# pip install pyjanitor
import janitor
import pandas as pd
df = pd.read_csv('Downloads/original.csv')
(df
.astype({"Entry":str})
.set_index('Entry')
.T
.pivot_longer(
index=None,
ignore_index=False,
names_to = '.value',
names_pattern='(.)')
)
0 1 2 3
Blue 3/20/20 3:09 PM O 12
Red 3/20/20 9:13 PM C 0
Purple 11/26/22 3:09 PM O 34
Green 3/20/20 3:09 PM O 24
Black 3/20/20 3:09 PM O 133
Orange 3/20/20 3:09 PM O 72
Yellow 3/20/20 3:09 PM O 2
Gold 3/20/20 3:00 PM O 13
White 3/20/20 3:00 PM O 31
Silver 3/20/20 8:49 PM O 43
Bronze 3/20/20 2:22 PM C 13
Platinum 3/20/20 3:00 PM O 59
Titanium 3/20/20 3:00 PM O 63
Blue 5/1/20 9:13 PM O 23
Red 5/1/20 9:13 PM C 0
Purple 5/1/20 5:24 PM O 45
Green 5/1/20 12:09 PM O 67
Black 5/1/20 3:09 PM O 56
Orange 5/1/20 3:09 PM O 754
Yellow 5/1/20 3:09 PM O 23
Gold 5/1/20 3:00 PM O 56
White 5/1/20 3:00 PM O 121
Silver 5/1/20 8:49 PM O 92
Bronze 5/1/20 2:22 PM C 13
Platinum 5/1/20 3:00 PM O 59
Titanium 5/1/20 3:00 PM O 63
3条答案
按热度按时间93ze6v8z1#
使用panda读取数据,并尝试以下代码
r6hnlfcb2#
您可以用途:
输出:
polhcujo3#
@Bushmaster的解决方案很好用,另一个选择是转置列,然后使用pivot_longger从pyjanitor进行透视: