Assume, you have a dataframe
0 1 2
0 10 20 30 1 40 50 60 2 70 80 90
The result for replaced 1 by diagonal of a dataframe is −
0 1 2 0 1 20 30 1 40 1 60 2 70 80 1
Solution
To solve this, we will follow the steps given below −
Define a dataframe
Create nested for loop to access all rows and columns,
for i in range(len(df)): for j in range(len(df)):
Check if the condition to match the diagonals, if it is matched then replace the position by 1. It is defined below,
if i == j: df.iloc[i ,j] = 1
Example
Let us see the below implementation to get a better understanding,
import pandas as pd
import numpy as np
data = [[10,20,30],[40,50,60],[70,80,90]]
df = pd.DataFrame(data)
print("Original DataFrame is\n ", df)
for i in range(len(df)):
for j in range(len(df)):
if i == j:
df.iloc[i ,j] = 1
print("Modified DataFrame is\n" ,df)Output
Original DataFrame is 0 1 2 0 10 20 30 1 40 50 60 2 70 80 90 Modified DataFrame is 0 1 2 0 1 20 30 1 40 1 60 2 70 80 1