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DOC: Improve pandas.Series.plot.kde docstring and kwargs rewording fo…
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…r whole file (#20041)
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@dukebody @jorisvandenbossche
dukebody authored and jorisvandenbossche committed Mar 10, 2018
1 parent c3d491a commit fb556ed
Showing 1 changed file with 91 additions and 26 deletions.
117 changes: 91 additions & 26 deletions pandas/plotting/_core.py
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Original file line number Diff line number Diff line change
Expand Up @@ -2532,7 +2532,8 @@ def line(self, **kwds):
Parameters
----------
`**kwds` : optional
Keyword arguments to pass on to :py:meth:`pandas.Series.plot`.
Additional keyword arguments are documented in
:meth:`pandas.Series.plot`.
Returns
-------
Expand All @@ -2556,7 +2557,8 @@ def bar(self, **kwds):
Parameters
----------
`**kwds` : optional
Keyword arguments to pass on to :py:meth:`pandas.Series.plot`.
Additional keyword arguments are documented in
:meth:`pandas.Series.plot`.
Returns
-------
Expand All @@ -2571,7 +2573,8 @@ def barh(self, **kwds):
Parameters
----------
`**kwds` : optional
Keyword arguments to pass on to :py:meth:`pandas.Series.plot`.
Additional keyword arguments are documented in
:meth:`pandas.Series.plot`.
Returns
-------
Expand All @@ -2586,7 +2589,8 @@ def box(self, **kwds):
Parameters
----------
`**kwds` : optional
Keyword arguments to pass on to :py:meth:`pandas.Series.plot`.
Additional keyword arguments are documented in
:meth:`pandas.Series.plot`.
Returns
-------
Expand All @@ -2603,7 +2607,8 @@ def hist(self, bins=10, **kwds):
bins: integer, default 10
Number of histogram bins to be used
`**kwds` : optional
Keyword arguments to pass on to :py:meth:`pandas.Series.plot`.
Additional keyword arguments are documented in
:meth:`pandas.Series.plot`.
Returns
-------
Expand All @@ -2613,26 +2618,74 @@ def hist(self, bins=10, **kwds):

def kde(self, bw_method=None, ind=None, **kwds):
"""
Kernel Density Estimate plot
Kernel Density Estimate plot using Gaussian kernels.
In statistics, kernel density estimation (KDE) is a non-parametric way
to estimate the probability density function (PDF) of a random
variable. This function uses Gaussian kernels and includes automatic
bandwith determination.
Parameters
----------
bw_method: str, scalar or callable, optional
The method used to calculate the estimator bandwidth. This can be
bw_method : str, scalar or callable, optional
The method used to calculate the estimator bandwidth. This can be
'scott', 'silverman', a scalar constant or a callable.
If None (default), 'scott' is used.
See :class:`scipy.stats.gaussian_kde` for more information.
ind : NumPy array or integer, optional
Evaluation points. If None (default), 1000 equally spaced points
are used. If `ind` is a NumPy array, the kde is evaluated at the
points passed. If `ind` is an integer, `ind` number of equally
spaced points are used.
`**kwds` : optional
Keyword arguments to pass on to :py:meth:`pandas.Series.plot`.
Evaluation points for the estimated PDF. If None (default),
1000 equally spaced points are used. If `ind` is a NumPy array, the
kde is evaluated at the points passed. If `ind` is an integer,
`ind` number of equally spaced points are used.
kwds : optional
Additional keyword arguments are documented in
:meth:`pandas.Series.plot`.
Returns
-------
axes : matplotlib.AxesSubplot or np.array of them
See also
--------
scipy.stats.gaussian_kde : Representation of a kernel-density
estimate using Gaussian kernels. This is the function used
internally to estimate the PDF.
Examples
--------
Given a Series of points randomly sampled from an unknown
distribution, estimate this distribution using KDE with automatic
bandwidth determination and plot the results, evaluating them at
1000 equally spaced points (default):
.. plot::
:context: close-figs
>>> s = pd.Series([1, 2, 2.5, 3, 3.5, 4, 5])
>>> ax = s.plot.kde()
An scalar fixed bandwidth can be specified. Using a too small bandwidth
can lead to overfitting, while a too large bandwidth can result in
underfitting:
.. plot::
:context: close-figs
>>> ax = s.plot.kde(bw_method=0.3)
.. plot::
:context: close-figs
>>> ax = s.plot.kde(bw_method=3)
Finally, the `ind` parameter determines the evaluation points for the
plot of the estimated PDF:
.. plot::
:context: close-figs
>>> ax = s.plot.kde(ind=[1, 2, 3, 4, 5])
"""
return self(kind='kde', bw_method=bw_method, ind=ind, **kwds)

Expand All @@ -2645,7 +2698,8 @@ def area(self, **kwds):
Parameters
----------
`**kwds` : optional
Keyword arguments to pass on to :py:meth:`pandas.Series.plot`.
Additional keyword arguments are documented in
:meth:`pandas.Series.plot`.
Returns
-------
Expand All @@ -2660,7 +2714,8 @@ def pie(self, **kwds):
Parameters
----------
`**kwds` : optional
Keyword arguments to pass on to :py:meth:`pandas.Series.plot`.
Additional keyword arguments are documented in
:meth:`pandas.Series.plot`.
Returns
-------
Expand Down Expand Up @@ -2711,7 +2766,8 @@ def line(self, x=None, y=None, **kwds):
x, y : label or position, optional
Coordinates for each point.
`**kwds` : optional
Keyword arguments to pass on to :py:meth:`pandas.DataFrame.plot`.
Additional keyword arguments are documented in
:meth:`pandas.DataFrame.plot`.
Returns
-------
Expand All @@ -2728,7 +2784,8 @@ def bar(self, x=None, y=None, **kwds):
x, y : label or position, optional
Coordinates for each point.
`**kwds` : optional
Keyword arguments to pass on to :py:meth:`pandas.DataFrame.plot`.
Additional keyword arguments are documented in
:meth:`pandas.DataFrame.plot`.
Returns
-------
Expand All @@ -2745,7 +2802,8 @@ def barh(self, x=None, y=None, **kwds):
x, y : label or position, optional
Coordinates for each point.
`**kwds` : optional
Keyword arguments to pass on to :py:meth:`pandas.DataFrame.plot`.
Additional keyword arguments are documented in
:meth:`pandas.DataFrame.plot`.
Returns
-------
Expand All @@ -2762,7 +2820,8 @@ def box(self, by=None, **kwds):
by : string or sequence
Column in the DataFrame to group by.
`**kwds` : optional
Keyword arguments to pass on to :py:meth:`pandas.DataFrame.plot`.
Additional keyword arguments are documented in
:meth:`pandas.DataFrame.plot`.
Returns
-------
Expand All @@ -2781,7 +2840,8 @@ def hist(self, by=None, bins=10, **kwds):
bins: integer, default 10
Number of histogram bins to be used
`**kwds` : optional
Keyword arguments to pass on to :py:meth:`pandas.DataFrame.plot`.
Additional keyword arguments are documented in
:meth:`pandas.DataFrame.plot`.
Returns
-------
Expand All @@ -2806,7 +2866,8 @@ def kde(self, bw_method=None, ind=None, **kwds):
points passed. If `ind` is an integer, `ind` number of equally
spaced points are used.
`**kwds` : optional
Keyword arguments to pass on to :py:meth:`pandas.DataFrame.plot`.
Additional keyword arguments are documented in
:meth:`pandas.DataFrame.plot`.
Returns
-------
Expand All @@ -2825,7 +2886,8 @@ def area(self, x=None, y=None, **kwds):
x, y : label or position, optional
Coordinates for each point.
`**kwds` : optional
Keyword arguments to pass on to :py:meth:`pandas.DataFrame.plot`.
Additional keyword arguments are documented in
:meth:`pandas.DataFrame.plot`.
Returns
-------
Expand All @@ -2842,7 +2904,8 @@ def pie(self, y=None, **kwds):
y : label or position, optional
Column to plot.
`**kwds` : optional
Keyword arguments to pass on to :py:meth:`pandas.DataFrame.plot`.
Additional keyword arguments are documented in
:meth:`pandas.DataFrame.plot`.
Returns
-------
Expand All @@ -2863,7 +2926,8 @@ def scatter(self, x, y, s=None, c=None, **kwds):
c : label or position, optional
Color of each point.
`**kwds` : optional
Keyword arguments to pass on to :py:meth:`pandas.DataFrame.plot`.
Additional keyword arguments are documented in
:meth:`pandas.DataFrame.plot`.
Returns
-------
Expand All @@ -2888,7 +2952,8 @@ def hexbin(self, x, y, C=None, reduce_C_function=None, gridsize=None,
gridsize : int, optional
Number of bins.
`**kwds` : optional
Keyword arguments to pass on to :py:meth:`pandas.DataFrame.plot`.
Additional keyword arguments are documented in
:meth:`pandas.DataFrame.plot`.
Returns
-------
Expand Down

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