Pandas1: Problem Solutions_RN32MAY2025DS

BigCountries.py

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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']]

CustomersWhoNeverOrder.py

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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'})

MakeAPandasDataframeWithTwo-DimensionalLists.py

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+#Q1
+#Create Pandas Dataframe from 2D List using pd.DataFrame()
+
+import pandas as pd  
+
+list_1 = [['Geek', 25],
+          ['is', 30],
+          ['for', 26],
+          ['Geeksforgeeks', 22]] 
+
+# creating df object with columns specified    
+df = pd.DataFrame(list_1, columns =['Tag','number']) 
+print(df )
+
+
+#Q2
+#Create Pandas Dataframe from 2D List using pd.DataFrame.from_records()
+
+import pandas as pd
+
+data = [['Geek1', 28, 'Analyst'],
+        ['Geek2', 35, 'Manager'],
+        ['Geek3', 29, 'Developer']]
+
+columns = ['Name', 'Age', 'Occupation']
+
+# Creating DataFrame using pd.DataFrame.from_records()
+df = pd.DataFrame.from_records(data, columns=columns)
+print(df)
+
+
+#Q3
+#Create Pandas Dataframe from 2D List using pd.DataFrame.from_dict()
+
+import pandas as pd
+
+data = [['Geek1', 26, 'Scientist'],
+        ['Geek2', 31, 'Researcher'],
+        ['Geek3', 24, 'Engineer']]
+
+columns = ['Name', 'Age', 'Occupation']
+
+# Creating DataFrame using pd.DataFrame.from_dict()
+df = pd.DataFrame.from_dict(dict(zip(columns, zip(*data))))
+print(df)
+
+
+
+#Q4
+#Create Pandas Dataframe from 2D List using Specifying Data Types
+import pandas as pd
+
+data = [['Geek1', 'Reacher', 25],
+        ['Geek2', 'Pete', 30],
+        ['Geek3', 'Wilson', 26],
+        ['Geek4', 'Williams', 22]]
+
+columns = ['FName', 'LName', 'Age']
+
+# Creating DataFrame with specified data types
+df = pd.DataFrame(data, columns=columns)
+print(df)

RecyclableAndLowFatProducts.py

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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']]