Pandas: skip rows while reading csv file to a Dataframe using read_csv() in Python

In this tutorial, we will discuss how to skip rows while reading a csv file to a Dataframe using aread_csv()method of Pandas library in Python. If you want you can learn more about the read_csv() method along with syntax, parameters, and various methods to skip rows while reading specific rows from csv in python pandas

• How to skip rows while reading CSV file using Pandas?
• Method 1: Skipping N rows from the starting while reading a csv file
• Method 2: Skipping rows at specific index positions while reading a csv file to Dataframe
• Skipping N rows from top except header while reading a csv file to Dataframe
• Skip rows from based on condition while reading a csv file to Dataframe
• Skip N rows from bottom/footer while reading a csv file to Dataframe

How to skip rows while reading CSV file using Pandas?

Python is a very useful language in today’s time, its also very useful for data analysis because of the different python packages. Python panda’s library implements a function to read a csv file and load data to dataframe quickly and also skip specified lines from csv file. Here we will use theread_csv()method of Pandas to skip n rows. i.e.,

pandas.read_csv(filepath_or_buffer, skiprows=N, ....)

Parameters:

Let’s, import the pandas’ module in python first:

Import pandas as pd

Let’s see the examples mentioned below and learn the process of Pandas: skip rows while reading csv file to a Dataframe using read_csv() in Python. Now, create one simple CSV file instru.csv

Name,Age,City
Tara,34,Agra
Rekha,31,Delhi
Aavi,16,Varanasi
Sarita,32,Lucknow
Mira,33,Punjab
Suri,35,Patna

Also Check:

• Pandas: Convert a dataframe column into a list using Series.to_list() or numpy.ndarray.tolist() in python
• Python Pandas: Select Rows in DataFrame by conditions on multiple columns

Let’s load this csv file to a dataframe using read_csv() and skip rows in various ways,

Method 1: Skipping N rows from the starting while reading a csv file

When we pass skiprows=2 it means it will skip those rows while reading csv file. For example, if we want to skip 2 lines from the top while readingusers.csvfile and initializing a dataframe.

import pandas as pd
# Skip 2 rows from top in csv and initialize a dataframe
usersDf = pd.read_csv("C:\\Users\HP\Desktop\instru.csv", skiprows=2)
print('Contents of the Dataframe created by skipping top 2 lines from csv file ')
print(usersDf)

Output:

Contents of the Dataframe created by skipping top 2 lines from csv file
  Rekha 31 Delhi
0 Aavi   16 Varanasi
1 Sarita 32 Lucknow
2 Mira   33 Punjab
3 Suri    35 Patna

Method 2: Skipping rows at specific index positions while reading a csv file to Dataframe

For skipping rows at specific index positions we have to give index positions like if we want to skip lines at index 0, 2, and 5 in dataframe ‘skiprows=[0,2,5]’.

import pandas as pd

# Skip  rows at specific index
usersDf = pd.read_csv("C:\\Users\HP\Desktop\instru.csv", skiprows=[0,2,5])
print('Contents of the Dataframe created by skipping specifying lines from csv file ')
print(usersDf)

Output:

Contents of the Dataframe created by skipping specifying lines from csv file
   Tara    34    Agra
0 Aavi   16     Varanasi
1 Sarita 32    Lucknow
2 Suri    35    Patna

It skipped all the lines at index positions 0, 2 & 5 from csv and loaded the remaining rows from csv.

Skipping N rows from top except header while reading a csv file to Dataframe

In the earlier example, we have seen that it removes the header also. In this, we want to remove 2 rows from starting but not the header one.

import pandas as pd
# Skip 2 rows from top except header
usersDf = pd.read_csv("C:\\Users\HP\Desktop\instru.csv", skiprows=[i for i in range(1,3)])
print('Contents of the Dataframe created by skipping 2 rows after header row from csv file ')
print(usersDf)

Output:

Contents of the Dataframe created by skipping 2 rows after header row from csv file
     Name Age City
0   Aavi    16   Varanasi
1  Sarita   32   Lucknow
2  Mira     33   Punjab
3  Suri      35   Patna

Skip rows from based on condition while reading a csv file to Dataframe

Here we will give some specific conditions using the lambda function for skipping rows in the dataframe.

import pandas as pd

def logic(index):
    if index % 3 == 0:
       return True
    return False
# Skip rows from based on condition like skip every 3rd line
usersDf = pd.read_csv("C:\\Users\HP\Desktop\instru.csv", skiprows= lambda x: logic(x) )
print('Contents of the Dataframe created by skipping every 3rd row from csv file ')
print(usersDf)

Output:

Contents of the Dataframe created by skipping every 3rd row from csv file
      Tara    34 Agra
0    Rekha 31 Delhi
1    Sarita 32 Lucknow
2    Mira   33 Punjab

Skip N rows from bottom/footer while reading a csv file to Dataframe

So here we use skipfooter & engine argument in pd.read_csv() to skip n rows from the bottom.

import pandas as pd

# Skip 2 rows from bottom
usersDf = pd.read_csv("C:\\Users\HP\Desktop\instru.csv", skipfooter=2, engine='python')
print('Contents of the Dataframe created by skipping bottom 2 rows from csv file ')
print(usersDf)

Output:

Contents of the Dataframe created by skipping bottom 2 rows from csv file
   Name Age City
0 Tara    34 Agra
1 Rekha 31 Delhi
2 Aavi    16 Varanasi
3 Sarita  32 Lucknow

Conclusion

In this article, you have learned different ways of how to skip rows while reading csv file to a Dataframe using the Python pandas read_csv() function.

Want to expert in the python programming language? Exploring Python Data Analysis using Pandas tutorial changes your knowledge from basic to advance level in python concepts.

Similar Tutorials:

• How to create DataFrame from a dictionary?
• How to create an empty DataFrame and add data to it later?
• How to convert lists to a dataframe?
• How to read a csv file to Dataframe with custom delimiter?