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 visualising clusters of multivariate data.
Andrews curves have the functional form:
- f(t) = x_1/sqrt(2) + x_2 sin(t) + x_3 cos(t) +
x_4 sin(2t) + x_5 cos(2t) + …
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_columnName of the column containing class names
- axmatplotlib axes object, default None
- samplesNumber of points to plot in each curve
- colorlist or tuple, optional
Colors to use for the different classes.
- colormapstr or matplotlib colormap object, default None
Colormap to select colors from. If string, load colormap with that name from matplotlib.
- **kwargs
Options to pass to matplotlib plotting method.
- Returns
- class:matplotlip.axis.Axes
Examples
>>> df = pd.read_csv( ... 'https://raw.github.com/pandas-dev/' ... 'pandas/main/pandas/tests/io/data/csv/iris.csv' ... ) >>> pd.plotting.andrews_curves(df, 'Name') <AxesSubplot:title={'center':'width'}>
