Indexing

1. loc——通过行标签索引行数据

1.1 loc[1]表示索引的是第1行（index 是整数）

import pandas as pd  

data = [[1,2,3],[4,5,6]]  
index = [0,1]  
columns=['a','b','c']  
df = pd.DataFrame(data=data, index=index, columns=columns)  
df.loc[1]  

'''
a    4 
b    5 
c    6 
'''  
  
df
    a    b    c
0    1    2    3
1    4    5    6

1.2  loc[‘d’]表示索引的是第’d’行（index 是字符）

data = [[1,2,3],[4,5,6]]  
index = ['d','e']  
columns=['a','b','c']  
df = pd.DataFrame(data=data, index=index, columns=columns)  
df.loc['d']  

'''
a    1 
b    2 
c    3 
'''  
df
     a    b    c
d    1    2    3
e    4    5    6

1.3 loc可以获取多行数据

data = [[1,2,3],[4,5,6]]  
index = ['d','e']  
columns=['a','b','c']  
df = pd.DataFrame(data=data, index=index, columns=columns)  
df.loc['d':]  

''''' 
   a  b  c 
d  1  2  3 
e  4  5  6 
'''  

1.4 loc扩展——索引某行某列

import pandas as pd 
 
data = [[1,2,3],[4,5,6]]  
index = ['d','e']  
columns=['a','b','c']  
df = pd.DataFrame(data=data, index=index, columns=columns)  
df.loc['d',['b','c']]
 
''''' 
b    2 
c    3 
'''  

1.5 loc扩展——索引某列

import pandas as pd
  
data = [[1,2,3],[4,5,6]]  
index = ['d','e']  
columns=['a','b','c']  
df = pd.DataFrame(data=data, index=index, columns=columns)  
df.loc[:,['c']]  

'''
   c 
d  3 
e  6 
'''  

当然获取某列数据最直接的方式是df.[列标签]，但是当列标签未知时可以通过这种方式获取列数据。

需要注意的是，dataframe的索引[1:3]是包含1,2,3的。

2. iloc——通过行号获取行数据

.iloc 则是基于序号的索引(还是行优先)，从0到length-1。

2.1 获取单行

import pandas as pd  

data = [[1,2,3],[4,5,6]]  
index = ['d','e']  
columns=['a','b','c']  
df = pd.DataFrame(data=data, index=index, columns=columns)  
df.loc[1]  

'''
a    4 
b    5 
c    6 
'''  

2.2 索引多行

import pandas as pd

data = [[1,2,3],[4,5,6]]
index = ['d','e']
columns=['a','b','c']
df = pd.DataFrame(data=data, index=index, columns=columns)  
df.iloc[0:]
"""
    a    b    c
d    1    2    3
e    4    5    6
"""

2.3 索引列数据

import pandas as pd 
 
data = [[1,2,3],[4,5,6]]  
index = ['d','e']  
columns=['a','b','c']  
df = pd.DataFrame(data=data, index=index, columns=columns)  
df.iloc[:,[1]]
 
''''' 
   b 
d  2 
e  5 
''' 

3. ix——结合前两种的混合索引

.ix 则相当于上述两个之和，两种index都能处理。

3.1 通过行号索引

import pandas as pd
 
data = [[1,2,3],[4,5,6]]  
index = ['d','e']  
columns=['a','b','c']  
df = pd.DataFrame(data=data, index=index, columns=columns)  

df.ix[1]
 
''''' 
a    4 
b    5 
c    6 
'''  

3.2 通过行标签索引

import pandas as pd 

data = [[1,2,3],[4,5,6]]  
index = ['d','e']  
columns=['a','b','c']  
df = pd.DataFrame(data=data, index=index, columns=columns)  
df.ix['e']

''''' 
a    4 
b    5 
c    6 
'''