Question

I have data in a 3d dictionary as:

 movieid, date,customer_id,views
 0, (2011,12,22), 0, 22
 0, (2011,12,22), 1, 2
 0, (2011,12,22), 2, 12
 .....
 0, (2011,12,22), 7, 2
 0, (2011,12,23), 0, 123

..
so basically the data represents how many times a movie has been watched each day.. by each customer (there are just 8 customers)..

Now, I want to calculate.. on average how many times a movie has been watched by each customer.

So basically

    movie_id,customer_id, avg_views
     0, 0, 33.2
     0, 1 , 22.3

  and so on

What is the pythonic way to solve this.

Thakns

Edit:

 data = defaultdict(lambda : defaultdict(dict))
 date = datetime.datetime(2011,1,22)
 data[0][date][0] = 22
 print data
defaultdict(<function <lambda> at 0x00000000022F7CF8>, 
 {0: defaultdict(<type 'dict'>, 
 {datetime.datetime(2011, 1, 22, 0, 0): {0: 22}}))

Suppose there are just 2 customers, 1 movie and 2 days worth of data

 movie_id, date, customer_id,views
 0 , 2011,1,22,0,22
 0 , 2011,1,22,1,23
 0 , 2011,1,23,0,44

note: The customer 1 didnt watched a movie id 0 on 23rd jan
Now the answer would

 movie_id,customer_id,avg_views
  0   , 0 ,    (22+44)/2
  0,    1,      (23)/1

Answer 1

sum makes this easy. In my original version I used dict.keys() a lot, but iterating over a dictionary gives you the keys by default.

This function calculates a single line of the result:

def average_daily_views(movie_id, customer_id, data):
    daily_values = [data[movie_id][date][customer_id] for date in data[movie_id]]
    return sum(daily_values)/len(daily_values)

Then you can just loop it to get whatever form you want. Maybe:

def get_averages(data):
    result = [average_daily_views(movie, customer, data) for customer in 
              data[movie] for movie in data]