我如何在Python中使用map reduce函数确定值？

Question

以下是您在杂货店中可以找到的食品数据列表。下方的CSV文件表示城市，食物类型，每磅平均价格以及加利福尼亚某城市的食物进餐时间。我需要确定在python中使用Map reduce函数，哪种食物类型的总价每磅最低。

Los Angeles,Vegetables,25.51,Breakfast
San Francisco,Fruits,259.32,Breakfast
Sandiego,Meat,22.94,Lunch
Sacramento,Dairy,53.71,Dinner
San Jose,Fish,44.16,Snack
Fresno,Poultry,393.05,Brunch
Oakland,Vegetables,15.99,Dinner
Bakersfield,Nuts,201.46,Dinner
Long Beach,Poultry,74.6,Snack
Anaheim,Grains,89.6,Breakfast
Riverside,Meat,152.75,Brunch
Irvine,Poultry,88.99,Brunch
Santa Barbara,Dairy,241.26,Lunch
Pasadena,Beans,789.7,Snack

这是我到目前为止所拥有的。任何帮助将不胜感激。

from mrjob.job import MRJob

class LowestPrice(MRJob):

    def mapper(self, _, line):
        line_cols = line.split(',')
        yield line_cols[1], 1

if __name__ == '__main__':
    LowestPrice.run()

Answer 1

import pandas as pd

data = pd.read_csv('/Users/shrek/Documents/data.csv', header=None)

print(data[2].min())
index = data[data[2]== data[2].min()].index[0]
print(data[1][index]+"in "+data[0][index]+" used in "+data[3][index]+" has lowest price per pound = "+str(data[2].min()))

输出将是：

Vegetablesin Oakland used in Dinner has lowest price per pound = 15.99