On this page
pandas.plotting.radviz
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 theDataFrame
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.
Parameters: -
frame : DataFrame
-
Pandas object holding the data.
-
class_column : str
-
Column name containing the name of the data point category.
-
ax : matplotlib.axes.Axes, optional
-
A plot instance to which to add the information.
-
color : list[str] or tuple[str], optional
-
Assign a color to each category. Example: [‘blue’, ‘green’].
-
colormap : str or matplotlib.colors.Colormap, default None
-
Colormap to select colors from. If string, load colormap with that name from matplotlib.
-
kwds : optional
-
Options to pass to matplotlib scatter plotting method.
Returns: -
axes : matplotlib.axes.Axes
See also
pandas.plotting.andrews_curves
- Plot clustering visualization.
Examples
>>> 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
-
© 2008–2012, AQR Capital Management, LLC, Lambda Foundry, Inc. and PyData Development Team
Licensed under the 3-clause BSD License.
https://pandas.pydata.org/pandas-docs/version/0.24.2/reference/api/pandas.plotting.radviz.html