Python Pandas: Get index of rows where column matches certain value

You can use the .loc method to filter the DataFrame and get the boolean mask, and then use the .index property to get the index of the rows that match the certain value. Here's an example:

Python Pandas: Get index of rows where column matches certain value using the index method

import pandas as pd

# create a sample dataframe
df = pd.DataFrame({'A': [1, 2, 3, 4, 5],
                   'B': [2, 3, 4, 5, 6],
                   'C': [3, 4, 5, 6, 7]},
                  index=[100, 101, 102, 103, 104])

# find the rows where column 'B' has the value 3
match = df.loc[df['B'] == 3].index
print(match)

This will output the index of the rows where column 'B' has the value 3:

Python Pandas: Get the index of the rows where column 'B' has the value 3

Int64Index([101], dtype='int64')

<div class="alert alert-info flex not-prose"> <span class="hidden md:block">Watch a video course </span> Python - The Practical Guide</div>

You can use the same approach to filter on multiple columns and multiple conditions. Example:

Python Pandas: filter on multiple columns and multiple conditions

df.loc[(df['A']==1) & (df['B']==2)].index

It will return the rows index which has A = 1 and B = 2