Pandas – find row by column value (id) and update its values

January 14, 2022

I’m looking for an efficient way to update one ow in Pandas Dataframe (like in DB).

There is an id column with unique values (ids)

contacts = 

   id  ... phone          email
0  33  ... +4219999999    WORK:pete@zzz.de
1  45  ... +4215444444    HOME:rot@zzz.de
2  20  ... +4213333333    WORK:aon@zzz.de
3  11  ... +4215553454    WORK:lev@zzz.de

I want to update row with id == 45 by a dict {'phone'='+4511111111','email':'freddy@gg.com'}

Basically, I want to replace it with data from a given dictionary.

This way I can get the row:

contact = contacts.query(f'internal_id == "45"')

How to modify the dataframe so all the values of the row change?

>Solution :

You can set_index with 'id' and update the relevant row with a dictionary by passing it to a Series:

df = df.set_index('id')
df.loc[45] = pd.Series(d)

Output:

          phone             email
id                               
33   4219999999  WORK:pete@zzz.de
45  +4511111111     freddy@gg.com
20   4213333333   WORK:aon@zzz.de
11   4215553454   WORK:lev@zzz.de