pandas.plotting.andrews_curves#

pandas.plotting.andrews_curves(frame, class_column, ax=None, samples=200, color=None, colormap=None, **kwargs)[source]#

Generate a matplotlib plot for visualizing clusters of multivariate data.

Andrews curves have the functional form:

$$f(t)=\frac{x_1}{\sqrt{2}}+x_2\sin (t)+x_3\cos (t)+x_4\sin (2t)+x_5\cos (2t)+\cdots$$

Where $x$ coefficients correspond to the values of each dimension and $t$ is linearly spaced between $-\pi$ and $+\pi$. Each row of frame then corresponds to a single curve.

Parameters:

frameDataFrame

Data to be plotted, preferably normalized to (0.0, 1.0).

class_columnlabel

Name of the column containing class names.

axaxes object, default None

Axes to use.

samplesint

Number of points to plot in each curve.

colorstr, list[str] or tuple[str], optional

Colors to use for the different classes. Colors can be strings or 3-element floating point RGB values.

colormapstr or matplotlib colormap object, default None

Colormap to select colors from. If a string, load colormap with that name from matplotlib.

**kwargs

Options to pass to matplotlib plotting method.

Returns:

matplotlib.axes.Axes

The matplotlib Axes object with the plot.

See also

plotting.parallel_coordinates

Plot parallel coordinates chart.

DataFrame.plot

Make plots of Series or DataFrame.

Examples

>>> df = pd.read_csv(
...     "https://raw.githubusercontent.com/pandas-dev/"
...     "pandas/main/pandas/tests/io/data/csv/iris.csv"
... )
>>> pd.plotting.andrews_curves(df, "Name")