函数Pandas 中的 DataFrame.to_pickle()
to_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:
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. |
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 and printing
data = pd.DataFrame(dct)
print(data)
# using to_pickle function to form file
# with name 'pickle_file'
data.to_pickle('pickle_file')
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')
输出 :
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
示例 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')
输出:
f1 b1
0 0 6
1 1 7
2 2 8
3 3 9
4 4 10
5 5 11