读书笔记 pandas 第1章 Series对象

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https://github.com/jakevdp/PythonDataScienceHandbook

Pandas 有三个基本数据结构：Series、DataFrame 和 Index。

NumPy 数组通过隐式定义的整数索引获取数值，

而 Pandas 的 Series 对象用一种显式定义的索引与数值关联。

导入

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import numpy as np
import pandas as pd

Series对象

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data = pd.Series([0.25, 0.5, 0.75, 1.0], index=['a', 'b', 'c', 'd'])
data

a    0.25
b    0.50
c    0.75
d    1.00
dtype: float64
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data.values

>>> array([ 0.25,  0.5 ,  0.75, 1.  ])
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data.index

>>> RangeIndex(start=0, stop=4, step=1)
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data[1:3]

>>> 1    0.50
    2    0.75
    dtype: float64
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data['b']

>>> 0.5
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'a' in data

>>> True
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data.keys()

>>> Index(['a', 'b', 'c', 'd'], dtype='object')
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list(data.items())

>>> [('a', 0.25), ('b', 0.5), ('c', 0.75), ('d', 1.0)]
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data['e'] = 1.25
data

a    0.25
b    0.50
c    0.75
d    1.00
e    1.25
dtype: float64

字典

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population_dict = {'California': 38332521,
                   'Texas': 26448193,
                   'New York': 19651127,
                   'Florida': 19552860,
                   'Illinois': 12882135}
population = pd.Series(population_dict)
population

California    38332521
Florida       19552860
Illinois      12882135
New York      19651127
Texas         26448193
dtype: int64
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population['California']

>>> 38332521
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population['California':'Illinois']

>>> California    38332521
    Florida       19552860
    Illinois      12882135
    dtype: int64

显式指定索引

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pd.Series([2, 4, 6])

>>> 0    2
    1    4
    2    6
    dtype: int64
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pd.Series({2:'a', 1:'b', 3:'c'}, index=[3, 2])

>>> 3    c
    2    a
    dtype: object