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 of Andrews curves, 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/master/pandas/tests/io/data/csv/iris.csv'
... )
>>> pd.plotting.andrews_curves(df, 'Name')

../../_images/pandas-plotting-andrews_curves-1.png

Plotting pandas.plotting.autocorrelation_plot