Completed Pandas10

1050Actors&Directors.py

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+import pandas as pd
+
+def actors_and_directors(actor_director: pd.DataFrame) -> pd.DataFrame:
+    result = actor_director.groupby(['actor_id', 'director_id']).size().reset_index(name='cnt')
+    result = result[(result['cnt'] > 2)]
+    # print((result))
+    return result[['actor_id', 'director_id']]

1484GroupSoldProductsByDate.py

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+import pandas as pd
+
+def categorize_products(activities: pd.DataFrame) -> pd.DataFrame:
+    grouped = activities.groupby(['sell_date'])
+    df1 = grouped.agg(
+        num_sold = ('product','nunique'),
+        products = ( 'product',lambda x: ','.join(sorted(set(x))))
+    ).reset_index()
+    # print(df1)
+    return df1

1693DailyLeadsPartners.py

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+import pandas as pd
+
+def daily_leads_and_partners(daily_sales: pd.DataFrame) -> pd.DataFrame:
+    group = daily_sales.groupby(['date_id', 'make_name'])
+    result = group.agg(
+        unique_leads=('lead_id', 'nunique'),
+        unique_partners=('partner_id', 'nunique')
+    ).reset_index()
+    return result
+    # dict = {}
+    # for i in range(len(daily_sales)):
+    #     dateid = daily_sales['date_id'][i]
+    #     make = daily_sales['make_name'][i]
+    #     leadid = daily_sales['lead_id'][i]
+    #     partnerid = daily_sales['partner_id'][i]
+    #     keytup = (dateid, make)
+    #     if keytup not in dict:
+    #         dict[keytup] = []
+    #         (dict[keytup]).append({leadid})
+    #         (dict[keytup]).append({partnerid})
+    #     else:
+    #         (dict[keytup])[0].add(leadid)
+    #         (dict[keytup])[1].add(partnerid)
+    # # print(dict)
+    # result = []
+    # for key, value in dict.items():
+    #     result.append([key[0], key[1] , len(value[0]), len(value[1])])
+    # # print(result)
+
+    # df = pd.DataFrame(result, columns = ['date_id', 'make_name', 'unique_leads', 'unique_partners'])
+    # return df
+