Pandas1

Big Countries

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+import pandas as pd
+
+def big_countries(world: pd.DataFrame) -> pd.DataFrame:
+    df = world[(world['area']>=3000000) | (world['population']>=25000000)]
+    return df[['name','population','area']]

Customers Who Never Order

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+import pandas as pd
+
+def find_customers(customers: pd.DataFrame, orders: pd.DataFrame) -> pd.DataFrame:
+    #df = customers[~customers['id'].isin(orders['customerId'])]
+    #return df[['name']].rename(columns={'name':'Customers'})
+    df = customers.merge(orders, left_on="id", right_on ="customerId", how="left")
+    df = df[df["customerId"].isna()]
+    return df[['name']].rename(columns={'name':'Customers'})

Dataframe from a 2-D list

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+# import pandas as pd 
+import pandas as pd  
+
+# List1  
+lst = [['This is', 1], ['a', 2], ['learning', 3], ['program', 4]] 
+
+# creating df object  
+df = pd.DataFrame(lst, columns =['Tag', 'number']) 
+print(df )

Recyclable and Low Fat Products

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+import pandas as pd
+
+def find_products(products: pd.DataFrame) -> pd.DataFrame:
+    df = products[(products['low_fats'] =='Y') & (products['recyclable']== 'Y')]
+    return df[['product_id']]