Creating the histogram provides the visual representation of data distribution. By using a histogram we can represent a large amount of data and its frequency as one continuous plot.
How to plot a histogram using Matplotlib
For creating the Histogram in Matplotlib we use hist() function which belongs to pyplot module. For plotting two histograms together, we have to use hist() function separately with two datasets by giving some settings.
Syntax of matplotlib.pyplot.hist
matplotlib.pyplot.hist(x, bins, edgecolor color, label)
Example 1:
Here, we are simply taking two series using the Numpy random and passing both series to the hist()function, and we’re using the same plot to plot two histograms together.
Python3
# importing librariesimport matplotlib.pyplot as pltimport numpy as np# generating two series of random# values using numpy random module# of shape (500,1)series1 = np.random.randn(500, 1)series2 = np.random.randn(400, 1)# plotting first histogramplt.hist(series1)# plotting second histogramplt.hist(series2)# Showing the plot using plt.show()plt.show() |
Output:
Example 2:
Here, we are using label, edgecolor, and opacity.
Python3
# importing librariesimport matplotlib.pyplot as pltimport numpy as npfrom numpy.lib.histograms import histogram# generating two series of random values# using numpy random module of shape (500,1)series1 = np.random.randn(500, 1)series2 = np.random.randn(400, 1)# plotting first histogramplt.hist(series1, label='series1', alpha=.8, edgecolor='red')# plotting second histogramplt.hist(series2, label='series2', alpha=0.7, edgecolor='yellow')plt.legend()# Showing the plot using plt.show()plt.show() |
Output:
Example 3:
Histograms represent two age groups using given data.
Python3
# importing librariesimport matplotlib.pyplot as plt# giving two age groups dataage_g1 = [1, 3, 5, 10, 15, 17, 18, 16, 19, 21, 23, 28, 30, 31, 33, 38, 32, 40, 45, 43, 49, 55, 53, 63, 66, 85, 80, 57, 75, 93, 95]age_g2 = [6, 4, 15, 17, 19, 21, 28, 23, 31, 36, 39, 32, 50, 56, 59, 74, 79, 34, 98, 97, 95, 67, 69, 92, 45, 55, 77, 76, 85]# plotting first histogramplt.hist(age_g1, label='Age group1', bins=14, alpha=.7, edgecolor='red')# plotting second histogramplt.hist(age_g2, label="Age group2", bins=14, alpha=.7, edgecolor='yellow')plt.legend()# Showing the plot using plt.show()plt.show() |
Output:
Example 4:
Changing bar color from the default
Python3
# importing librariesimport matplotlib.pyplot as plt# giving two age groups dataage_g1 = [1, 3, 5, 10, 15, 17, 18, 16, 19, 21, 23, 28, 30, 31, 33, 38, 32, 40, 45, 43, 49, 55, 53, 63, 66, 85, 80, 57, 75, 93, 95]age_g2 = [6, 4, 15, 17, 19, 21, 28, 23, 31, 36, 39, 32, 50, 56, 59, 74, 79, 34, 98, 97, 95, 67, 69, 92, 45, 55, 77, 76, 85]# plotting first histogramplt.hist(age_g1, label='Age group1', alpha=.7, color='red')# plotting second histogramplt.hist(age_g2, label="Age group2", alpha=.5, edgecolor='black', color='yellow')plt.legend()# Showing the plot using plt.show()plt.show() |
Output:
