每个唯一值的 Excel 文件（多张）的数据帧

Question

I have three different dataframes which all contain a column with certain IDs.

DF_1

DF_2

DF_3

What I am trying to achieve is to create an Excel sheet with the ID as its name with the dataframes as the sheets 'DF_1, DF_2, DF_3' per unique value. So '1.xlsx' should contain three sheets (the dataframes) with only the records that are of associated with that ID. The thing I get stuck at is either getting the multiple sheets or only the corresponding values per unique value.

for name, r in df_1.groupby("ID"):
   r.groupby("ID").to_excel(f'{name}.xlsx', index=False)

This piece of code gives me the correct output, but only for df_1. I get 5 Excel files with the corresponding rows per ID, but only one sheet, namely for df_1. I can't figure out how to include df_2 and df_3 per ID. When I try to use the following piece of code with nested loops, I get all the rows instead of per unique value:

writer = pd.ExcelWriter(f'{name}.xlsx')
r.to_excel(writer, sheet_name=f'{name}_df1')
r.to_excel(writer, sheet_name=f'{name}_df2')
r.to_excel(writer, sheet_name=f'{name}_df3')
writer.save()

There is more data transformation going on before this part, and the final dataframes are the once that are needed eventually. Frankly, I have no idea how to fix this or how to achieve this. Hopefully, someone has some insightful comments.

Answer 1

Can you try the following:

unique_ids = df_1['ID'].unique()
for name in unique_ids:
    writer = pd.ExcelWriter(f'{name}.xlsx')

    r1 = df_1[df_1['ID'].eq(name)]
    r1.to_excel(writer, sheet_name=f'{name}_df1')

    r2 = df_2[df_2['ID'].eq(name)]
    r2.to_excel(writer, sheet_name=f'{name}_df2')

    r3 = df_3[df_3['ID'].eq(name)]
    r.to_excel(writer, sheet_name=f'{name}_df3')

    writer.save()