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 pd import pandas as pd
# list of name, degree, score nme = [ "aparna" , "pankaj" , "sudhir" , "Geeku" ]
deg = [ "MBA" , "BCA" , "M.Tech" , "MBA" ]
scr = [ 90 , 40 , 80 , 98 ]
# dictionary of lists dict = { 'name' : nme, 'degree' : deg, 'score' : scr}
df = pd.DataFrame( dict )
print (df)
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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 dataframe df.to_csv( 'file1.csv' )
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Output:
Saving CSV without headers and index.
Here, we are saving the file with no header and no index number.
Python3
# saving the dataframe df.to_csv( 'file2.csv' , header = False , index = False )
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Output:
Save the CSV file to a specified location
We can also, save our file at some specific location.
Python3
# saving the dataframe df.to_csv(r 'C:\Users\Admin\Desktop\file3.csv' )
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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 pd
import numpy as np
users = { 'Name' : [ 'Amit' , 'Cody' , 'Drew' ],
'Age' : [ 20 , 21 , 25 ]}
#create DataFrame df = 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)
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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
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