# 索引使用类似于切片,但是包含最后一个索引
se = Series(np.arange(6), index=['a','b','c','d','e','f'])
se
a 0
b 1
c 2
d 3
e 4
f 5
dtype: int32
se['b':'c']# 切片全部包含
b 1
c 2
dtype: int32
se[['c','e','d']]# 指定Series对象的索引
c 2
e 4
d 3
dtype: int32
se[se<3]
a 0
b 1
c 2
dtype: int32
对DataFrame对象索引 其实是获取一个或者多个列
frame
cal
china
cannada
a
0
1
2
b
3
4
5
d
6
7
8
frame['cal']
a 0
b 3
d 6
Name: cal, dtype: int32
frame[['cal','china']]# 获取两列
cal
china
a
0
1
b
3
4
d
6
7
frame[:2]#选取行,
cal
china
cannada
a
0
1
2
b
3
4
5
frame[frame['china']>1]
cal
china
cannada
b
3
4
5
d
6
7
8
frame.ix['d']
D:\anacoda\lib\site-packages\ipykernel_launcher.py:1: DeprecationWarning:
.ix is deprecated. Please use
.loc for label based indexing or
.iloc for positional indexing
See the documentation here:
http://pandas.pydata.org/pandas-docs/stable/indexing.html#ix-indexer-is-deprecated
"""Entry point for launching an IPython kernel.
cal 6
china 7
cannada 8
Name: d, dtype: int32