pandas column sum code example

Example 1: pandas ttable with sum totals

import numpy as np
import pandas as pd


df = pd.DataFrame({'a': [10,20],'b':[100,200],'c': ['a','b']})

df.loc['Column_Total']= df.sum(numeric_only=True, axis=0)
df.loc[:,'Row_Total'] = df.sum(numeric_only=True, axis=1)

print(df)

                 a      b    c  Row_Total
0             10.0  100.0    a      110.0
1             20.0  200.0    b      220.0
Column_Total  30.0  300.0  NaN      330.0

Example 2: python column = sum of list of columns

list_of_my_columns = ['Col A', 'Col E', 'Col Z']
df['Sum'] = df[list_of_my_columns].sum(axis=1)

Example 3: pandas sum missing values

dfObj.isnull().sum()

Example 4: pandas sum

df.at['Total', 'MyColumn'] = df['MyColumn'].sum()
print (df)
         X  MyColumn      Y      Z
0        A      84.0   13.0   69.0
1        B      76.0   77.0  127.0
2        C      28.0   69.0   16.0
3        D      28.0   28.0   31.0
4        E      19.0   20.0   85.0
5        F      84.0  193.0   70.0
Total  NaN     319.0    NaN    NaN

Example 5: pandas sum

# select numeric columns and calculate the sums
sums = df.select_dtypes(pd.np.number).sum().rename('total')

# append sums to the data frame
df.append(sums)
#         X  MyColumn      Y      Z
#0        A      84.0   13.0   69.0
#1        B      76.0   77.0  127.0
#2        C      28.0   69.0   16.0
#3        D      28.0   28.0   31.0
#4        E      19.0   20.0   85.0
#5        F      84.0  193.0   70.0
#total  NaN     319.0  400.0  398.0