# -*- coding: utf-8 -*-
"""
Created on Thu Oct 24 11:18:32 2019
@author: weiping
"""
import pandas as pd
'''
Series
'''
ser = pd.Series([3,5,-6,9])
ser
ser.values #series 的數據值
ser.index #series的索引
'''
series 類似一個有序的字典{鍵：值},可以通過字典來創建 series
'''
keyword = {'a':34,'b':35,'c':36}
serk = pd.Series(keyword)
ser2 = pd.Series([2,3,5],index = ['a','b','c'])
ser2
ser2[0],ser2['a'] #通過序列號或者 索引名 來篩選數據都可以
ser2[['a','c','d']]
ser2*3
ser2[ser2>2]
'''
series的列名以及序列名
'''
ser2 = pd.Series([2,3,5],index = ['a','b','c'])
ser2.name = 'popu'
ser2.index.name = 'abc'
#ser2.values.name = 'sj' ##報錯 AttributeError: 'numpy.ndarray' object has no attribute 'name'
ser2
'''
series 在算術計算中會自動對齊索引
'''
ser1 = pd.Series([2,3,4],index = ['a','b','c'])
ser2 = pd.Series([5,6,7],index = ['c','a','b'])
ser3 = ser1 + ser2
ser3
'''
Out[16]:
a 8
b 10
c 9
dtype: int64
'''
ser4 = pd.Series(ser1,index = ['a','c','d'])
ser4
'''
Out[19]:
a 2.0
c 4.0
d NaN
dtype: float64
series可以通過 索引直接篩選數據，沒有的會補nan
'''
pd.isnull(ser4) #返回bool值 True / False 判斷數據是否爲 nan
pd.notnull(ser4)
'''
Out[22]:
a True
c True
d False
dtype: bool
'''
#代碼可以直接執行
