How to Get the First Row of a Column in Pandas Dataframe? – Definitive Guide

Pandas dataframe stores values as rows and columns.

You can get the first row of a column in the pandas dataframe using df.loc[0, ‘Column Name’] statement.

Basic Example

  • Use the loc attribute with a row axis value of 0 to get the first row of a column in the pandas dataframe.
df.loc[0, 'Column Name']
  • The first-row value of the column printed.

This tutorial teaches you how to get the first row of a column in the Pandas Dataframe.

Sample Dataframe

For demonstration, first, create a dataframe with three columns.

import pandas as pd
import numpy as np

data = {'Column 1': [1,2,np.nan,4,5,np.nan,None],
        'Column 2': [2,2,np.nan,4,np.nan,np.nan,None],
        'Column 3': [3,2,None,4,5,None,None]

df = pd.DataFrame(data,columns=['Column 1','Column 2','Column 3'])


Dataframe Will Look Like

Column 1Column 2Column 3

Now, you’ll use this dataframe and select the first row of any given column.

Using loc attribute

The loc selects rows based on their label(s).

  • Pass only the row and column labels to get any cell value of a pandas dataframe.
  • The first row’s index will be 0 if you’ve NOT used any custom row index
  • If you’ve used any custom index, use that index name as the first parameter and the column name as the second parameter to get the first row of any column

Get the index of the First row




Now use this index and the column name to select the first row of the specific column.


The following code demonstrates how to select the first row of the column with the name Column 1.

df.loc[0, 'Column 1']



Using iloc attribute

The iloc selects rows based on Integers.

The first row’s index will be 0.

  • Use the 0 in the row index and the appropriate column index in the iloc attribute.


df.iloc[0, 0]

You’ll see the below output. The first row of the first column is printed.



Using Head() Method

The head() method prints the first n rows of the dataframe.

To print only the first row of a specific column,

  • Select the subset of that column using df[[column name]]
  • Use the head(1) to print the value


df[['Column 1']].head(1)


Column 1

Additional Resources

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