python大法好，这些你可不要忽略了！

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）

[python] iew plain copy

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)

print df.loc[1]

'''''

a 4

b 5

c 6

'''

1.2 loc[‘d’]表示索引的是第’d’行（index 是字符）

[python] iew plain copy

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)

print df.loc['d']

'''''

a 1

b 2

c 3

'''

1.3 如果想索引列数据，像这样做会报错

[python] iew plain copy

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)

print df.loc['a']

'''''

KeyError: 'the label [a] is not in the [index]'

'''

1.4 loc可以获取多行数据

[python] iew plain copy

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)

print df.loc['d':]

'''''

a b c

d 1 2 3

e 4 5 6

'''

1.5 loc扩展——索引某行某列

[python] iew plain copy

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)

print df.loc['d',['b','c']]

'''''

b 2

c 3

'''

1,6 loc扩展——索引某列

[python] iew plain copy

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)

print 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。

2. iloc——通过行号获取行数据

2.1 想要获取哪一行就输入该行数字

[python] iew plain copy

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)

print df.loc[1]

'''''

a 4

b 5

c 6

'''

2.2 通过行标签索引会报错

[python] iew plain copy

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)

print df.iloc['a']

'''''

'''

2.3 同样通过行号可以索引多行

[python] iew plain copy

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)

print df.iloc[0:]

'''''

a b c

d 1 2 3

e 4 5 6

'''

2.4 iloc索引列数据

[python] iew plain copy

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)

print df.iloc[:,[1]]

'''''

b

d 2

e 5

'''

3. ix——结合前两种的混合索引

3.1 通过行号索引

[python] iew plain copy

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)

print df.ix[1]

'''''

a 4

b 5

c 6

'''

3.2 通过行标签索引

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）

[python] iew plain copy

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)

print df.loc[1]

'''''

a 4

b 5

c 6

'''

1.2 loc[‘d’]表示索引的是第’d’行（index 是字符）

[python] iew plain copy

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)

print df.loc['d']

'''''

a 1

b 2

c 3

'''

1.3 如果想索引列数据，像这样做会报错

[python] iew plain copy

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)

print df.loc['a']

'''''

KeyError: 'the label [a] is not in the [index]'

'''

1.4 loc可以获取多行数据

[python] iew plain copy

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)

print df.loc['d':]

'''''

a b c

d 1 2 3

e 4 5 6

'''

1.5 loc扩展——索引某行某列

[python] iew plain copy

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)

print df.loc['d',['b','c']]

'''''

b 2

c 3

'''

1,6 loc扩展——索引某列

[python] iew plain copy

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)

print 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，与平时的不同。

2. iloc——通过行号获取行数据

2.1 想要获取哪一行就输入该行数字

[python] iew plain copy

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)

print df.loc[1]

'''''

a 4

b 5

c 6

'''

2.2 通过行标签索引会报错

[python] iew plain copy

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)

print df.iloc['a']

'''''

'''

2.3 同样通过行号可以索引多行

[python] iew plain copy

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)

print df.iloc[0:]

'''''

a b c

d 1 2 3

e 4 5 6

'''

2.4 iloc索引列数据

[python] iew plain copy

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)

print df.iloc[:,[1]]

'''''

b

d 2

e 5

'''

3. ix——结合前两种的混合索引

3.1 通过行号索引

[python] iew plain copy

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)

print df.ix[1]

'''''

a 4

b 5

c 6

'''

3.2 通过行标签索引

[python] iew plain copy

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)

print df.ix['e']

'''''

a 4

b 5

c 6

'''