python - 创建计算百分比重复 N 次的新列

Question

我想知道如何计算这些列的百分比并将其保存在旁边的新列中N次。示例

d1 = [['0.00', '10','11','15'], ['2.99', '30','40','0'], ['4.99', '5','0','2']]

df1 = pd.DataFrame(d1, columns = ['Price', '1','2','3']) 

我希望以下操作迭代所有列(当然除了价格之外)

df1['1%'] = df1['1'] / df1['1'].sum() (I got an error when I tried this)

结果:

d2 = [['0.00', '10','0.22','11','0.2156','15','0.8823'], ['2.99', '30','0.66','40','0.7843','0','0'], ['4.99', '5','0.11','0','0','2','0.1176']]

df2 = pd.DataFrame(d2, columns = ['Price', '1','1%','2','2%','3','3%']) 

(列可以是 N 次，所以我需要迭代所有列)

Answer 1

IIUC，您需要:

m=df1.set_index('Price').div(df1.set_index('Price').sum()).add_suffix('%')
df2=pd.concat([df1.set_index('Price'),m],axis=1).sort_index(axis=1).reset_index()

<小时/>

   Price   1        1%   2        2%   3        3%
0   0.00  10  0.222222  11  0.215686  15  0.882353
1   2.99  30  0.666667  40  0.784314   0  0.000000
2   4.99   5  0.111111   0  0.000000   2  0.117647

注意:这是假设数据类型是:

df1.dtypes
Price    float64
1          int32
2          int32
3          int32