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In Seaborn, you can plot a normal distribution by using the seaborn.distplot() function and passing in the data you want to plot as the first parameter, followed by the type of distribution you want to plot as the second parameter. You can then specify other parameters such as the size and color of the plot if desired.
You can use the following methods to plot a normal distribution with the data visualization library in Python:
Method 1: Plot Normal Distribution Histogram
sns.displot(x)
Method 2: Plot Normal Distribution Curve
sns.displot(x, kind='kde')
Method 3: Plot Normal Distribution Histogram with Curve
sns.displot(x, kde=True)
The following examples show how to use each method in practice.
Example 1: Plot a Normal Distribution Histogram
The following code shows how to plot a normal distribution histogram in seaborn:
import numpy as np import seaborn as sns #make this example reproducible np.random.seed(0) #create data x = np.random.normal(size=1000) #create normal distribution histogram sns.displot(x)
Example 2: Plot a Normal Distribution Curve
The following code shows how to plot a normal distribution curve in seaborn:
import numpy as np import seaborn as sns #make this example reproducible np.random.seed(0) #create data x = np.random.normal(size=1000) #create normal distribution curve sns.displot(x, kind='kde')
Example 3: Plot a Normal Distribution Histogram with Curve
import numpy as np import seaborn as sns #make this example reproducible np.random.seed(0) #create data x = np.random.normal(size=1000) #create normal distribution curve sns.displot(x, kde=True)
The following tutorials explain how to perform other common operations in seaborn: