Python Pickle - Pandas DataFrame

To pickle a DataFrame in Python use pickle.dump(), and to unpickle the DataFrame, use pickle.load().

In this tutorial, we shall learn how to pickle a DataFrame, with the help of example programs.

1. Pickle a DataFrame

In the following example, we will initialize a DataFrame and them Pickle it to a file.

Following are the steps to Pickle a Pandas DataFrame.

Create a file in write mode and handle the file as binary.
Call the function pickle.dump(file, dataframe).

Python Program

import numpy as np
import pandas as pd
import pickle

#dataframe
df = pd.DataFrame(
	[['Somu', 68, 84, 78, 96],
	['Kiku', 74, 56, 88, 85],
	['Amol', 77, 73, 82, 87],
	['Lini', 78, 69, 87, 92]],
	columns=['name', 'physics', 'chemistry','algebra','calculus'])

#create a file
picklefile = open('df_marks', 'wb')
#pickle the dataframe
pickle.dump(df, picklefile)
#close file
picklefile.close()

A pickle file would be created in the current working directory.

2. Un-pickle a DataFrame

In the following example, we will read the pickle file and them unpickle it to a dataframe.

Following are the steps to Unpickle a Pandas DataFrame.

Read the file in read mode and handle the file as binary.
Call the function pickle.load(file).

Python Program

import numpy as np
import pandas as pd
import pickle

#read the pickle file
picklefile = open('df_marks', 'rb')
#unpickle the dataframe
df = pickle.load(picklefile)
#close file
picklefile.close()

#print the dataframe
print(type(df))
print(df)

Output

<class 'pandas.core.frame.DataFrame'>
   name  physics  chemistry  algebra  calculus
0  Somu       68         84       78        96
1  Kiku       74         56       88        85
2  Amol       77         73       82        87
3  Lini       78         69       87        92

Summary

In this tutorial of Python Examples, we learned how to serialize and de-serialize a Pandas DataFrame using Pickle library.