Pandas——ix vs loc vs iloc區別

重點：loc一般是索引標籤，iloc只能索引數字，而ix可以索引兩種類型：標籤和數字。

1. loc——通過行標籤索引行數據（loc會把：的最後一位也算進去）

1.1 loc[1]表示索引的是第1行（index 是整數）

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）

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 如果想索引列數據，像這樣做會報錯

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可以獲取多行數據

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擴展——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)
print df.loc['d',['b','c']]
'''''
b    2
c    3
'''

1,6 loc擴展——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)
print df.loc[:,['c']]
'''''
   c
d  3
e  6
'''

當然獲取某列數據最直接的方式是df.[列標籤]，但是當列標籤未知時可以通過這種方式獲取列數據。

需要注意的是，dataframe的索引[1:3]是包含1,2,3的，與平時的不同。

2. iloc——通過行號獲取行數據

2.1 想要獲取哪一行就輸入該行數字

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 通過行標籤索引會報錯

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']
'''''
TypeError: cannot do label indexing on <class 'pandas.core.index.Index'> with these indexers [a] of <type 'str'>
'''

2.3 同樣通過行號可以索引多行

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)
print df.iloc[0:]
'''''
   a  b  c
d  1  2  3
e  4  5  6
'''

2.4 iloc索引列數據

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——結合前兩種的混合索引

3.1 通過行號索引

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

3.2 通過行標籤索引

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)
print df.ix['e']
'''''
a    4
b    5
c    6
'''