pandas.plotting.radviz(frame, class_column, ax=None, color=None, colormap=None, **kwds)
[source]
Plot a multidimensional dataset in 2D.
Each Series in the DataFrame is represented as a evenly distributed slice on a circle. Each data point is rendered in the circle according to the value on each Series. Highly correlated Series
in the DataFrame
are placed closer on the unit circle.
RadViz allow to project a N-dimensional data set into a 2D space where the influence of each dimension can be interpreted as a balance between the influence of all dimensions.
More info available at the original article describing RadViz.
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See also
plotting.andrews_curves
>>> df = pd.DataFrame({ ... 'SepalLength': [6.5, 7.7, 5.1, 5.8, 7.6, 5.0, 5.4, 4.6, ... 6.7, 4.6], ... 'SepalWidth': [3.0, 3.8, 3.8, 2.7, 3.0, 2.3, 3.0, 3.2, ... 3.3, 3.6], ... 'PetalLength': [5.5, 6.7, 1.9, 5.1, 6.6, 3.3, 4.5, 1.4, ... 5.7, 1.0], ... 'PetalWidth': [1.8, 2.2, 0.4, 1.9, 2.1, 1.0, 1.5, 0.2, ... 2.1, 0.2], ... 'Category': ['virginica', 'virginica', 'setosa', ... 'virginica', 'virginica', 'versicolor', ... 'versicolor', 'setosa', 'virginica', ... 'setosa'] ... }) >>> rad_viz = pd.plotting.radviz(df, 'Category') # doctest: +SKIP
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Licensed under the 3-clause BSD License.
https://pandas.pydata.org/pandas-docs/version/0.25.0/reference/api/pandas.plotting.radviz.html