Done Pandas10

Problem1_GroupsoldByDate.py

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+import pandas as pd
+
+#Soln 1 Without pandas
+# def categorize_products(activities: pd.DataFrame) -> pd.DataFrame:
+#    dict={}  
+
+#    for i in range(len(activities)):
+#        sell_date=activities['sell_date'][i]
+#        product=activities['product'][i]
+
+#        if sell_date not in dict:
+#             dict[sell_date]=set()
+#        dict[sell_date].add(product)
+
+
+#    result=[]  
+
+#    for key,value in dict.items():
+#         temp=[]
+#         for product in value:
+#             temp.append(product)
+#         temp.sort()
+#         s=','.join(temp)
+#         result.append([key,len(value),s])
+
+#    df=pd.DataFrame(result,columns=['sell_date','num_sold','products'])
+#    return df.sort_values(by='sell_date')
+
+#Soln 2 With pandas
+def categorize_products(activities: pd.DataFrame) -> pd.DataFrame:
+    groups=activities.groupby('sell_date').agg(
+        num_sold=('product','nunique'),
+        products=('product',lambda x: ','.join(sorted(set (x))))
+    ).reset_index()
+    return groups.sort_values(by='sell_date')

Problem2_DailyLeadsPartners.py

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+import pandas as pd
+
+def daily_leads_and_partners(daily_sales: pd.DataFrame) -> pd.DataFrame:
+    df= daily_sales.groupby(['date_id','make_name']).agg(
+        unique_leads=('lead_id','nunique'),
+        unique_partners=('partner_id','nunique')
+    ).reset_index()
+    return df

Problem3_ActorDirector.py

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+import pandas as pd
+
+def actors_and_directors(actor_director: pd.DataFrame) -> pd.DataFrame:
+    df=actor_director.groupby(['actor_id','director_id'])['timestamp'].size().reset_index(name='count')
+    df=df[df['count']>=3]
+    return df[['actor_id','director_id']] # type: ignore