Get Variance of NumPy Array in Python – np.var() Function (3 Examples)
This article shows how to apply the np.var function in the Python programming language.
Preparing the Examples
import numpy # Import numpy |
import numpy # Import numpy
x = np.array([[8, 2, 1, 7, 7, 5], # Constructing a NumPy array in Python [4, 10, 5, 9, 1, 4]]) print(x) # [[ 8 2 1 7 7 5] # [ 4 10 5 9 1 4]] |
x = np.array([[8, 2, 1, 7, 7, 5], # Constructing a NumPy array in Python [4, 10, 5, 9, 1, 4]]) print(x) # [[ 8 2 1 7 7 5] # [ 4 10 5 9 1 4]]
Example 1: Calculate Variance of All Array Values in Python
print(np.var(x)) # Computing the variance of all values # 8.354166666666666 |
print(np.var(x)) # Computing the variance of all values # 8.354166666666666
Example 2: Calculate Variance by Array Rows in Python
print(np.var(x, axis = 1)) # Computing the variance by rows # [7. 9.58333333] |
print(np.var(x, axis = 1)) # Computing the variance by rows # [7. 9.58333333]
Example 3: Calculate Variance by Array Columns in Python
print(np.var(x, axis = 0)) # Computing the variance by columns # [ 4. 16. 4. 1. 9. 0.25] |
print(np.var(x, axis = 0)) # Computing the variance by columns # [ 4. 16. 4. 1. 9. 0.25]