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