Series的idxmax和argmax

转载至：https://www.cnblogs.com/liulangmao/p/9211537.html

pandas Series 的 argmax 方法和 idxmax 方法用于获取 Series 的最大值的索引值:

举个栗子:

有一个pandas Series,它的索引是国家名,数据是就业率,要找出就业率最高的国家:

import pandas as pd

countries = [

    'Afghanistan', 'Albania', 'Algeria', 'Angola',

    'Argentina', 'Armenia', 'Australia', 'Austria',

    'Azerbaijan', 'Bahamas', 'Bahrain', 'Bangladesh',

    'Barbados', 'Belarus', 'Belgium', 'Belize',

    'Benin', 'Bhutan', 'Bolivia', 'Bosnia and Herzegovina',

]

employment_values = [

    55.70000076,  51.40000153,  50.5       ,  75.69999695,

    58.40000153,  40.09999847,  61.5       ,  57.09999847,

    60.90000153,  66.59999847,  60.40000153,  68.09999847,

    66.90000153,  53.40000153,  48.59999847,  56.79999924,

    71.59999847,  58.40000153,  70.40000153,  41.20000076,

]

# Employment data in 2007 for 20 countries

employment = pd.Series(employment_values, index=countries)

可以这样做:

max_country = employment.idxmax()     

max_country = employment.argxmax()  

# 结果: 'Angola'

如果是一个没有索引值的Series,则返回它的位置索引:

pure_employment = pd.Series(employment_values)

print(pure_employment.argmax())

print(pure_employment.idxmax())

# 结果: 3

巴特西

Series的idxmax和argmax

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