Histograms are immensely powerful visualizations that show the number of occurrences for each value of a variable, creating a distribution of results. If a variable is a continuous value, occurrences are grouped into bins. For example, when analyzing a school's test results, we could count the number of students who scored in the range 100% to 95%, 95% to 90%, 90% to 85%, etc.
Since histograms are a special case of bar charts, the can be created with
plt.bar(). However, this requires manually binning the values. With, Matplotlib's
plt.hist(), users can pass in raw data and Matplotlib will automatically bin and count the values to produce a histogram.
To create a histogram use the
import matplotlib.pyplot as plt values = [1, 1, 2, 3, 8, 7, 5, 4, 1, 3, 2, 4, 5, 8, 9] # Create a histogram here plt.hist(values) plt.ylabel("Quantity") plt.xlabel("Value") plt.show()
Matplotlib allows for many histogram customizations: