Write Python Pandas Dataframe to CSV

In this article, you will learn how to convert a Python Pandas dataframe to a CSV.

After dealing with a dataset and performing all preprocessing, we must save the preprocessed information in a data format such as csv, excel, or others. CSV (Comma-separated-values) is widely used for data exchange in data-based applications. In web applications, we generally store the data in an array, dataframe, lists, tuples, dictionaries, etc. There may be a need for clients to export this data to a CSV file. The data in CSV is stored as sequences of records. Like in other programming languages, we can also write data to a CSV file using Python Pandas.

Pandas to_csv()

Python pandas provides the to_csv() method to convert data to a CSV file. If a file argument is provided, the output is written to a file. Otherwise, the CSV string is returned. It has so many attributes, but here we have mentioned only the most used attributes.

dataframe.to_csv(path,sep,na_rep,float_format, columns, header, index, mode, compression)

path- File path, if we leave it blank or none, the result is returned as a string.
sep- the string delimiter of length 1 for the output file.
na_rep- the string represents the missing data.
float_format- the string format for floating point numbers.
columns- optional, columns or sequence to write.
header- default True, list of column names.
index - default True, row names.
mode- write mode, default 'w'.
compression- represents the compression mode, the possible values are 'infer', 'gzip', 'bz2', 'zip', 'xz', None and the default is 'infer'.

Example1: Write dataframe to CSV Python

Here is the simple code to write a dataframe to a CSV file.

import pandas as pd  
   
# dictionary of lists  
stu_dict = {'Name': ["Smith", "Priska", "Kashyap", "Andy"]
        ,'Subject': ["Phy", "Maths", "Chm", "Bio"],
        'Marks': [90, 99, 92, 89]}  
     
df = pd.DataFrame(stu_dict) 
  
# write dataframe to csv
df.to_csv('highest_score.csv')

Once you run the above code, it generates and saves the CSV file in your working directory. You can also specify the full file path.

Example2: Write specific dataframe values to CSV

Here, we write some specific columns of dataframe to a CSV file.

import pandas as pd  
   
# dictionary of lists  
stu_dict = {'Name': ["Smith", "Priska", "Kashyap", "Andy"],
            'Class':["6A","10A","8B","9C"],
            'Subject': ["Phy", "Maths", "Chm", "Bio"],
            'Marks': [90, 99, 92, 89]}  
     
df = pd.DataFrame(stu_dict,
                  columns = ['Name', 'Subject', 'Marks']) 
  
# write dataframe to csv
df.to_csv('highest_score.csv', index = False, header = True) 

Once you run the above code, it generates and saves the CSV file in your working directory.

Example3: Write multiple dataframes to a CSV file

Here, we write multiple dataframe values to a CSV file.

import pandas as pd  
   
# dictionary of lists
pre_stu_dict = {'Name': ["Alisa", "Alya", "Kim", "Gaga"],
            'Class':["1A","3C","2B","4A"],
            'Subject': ["Eng", "Maths", "Sci", "GK"],
            'Marks': [95, 98, 89, 93]}

sec_stu_dict = {'Name': ["Smith", "Priska", "Kashyap", "Andy"],
            'Class':["6A","10A","8B","9C"],
            'Subject': ["Phy", "Maths", "Chm", "Bio"],
            'Marks': [90, 99, 92, 89]}  
     
df1 = pd.DataFrame(pre_stu_dict,
                  columns = ['Name', 'Subject', 'Marks'])
df2 = pd.DataFrame(sec_stu_dict,
                  columns = ['Name', 'Subject', 'Marks']) 
  
# write dataframes to csv
pd.concat([df1, df2]).to_csv('highest_score.csv',
                                     index = False, header = True) 

Once you run the above code, it generates and saves the CSV file in your working directory.

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