scatter_matrix(frame, alpha=0.5, figsize=None, ax=None, grid=False, diagonal='hist', marker='.', density_kwds=None, hist_kwds=None, range_padding=0.05, **kwargs)

Parameters

frame : DataFrame

alpha : float, optional

Amount of transparency applied.

figsize : (float,float), optional

A tuple (width, height) in inches.

ax : Matplotlib axis object, optional

grid : bool, optional

Setting this to True will show the grid.

diagonal : {'hist', 'kde'}

Pick between 'kde' and 'hist' for either Kernel Density Estimation or Histogram plot in the diagonal.

marker : str, optional

Matplotlib marker type, default '.'.

density_kwds : keywords

Keyword arguments to be passed to kernel density estimate plot.

hist_kwds : keywords

Keyword arguments to be passed to hist function.

range_padding : float, default 0.05

Relative extension of axis range in x and y with respect to (x_max - x_min) or (y_max - y_min).

**kwargs :

Keyword arguments to be passed to scatter function.

Returns

numpy.ndarray

A matrix of scatter plots.

Draw a matrix of scatter plots.

Examples

.. plot:: 
    ('context', 'close-figs')
    

>>> df = pd.DataFrame(np.random.randn(1000, 4), columns=['A','B','C','D'])
>>> pd.plotting.scatter_matrix(df, alpha=0.2)
array([[<AxesSubplot:xlabel='A', ylabel='A'>,
    <AxesSubplot:xlabel='B', ylabel='A'>,
    <AxesSubplot:xlabel='C', ylabel='A'>,
    <AxesSubplot:xlabel='D', ylabel='A'>],
   [<AxesSubplot:xlabel='A', ylabel='B'>,
    <AxesSubplot:xlabel='B', ylabel='B'>,
    <AxesSubplot:xlabel='C', ylabel='B'>,
    <AxesSubplot:xlabel='D', ylabel='B'>],
   [<AxesSubplot:xlabel='A', ylabel='C'>,
    <AxesSubplot:xlabel='B', ylabel='C'>,
    <AxesSubplot:xlabel='C', ylabel='C'>,
    <AxesSubplot:xlabel='D', ylabel='C'>],
   [<AxesSubplot:xlabel='A', ylabel='D'>,
    <AxesSubplot:xlabel='B', ylabel='D'>,
    <AxesSubplot:xlabel='C', ylabel='D'>,
    <AxesSubplot:xlabel='D', ylabel='D'>]], dtype=object)

See :

Local connectivity graph

Hover to see nodes names; edges to Self not shown, Caped at 50 nodes.

Using a canvas is more power efficient and can get hundred of nodes ; but does not allow hyperlinks; , arrows or text (beyond on hover)

SVG is more flexible but power hungry; and does not scale well to 50 + nodes.

All aboves nodes referred to, (or are referred from) current nodes; Edges from Self to other have been omitted (or all nodes would be connected to the central node "self" which is not useful). Nodes are colored by the library they belong to, and scaled with the number of references pointing them

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File: /pandas/plotting/_misc.py#72
type: <class 'function'>
Commit: