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In Matplotlib, the bin size of a histogram can be adjusted by changing the “bins” argument within the plt.hist() function. This argument takes an integer or a sequence of integers that represent the number of bins or bin edges in the histogram. The default value is 10, but the bin size can be increased or decreased depending on the data. Additionally, the “range” argument can be used to specify the range of the data to be included in the histogram.
You can use one of the following methods to adjust the bin size of histograms in Matplotlib:
Method 1: Specify Number of Bins
plt.hist(data, bins=6)
Method 2: Specify Bin Boundaries
plt.hist(data, bins=[0, 4, 8, 12, 16, 20])
Method 3: Specify Bin Width
w=2 plt.hist(data, bins=np.arange(min(data), max(data) + w, w))
The following examples show how to use each of these methods in practice.
Example 1: Specify Number of Bins
The following code shows how to specify the number of bins to use in a histogram:
import matplotlib.pyplot as plt
#define data
data = [1, 2, 2, 4, 5, 5, 6, 8, 9, 12, 14, 15, 15, 15, 16, 17, 19]
#create histogram with specific number of bins
plt.hist(data, edgecolor='black', bins=6)
Keep in mind that the more bins you specify, the more narrow the bins will be.
Example 2: Specify Bin Boundaries
The following code shows how to specify the actual bin boundaries in a histogram:
import matplotlib.pyplot as plt
#define data
data = [1, 2, 2, 4, 5, 5, 6, 8, 9, 12, 14, 15, 15, 15, 16, 17, 19]
#create histogram with specific bin boundaries
plt.hist(data, edgecolor='black', bins=[0, 4, 8, 12, 16, 20])
Example 3: Specify Bin Width
The following code shows how to specify the bin width in a histogram:
import matplotlib.pyplot as plt import numpy as np #define data data = [1, 2, 2, 4, 5, 5, 6, 8, 9, 12, 14, 15, 15, 15, 16, 17, 19] #specify bin width to use w=2 #create histogram with specified bin width plt.hist(data, edgecolor='black', bins=np.arange(min(data), max(data) + w, w))
Keep in mind that the smaller the bin width you specify, the more narrow the bins will be.
The following tutorials explain how to perform other common functions in Matplotlib: