Series (下)

接續上一次的內容，Series 在許多應用還有一個好用的特性，在進行算術運算時，會自動按照索引標籤對齊:

In [40]: obj3
Out[40]:
Ohio      35000
Texas     71000
Oregon    16000
Utah       5000
dtype: int64

In [41]: obj4
Out[41]:
California       NaN
Ohio         35000.0
Oregon       16000.0
Texas        71000.0
dtype: float64

In [42]: obj3 + obj4
Out[42]"
California         NaN
Ohio           70000.0
Oregon         32000.0
Texas         142000.0
Utah               NaN
dtype: float64

如果你使用過資料庫，可以把這個功能養成是類似 join 操作

Series 物健身本與他的索引都有一個 name 屬性，這個屬性與 pandas 功能的其他領域整合:

In [43]: obj4.name = "population"

In [44]: obj4.index.name = "state"

In [45]: obj4
Out[45]:
state
California         NaN
Ohio           35000.0
Oregon         16000.0
Texas          71000.0
Name: population, dtype: float64

也可以透過賦值來進行修改 Series 的索引:

In [46]: obj
Out[46]:
0 4
1 7
2 5
3 3
dtype: int64

In [47]: obj.index = ["Bob", "Steve", "Jeff", "Ryan"]

In [48]: obj
Out[48]:
Bob      4
Steve    7
Jeff     5
Ryan     3
dtype: int64

今日的分享就到這囉，我們明天見，掰掰！