Pandas 1 Completed

README.md

@@ -2,9 +2,104 @@
 
 1 Problem 1 : Make a Pandas DataFrame with two-dimensional list	(	https://www.geeksforgeeks.org/make-a-pandas-dataframe-with-two-dimensional-list-python/)
 
+Create Pandas Dataframe from 2D List using pd.DataFrame()
+In this example below code creates a Pandas DataFrame ('df') from a two-dimensional list ('lst') with specified column names ('Tag' and 'number') and prints the resulting DataFrame.
+------------------------------------------------------
+import pandas as pd
+lst = [['geek', 25], ['is', 30],
+      ['for', 26], ['Geeksforgeeks', 22]]
+# creating df object with columns specified
+df = pd.Dataframe(lst, columns=['Tag', 'number])
+print(df)
+------------------------------------------------------
+#Create Pandas Dataframe from 2D List using pd.DataFrame.from_records()
+
+import pandas as pd
+
+# Two-dimensional list
+data = [['Geek1', 28, 'Analyst'],
+        ['Geek2', 35, 'Manager'],
+        ['Geek3', 29, 'Developer']]
+
+# Column names
+columns = ['Name', 'Age', 'Occupation']
+
+# Creating DataFrame using pd.DataFrame.from_records()
+df = pd.DataFrame.from_records(data,columns=columns)
+
+print(df)
+
+------------------------------------------------------
+#Create Pandas Dataframe from 2D List using pd.DataFrame.from_dict()
+
+import pandas as pd
+
+# Two-dimensional list
+data = [['Geek1', 26, 'Scientist'],
+        ['Geek2', 31, 'Researcher'],
+        ['Geek3', 24, 'Engineer']]
+
+# Column names
+columns = ['Name', 'Age', 'Occupation']
+
+# Creating DataFrame using pd.DataFrame.from_dict()
+df = pd.DataFrame.from_dict(dict(zip(columns, zip(*data))))
+
+# Displaying the DataFrame
+print(df)
+------------------------------------------------------------
+#Create Pandas Dataframe from 2D List using Specifying Data Types
+
+import pandas as pd
+
+# Two-dimensional list
+data = [['Geek1', 'Reacher', 25],
+        ['Geek2', 'Pete', 30],
+        ['Geek3', 'Wilson', 26],
+        ['Geek4', 'Williams', 22]]
+
+# Column names
+columns = ['FName', 'LName', 'Age']
+
+# Creating DataFrame with specified data types
+df = pd.DataFrame(data, columns = columns)
+
+# Displaying the DataFrame
+print(df)
+
+
+------------------------------------------------------------
+
+------------------------------------------------------
 2 Problem 2 :Big Countries	(	https://leetcode.com/problems/big-countries/ )
+------------------------------------------------------------
+import pandas as pd
+
+def big_countries(world: pd.DataFrame) -> pd.DataFrame: 
+    df = world[(world['area'] >= 3000000) | (world['population'] >= 25000000)]
+    #always give condition within ()
+    return df[['name', 'population', 'area']]
+------------------------------------------------------------------------------
 
 3 Problem 3 :Recyclable and Low Fat Products	(	https://leetcode.com/problems/recyclable-and-low-fat-products/ )
 
+------------------------------------------------------------
+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"]]
+
+
+------------------------------------------------------------
+------------------------------------------------------------
+------------------------------------------------------------
+------------------------------------------------------------------------------------------------------------------------
+
 4 Problem 4 :Customer Who Never Order	(	https://leetcode.com/problems/customers-who-never-order/  )
 
+import pandas as pd
+
+def find_customers(customers: pd.DataFrame, orders: pd.DataFrame) -> pd.DataFrame:
+    merged_df = customers.merge(orders, left_on='id', right_on='customerId', how='left')
+    return merged_df[merged_df['customerId'].isna()][['name']]