如何高效学习Python中的Numpy和Pandas？
摘要：博客地址：http:www.cnblogs.comyudanqu 1 import numpy as np 2 import pandas as pd 3 from pandas import Series,DataFrame 4
博客地址：http://www.cnblogs.com/yudanqu/
1 import numpy as np
2 import pandas as pd
3 from pandas import Series,DataFrame
4
5 #Series
6 s1 = Series([1,2,3], index=['A','B','C'])
7 s2 = Series([4,5,6,7], index=['B','C','D','E'])
8
9 s1 + s2
10 # 结果：A NaN
11 # B 6.0
12 # C 8.0
13 # D NaN
14 # E NaN
15 # dtype: float64
16 # 对应项相加，其他为nan
17
18 #DataFrame
19 df1 = DataFrame(np.arange(4).reshape(2,2),index=['A','B'],columns=['BJ','SH'])
20 df2 = DataFrame(np.arange(9).reshape(3,3),index=['A','B','C'],columns=['BJ','SH','GZ'])
21 df1 + df2
22 #结果： BJ GZ SH
23 # A 0.0 NaN 2.0
24 # B 5.0 NaN 7.0
25 # C NaN NaN NaN
26
27 df3 = Datadf3 = DataFrame([[1,2,3],[4,5,np.nan],[7,8,9]],index=['A','B','C'],columns=['c1','c2','c3'])
28 '''
29 c1 c2 c3
30 A 1 2 3.0
31 B 4 5 NaN
32 C 7 8 9.0
33 '''
34 df3.sum()
35 #结果：c1 12.0
36 # c2 15.0
37 # c3 12.0
38 # dtype: float64
39 #这里的nan与实数相运算并不返回nan
40 df3.sum(axis=1) #则求得每一行的和，即ABC，由于默认axis=0，所以不写表示求的列
41
42 df3.min() #求最小值，max同理。