Pandas: How to Skip Rows when Reading Excel File

You can use the following methods to skip rows when reading an Excel file into a pandas DataFrame:

Method 1: Skip One Specific Row

#import DataFrame and skip row in index position 2
df = pd.read_excel('my_data.xlsx', skiprows=[2])

Method 2: Skip Several Specific Rows

#import DataFrame and skip rows in index positions 2 and 4
df = pd.read_excel('my_data.xlsx', skiprows=[2, 4])

Method 3: Skip First N Rows

#import DataFrame and skip first 2 rows
df = pd.read_excel('my_data.xlsx', skiprows=2)

The following examples show how to use each method in practice with the following Excel file called player_data.xlsx:

Example 1: Skip One Specific Row

We can use the following code to import the Excel file and skip the row in index position 2:

import pandas as pd

#import DataFrame and skip row in index position 2
df = pd.read_excel('player_data.xlsx', skiprows=[2])

#view DataFrame
print(df)

  team  points  rebounds  assists
0    A      24         8        5
1    C      15         4        7
2    D      19         4        8
3    E      32         6        8
4    F      13         7        9

Notice that row in index position 2 (with team ‘B’) was skipped when importing the Excel file into the pandas DataFrame.

Note: The first row in the Excel file is considered to be row 0.

Example 2: Skip Several Specific Rows

We can use the following code to import the Excel file and skip the rows in index positions 2 and 4:

import pandas as pd

#import DataFrame and skip rows in index positions 2 and 4
df = pd.read_excel('player_data.xlsx', skiprows=[2, 4])

#view DataFrame
print(df)

  team  points  rebounds  assists
0    A      24         8        5
1    C      15         4        7
2    E      32         6        8
3    F      13         7        9

Notice that the rows in index positions 2 and 4 (with team ‘B’ and ‘D’) were skipped when importing the Excel file into the pandas DataFrame.

Example 3: Skip First N Rows

We can use the following code to import the Excel file and skip the first two rows:

import pandas as pd

#import DataFrame and skip first 2 rows
df = pd.read_excel('player_data.xlsx', skiprows=2)

#view DataFrame
print(df)

   B  20  12  3
0  C  15   4  7
1  D  19   4  8
2  E  32   6  8
3  F  13   7  9

Notice that the first two rows in the Excel file were skipped and the next available row (with team ‘B’) became the header row for the DataFrame.

Additional Resources

The following tutorials explain how to perform other common tasks in Python:

How to Read Excel Files with Pandas
How to Export Pandas DataFrame to Excel
How to Export NumPy Array to CSV File