How to use pandas to agg data with different condition for different columns?

Question

Agg by sales

Original Data:

Sales	Product	Qty
James	apple	10
Johnson	apple	1
Jessie	banana	2
Judy	melon	5
James	melon	5
Jessie	apple	8

To:

Sales	Apple	Melon	Banana	Total
James	10	5	0	15
Judy	0	5	0	5
Jessie	8	0	2	10
Johnson	1	0	0	1

I'd like to calcuate the amount for each product and group by each sales with pandas, so how to do this by pandas?

Answer 1

With df as your dataframe name Try:

temp_df = df.pivot_table(index='Sales', columns='Product', aggfunc=sum)
cols = [ind[1] for ind in np.array(temp_df.columns)]
data = np.array(temp_df)
final_df = pd.DataFrame({'Sales':temp_df.index})
for i, col in enumerate(cols):
    final_df = pd.concat((final_df, pd.DataFrame({col:data[:, i]})), axis=1)
final_df = final_df.fillna(0)
final_df['total'] = final_df.iloc[:, 1:].sum(axis=1)