我如何才能获得工作时间排名前五的名字，谁使用熊猫数据框架工作最多

Question

我想逐个打印每个名字及其工作时间

熊猫数据帧：

df = pd.DataFrame({'NAME': ['Joesph Morse', 'Katie Plotkin', 'Denny Heaps', 'Evelia Chesson', 'Drew Hassett', 'Robt Buckles', 'Suzy Lafler'], 'CITY': ["New York", "Boston", "Los Angeles", "Chicago", "Atlanta",
"Salt Lake City", "Dallas"], 'WORK HOURS': [3, 7, 0, 6, 10, 1, 9]}
)

目前，我的目标是"Work Hours"列，nlargest可以过滤该行中最前面的大数字，但它不能帮助我获得员工的姓名和他们的工作时间。我怎么也能得到他们的名字？

row = df['WORK HOURS']
leading_workers =  row.nlargest(5, 'all')
print('Top First worker',leading_workers.values[0]) # user_1
print('Top Second worker',leading_workers.values[1]) # user_2
print('Top Third worker',leading_workers.values[2]) # user_3
print('Top Forth worker',leading_workers.values[3]) # user_4
print('Top Fifth worker',leading_workers.values[4]) # user_5

Answer 1

将DataFrame.nlargest与指定的列名称一起用于测试，并为leading_workers:选择NAME

leading_workers = df.nlargest(5, 'WORK HOURS', 'all')['NAME']
print (leading_workers)
4      Drew Hassett
6       Suzy Lafler
1     Katie Plotkin
3    Evelia Chesson
0      Joesph Morse
Name: NAME, dtype: object
for w in leading_workers:
print (w)
Drew Hassett
Suzy Lafler
Katie Plotkin
Evelia Chesson
Joesph Morse

Answer 2

import pandas as pd
df = pd.DataFrame({'NAME': ['Joesph Morse', 'Katie Plotkin', 'Denny Heaps',
'Evelia Chesson', 'Drew Hassett', 'Robt Buckles', 'Suzy Lafler'],
'CITY': ["New York", "Boston", "Los Angeles", "Chicago", "Atlanta",
"Salt Lake City", "Dallas"],
'WORK HOURS': [3, 7, 0, 6, 10, 1, 9]}
)
df.sort_values(by='WORK HOURS',ascending=False,inplace=True)

是另一种方法，用输出

NAME            CITY            WORK HOURS
4   Drew Hassett    Atlanta         10
6   Suzy Lafler     Dallas          9
1   Katie Plotkin   Boston          7
3   Evelia Chesson  Chicago         6
0   Joesph Morse    New York        3
5   Robt Buckles    Salt Lake City  1
2   Denny Heaps     Los Angeles     0

如果你想要前5行

df.head(5)
NAME            CITY            WORK HOURS
4   Drew Hassett    Atlanta         10
6   Suzy Lafler     Dallas          9
1   Katie Plotkin   Boston          7
3   Evelia Chesson  Chicago         6
0   Joesph Morse    New York        3