pandas.plotting.scatter_matrix — pandas 3.0.0.dev0+2100.gf496acffcc documentation (original) (raw)

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.

Each pair of numeric columns in the DataFrame is plotted against each other, resulting in a matrix of scatter plots. The diagonal plots can display either histograms or Kernel Density Estimation (KDE) plots for each variable.

Parameters:

frameDataFrame

The data to be plotted.

alphafloat, optional

Amount of transparency applied.

figsize(float,float), optional

A tuple (width, height) in inches.

axMatplotlib axis object, optional

An existing Matplotlib axis object for the plots. If None, a new axis is created.

gridbool, 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.

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.

See also

plotting.parallel_coordinates

Plots parallel coordinates for multivariate data.

plotting.andrews_curves

Generates Andrews curves for visualizing clusters of multivariate data.

plotting.radviz

Creates a RadViz visualization.

plotting.bootstrap_plot

Visualizes uncertainty in data via bootstrap sampling.

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)