In this article, we will learn how we can export a Pandas DataFrame to a CSV file by using the Pandas to_csv() method. By default, the to csv() method exports DataFrame to a CSV file with row index as the first column and comma as the delimiter.
Creating DataFrame to Export Pandas DataFrame to CSV
Python3
# importing pandas as pdimport pandas as pd# list of name, degree, scorenme = ["aparna", "pankaj", "sudhir", "Geeku"]deg = ["MBA", "BCA", "M.Tech", "MBA"]scr = [90, 40, 80, 98]# dictionary of listsdict = {'name': nme, 'degree': deg, 'score': scr} df = pd.DataFrame(dict)print(df) |
Output:
name degree score 0 aparna MBA 90 1 pankaj BCA 40 2 sudhir M.Tech 80 3 Geeku MBA 98
Export CSV to a working directory
Here, we simply export a Dataframe to a CSV file using df.to_csv().
Python3
# saving the dataframedf.to_csv('file1.csv') |
Output:
Saving CSV without headers and index.
Here, we are saving the file with no header and no index number.
Python3
# saving the dataframedf.to_csv('file2.csv', header=False, index=False) |
Output:
Save the CSV file to a specified location
We can also, save our file at some specific location.
Python3
# saving the dataframedf.to_csv(r'C:\Users\Admin\Desktop\file3.csv') |
Output:
Write a DataFrame to CSV file using tab separator
We can also save our file with some specific separate as we want. i.e, “\t” .
Python3
import pandas as pdimport numpy as npusers = {'Name': ['Amit', 'Cody', 'Drew'], 'Age': [20,21,25]}#create DataFramedf = pd.DataFrame(users, columns=['Name','Age'])print("Original DataFrame:")print(df)print('Data from Users.csv:')df.to_csv('Users.csv', sep='\t', index=False,header=True)new_df = pd.read_csv('Users.csv')print(new_df) |
Output:
Original DataFrame: Name Age 0 Amit 20 1 Cody 21 2 Drew 25 Data from Users.csv: Name\tAge 0 Amit\t20 1 Cody\t21 2 Drew\t25
