下面是我的数据:数据帧-df_AW17
Product ID Season Division Brand Category Sub Category AW16 (Sales) AW17 (Sales)
Blazer 1 AW17 Men's Wear Brand 1 Top BLAZER 198
Blazer 2 AW16 Men's Wear Brand 1 Top BLAZER 138
Blazer 2 AW17 Men's Wear Brand 1 Top BLAZER 270
Blazer 3 AW17 Men's Wear Brand 1 Top BLAZER 27
Blazer 4 AW17 Men's Wear Brand 1 Top BLAZER 192
Blazer-10 AW17 Women's Wear Brand 1 Top BLAZER 15
Blazer-11 AW16 Women's Wear Brand 1 Top BLAZER 10
Blazer-11 AW17 Women's Wear Brand 1 Top BLAZER 14
Blazer-12 AW17 Women's Wear Brand 1 Top BLAZER 16
Blazer-13 AW17 Women's Wear Brand 1 Top BLAZER 207
Blazer-5 AW16 Women's Wear Brand 1 Top BLAZER 126
Blazer-5 AW17 Women's Wear Brand 1 Top BLAZER 200
Blazer-6 AW17 Men's Wear Brand 1 Top BLAZER 5
Blazer-7 AW17 Women's Wear Brand 1 Top BLAZER 299
Blazer-8 AW17 Women's Wear Brand 1 Top BLAZER 147
Blazer-9 AW17 Men's Wear Brand 1 Top BLAZER 23
Jacket-10 AW17 Men's Wear Brand 1 Top JACKETS 20
Jacket-11 AW17 Men's Wear Brand 1 Top JACKETS 5
Jacket-12 AW16 Men's Wear Brand 1 Top JACKETS 5
Jacket-12 AW17 Men's Wear Brand 1 Top JACKETS 12
Jacket-13 AW16 Women's Wear Brand 1 Top JACKETS 15
它具有产品ID的值,我需要使用Season AW16,AW17和给定的AW16(销售),AW17(销售)作为新列来获得销售增长百分比。问题是我无法对公式进行分组或放置,因为“销售”的列值在特定产品ID的不同行中。
我试图做。
df_AW17['Sales Growth %'] = df_AW17.groupby(['Product ID'])(((df_AW17['AW17 (Sales)'] - df_AW17['AW16 (Sales)']) / df_AW17['AW16 (Sales)']) * 100)
。
我想要的结果是从产品ID的AW16年(销售)到AW17年(销售)的销售额增长百分比。
答案 0 :(得分:0)
由于数据框中的所有行似乎都具有唯一的产品ID,创建新列之后执行的更简单的操作是否不能满足目的?
df_AW17['Sales_growth_pct'] = (df_AW17['AW17 (Sales)'] - df_AW17['AW16 (Sales)']) / df_AW17['AW16 (Sales)']