数据透视表总和：KeyError（'％s不在索引中'％objarr [mask]）

Question

I have a table like:

    Category Customer  Month  Year            Unit Unit Symbol  Value
0        AF   Brand1      1  2017     Gross Sales           $      1
1        AF   Brand1      1  2017  Sales quantity         EAU      1
2        AF   Brand1      2  2017     Gross Sales           $      1
3        AF   Brand1      2  2017  Sales quantity         EAU      1
4        AF   Brand1      3  2017     Gross Sales           $      1
5        AF   Brand1      3  2017  Sales quantity         EAU      1
6        AF   Brand1      4  2017     Gross Sales           $      1
7        AF   Brand1      4  2017  Sales quantity         EAU      1
8        AF   Brand1      5  2017     Gross Sales           $      1
9        AF   Brand1      5  2017  Sales quantity         EAU      1
10       AF   Brand2      1  2017     Gross Sales           $      1
11       AF   Brand2      1  2017  Sales quantity         EAU      1
12       AF   Brand2      2  2017     Gross Sales           $      1
13       AF   Brand2      2  2017  Sales quantity         EAU      1
14       AF   Brand2      3  2017     Gross Sales           $      1
15       AF   Brand2      3  2017  Sales quantity         EAU      1
16       AF   Brand2      4  2017     Gross Sales           $      1
17       AF   Brand2      4  2017  Sales quantity         EAU      1
18       AF   Brand2      5  2017     Gross Sales           $      1
19       AF   Brand2      5  2017  Sales quantity         EAU      1

Which I have already loaded into memory

I want to remove the Customer column, and aggregate the Value column forall records where other column values are the same.

EG: For all records where Category, Month, Year, Unit and Symbol are the same, I want the Value field to be summated into a new frame as shown below:

Category Month  Year            Unit Unit Symbol  Value
0   AF    1     2017     Gross Sales           $      2
1   AF    1     2017  Sales quantity         EAU      2
2   AF    2     2017     Gross Sales           $      2
3   AF    2     2017  Sales quantity         EAU      2
4   AF    3     2017     Gross Sales           $      2
5   AF    3     2017  Sales quantity         EAU      2
6   AF    4     2017     Gross Sales           $      2
7   AF    4     2017  Sales quantity         EAU      2
8   AF    5     2017     Gross Sales           $      2
9   AF    5     2017  Sales quantity         EAU      2

I have tried different variations on:

df.pivot_table(columns=['Unit', 'Unit Symbol', 'month', 'year'], index='Category', aggfunc=sum, values="Value")

but it always returns an error, like KeyError('%s not in index' % objarr[mask]) Followed by a list of my Customers. This doesn't make sense to me as I am pivoting my data to get rid of my customers and aggregate.

I have 12 different customers and 13 different Categories. Not all customers feature all categories and vice versa. Their associations change over time, so hard coding this is not practical.

How can I summate my table in this fashion?

Answer 1

df.pivot_table(index=['Category','Month','Year','Unit','Unit Symbol'],values="Value",aggfunc=np.sum).reset_index().assign(Customer='Total')

Output:

  Category  Month  Year            Unit Unit Symbol  Value Customer
0       AF      1  2017     Gross Sales           $      2    Total
1       AF      1  2017  Sales quantity         EAU      2    Total
2       AF      2  2017     Gross Sales           $      2    Total
3       AF      2  2017  Sales quantity         EAU      2    Total
4       AF      3  2017     Gross Sales           $      2    Total
5       AF      3  2017  Sales quantity         EAU      2    Total
6       AF      4  2017     Gross Sales           $      2    Total
7       AF      4  2017  Sales quantity         EAU      2    Total
8       AF      5  2017     Gross Sales           $      2    Total
9       AF      5  2017  Sales quantity         EAU      2    Total