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Histogram Matplotlib

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How do you do a histogram in Matplotlib?

Create Histogram In Matplotlib, we use the hist() function to create histograms. The hist() function will use an array of numbers to create a histogram, the array is sent into the function as an argument.

What is histogram Matplotlib?

Advertisements. A histogram is an accurate representation of the distribution of numerical data. It is an estimate of the probability distribution of a continuous variable. It is a kind of bar graph.

What does hist () do?

hist( x ) creates a histogram bar chart of the elements in vector x . The elements in x are sorted into 10 equally spaced bins along the x-axis between the minimum and maximum values of x . hist displays bins as rectangles, such that the height of each rectangle indicates the number of elements in the bin.

Is histogram supported by Pyplot?

pyplot. hist() is a widely used histogram plotting function that uses np. histogram() and is the basis for Pandas' plotting functions. Matplotlib, and especially its object-oriented framework, is great for fine-tuning the details of a histogram.


import matplotlib.pyplot as plt
import numpy as np

mu, sigma = 100, 15
x = mu + sigma * np.random.randn(10000)
hist, bins = np.histogram(x, bins=50)
width = 0.7 * (bins[1] - bins[0])
center = (bins[:-1] + bins[1:]) / 2
plt.bar(center, hist, align='center', width=width)
plt.show()

enter image description here

The object-oriented interface is also straightforward:

fig, ax = plt.subplots()
ax.bar(center, hist, align='center', width=width)
fig.savefig("1.png")

If you are using custom (non-constant) bins, you can pass compute the widths using np.diff, pass the widths to ax.bar and use ax.set_xticks to label the bin edges:

import matplotlib.pyplot as plt
import numpy as np

mu, sigma = 100, 15
x = mu + sigma * np.random.randn(10000)
bins = [0, 40, 60, 75, 90, 110, 125, 140, 160, 200]
hist, bins = np.histogram(x, bins=bins)
width = np.diff(bins)
center = (bins[:-1] + bins[1:]) / 2

fig, ax = plt.subplots(figsize=(8,3))
ax.bar(center, hist, align='center', width=width)
ax.set_xticks(bins)
fig.savefig("/tmp/out.png")

plt.show()

enter image description here


If you don't want bars you can plot it like this:

import numpy as np
import matplotlib.pyplot as plt

mu, sigma = 100, 15
x = mu + sigma * np.random.randn(10000)

bins, edges = np.histogram(x, 50, normed=1)
left,right = edges[:-1],edges[1:]
X = np.array([left,right]).T.flatten()
Y = np.array([bins,bins]).T.flatten()

plt.plot(X,Y)
plt.show()

histogram


I know this does not answer your question, but I always end up on this page, when I search for the matplotlib solution to histograms, because the simple histogram_demo was removed from the matplotlib example gallery page.

Here is a solution, which doesn't require numpy to be imported. I only import numpy to generate the data x to be plotted. It relies on the function hist instead of the function bar as in the answer by @unutbu.

import numpy as np
mu, sigma = 100, 15
x = mu + sigma * np.random.randn(10000)

import matplotlib.pyplot as plt
plt.hist(x, bins=50)
plt.savefig('hist.png')

enter image description here

Also check out the matplotlib gallery and the matplotlib examples.


If you're willing to use pandas:

pandas.DataFrame({'x':hist[1][1:],'y':hist[0]}).plot(x='x',kind='bar')