[译] Pandas中根据列的值选取多行数据

# 选取等于某些值的行记录 用 == 
df.loc[df[\'column_name\'] == some_value]

# 选取某列是否是某一类型的数值 用 isin
df.loc[df[\'column_name\'].isin(some_values)]

# 多种条件的选取 用 &
df.loc[(df[\'column\'] == some_value) & df[\'other_column\'].isin(some_values)]

# 选取不等于某些值的行记录 用 ！=
df.loc[df[\'column_name\'] != some_value]

# isin返回一系列的数值,如果要选择不符合这个条件的数值使用~
df.loc[~df[\'column_name\'].isin(some_values)]

import pandas as pd 
import numpy as np
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})
print(df)

     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

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

# 如果你想包括多个值，把它们放在一个list里面，然后使用isin
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

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

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

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