Pandas 中的 DataFrame.read_pickle() 方法

先决条件： pd.to_pickle 方法（）

read_pickle()方法用于将给定对象腌制（序列化）到文件中。此方法使用如下给出的语法：

句法：

pd.read_pickle(path, compression='infer')

参数：

Arguments	Type	Description
path	str	File path where the pickled object will be loaded.
compression	{‘infer’, ‘gzip’, ‘bz2’, ‘zip’, ‘xz’, None}, default ‘infer’	For on-the-fly decompression of on-disk data. If ‘infer’, then use gzip, bz2, xz or zip if path ends in ‘.gz’, ‘.bz2’, ‘.xz’, or ‘.zip’ respectively, and no decompression otherwise. Set to None for no decompression.

以下是上述方法的实现以及一些示例：

示例 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 
data = pd.DataFrame(dct) 
  
# using to_pickle function to form file 
# with name 'pickle_file' 
pd.to_pickle(data,'./pickle_file.pkl')
  
# unpickled the data by using the
# pd.read_pickle method
unpickled_data = pd.read_pickle("./pickle_file.pkl")
print(unpickled_data)

输出 ：

示例 2：

Python3

# importing packages 
import pandas as pd 
  
# dictionary of data 
dct = {"f1": range(6), "b1": range(6, 12)} 
  
# forming dataframe 
data = pd.DataFrame(dct) 
  
# using to_pickle function to form file 
# with name 'pickle_data' 
pd.to_pickle(data,'./pickle_data.pkl')
  
# unpickled the data by using the
# pd.read_pickle method
unpickled_data = pd.read_pickle("./pickle_data.pkl")
print(unpickled_data)

输出 ：