Standard Deviation in Python (5 Examples) | List, DataFrame Column & Row | std & groupby Functions

How to calculate the standard deviation in the Python programming language. More details: https://statisticsglobe.com/standard-deviation-python
Python code of this video:

my_list = [2, 7, 5, 5, 3, 9, 5, 9, 3, 1, 1] # Create example list
print(my_list) # Print example list
# [2, 7, 5, 5, 3, 9, 5, 9, 3, 1, 1]

import numpy as np # Load NumPy library

print(np.std(my_list)) # Get standard deviation of list
# 2.7423823870906103

import pandas as pd # Import pandas library in Python

data = pd.DataFrame({'x1':range(42, 11, - 2), # Create pandas DataFrame
'x2':[5, 9, 7, 3, 1, 4, 5, 4, 1, 2, 3, 3, 8, 1, 7, 5],
'x3':range(200, 216),
'group':['A', 'C', 'B', 'C', 'B', 'B', 'C', 'A', 'C', 'A', 'C', 'A', 'B', 'C', 'B', 'B']})
print(data) # Print pandas DataFrame

print(data['x1'].std()) # Get standard deviation of one column
# 9.521904571390467

print(data.std(numeric_only = True)) # Get standard deviation of all columns
# x1 9.521905
# x2 2.516611
# x3 4.760952
# dtype: float64

print(data.std(axis = 1)) # Get standard deviation of rows
# 0 103.568013
# 1 103.074407
# 2 104.787086
# 3 107.220956
# 4 108.932701
# 5 108.868422
# 6 109.546033
# 7 110.924900
# 8 112.988200
# 9 113.694034
# 10 114.421735
# 11 115.494589
# 12 115.001449
# 13 118.306100
# 14 117.542900
# 15 119.274194
# dtype: float64

print(data.std(axis = 1, numeric_only = True)) # Get standard deviation of rows
# x1 x2 x3
# group
# A 9.574271 1.290994 4.787136
# B 11.290114 2.581989 5.645057
# C 8.891944 3.011091 4.445972

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