance, 'matplotlib'. Alternatively, to
specify the ``plotting.backend`` for the whole session, set
``pd.options.plotting.backend``.
legend : bool, default False
Whether to show the legend.
**kwargs
All other plotting keyword arguments to be passed to
:meth:`matplotlib.pyplot.hist`.
Returns
-------
matplotlib.Axes or numpy.ndarray of them
See Also
--------
matplotlib.pyplot.hist : Plot a histogram using matplotlib.
Examples
--------
This example draws a histogram based on the length and width of
some animals, displayed in three bins
.. plot::
:context: close-figs
>>> data = {
... "length": [1.5, 0.5, 1.2, 0.9, 3],
... "width": [0.7, 0.2, 0.15, 0.2, 1.1],
... }
>>> index = ["pig", "rabbit", "duck", "chicken", "horse"]
>>> df = pd.DataFrame(data, index=index)
>>> hist = df.groupby("length").hist(bins=3)
"""
result = self._op_via_apply(
"hist",
column=column,
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