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DataFrame.to_pickle() in function Pandas

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  • Last Updated : 05 Jun, 2020

The to_pickle() method is used to pickle (serialize) the given object into the file. This method uses the syntax as given below :

Syntax:

DataFrame.to_pickle(self, path,
                    compression='infer',
                    protocol=4)
    Arguments                                                        Type    Description
     path             str File path where the pickled object will be stored.
  compression                 {‘infer’, ‘gzip’, ‘bz2’, ‘zip’, ‘xz’, None}                       A string representing the compression to use in the output file. By default, infers from the file extension in specified path.
 protocol              int Int which indicates which protocol should be used by the pickler, default HIGHEST_PROTOCOL (see [1]_ paragraph 12.1.2). The possible values are 0, 1, 2, 3, 4. A negative value for the protocol parameter is equivalent to setting its value to HIGHEST_PROTOCOL.

Example 1:

Python3




# importing packages
import pandas as pd
  
# dictionary of data
dct = {'ID': {0: 23, 1: 43, 2: 12,
              3: 13, 4: 67, 5: 89,
              6: 90, 7: 56, 8: 34}, 
       'Name': {0: 'Ram', 1: 'Deep',
                2: 'Yash', 3: 'Aman'
                4: 'Arjun', 5: 'Aditya',
                6: 'Divya', 7: 'Chalsea',
                8: 'Akash' }, 
       'Marks': {0: 89, 1: 97, 2: 45, 3: 78,
                 4: 56, 5: 76, 6: 100, 7: 87,
                 8: 81}, 
       'Grade': {0: 'B', 1: 'A', 2: 'F', 3: 'C',
                 4: 'E', 5: 'C', 6: 'A', 7: 'B',
                 8: 'B'}
      }
  
# forming dataframe and printing
data = pd.DataFrame(dct)
print(data)
  
# using to_pickle function to form file 
# with name 'pickle_file'
data.to_pickle('pickle_file')


Output :

   ID     Name  Marks Grade
0  23      Ram     89     B
1  43     Deep     97     A
2  12     Yash     45     F
3  13     Aman     78     C
4  67    Arjun     56     E
5  89   Aditya     76     C
6  90    Divya    100     A
7  56  Chalsea     87     B
8  34    Akash     81     B

Example 2:

Python3




# importing packages
import pandas as pd
   
# dictionary of data
dct = {"f1": range(6), "b1": range(6, 12)}
   
# forming dataframe and printing
data = pd.DataFrame(dct)
print(data)
   
# using to_pickle function to form 
# file with name 'pickle_file'
data.to_pickle('pickle_file')


Output:

   f1  b1
0   0   6
1   1   7
2   2   8
3   3   9
4   4  10
5   5  11

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