pandas.plotting.scatter_matrix#

pandas.plotting.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)[source]#

Draw a matrix of scatter plots.

Parameters:

frameDataFrame

alphafloat, optional

Amount of transparency applied.

figsize(float,float), optional

A tuple (width, height) in inches.

axMatplotlib axis object, optional

gridbool, optional

Setting this to True will show the grid.

diagonal{‘hist’, ‘kde’}

Pick between ‘kde’ and ‘hist’ for either Kernel Density Estimation orHistogram plot in the diagonal.

markerstr, optional

Matplotlib marker type, default ‘.’.

density_kwdskeywords

Keyword arguments to be passed to kernel density estimate plot.

hist_kwdskeywords

Keyword arguments to be passed to hist function.

range_paddingfloat, 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.

Examples

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