Pandas 根据列的数值选择DataFrame的多行

骑猪看日落 2023-06-14 04:23 36阅读 0赞

** 1. 选取等于某个特定值的行记录，用 == **

df.loc[df['column_name'] == some_value]

**2. 选取等于某些的数值的行记录，用 isin**

df.loc[df['column_name'].isin(some_values)]

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**3. 选取不等于某个特定值的行记录，用 !=**

df.loc[df['column_name'] != some_value]

**4. 选取不符合某些特定值的行记录，用~isin**

df.loc[~df['column_name'].isin(some_values)

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**5. 多种条件的选取合并，用 & **

df.loc[(df['column'] == some_value) & df['other_column'].isin(some_values)]

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### 样例 Example ###

**输入：**

import numpy as np
    import pandas as pd
    
    df = pd.DataFrame({'A': 'foo bar foo bar foo bar foo foo'.split(),
                       'B': 'one one two three two two one three'.split(),
                       'C': np.arange(8), 'D': np.arange(8) * 2})

A      B  C   D
    0  foo    one  0   0
    1  bar    one  1   2
    2  foo    two  2   4
    3  bar  three  3   6
    4  foo    two  4   8
    5  bar    two  5  10
    6  foo    one  6  12
    7  foo  three  7  14

生成数据的Python代码 ：

1. 输出某个特定值。

print(df.loc[df['A'] == 'foo'])

A      B  C   D
    0  foo    one  0   0
    2  foo    two  2   4
    4  foo    two  4   8
    6  foo    one  6  12
    7  foo  three  7  14

2. 输出某些特定值。

print(df.loc[df['B'].isin(['one','three'])])

A      B  C   D
    0  foo    one  0   0
    1  bar    one  1   2
    3  bar  three  3   6
    6  foo    one  6  12
    7  foo  three  7  14

3. 把某一列设为索引，然后输出某个特定值。

df = df.set_index(['B'])
    print(df.loc['one'])

A  C   D
    B              
    one  foo  0   0
    one  bar  1   2
    one  foo  6  12