import pandas as pd

from pandas import Series, DataFrame

obj = pd.Series([4,7,-5,3])
obj

obj.values

obj.index

obj2 = pd.Series([4,5,-5,4], index=['a', 'b','c','ss'])
obj2

obj2['a']    

obj2[obj2>0]

obj2*2

import numpy as np
np.exp(obj2)

dict = {'a':3, 'b':4, '()':4}

obj3 = pd.Series(dict)
obj3

states=['a','b',')','()']
obj4 = pd.Series(dict, index=states)
obj4

pd.isnull(obj4)

pd.notnull(obj4)

obj3

obj4

obj3+obj4

data = {'state':['a','v','r','b'],
       'year':[1222,1666,1777,1000],
       'pop':[1,2.5,13,5]}
frame = pd.DataFrame(data)
frame

frame.head()    

pd.DataFrame(data,columns=['year','state','pop','nothing'])

frame.year

frame.pop

frame.values # 返回所有数组

obj = pd.Series(range(3), index=['1','2','a'])

index = obj.index
index

index[2:]

index object 是不可更改的

index[1]='g'

frame

frame.columns

Index(['pop', 'state', 'year'], dtype='object')

和python不同，pandas允许index有重复labels：

dup = pd.Index(['a','a','c','abr'])

dup

Index(['a', 'a', 'c', 'abr'], dtype='object')