Compute the histogram of a set of data using NumPy in Python

Numpy provides us the feature to compute the Histogram for the given data set using NumPy.histogram() function. The formation of histogram depends on the data set, whether it is predefined or randomly generated.

Syntax : numpy.histogram(data, bins=10, range=None, normed=None, weights=None, density=None)

Case 1: Computing the Numpy Histogram with the help of Random Data set

Python3

# import Numpy and matplotlib
from matplotlib import pyplot as plt
import numpy as np


# Creating random dataset
data_set = np.random.randint(100, size=(50))

# Creation of plot
fig = plt.figure(figsize=(10, 6))

# plotting the Histogram with certain intervals
plt.hist(data_set, bins=[0, 10, 20, 30, 40, 50,
                         60, 70, 80, 90, 100])

# Giving title to Histogram
plt.title("Random Histogram")

# Displaying Histogram
plt.show()

Output:

In the above example, we created a random data set using np.random.randint() and plot the Numpy Histogram

Case 2: Computing the Numpy Histogram with the help of Pre-defined Data set

Python3

# import Numpy and matplotlib
from matplotlib import pyplot as plt
import numpy as np


# Using predefined dataset
data_set = [45, 85, 95, 10, 58, 77, 92, 72, 52,
            22, 32, 5, 95, 2, 23, 24, 50, 40, 60,
            69, 44, 80, 21, 15, 17, 55, 21, 88]

# Creation of plot
fig = plt.figure(figsize=(10, 5))

# plotting the Histogram with certain intervals
plt.hist(data_set, bins=[0, 15, 30, 45, 60, 75, 90, 105])

# Giving title to Histogram
plt.title("Predefined Histogram")

# Displaying Histogram
plt.show()

In the above example, we take a predefined data set and plot the Numpy Histogram.