Python 3 解法, 执行用时: 773ms, 内存消耗: 524288KB, 提交时间: 2022-06-27

import pandas as pd
sales = pd.read_csv('sales.csv')
print(sales.sort_values(by=['monetary'],ascending=False).reset_index(drop=True).head(3))

Python 3 解法, 执行用时: 784ms, 内存消耗: 524288KB, 提交时间: 2022-07-23

import pandas as pd
sales = pd.read_csv('sales.csv')

import pandas as pd
sales = pd.read_csv('sales.csv')

data = sales.sort_values(by='monetary', ascending=False).reset_index(drop=True)[:3]

print(data)

Python 3 解法, 执行用时: 790ms, 内存消耗: 524288KB, 提交时间: 2022-07-16

import pandas as pd
sales = pd.read_csv('sales.csv')
 
print(sales.sort_values(by='monetary',ascending=False).reset_index(drop=True).head(3))

Python 3 解法, 执行用时: 793ms, 内存消耗: 524288KB, 提交时间: 2022-07-25

import pandas as pd
sales = pd.read_csv('sales.csv')
data=sales.sort_values('monetary',ascending=False).reset_index(drop=True).head(3)
print(data)

Python 3 解法, 执行用时: 793ms, 内存消耗: 524288KB, 提交时间: 2022-07-13

import pandas as pd
sales = pd.read_csv('sales.csv')
s=sales.sort_values(by=['monetary'],axis=0,ascending=[False],kind='quicksort', na_position='last')
s1=s.reset_index(drop=True)
print(s1.head(3))