matplotlib.pyplot.ecdf#

matplotlib.pyplot.ecdf(x,weights=None,*,complementary=False,orientation='vertical',compress=False,data=None,**kwargs)[source]#

Compute and plot the empirical cumulative distribution function ofx.

Added in version 3.8.

Parameters:

x1d array-like

The input data. Infinite entries are kept (and move the relevantend of the ecdf from 0/1), but NaNs and masked values are errors.

weights1d array-like or None, default: None

The weights of the entries; must have the same shape asx.Weights corresponding to NaN data points are dropped, and then theremaining weights are normalized to sum to 1. If unset, allentries have the same weight.

complementarybool, default: False

Whether to plot a cumulative distribution function, which increasesfrom 0 to 1 (the default), or a complementary cumulativedistribution function, which decreases from 1 to 0.

orientation{"vertical", "horizontal"}, default: "vertical"

Whether the entries are plotted along the x-axis ("vertical", thedefault) or the y-axis ("horizontal"). This parameter takes thesame values as inhist.

compressbool, default: False

Whether multiple entries with the same values are grouped together(with a summed weight) before plotting. This is mainly useful ifx contains many identical data points, to decrease the renderingcomplexity of the plot. Ifx contains no duplicate points, thishas no effect and just uses some time and memory.

Returns:

Line2D

Other Parameters:

dataindexable object, optional

If given, the following parameters also accept a strings, which isinterpreted asdata[s] ifs is a key indata:

x,weights

**kwargs

Keyword arguments control theLine2D properties:

Property	Description
agg_filter	a filter function, which takes a (m, n, 3) float array and a dpi value, and returns a (m, n, 3) array and two offsets from the bottom left corner of the image
alpha	float or None
animated	bool
antialiased oraa	bool
clip_box	BboxBase or None
clip_on	bool
clip_path	Patch or (Path, Transform) or None
color orc	color
dash_capstyle	CapStyle or {'butt', 'projecting', 'round'}
dash_joinstyle	JoinStyle or {'miter', 'round', 'bevel'}
dashes	sequence of floats (on/off ink in points) or (None, None)
data	(2, N) array or two 1D arrays
drawstyle ords	{'default', 'steps', 'steps-pre', 'steps-mid', 'steps-post'}, default: 'default'
figure	Figure orSubFigure
fillstyle	{'full', 'left', 'right', 'bottom', 'top', 'none'}
gapcolor	color or None
gid	str
in_layout	bool
label	object
linestyle orls	{'-', '--', '-.', ':', '', (offset, on-off-seq), ...}
linewidth orlw	float
marker	marker style string,Path orMarkerStyle
markeredgecolor ormec	color
markeredgewidth ormew	float
markerfacecolor ormfc	color
markerfacecoloralt ormfcalt	color
markersize orms	float
markevery	None or int or (int, int) or slice or list[int] or float or (float, float) or list[bool]
mouseover	bool
path_effects	list ofAbstractPathEffect
picker	float or callable[[Artist, Event], tuple[bool, dict]]
pickradius	float
rasterized	bool
sketch_params	(scale: float, length: float, randomness: float)
snap	bool or None
solid_capstyle	CapStyle or {'butt', 'projecting', 'round'}
solid_joinstyle	JoinStyle or {'miter', 'round', 'bevel'}
transform	unknown
url	str
visible	bool
xdata	1D array
ydata	1D array
zorder	float

Notes

Note

This is thepyplot wrapper foraxes.Axes.ecdf.

The ecdf plot can be thought of as a cumulative histogram with one binper data entry; i.e. it reports on the entire dataset without anyarbitrary binning.

Ifx contains NaNs or masked entries, either remove them first fromthe array (if they should not taken into account), or replace them by-inf or +inf (if they should be sorted at the beginning or the end ofthe array).

Examples usingmatplotlib.pyplot.ecdf#

Cumulative distributions

Cumulative distributions