Pandas中的DataFrame.read_pickle()方法

read_pickle()方法被用来将给定的对象腌制（序列化）到文件中。这个方法使用下面的语法。

语法:

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

参数:

参数	类型	描述
path	str	将加载腌制对象的文件路径。
compression	{‘infer’, ‘gzip’, ‘bz2’, ‘zip’, ‘xz’, None}, 默认 ‘infer’	用于磁盘上数据的即时解压。如果是’infer’，那么如果路径以’.gz’、’.bz2’、’.xz’或’.zip’结尾，则分别使用gzip、bz2、xz或zip，否则不进行解压。设置为None表示不解压。

下面是上述方法的实现和一些例子。

示例 1:

# 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 :

Pandas中的DataFrame.read_pickle()方法

示例 2:

# 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 :

Pandas中的DataFrame.read_pickle()方法