How to Return Excel Specified Rows by Pandas skiprows

In many situations, you only need to fetch from a specified row rather than loading the whole Excel sheet using Python Pandas.

We also have a tutorial for loading workbooks and specific sheets using the read_excel method.

In this tutorial, we will show you how to skip specific rows or return only rows from the specified number.

Using skiprows attribute in read_excel method

The easiest way is using the skiprows parameter of the read_excel method of Pandas.

In the example below, we will load a sample sheet and only data from row number four to the end will be returned.

For an idea, this is our sample sheet in the “test_Pandas.xlsx” Workbook:

You can see that it contains a total of eleven rows including the header row.

The code:

import pandas as pd_skip

#Loading a sheet "Products"

df_specified = pd_skip.read_excel('test_pandas.xlsx', sheet_name="Products", skiprows=range(1, 3))


#Return rows after 3 to end

print(df_specified)

Output:

You can see in the above graphic and compare the sample sheet – it only started to display from p003 product which is row number 4.

Omitting header row example

In the code below, we specified range(0,3) and see the output:

import pandas as pd_skip

#Loading a sheet "Products" and omitting the header row

df_specified = pd_skip.read_excel('test_pandas.xlsx', sheet_name="Products", skiprows=range(0, 3))


#Return rows after 3 to end

print(df_specified)

Output:

Skip rows by using a list of row numbers

In the example below, we used a Python list in the skiprows parameter to omit certain rows. We will omit every other row – so display only Odd rows including the header:

import pandas as pd_skip

#Using a list to specify which rows to omit in the data frame

df_specified = pd_skip.read_excel('test_pandas.xlsx', sheet_name="Products", skiprows=[1,3,5,7,9], index_col=0)


#Display data frame

print(df_specified)

Output: