numpy函数应用与映射

from  pandas import  Index
from  pandas import Series,DataFrame
import  numpy as  np
import pandas as pd

#numpy函数在Series/DataFrame的应用
frame=DataFrame(np.arange(9).reshape(3,3),
                columns= ['A','B','C'],
                index= ['a','b','c'])
print(frame)
'''
   A  B  C
a  0  1  2
b  3  4  5
c  6  7  8
'''

print(np.square(frame))
'''
    A   B   C
a   0   1   4
b   9  16  25
c  36  49  64
'''

series=frame.A

print(series)
'''
a    0
b    3
c    6
Name: A, dtype: int32
'''

print(np.square(series))
'''
a     0
b     9
c    36
Name: A, dtype: int32
'''

#lambda(匿名函数)以及应用
print(frame)
'''
   A  B  C
a  0  1  2
b  3  4  5
c  6  7  8
'''

print(frame.max())
'''
A    6
B    7
C    8
dtype: int32
'''

#按列
f= lambda  x: x.max() - x.min()
print(frame.apply(f))
'''
A    6
B    6
C    6
dtype: int64
'''

# print(frame.apply(f), axis = 1)  # ??作用到每一列

def f(x):
    return  Series([x.min(),x.max()],index=['min','max'])

print(frame.apply(f))
'''
     A  B  C
min  0  1  2
max  6  7  8
'''

#applymap和map：作用到每一个元素
_format= lambda  x: '%.2f'% x
print(frame.applymap(_format))      # 针对DataFrame
'''
   A     B     C
a  0.00  1.00  2.00
b  3.00  4.00  5.00
c  6.00  7.00  8.00
'''

print(frame['A'].map(_format))      # 针对Series
'''
a    0.00
b    3.00
c    6.00
Name: A, dtype: object
'''