I have a csv file that I converted into dataframe using Pandas. Here's the dataframe:
Customer ProductID Count
John 1 50
John 2 45
Mary 1 75
Mary 2 10
Mary 5 15
I need an output in the form of a dictionary that looks like this:
{ProductID:1, Count:{John:50, Mary:75}},
{ProductID:2, Count:{John:45, Mary:10}},
{ProductID:5, Count:{John:0, Mary:15}}
I read the following answers:
python pandas dataframe to dictionary and
Convert dataframe to dictionary
This is the code that I'm having:
df = pd.read_csv('customer.csv')
dict1 = df.set_index('Customer').T.to_dict('dict')
dict2 = df.to_dict(orient='records')
and this is my current output:
dict1 = {'John': {'Count': 45, 'ProductID': 2}, 'Mary': {'Count': 15, 'ProductID': 5}}
dict2 = [{'Count': 50, 'Customer': 'John', 'ProductID': 1},
{'Count': 45, 'Customer': 'John', 'ProductID': 2},
{'Count': 75, 'Customer': 'Mary', 'ProductID': 1},
{'Count': 10, 'Customer': 'Mary', 'ProductID': 2},
{'Count': 15, 'Customer': 'Mary', 'ProductID': 5}]
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