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