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
原文：https://www.cnblogs.com/loubin/p/11314477.html