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.
