df.loc change more than one column based on condition

December 17, 2022

What I want to try is change more than one column based on condition.

Example("Data just for the explanation") =>

import pandas as pd


data = {'s' : ["placementTop","placementProductPage","safgasf", "aslgkmalksg", "ıowjsakguıwa", "placementTop","placementProductPage", "placementTop","placementProductPage",], "State": ["enabled","paused","sagasg", "sagaskg", "sagkşlaksg", "sagaskg", "sagkşlaksg", "sagaskg", "sagkşlaksg"], "x": [10,20,25,30,5,30,5,30,5], "y" : [12,20,25,30,5,20,25,30,5]}

df = pd.DataFrame(data)


filter = df.loc[(df["s"] == "placementTop") & (df["State"] == "enabled"), "x"] = 2


print(df)

                      s       State   x   y
0          placementTop     enabled   2  12
1  placementProductPage      paused  20  20
2               safgasf      sagasg  25  25
3           aslgkmalksg     sagaskg  30  30
4          ıowjsakguıwa  sagkşlaksg   5   5
5          placementTop     sagaskg  30  20
6  placementProductPage  sagkşlaksg   5  25
7          placementTop     sagaskg  30  30
8  placementProductPage  sagkşlaksg   5   5

This is working for me but I want to change y column too at the same time.

>Solution :

This will update the x and y columns for the rows that meet the condition s == "placementTop" and State == "enabled"

df.loc[(df["s"] == "placementTop") & (df["State"] == "enabled"), ["x", "y"]] = 2

Output:

                      s       State  x   y
0          placementTop     enabled  2  2
1  placementProductPage      paused 20  20
2               safgasf      sagasg 25  25
3           aslgkmalksg     sagaskg 30  30
4          ıowjsakguıwa  sagkşlaksg  5   5
5          placementTop     sagaskg 30  20
6  placementProductPage  sagkşlaksg  5  25
7          placementTop     sagaskg 30  30
8  placementProductPage  sagkşlaksg  5   5