A histogram is a graph that displays the frequency of values in a metric variable’s intervals. These intervals are referred to as “bins,” and they are all the same width.
We can create a histogram from the panda’s data frame using the df.hist() function.
Syntax:
DataFrame.hist(column=None, by=None, grid=True, xlabelsize=None, xrot=None, ylabelsize=None, yrot=None, ax=None, sharex=False, sharey=False, figsize=None, layout=None, bins=10, backend=None, legend=False, **kwargs)
Example 1: Creating a basic histogram( histogram for individual columns)
We use df.hist() and plot.show() to display the Histogram.
CSV file used: gene_expression.csv
Python3
# import libraries and packages import numpy as np import pandas as pd import matplotlib.pyplot as plt import seaborn as sns # reading the CSV file df = pd.read_csv('gene_expression.csv') # displaying the DataFrame print(df) # creating a basic histogram df.hist() plt.show() |
Output:
Example 2: Creating a modified histogram(plotting histogram by the group)
In this example, we add extra parameters to the hist method. We have changed the fig size, no of bins is specified as 15, and by parameter is given which ensures histograms for each cancer group are created.
Python3
# import libraries and packages import numpy as np import pandas as pd import matplotlib.pyplot as plt import seaborn as sns # reading the CSV file df = pd.read_csv('gene_expression.csv') # displaying the DataFrame print(df) # creating a basic histogram df.hist(by='Cancer Present', figsize=[12, 8], bins=15) plt.show() |
Output:
