Pandas10

Daily Leads and partners.py

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

actors and directors.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']).count().reset_index()
+    df=df[df['timestamp']>=3]
+    return df[['actor_id','director_id']]

group sold products by the date.py

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