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We can use plt.hist()the method to draw a histogram from a list of data.

plt.hist()Method Syntax

matplotlib.pyplot.hist(x,
                       bins=None,
                       range=None,
                       density=False,
                       weights=None,
                       cumulative=False,
                       bottom=None,
                       histtype='bar',
                       align='mid',
                       orientation='vertical',
                       rwidth=None,
                       log=False,
                       color=None,
                       label=None,
                       stacked=False, *,
                       data=None,
                       **kwargs)

Example: Draw a histogram from a list of data using Matplotlib

import matplotlib.pyplot as plt

data = [3, 4, 2, 3, 4, 5, 4, 7, 8, 5, 4, 6, 2, 1, 0, 9, 7, 6, 6, 5, 4]

n, bins, patches = plt.hist(data)
plt.xlabel("Values")
plt.ylabel("Frequency")
plt.title("Histogram")
plt.show()

Here, we datahave the values ​​in a list . We pass this list into plt.hist()the command to generate a histogram from the list of values. plt.hist()The method returns the frequency of the bin, the endpoints of the bin, and the list of patches used to create the histogram.

In this example, we did not set binsa value for the parameter. By default, binsthe value of is 10, so the script creates a histogram from the data list with 10 bins.

binsIn addition, we can use the command to control the number of bins when making a histogram .

import matplotlib.pyplot as plt

data = [3, 4, 2, 3, 4, 5, 4, 7, 8, 5, 4, 6, 2, 1, 0, 9, 7, 6, 6, 5, 4]
n, bins, patches = plt.hist(data, bins=20)
plt.xlabel("Values")
plt.ylabel("Frequency")
plt.title("Histogram with 20 bins")
plt.show()

This process displays a histogram consisting of 20 bins, which is the result of evenly dividing the entire range of list values.

By default, densitythe value of the parameter is set to False; this means that we get a plot of the exact counts for each in the histogram bin. If we want a probability density plot for each bin in the list, we need to densityset to True. If densityis True, the integral of the area under the histogram is 1.

import matplotlib.pyplot as plt

data = [3, 4, 2, 3, 4, 5, 4, 7, 8, 5, 4, 6, 2, 1, 0, 9, 7, 6, 6, 5, 4]
n, bins, patches = plt.hist(data, bins=20, density=True)
plt.xlabel("Weight")
plt.ylabel("Probability")
plt.title("Histogram with Probability Plot")
plt.show()

Now we can colorset the color of the histogram using the parameter.

import matplotlib.pyplot as plt

data = [3, 4, 2, 3, 4, 5, 4, 7, 8, 5, 4, 6, 2, 1, 0, 9, 7, 6, 6, 5, 4]
n, bins, patches = plt.hist(data, bins=20, density=True, color="red")
plt.xlabel("Weight")
plt.ylabel("Probability")
plt.title("Red Histogram Plot")
plt.show()

This method produces a red histogram.