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 dimensionand\(t\) 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 stringsor 3-element floating point RGB values.

colormapstr or matplotlib colormap object, default None

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

**kwargs

Options to pass to matplotlib plotting method.

Returns:

matplotlib.axes.Axes

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')