I have a dataset containing several sells register from different vendors, locations, dates, and products. The data set is like this:
local categoria fabricante tipo consistencia peso pacote ordem vendas_kg
AREA I SABAO ASATP DILUIDO LIQUIDO 1501 A 2000g PLASTICO 1 10
AREA I SABAO TEPOS DILUIDO LIQUIDO 1501 A 2000g PLASTICO 1 20
AREA I SABAO ASATP CAPSULA LIQUIDO 1501 A 2000g PLASTICO 1 20
AREA I SABAO TEPOS CAPSULA LIQUIDO 1501 A 2000g PLASTICO 1 30
AREA I SABAO ASATP DILUIDO LIQUIDO 1501 A 2000g PLASTICO 2 20
AREA I SABAO TEPOS DILUIDO LIQUIDO 1501 A 2000g PLASTICO 2 30
AREA I SABAO ASATP CAPSULA LIQUIDO 1501 A 2000g PLASTICO 2 20
AREA I SABAO TEPOS CAPSULA LIQUIDO 1501 A 2000g PLASTICO 2 30
AREA II SABAO ASATP DILUIDO LIQUIDO 1501 A 2000g PLASTICO 1 10
AREA II SABAO TEPOS DILUIDO LIQUIDO 1501 A 2000g PLASTICO 1 15
AREA II SABAO ASATP CAPSULA LIQUIDO 1501 A 2000g PLASTICO 1 25
AREA II SABAO TEPOS CAPSULA LIQUIDO 1501 A 2000g PLASTICO 1 35
AREA II SABAO ASATP DILUIDO LIQUIDO 1501 A 2000g PLASTICO 2 20
AREA II SABAO TEPOS DILUIDO LIQUIDO 1501 A 2000g PLASTICO 2 25
AREA II SABAO TEPOS CAPSULA LIQUIDO 1501 A 2000g PLASTICO 2 20
AREA II SABAO TEPOS CAPSULA LIQUIDO 1501 A 2000g PLASTICO 2 30
I'm pivoting this data set usig the following code:
temp_df = pd.pivot_table(df,index=['local','tipo','ordem'], values=['vendas_kg'] , aggfunc=[np.sum], columns=['fabricante'], fill_values=0, margins=True, margins_name= 'Total')
and I get this output:
sum sum
vendas_kg vendas_kg
fabricante ASATP TEPOS Total
local tipo ordem
AREA I DILUIDO 1 10 20 30
2 20 30 50
CAPSULA 1 10 20 30
2 20 30 50
AREA II DILUIDO 1 10 15 25
2 20 25 45
CAPSULA 1 25 35 55
2 20 30 50
I want to calculate the percentage for each ['ordem'] and for the percentage for each segment.g. ordem,tipo and local, like this:
sum sum
vendas_kg vendas_kg
fabricante ASATP TEPOS % segment Total
local tipo ordem
AREA I DILUIDO 1 33% 66% 50% 30
2 40% 60% 50% 50
CAPSULA 1 33% 66% 50% 30
2 40% 60% 50% 50
AREA II DILUIDO 1 40% 60% 31.25% 25
2 44.44% 55.56% 47.37% 45
CAPSULA 1 43.64% 57.36% 53.63% 55
2 40% 60% 53.63% 50
So the total sales for AREA I DILUIDO 1 is 30, ASATP sales represent 33% of it and TEPOS 66%, and from the total sales of AREA I 1 the DILUIDOs sales represent 50% and so on.
I also want to compare the sales difference between ['ordem'] e.g. percentage growth of segment and ['fabricante'] and store in a new table like this:
% change in % change in
vendas_kg vendas_kg % change in % change in
fabricante ASATP TEPOS % segment Total
AREA I DILUIDO 1 0 0 0 0
2 +7% -6% 0 20
3 0 0 0 0
AREA I CAPSULA 1 0 0 0 0
2 +7% -6% 0 20
3 0 0 0 0
AREA II DILUIDO 1 0 0 0 0
2 +4.44% -4.44% +16.12% 20
3 0 0 0 0
AREA II CAPSULA 1 0 0 0 0
2 -3.64% +3.64% 0 5
3 0 0 0 0
I'm stuck at this over the last 5 days, I have way more categories in ['fabricante']['tipo'] and ['local'] so it must work for more than two categories in each. Thanks for the help in advance, feel free to contact me in case of doubts.
To take the percents:
df_percent = temp_df.iloc[:, [0,1]].apply(lambda x: round(x / x.sum() * 100, 2), axis = 1)
to take the the variation, use diff
df_diff_percent = df_percent.groupby(level=[0,1]).diff().fillna(0)
sum
vendas_kg
fabricante ASATP TEPOS
local tipo ordem
AREA I CAPSULA 1 0.00 0.00
2 0.00 0.00
DILUIDO 1 0.00 0.00
2 6.67 -6.67
AREA II CAPSULA 1 0.00 0.00
2 -41.67 41.67
来源：https://stackoverflow.com/questions/55288279/percentage-calculation-in-pivot-table-pandas-with-columns