Python - Pandas: get row indices for a particular value in a column

Question

Given a pandas dataframe, is there a way to get the indices of rows where a column has particular values?

Consider the following toy example:

CSV (save as test1.csv)

id,val1,val2
1,20,A
1,19,A
1,23,B
2,10,B
2,10,A
2,14,A

What I currently have is this:

import pandas as pd

df = pd.read_csv('test1.csv')
print(df)

print(df[df['id']==1].index.to_list())
print(df[df['id']==2].index.to_list())

   id  val1 val2
0   1    20    A
1   1    19    A
2   1    23    B
3   2    10    B
4   2    10    A
5   2    14    A
[0, 1, 2]
[3, 4, 5]

Is there an option/functionality that can give me something like the following? (I want to be able to do this for large value lists, fast!)

print(df['id'].someFn([1,2]))

Desired output:

{1:[0,1,2], 2:[3,4,5]}

Answer 1

Try groupby:

{k: list(d.index) for k, d in df.groupby('id')}

Output:

{1: [0, 1, 2], 2: [3, 4, 5]}