[英]Percentage calculation in pivot table pandas with columns
我有一个数据集,其中包含来自不同供应商、地点、日期和产品的多个销售登记册。 数据集是这样的:
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
我正在使用以下代码旋转此数据集:
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')
我得到这个输出:
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
我想计算每个 ['ordem'] 的百分比和每个段的百分比。 ordem、tipo 和 local,像这样:
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
因此,AREA I DILUIDO 1 的总销售额为 30,ASAP 销售额占其中的 33%,TEPOS 占 66%,从 AREA I 1 的总销售额中,DILUIDOs 的销售额占 50%,依此类推。
我还想比较 ['ordem'] 之间的销售差异,例如段和 ['fabricante'] 的百分比增长,并存储在这样的新表中:
% 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
在过去的 5 天里,我一直坚持这一点,我在 ['fabricante']['tipo'] 和 ['local'] 中有更多的类别,所以它必须在每个类别中适用于两个以上的类别。 提前感谢您的帮助,如有疑问,请随时与我联系。
取百分比:
df_percent = temp_df.iloc[:, [0,1]].apply(lambda x: round(x / x.sum() * 100, 2), axis = 1)
采取变化,使用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
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