并在此先感谢您的帮助。
我希望通过将现有列的子集除以另一个现有列来在 pandas 数据框中创建多个新列,并使用后缀动态命名。下面是虚拟代码,说明了我想做的事情的一般要点,除了 25 多个具有各种转换的列。
R代码
library(dplyr)
player = c('John','Peter','Michael')
min = c(20, 23, 35)
points = c(10,12,14)
rebounds = c(5,7,9)
assists = c(4,6,7)
df = data.frame(player,min,points,rebounds,assists)
df = df %>%
mutate_at(vars(points:assists),.funs=funs(per_min=./min))
预期输出
player min points rebounds assists points_per_min rebounds_per_min assists_per_min
1 John 20 10 5 4 0.5000000 0.2500000 0.2000000
2 Peter 23 12 7 6 0.5217391 0.3043478 0.2608696
3 Michael 35 14 9 7 0.4000000 0.2571429 0.2000000
我知道我可以在 pandas 中重现上述内容,如下所示:
import pandas as pd
data = pd.DataFrame({'player':['John','Peter','Michael'],
'min':[20,23,35],
'points':[10,12,14],
'rebounds':[5,7,9],
'assists':[4,6,7]})
df = pd.DataFrame(data)
df['points_per_minute'] = df['points']/df['min']
df['rebounds_per_minute'] = df['rebounds']/df['min']
df['assists_per_minute'] = df['assists']/df['min']
df.head()
player min points rebounds assists points_per_minute rebounds_per_minute assists_per_minute
0 John 20 10 5 4 0.500000 0.250000 0.20000
1 Peter 23 12 7 6 0.521739 0.304348 0.26087
2 Michael 35 14 9 7 0.400000 0.257143 0.20000
但是,我必须对 25+ 列执行此操作,并进行不同的转换,并且显式命名每一列,操作将变得相当麻烦。有任何 pandas 复制吗?
最佳答案
与基础 R 类似,使用基本算术按列 block 分配。通常基础 R 可以更好地转换为 Numpy/Pandas。
R
cols <- c("points", "rebounds", "assists")
df[paste0(cols, "_per_min")] <- df[cols] / df$min
Pandas
cols = ["points", "rebounds", "assists"]
df[[col+'_per_min' for col in cols]] = df[cols].div(df['min'], axis='index')
关于python - 等效于 Python pandas 中的 'mutate_at' dplyr 函数,我们在Stack Overflow上找到一个类似的问题: https://stackoverflow.com/questions/57348289/