How to perform arithmetic operations with specific elements of a dataframe? - python-3.x

Question

I am trying to understand how to perform arithmetic operations on a dataframe in python.
import pandas as pd
import numpy as np
df = pd.DataFrame({'col1':[2,38,7,5],'col2':[1,3,2,4]})
print (unsorted_df.sum())
This is what I'm getting (in terms of the output), but I want to have more control over which sum I am getting.
col1 52
col2 10
dtype: int64
Just wondering how I would add individual elements in the dataframe together.

Answer 1

Your question is not very clear but still I will try to cover all possible scenarios,
Input:
df
col1 col2
0 2 1
1 38 3
2 7 2
3 5 4
If you want the sum of columns,
df.sum(axis = 0)
Output:
col1 52
col2 10
dtype: int64
If you want the sum of rows,
df.sum(axis = 1)
0 3
1 41
2 9
3 9
dtype: int64
If you want to add a list of numbers into a column,
num = [1, 2, 3, 4]
df['col1'] = df['col1'] + num
df
Output:
col1 col2
0 3 1
1 40 3
2 10 2
3 9 4
If you want to add a list of numbers into a row,
num = [1, 2]
df.loc[0] = df.loc[0] + num
df
Output:
col1 col2
0 3 3
1 38 3
2 7 2
3 5 4
If you want to add a single number to a column,
df['col1'] = df['col1'] + 2
df
Output:
col1 col2
0 4 1
1 40 3
2 9 2
3 7 4
If you want to add a single number to a row,
df.loc[0] = df.loc[0] + 2
df
Output:
col1 col2
0 4 3
1 38 3
2 7 2
3 5 4
If you want to add a number to any number(an element of row i and column j),
df.iloc[1,1] = df.iloc[1,1] + 5
df
Output:
col1 col2
0 2 1
1 38 8
2 7 2
3 5 4