python pandas pivot_table count frequency in one column

Question

I am still new to Python pandas' pivot_table and would like to ask a way to count frequencies of values in one column, which is also linked to another column of ID. The DataFrame looks like the following.

import pandas as pd
df = pd.DataFrame({'Account_number':[1,1,2,2,2,3,3],
                   'Product':['A', 'A', 'A', 'B', 'B','A', 'B']
                  })

For the output, I'd like to get something like the following:

                Product
                A      B
Account_number           
      1         2      0
      2         1      2
      3         1      1

So far, I tried this code:

df.pivot_table(rows = 'Account_number', cols= 'Product', aggfunc='count')

This code gives me the two same things. What is the problems with the code above? A part of the reason why I am asking this question is that this DataFrame is just an example. The real data that I am working on has tens of thousands of account_numbers. Thanks for your help in advance!

question from:https://stackoverflow.com/questions/22412033/python-pandas-pivot-table-count-frequency-in-one-column

Answer 1

You need to specify the aggfunc as len:

In [11]: df.pivot_table(index='Account_number', columns='Product', 
                        aggfunc=len, fill_value=0)
Out[11]:
Product         A  B
Account_number
1               2  0
2               1  2
3               1  1

It looks like count, is counting the instances of each column (Account_number and Product), it's not clear to me whether this is a bug...