Pandas-数据结构-DataFrame（三）：列索引【df[‘列名‘]、df[[‘列名1‘,‘列名2‘]]、df.iloc[:, 2:6]】

古城微笑少年丶 2023-09-29 09:29 17阅读 0赞

### 1、df\[‘col\_name’\]：按照“列名”索引提取列数据 ###

按照列名选择列，只选择一列输出Series，选择多列输出Dataframe

*  `df[]`一般用于选择列，`[]`中写列名（所以一般数据colunms都会单独制定，不会用默认数字列名，以免和index冲突）；
 *  单选列为Series，print结果为Series格式；
 *  多选列为Dataframe，print结果为Dataframe格式；

import numpy as np
    import pandas as pd
    
    df = pd.DataFrame(np.random.rand(12).reshape(3, 4) * 100,
                      index=['one', 'two', 'three'],
                      columns=['a', 'b', 'c', 'd'])
    print("df = ", df)
    print('-' * 100)
    
    # 按照列名选择列，只选择一列输出Series，选择多列输出Dataframe
    data1 = df['a']
    data2 = df[['a', 'c']]
    print("data1 = \n{0}\ntype(data1) = {1}".format(data1, type(data1)))
    print('-' * 100)
    print("data2 = \n{0}\ntype(data2) = {1}".format(data2, type(data2)))

打印结果：

df =                 a          b          c          d
    one    12.427304  39.089892  22.467365  22.711018
    two    50.808058  67.916443  39.312617  95.227642
    three   3.399731  57.874266  45.771234  99.649908
    ----------------------------------------------------------------------------------------------------
    data1 = 
    one      12.427304
    two      50.808058
    three     3.399731
    Name: a, dtype: float64
    type(data1) = <class 'pandas.core.series.Series'>
    ----------------------------------------------------------------------------------------------------
    data2 = 
                   a          c
    one    12.427304  22.467365
    two    50.808058  39.312617
    three   3.399731  45.771234
    type(data2) = <class 'pandas.core.frame.DataFrame'>