`scipy.stats._stats_py:cumfreq`

source: build-install/usr/lib/python3.14/site-packages/scipy/stats/_stats_py.py:2357

Signature

def cumfreq(a, numbins = 10, defaultreallimits = None, weights = None)

Summary

Return a cumulative frequency histogram, using the histogram function.

Extended Summary

A cumulative histogram is a mapping that counts the cumulative number of observations in all of the bins up to the specified bin.

Parameters

a : array_like: Input array.
numbins : int, optional: The number of bins to use for the histogram. Default is 10.
defaultreallimits : tuple (lower, upper), optional: The lower and upper values for the range of the histogram. If no value is given, a range slightly larger than the range of the values in a is used. Specifically (a.min() - s, a.max() + s), where s = (1/2)(a.max() - a.min()) / (numbins - 1).
weights : array_like, optional: The weights for each value in a. Default is None, which gives each value a weight of 1.0

Returns

cumcount : ndarray: Binned values of cumulative frequency.
lowerlimit : float: Lower real limit
binsize : float: Width of each bin.
extrapoints : int: Extra points.

Examples

import numpy as np
import matplotlib.pyplot as plt
from scipy import stats
rng = np.random.default_rng()
x = [1, 4, 2, 1, 3, 1]
res = stats.cumfreq(x, numbins=4, defaultreallimits=(1.5, 5))

✓

res.cumcount
res.extrapoints

✗

np.int64(3)

Create a normal distribution with 1000 random values

samples = stats.norm.rvs(size=1000, random_state=rng)

✓

Calculate cumulative frequencies

res = stats.cumfreq(samples, numbins=25)

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Calculate space of values for x

x = res.lowerlimit + np.linspace(0, res.binsize*res.cumcount.size,
                                 res.cumcount.size + 1)

✓

Plot histogram and cumulative histogram

fig = plt.figure(figsize=(10, 4))
ax1 = fig.add_subplot(1, 2, 1)
ax2 = fig.add_subplot(1, 2, 2)

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ax1.hist(samples, bins=25)
ax1.set_title('Histogram')
ax2.bar(x[:-1], res.cumcount, width=res.binsize, align='edge')
ax2.set_title('Cumulative histogram')
ax2.set_xlim([x.min(), x.max()])

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(-3.362478726049059, 4.2456826787257675)

plt.show()

✓