df中一列list拆成多列

最新推荐文章于 2024-08-04 19:55:05 发布

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本文介绍如何使用pandas将DataFrame中的list拆分成多个独立列，以'实测方法2'为例，通过应用pd.Series实现数据结构调整，提高大数据处理效率。

df中一列list拆成多列

import numpy as np
import pandas as pd
list1 = [["info1", ["zhangsan", "nan", "27fen"]], ["info2", ["lisi", "nv", "35fen"]],
         ["info3", ["wangwu", "nan", "45fen"]]]
df = pd.DataFrame(list1, columns=["A", "B"])
df_1 = pd.DataFrame(df["B"].values.tolist(), columns=["C", "D", "E"])
df = pd.concat([df, df_1], axis=1)
print(df)

要把df中的“B”列d拆成3列

C:\Users\phoeb\PycharmProjects\pythonProject\venv\Scripts\python.exe C:/Users/phoeb/PycharmProjects/pythonProject/numpysty.py
       A                       B         C    D      E
0  info1  [zhangsan, nan, 27fen]  zhangsan  nan  27fen
1  info2       [lisi, nv, 35fen]      lisi   nv  35fen
2  info3    [wangwu, nan, 45fen]    wangwu  nan  45fen

Process finished with exit code 0

方法1

方法2

实测方法2 在数据量大时更有效


    result = pd.DataFrame(all_log["mail_attach"].values.tolist(),
                          columns=['mail_attach_name', 'mail_attach_ordinal', 'mail_attach_name_suffix',
                                   "mail_attach_size"])
    result = all_log["mail_attach"].apply(pd.Series, index=['mail_attach_name', 'mail_attach_ordinal',
                                                            'mail_attach_name_suffix', "mail_attach_size"])