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78 lines
2.4 KiB
Python
78 lines
2.4 KiB
Python
import numpy as np
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import pandas.core.common as com
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from pandas.core.dtypes.generic import (
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ABCIndexClass)
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from pandas.plotting._matplotlib.tools import _flatten, _set_ticks_props, _subplots
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def ed_hist_frame(ed_df, column=None, by=None, grid=True, xlabelsize=None,
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xrot=None, ylabelsize=None, yrot=None, ax=None, sharex=False,
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sharey=False, figsize=None, layout=None, bins=10, **kwds):
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"""
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See :pandas_docs:`pandas.DataFrame.hist` for usage.
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Notes
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-----
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Derived from ``pandas.plotting._core.hist_frame 0.24.2`` - TODO update to ``0.25.1``
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Ideally, we'd call `hist_frame` directly with histogram data,
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but weights are applied to ALL series. For example, we can
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plot a histogram of pre-binned data via:
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.. code-block:: python
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counts, bins = np.histogram(data)
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plt.hist(bins[:-1], bins, weights=counts)
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However,
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.. code-block:: python
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ax.hist(data[col].dropna().values, bins=bins, **kwds)
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is for ``[col]`` and weights are a single array.
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Examples
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--------
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.. plot::
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:context: close-figs
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>>> df = ed.DataFrame('localhost', 'flights')
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>>> hist = df.select_dtypes(include=[np.number]).hist(figsize=[10,10])
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"""
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# Start with empty pandas data frame derived from
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ed_df_bins, ed_df_weights = ed_df._hist(num_bins=bins)
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if by is not None:
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raise NotImplementedError("TODO")
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if column is not None:
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if not isinstance(column, (list, np.ndarray, ABCIndexClass)):
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column = [column]
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ed_df_bins = ed_df_bins[column]
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ed_df_weights = ed_df_weights[column]
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naxes = len(ed_df_bins.columns)
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fig, axes = _subplots(naxes=naxes, ax=ax, squeeze=False,
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sharex=sharex, sharey=sharey, figsize=figsize,
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layout=layout)
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_axes = _flatten(axes)
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for i, col in enumerate(com.try_sort(ed_df_bins.columns)):
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ax = _axes[i]
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# pandas code
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# pandas / plotting / _core.py: 2410
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# ax.hist(data[col].dropna().values, bins=bins, **kwds)
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ax.hist(ed_df_bins[col][:-1], bins=ed_df_bins[col], weights=ed_df_weights[col], **kwds)
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ax.set_title(col)
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ax.grid(grid)
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_set_ticks_props(axes, xlabelsize=xlabelsize, xrot=xrot,
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ylabelsize=ylabelsize, yrot=yrot)
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fig.subplots_adjust(wspace=0.3, hspace=0.3)
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return axes
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