Get Variance in Python – List & pandas DataFrame Column (4 Examples)
This post explains how to calculate the variance in the Python programming language.
Example 1: Calculating the Variance of a List Object
my_lt = [10, 6, 2, 2, 15, 20, 3, 7, 4] # Constructing a list in Python print(my_lt) # [10, 6, 2, 2, 15, 20, 3, 7, 4] |
my_lt = [10, 6, 2, 2, 15, 20, 3, 7, 4] # Constructing a list in Python print(my_lt) # [10, 6, 2, 2, 15, 20, 3, 7, 4]
import numpy as np # Load NumPy library |
import numpy as np # Load NumPy library
print(np.var(my_lt)) # Computing the variance of a list # 34.888888888888886 |
print(np.var(my_lt)) # Computing the variance of a list # 34.888888888888886
Example 2: Calculating the Variance of the Columns in a pandas DataFrame
import pandas as pd # Import pandas library |
import pandas as pd # Import pandas library
my_df = pd.DataFrame({'A':range(10, 17), # Constructing a pandas DataFrame 'B':[6, 1, 8, 5, 3, 8, 9], 'C':range(2, 9), 'GRP':['gr1', 'gr2', 'gr1', 'gr3', 'gr1', 'gr2', 'gr3']}) print(my_df) # A B C GRP # 0 10 6 2 gr1 # 1 11 1 3 gr2 # 2 12 8 4 gr1 # 3 13 5 5 gr3 # 4 14 3 6 gr1 # 5 15 8 7 gr2 # 6 16 9 8 gr3 |
my_df = pd.DataFrame({'A':range(10, 17), # Constructing a pandas DataFrame 'B':[6, 1, 8, 5, 3, 8, 9], 'C':range(2, 9), 'GRP':['gr1', 'gr2', 'gr1', 'gr3', 'gr1', 'gr2', 'gr3']}) print(my_df) # A B C GRP # 0 10 6 2 gr1 # 1 11 1 3 gr2 # 2 12 8 4 gr1 # 3 13 5 5 gr3 # 4 14 3 6 gr1 # 5 15 8 7 gr2 # 6 16 9 8 gr3
print(my_df.var()) # Computing the variance of all columns # A 4.666667 # B 8.571429 # C 4.666667 # dtype: float64 |
print(my_df.var()) # Computing the variance of all columns # A 4.666667 # B 8.571429 # C 4.666667 # dtype: float64
Example 3: Calculating the Variance of the Columns in a pandas DataFrame by Group
print(my_df.groupby('GRP').var()) # Computing the column variances by group # A B C # GRP # gr1 4.0 6.333333 4.0 # gr2 8.0 24.500000 8.0 # gr3 4.5 8.000000 4.5 |
print(my_df.groupby('GRP').var()) # Computing the column variances by group # A B C # GRP # gr1 4.0 6.333333 4.0 # gr2 8.0 24.500000 8.0 # gr3 4.5 8.000000 4.5
Example 4: Calculating the Variance of the Rows in a pandas DataFrame
print(my_df.var(axis = 1)) # Computing the variance of all rows # 0 16.000000 # 1 28.000000 # 2 16.000000 # 3 21.333333 # 4 32.333333 # 5 19.000000 # 6 19.000000 # dtype: float64 |
print(my_df.var(axis = 1)) # Computing the variance of all rows # 0 16.000000 # 1 28.000000 # 2 16.000000 # 3 21.333333 # 4 32.333333 # 5 19.000000 # 6 19.000000 # dtype: float64