基于numpy的Series及DataFrame数据结构
Project description
arraytool
介绍
基于numpy的Series及DataFrame数据结构。
arraytool包中对应于Series及DataFrame的数据类分别为ArraySeries及ArrayFrame,两者同Series及DataFrame之间可方便地进行转换。
安装
pip install arraytool
引入
import arraytool
from arraytool import ArraySeries, ArrayFrame
ArraySeries
构造
>>> s1 = ArraySeries(['a','bb','ccc'])
>>> s1
0 a
1 bb
2 ccc
dtype: object
取值
>>> s1[2]
'ccc'
>>> s1[:2]
0 a
1 bb
dtype: object
使用索引
>>> s2 = ArraySeries([2,3,4,5],list('aabc'))
>>> s2.iloc[:2]
a 2
a 3
dtype: object
>>> s2.loc['a']
a 2
a 3
dtype: object
>>> s2.loc['b']
4
>>> s2.loc[list('ab')]
a 2
a 3
b 4
dtype: object
ArrayFrame
构造
>>> af = ArrayFrame()
>>> af['A'] = list('abcd')
>>> af['B'] = range(4)
>>> af['C'] = [True,True,False,False]
>>> af
A B C
0 a 0 True
1 b 1 True
2 c 2 False
3 d 3 False
取值
>>> af[list('BC')]
B C
0 0 True
1 1 True
2 2 False
3 3 False
使用索引
iloc索引
>>> af.iloc[0,0]
'a'
>>> af.iloc[0]
A B C
0 a 0 True
loc索引
>>> af.set_index(index_cols='A')
>>> af
A B C
A
a a 0 True
b b 1 True
c c 2 False
d d 3 False
>>> af.loc['a','C']
True
>>> af.loc[list('bd'),list('AC')]
A C
A
b b True
d d False
ix索引
类R语言data.frame的索引语法,使用pandas弃用的ix索引器。
>>> af.ix[2,'B']
2
>>> af.ix[:2,list('AB')]
A B
A
a a 0
b b 1
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