pandas： series

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本文介绍Pandas库中Series对象的基本用法及如何处理时间序列数据，包括创建Series、通过字典构建Series、获取Series索引、选取特定元素及截取时间序列数据等关键操作。

Series是一种类似于一维数组的对象，它由一组数据（各种Numpy数据类型）以及一组与之相关的数据标签（即索引）组成。仅由一组数据即可产生简单的Series。

In [2]:

s = Series(np.random.randn(5),index =['a','b','c','d','e'])s 

Out[2]:

a   -2.895114
b   -1.231825
c    0.471328
d   -1.287756
e    1.475353
dtype: float64

In [3]:

'b' in s

Out[3]:

True

In [4]:

s['b']

Out[4]:

-1.2318253286905612

In [5]:

s.index

Out[5]:

Index(['a', 'b', 'c', 'd', 'e'], dtype='object')

to_dict查看词典

In [6]:

mapping = s.to_dict()mapping 

Out[6]:

{'a': -2.8951137320706906,
 'b': -1.2318253286905612,
 'c': 0.47132812495267679,
 'd': -1.2877558861047,
 'e': 1.4753528130026292}

通过词典的方式也可以构建Series

In [7]:

Series(mapping)

Out[7]:

a   -2.895114
b   -1.231825
c    0.471328
d   -1.287756
e    1.475353
dtype: float64

默认取数据的长度是一年

In [8]:

ts = get_price('600208.XSHG')['ClosingPx'][-10:]ts

Out[8]:

2013-12-20    3.0528
2013-12-23    3.0624
2013-12-24    3.0528
2013-12-25    3.0431
2013-12-26    2.9950
2013-12-27    3.0431
2013-12-30    3.0528
2013-12-31    3.0816
2014-01-02    3.0720
2014-01-03    3.0142
Name: ClosingPx, dtype: float64

声明了strat_date & end_date 以后才可以进行更个性化的定制，默认是A股，美股别忘记加上国家'us'

In [11]:

tsspecial = get_price('000001.XSHE', start_date='2008-04-01', end_date='2015-04-12')['ClosingPx'][-90:]
tsspecial

Out[11]:

2014-11-26     7.6032
2014-11-27     7.6711
2014-11-28     8.4375
2014-12-01     8.2679
2014-12-02     8.8987
2014-12-03     8.8851
2014-12-04     9.4684
2014-12-05     9.8550
2014-12-08    10.3298
2014-12-09     9.2989
2014-12-10     9.6244
2014-12-11     9.4413
2014-12-12     9.4549
2014-12-15     9.2107
2014-12-16     9.7601
               ...   
2015-03-20    10.3909
2015-03-23    10.4655
2015-03-24    10.4112
2015-03-25    10.1128
2015-03-26    10.2484
2015-03-27    10.2281
2015-03-30    10.6215
2015-03-31    10.6825
2015-04-01    10.8249
2015-04-02    10.7164
2015-04-03    10.7503
2015-04-07    11.4015
2015-04-08    12.1543
2015-04-09    12.2086
2015-04-10    13.4294
Name: ClosingPx, dtype: float64

从头去前五项

In [12]:

ts[:5]

Out[12]:

2013-12-20    3.0528
2013-12-23    3.0624
2013-12-24    3.0528
2013-12-25    3.0431
2013-12-26    2.9950
Name: ClosingPx, dtype: float64

In [13]:

ts.index

Out[13]:

DatetimeIndex(['2013-12-20', '2013-12-23', '2013-12-24', '2013-12-25',
               '2013-12-26', '2013-12-27', '2013-12-30', '2013-12-31',
               '2014-01-02', '2014-01-03'],
              dtype='datetime64[ns]', freq=None)

In [14]:

date = ts.index[6]date

Out[14]:

Timestamp('2013-12-30 00:00:00')

In [15]:

ts[date]

Out[15]:

3.0528

In [16]:

ts[6]

Out[16]:

3.0528

米筐技能：同时读取多只股票，更多米筐技请参考basic_demo.

In [18]:

dfcn = get_price(['000024.XSHE', '000001.XSHE', '000002.XSHE'], start_date='2005-04-01', end_date='2015-04-12')['ClosingPx'][-10:]