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.
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_coordinatesPlots parallel coordinates for multivariate data.
plotting.andrews_curvesGenerates Andrews curves for visualizing clusters of multivariate data.
plotting.radvizCreates a RadViz visualization.
plotting.bootstrap_plotVisualizes 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)