[Python] Verwendung der Pandas-Serie

import pandas as pd
from pandas import Series

obj = Series([3,9,12])
obj

0     3
1     9
2    12
dtype: int64

obj.values
array([ 3,  9, 12])

obj.index
RangeIndex(start=0, stop=3, step=1)

ww2_cas = Series([8700000, 4300000, 3000000, 2100000, 400000], index=['USSR', 'Germany', 'China', 'Japan', 'USA'])
ww2_cas

USSR       8700000
Germany    4300000
China      3000000
Japan      2100000
USA         400000
dtype: int64

ww2_cas['USA']
400000

ww2_cas>4000000
USSR        True
Germany     True
China      False
Japan      False
USA        False
dtype: bool

ww2_cas[ww2_cas>4000000]
USSR       8700000
Germany    4300000
dtype: int64

'USSR' in ww2_cas
True

ww2_dic = ww2_cas.to_dict()
ww2_dic
{'China': 3000000,
 'Germany': 4300000,
 'Japan': 2100000,
 'USA': 400000,
 'USSR': 8700000}

ww2_Series = Series(ww2_dic)
ww2_Series
China      3000000
Germany    4300000
Japan      2100000
USA         400000
USSR       8700000
dtype: int64
In [ ]:

countries = ['China', 'Germony', 'Japan', 'USA', 'USSR', 'Argentina']
obj2 = Series(ww2_dic, index=countries)
obj2

China        3000000.0
Germony            NaN
Japan        2100000.0
USA           400000.0
USSR         8700000.0
Argentina          NaN
dtype: float64

pd.isnull(obj2)

China        False
Germony       True
Japan        False
USA          False
USSR         False
Argentina     True
dtype: bool

pd.notnull(obj2)

China         True
Germony      False
Japan         True
USA           True
USSR          True
Argentina    False
dtype: bool

obj2.name = 'Opfer des Zweiten Weltkriegs'
obj2

China        3000000.0
Germony            NaN
Japan        2100000.0
USA           400000.0
USSR         8700000.0
Argentina          NaN
Name:Opfer des Zweiten Weltkriegs, dtype: float64

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