Getting the Row Index in Pandas

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Getting the Row Index in Pandas: A Guide

When working with large data sets in Pandas, it is often necessary to retrieve the index of a specific row in the data frame.

In this guide post, we will explore different methods to get the row index in Pandas.

Using df.index method

The simplest way to get the index of a Pandas data frame is by using the df.index property.

This returns a range of indices for the data frame, starting from 0 and incrementing by 1 for each row.

For example:

import pandas as pd

df = pd.DataFrame({'Name': ['John', 'Jane', 'Jim', 'Jill'],
                   'Grade': [85, 75, 95, 65]})

print(df.index)

This will produce the following output:

RangeIndex(start=0, stop=4, step=1)

Using df.index.get_loc() method

To get the index of a specific row, we can use the df.index.get_loc() method.

This method takes a row label as an argument and returns its index.

For example:

import pandas as pd

df = pd.DataFrame({'Name': ['John', 'Jane', 'Jim', 'Jill'],
                   'Grade': [85, 75, 95, 65]})

index = df.index.get_loc('Jim')
print(index)

This will produce the following output:

2

Using df.loc[] method

Another way to get the index of a specific row is by using the df.loc[] method.

This method takes a row label as an argument and returns the entire row as a Pandas series, including both the index and the values.

To get just the index, we can access the name attribute of the series.

For example:

import pandas as pd

df = pd.DataFrame({'Name': ['John', 'Jane', 'Jim', 'Jill'],
                   'Grade': [85, 75, 95, 65]})

row = df.loc['Jim']
index = row.name
print(index)

This will produce the following output:

2

Summary

In conclusion, getting the row index in Pandas is a simple operation that can be performed using a variety of methods.

Whether you need to retrieve the index of a specific row, or the range of indices for the entire data frame, Pandas provides a convenient and efficient solution.

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