Slice pandas DataFrame by Index in Python (Example)

 

This tutorial illustrates how to split a pandas DataFrame at a certain row index position in the Python programming language.

The tutorial consists of these contents:

Let’s get started…

 

Example Data & Add-On Libraries

We first need to import the pandas library:

import pandas as pd                         # Load pandas

As a next step, I’ll also need to create some data that we can use in the exemplifying code below:

data = pd.DataFrame({'x1':range(10, 18),    # Create pandas DataFrame
                     'x2':['a', 'b', 'b', 'c', 'd', 'a', 'b', 'd'],
                     'x3':range(27, 19, - 1),
                     'x4':['x', 'z', 'y', 'y', 'x', 'y', 'z', 'x']})
print(data)                                 # Print pandas DataFrame

 

table 1 DataFrame slice pandas dataframe index python

 

As you can see based on Table 1, the exemplifying data is a pandas DataFrame containing eight rows and four columns.

 

Example: Split pandas DataFrame at Certain Index Position

This example explains how to divide a pandas DataFrame into two different subsets that are split at a particular row index.

For this, we first have to define the index location at which we want to slice our data set (i.e. 3):

split_point = 3                             # Define split point
print(split_point)                          # Print split point
# 3

In the next step, we can use this splitting point to extract all rows before this index point:

data_upper = data.iloc[:split_point]        # Create upper data set
print(data_upper)                           # Print DataFrame of upper rows

 

table 2 DataFrame slice pandas dataframe index python

 

After executing the previous syntax the pandas DataFrame subset shown in Table 2 has been created.

Next, we can use our splitting point once again to select only the rows below the splitting point:

data_lower = data.iloc[split_point:]        # Create lower data set
print(data_lower)                           # Print DataFrame of lower rows

 

table 3 DataFrame slice pandas dataframe index python

 

Table 3 shows the output of the previous Python programming syntax – A second pandas DataFrame subset containing all rows below the slicing point.

 

Video & Further Resources

I have recently released a video on my YouTube channel, which illustrates the Python code of this tutorial. You can find the video below.

 

 

Also, you could read some related tutorials on this website. A selection of tutorials is shown below:

 

This article has explained how to slice a pandas DataFrame at a specific row index position in the Python programming language. If you have any further comments and/or questions, please let me know in the comments section.

 

Subscribe to the Statistics Globe Newsletter

Get regular updates on the latest tutorials, offers & news at Statistics Globe.
I hate spam & you may opt out anytime: Privacy Policy.


Leave a Reply

Your email address will not be published. Required fields are marked *

Fill out this field
Fill out this field
Please enter a valid email address.

Top