├── DataLemur ├── 1.Easy │ ├── 01 - Histogram of Tweets.sql │ ├── 02 - Data Science Skills.sql │ ├── 03 - Page With No Likes.sql │ ├── 04 - Unfinished Parts.sql │ ├── 05 - Laptop vs Mobile Viewership.sql │ ├── 06 - Average Post Hiatus(Part 1).sql │ ├── 07 - Teams Power Users.sql │ ├── 08 - Duplicate Job Listings.sql │ ├── 09 - Cities With Completed Trades.sql │ ├── 10 - Average Review Ratings.sql │ ├── 11 - Well Paid Employees.sql │ ├── 12 - App Click-through Rate (CTR).sql │ ├── 13 - Second Day Confirmation.sql │ ├── 14 - IBM db2 Product Analytics.sql │ ├── 15 - Cards Issued Difference.sql │ ├── 16 - Compressed Mean.sql │ ├── 17 - Pharmacy Analytics (Part 1).sql │ ├── 18 - Pharmacy Analytics (Part 2).sql │ ├── 19 - Pharmacy Analytics (Part 3).sql │ ├── 20 - Patient Support Analysis (Part 1).sql │ └── Final Account Balance.sql ├── 2.Medium │ ├── 21 - User's Third Transaction.sql │ ├── 22 - Second Highest Salary.sql │ ├── 23 - Sending vs Opening Snaps.sql │ ├── 24 - Tweets' Rolling Averages.sql │ ├── 25 - Highest-Grossing Items.sql │ ├── 26 - Top Three Salaries.sql │ ├── 27 - Signup Activation Rate.sql │ ├── 28 - Supercloud Customer.sql │ ├── 29 - Odd and Even Measurements.sql │ ├── 30 - Swapped Food Delivery.sql │ ├── 31 - FAANG Stock Min-Max (Part 1).sql │ ├── 32 - User Shopping Speers.sql │ ├── 33 - Histogram of Users and Purchases.sql │ ├── 34 - Compressed Mode.sql │ ├── 35 - Card Launch Success.sql │ ├── 36 - International Call Percentage.sql │ ├── 37 - Patient Support Analysis (Part 2).sql │ └── Spotify Streaming History.sql └── 3.Hard │ ├── 38 - Active User Retention.sql │ ├── 39 - Y-on-Y Growth Rate.sql │ └── 40 - Maximize Prime Item Inventory.sql ├── HackerRank ├── 1.Basic │ ├── 01 - Revising the Select Query I.sql │ ├── 02 - Revising the Select Query II.sql │ ├── 03 - Select All.sql │ ├── 04 - Select By ID.sql │ ├── 05 - Japanese Cities' Attributes.sql │ ├── 06 - Japanese Cities' Names.sql │ ├── 07 - Weather Observation Station 1.sql │ ├── 08 - Weather Observation Station 3.sql │ ├── 09 - Weather Observation Station 4.sql │ ├── 10 - Weather Observation Station 6.sql │ ├── 11 - Weather Observation Station 7.sql │ ├── 12 - Weather Observation Station 8.sql │ ├── 13 - Weather Observation Station 9.sql │ ├── 14 - Weather Observation Station 10.sql │ ├── 15 - Weather Observation Station 11.sql │ ├── 16 - Weather Observation Station 12.sql │ ├── 17 - Higher than 75 Marks.sql │ ├── 18 - Employee Names.sql │ ├── 19 - Employee Salaries.sql │ ├── 20 - Type of Triangle.sql │ ├── 21 - The PADS.sql │ ├── 22 - Revising Aggregations - The Count Function.sql │ ├── 23 - Revising Aggregations - The Sum Function.sql │ ├── 24 - Revising Aggregations - Averages.sql │ ├── 25 - Average Population.sql │ ├── 26 - Japan Population.sql │ ├── 27 - Population Density Difference.sql │ ├── 28 - The Blunder.sql │ ├── 29 - Top Earners.sql │ ├── 30 - Weather Observation Station 2.sql │ ├── 31 - Weather Observation Station 13.sql │ ├── 32 - Weather Observation Station 14.sql │ ├── 33 - Weather Observation Station 15.sql │ ├── 34 - Weather Observation Station 16.sql │ ├── 35 - Weather Observation Station 17.sql │ ├── 36 - Weather Observation Station 18.sql │ ├── 37 - Weather Observation Station 19.sql │ ├── 38 - Population Census.sql │ ├── 39 - African Cities.sql │ └── 40 - Average Population of Each Continent.sql ├── 2.Intermediate │ ├── 01 - Weather Observation Station 5.sql │ ├── 02 - Binary Tree Nodes.sql │ ├── 03 - New Companies.sql │ ├── 04 - Weather Observation Station 20.sql │ ├── 05 - The Report.sql │ ├── 06 - Top Competitors.sql │ ├── 07 - Ollivander's Inventory.sql │ ├── 08 - Challenges.sql │ ├── 09 - Contest Learderboard.sql │ ├── 10 - SQL Project Planning.sql │ ├── 11 - Placements.sql │ └── 12 - Symmetric Pairs.sql └── 3.Advanced │ ├── 01 - Draw The Triangle 1.sql │ ├── 02 - Draw The Triangle 2.sql │ └── 03 - Print Prime Numbers.sql ├── LICENSE ├── LeetCode ├── 1.Easy │ ├── 1050 - Actors and Directors Who Cooperated At Least Three Times.sql │ ├── 1068 - Product Sales Analysis I.sql │ ├── 1075 - Project Employees I.sql │ ├── 1084 - Sales Analysis III.sql │ ├── 1141 - User Activity for the Past 30 Days I.sql │ ├── 1148 - Article Views I.sql │ ├── 1179 - Reformat Department Table.sql │ ├── 1211 - Queries Quality and Percentage.sql │ ├── 1251 - Average Selling Price.sql │ ├── 1280 - Students and Examinations.sql │ ├── 1327 - List the Products Ordered in a Period.sql │ ├── 1378 - Replace Employee ID With The Unique Identifier.sql │ ├── 1407 - Top Travellers.sql │ ├── 1484 - Group Sold Products By The Date.sql │ ├── 1517 - Find Users With Valid E-Mails.sql │ ├── 1527 - Patients With a Condition.sql │ ├── 1581 - Customer Who Visited but Did Not Make Any Transactions.sql │ ├── 1587 - Bank Account Summary II.sql │ ├── 1633 - Percentage of Users Attended a Contest.sql │ ├── 1661 - Average TIme of Process per Machine.sql │ ├── 1667 - Fix Names in a Table.sql │ ├── 1683 - Invalid Tweets.sql │ ├── 1693 - Daily Leads and Partners.sql │ ├── 1729 - Find Followers Count.sql │ ├── 1731 - The Number of Employees Which Report to Each Employee.sql │ ├── 1741 - Find Total Time Spent by Each Employee.sql │ ├── 175 - Combine Two Tables.sql │ ├── 1757 - Recyclable and Low Fat Products.sql │ ├── 1789 - Primary Department for Each Employee.sql │ ├── 1795 - Rearrange Products Table.sql │ ├── 181 - Employees Earning More Than Their Managers.sql │ ├── 182 - Duplicate Emails.sql │ ├── 183 - Customers Who Never Order.sql │ ├── 1873 - Calculate Special Bonus.sql │ ├── 1890 - The Latest Login in 2020.sql │ ├── 196 - Delete Duplicate Emails.sql │ ├── 1965 - Employees With Missing Information.sql │ ├── 197 - Rising Temperature.sql │ ├── 1978 - Employees Whose Manager Left the Company.sql │ ├── 2356 - Number of Unique Subjects Taught by Each Teacher.sql │ ├── 3436 - Find Valid Emails.sql │ ├── 3465 - Find Products with Valid Serial Numbers.sql │ ├── 3570 - Find Books with No Available Copies.sql │ ├── 511 - Game Play Analysis I.sql │ ├── 577 - Employee Bonus.sql │ ├── 584 - Find Customer Referee.sql │ ├── 586 - Customer Placing the Largest Number of Orders.sql │ ├── 595 - Big Countries.sql │ ├── 596 - Classes With at Least 5 Students.sql │ ├── 607 - Sales Person.sql │ ├── 610 - Triangle Judgement.sql │ ├── 619 - Biggest Single Number.sql │ ├── 620 - Not Boring Movies.sql │ └── 627 - Swap Salary.sql ├── 2.Medium │ ├── 1045 - Customers Who Bought All Products.sql │ ├── 1070 - Product Sales Analysis III.sql │ ├── 1158 - Market Analysis I.sql │ ├── 1164 - Product Price at a Given Date.sql │ ├── 1174 - Immediate Food Delivery II.sql │ ├── 1193 - Monthly Transactions I.sql │ ├── 1204 - Last Person to Fit in the Bus.sql │ ├── 1321 - Restaurant Growth.sql │ ├── 1341 - Movie Rating.sql │ ├── 1393 - Capital Gain | Loss.sql │ ├── 176 - Second Highest Salary.sql │ ├── 177 - Nth Highest Salary.sql │ ├── 178 - Rank Scores.sql │ ├── 180 - Consecutive Numbers.sql │ ├── 184 - Department Highest Salary.sql │ ├── 1907 - Count Salary Categories.sql │ ├── 1934 - Confirmation Rate.sql │ ├── 3220 - Odd and Even Transactions.sql │ ├── 3421 - Find Students Who Improved.sql │ ├── 3475 - DNA Pattern Recognition.sql │ ├── 3497 - Analyze Subscription Conversion.sql │ ├── 550 - Game Play Analysis IV.sql │ ├── 570 - Managers with at Least 5 Direct Reports.sql │ ├── 585 - Investments in 2016.sql │ ├── 602 - Friend Requests II: Who Has the Most Friends.sql │ ├── 608 - Tree Node.sql │ └── 626 - Exchange Seats.sql ├── 3.Hard │ └── 185 - Department Top Three Salaries.sql ├── Introduction to Pandas │ ├── 01 - Create a DataFrame from List.py │ ├── 02 - Get the Size of a DataFrame.py │ ├── 03 - Display the First Three Rows.py │ ├── 04 - Select Data.py │ ├── 05 - Create a New Column.py │ ├── 06 - Drop Duplicate Rows.py │ ├── 07 - Drop Missing Data.py │ ├── 08 - Modify Columns.py │ ├── 09 - Rename Columns.py │ ├── 10 - Change Data Type.py │ ├── 11 - Fill Missing Data.py │ ├── 12 - Reshape Data: Concatenate.py │ ├── 13 - Reshape Data: Pivot.py │ ├── 14 - Reshape Data Melt.py │ └── 15 - Method Chaining.py ├── Pandas │ ├── 1.Easy │ │ ├── 1050 - Actors and Directors Who Cooperated At Least Three Times.py │ │ ├── 1068 - Product Sales Analysis I.py │ │ ├── 1075 - Project Employees I.py │ │ ├── 1084 - Sales Analysis III.py │ │ ├── 1141 - User Activity for the Past 30 Days I.py │ │ ├── 1148 - Article Views I.py │ │ ├── 1179 - Reformat Department Table.py │ │ ├── 1211 - Queries Quality and Percentage.py │ │ ├── 1251 - Average Selling Price.py │ │ ├── 1280 - Students and Examinations.py │ │ ├── 1327 - List the Products Ordered in a Period.py │ │ ├── 1378 - Replace Employee ID With The Unique Identifier.py │ │ ├── 1407 - Top Travellers.py │ │ ├── 1484 - Group Sold Products By The Date.py │ │ ├── 1517 - Find Users With Valid E-Mails.py │ │ ├── 1527 - Patients With a Condition.py │ │ ├── 1581 - Customer Who Visited but Did Not Make Any Transactions.py │ │ ├── 1587 - Bank Account Summary II.py │ │ ├── 1633 - Percentage of Users Attended a Contest.py │ │ ├── 1661 - Average TIme of Process per Machine.py │ │ ├── 1667 - Fix Names in a Table.py │ │ ├── 1683 - Invalid Tweets.py │ │ ├── 1693 - Daily Leads and Partners.py │ │ ├── 1729 - Find Followers Count.py │ │ ├── 1731 - The Number of Employees Which Report to Each Employee.py │ │ ├── 1741 - Find Total Time Spent by Each Employee.py │ │ ├── 175 - Combine Two Tables.py │ │ ├── 1757 - Recyclable and Low Fat Products.py │ │ ├── 1789 - Primary Department for Each Employee.py │ │ ├── 1795 - Rearrange Products Table.py │ │ ├── 181 - Employees Earning More Than Their Managers.py │ │ ├── 182 - Duplicate Emails.py │ │ ├── 183 - Customers Who Never Order.py │ │ ├── 1873 - Calculate Special Bonus.py │ │ ├── 1890 - The Latest Login in 2020.py │ │ ├── 196 - Delete Duplicate Emails.py │ │ ├── 1965 - Employees With Missing Information.py │ │ ├── 197 - Rising Temperature.py │ │ ├── 1978 - Employees Whose Manager Left the Company.py │ │ ├── 2356 - Number of Unique Subjects Taught by Each Teacher.py │ │ ├── 2877 - Create a DataFrame from List.py │ │ ├── 2878 - Get the Size of a DataFrame.py │ │ ├── 2879 - Display the First Three Rows.py │ │ ├── 2880 - Select Data.py │ │ ├── 2881 - Create a New Column.py │ │ ├── 2882 - Drop Duplicate Rows.py │ │ ├── 2883 - Drop Missing Data.py │ │ ├── 2884 - Modify Columns.py │ │ ├── 2885 - Rename Columns.py │ │ ├── 2886 - Change Data Type.py │ │ ├── 2887 - Fill Missing Data.py │ │ ├── 2888 - Reshape Data: Concatenate.py │ │ ├── 2889 - Reshape Data: Pivot.py │ │ ├── 2890 - Reshape Data Melt.py │ │ ├── 2891 - Method Chaining.py │ │ ├── 3436 - Find Valid Emails.py │ │ ├── 3465 - Find Products with Valid Serial Numbers.py │ │ ├── 3570 - Find Books with No Available Copies.py │ │ ├── 511 - Game Play Analysis I.py │ │ ├── 577 - Employee Bonus.py │ │ ├── 584 - Find Customer Referee.py │ │ ├── 586 - Customer Placing the Largest Number of Orders.py │ │ ├── 595 - Big Countries.py │ │ ├── 596 - Classes With at Least 5 Students.py │ │ ├── 607 - Sales Person.py │ │ ├── 610 - Triangle Judgement.py │ │ ├── 619 - Biggest Single Number.py │ │ ├── 620 - Not Boring Movies.py │ │ └── 627 - Swap Salary.py │ └── 2.Medium │ │ ├── 176 - Second Highest Salary.py │ │ ├── 177 - Nth Highest Salary.py │ │ ├── 178 - Rank Scores.py │ │ ├── 180 - Consecutive Numbers.py │ │ └── 184 - Department Highest Salary.py └── SQL50 │ ├── 1. Select │ ├── 1148 - Article Views I.sql │ ├── 1683 - Invalid Tweets.sql │ ├── 1757 - Recyclable and Low Fat Products.sql │ ├── 584 - Find Customer Referee.sql │ └── 595 - Big Countries.sql │ ├── 2. Basic Joins │ ├── 1068 - Product Sales Analysis I.sql │ ├── 1280 - Students and Examinations.sql │ ├── 1378 - Replace Employee ID With The Unique Identifier.sql │ ├── 1581 - Customer Who Visited but Did Not Make Any Transactions.sql │ ├── 1661 - Average TIme of Process per Machine.sql │ ├── 1934 - Confirmation Rate.sql │ ├── 197 - Rising Temperature.sql │ ├── 570 - Managers with at Least 5 Direct Reports.sql │ └── 577 - Employee Bonus.sql │ ├── 3. Basic Aggregate Functions │ ├── 1075 - Project Employees I.sql │ ├── 1174 - Immediate Food Delivery II.sql │ ├── 1193 - Monthly Transactions I.sql │ ├── 1211 - Queries Quality and Percentage.sql │ ├── 1251 - Average Selling Price.sql │ ├── 1633 - Percentage of Users Attended a Contest.sql │ ├── 550 - Game Play Analysis IV.sql │ └── 620 - Not Boring Movies.sql │ ├── 4. Sorting and Grouping │ ├── 1045 - Customers Who Bought All Products.sql │ ├── 1070 - Product Sales Analysis III.sql │ ├── 1141 - User Activity for the Past 30 Days I.sql │ ├── 1729 - Find Followers Count.sql │ ├── 2356 - Number of Unique Subjects Taught by Each Teacher.sql │ ├── 596 - Classes With at Least 5 Students.sql │ └── 619 - Biggest Single Number.sql │ ├── 5. Advanced Select and Joins │ ├── 1164 - Product Price at a Given Date.sql │ ├── 1204 - Last Person to Fit in the Bus.sql │ ├── 1731 - The Number of Employees Which Report to Each Employee.sql │ ├── 1789 - Primary Department for Each Employee.sql │ ├── 180 - Consecutive Numbers.sql │ ├── 1907 - Count Salary Categories.sql │ └── 610 - Triangle Judgement.sql │ ├── 6. Subqueries │ ├── 1321 - Restaurant Growth.sql │ ├── 1341 - Movie Rating.sql │ ├── 185 - Department Top Three Salaries.sql │ ├── 1978 - Employees Whose Manager Left the Company.sql │ ├── 585 - Investments in 2016.sql │ ├── 602 - Friend Requests II: Who Has the Most Friends.sql │ └── 626 - Exchange Seats.sql │ └── 7. Advanced String Functions - Regex - Clause │ ├── 1327 - List the Products Ordered in a Period.sql │ ├── 1484 - Group Sold Products By The Date.sql │ ├── 1517 - Find Users With Valid E-Mails.sql │ ├── 1527 - Patients With a Condition.sql │ ├── 1667 - Fix Names in a Table.sql │ ├── 176 - Second Highest Salary.sql │ └── 196 - Delete Duplicate Emails.sql ├── README.md └── SQL-Practice ├── Hospital_DB ├── 1.Easy │ ├── 01.sql │ ├── 02.sql │ ├── 03.sql │ ├── 04.sql │ ├── 05.sql │ ├── 06.sql │ ├── 07.sql │ ├── 08.sql │ ├── 09.sql │ ├── 10.sql │ ├── 11.sql │ ├── 12.sql │ ├── 13.sql │ ├── 14.sql │ ├── 15.sql │ └── 16.sql ├── 2.Medium │ ├── 01.sql │ ├── 02.sql │ ├── 03.sql │ ├── 04.sql │ ├── 05.sql │ ├── 06.sql │ ├── 07.sql │ ├── 08.sql │ ├── 09.sql │ ├── 10.sql │ ├── 11.sql │ ├── 12.sql │ ├── 13.sql │ ├── 14.sql │ ├── 15.sql │ ├── 16.sql │ ├── 17.sql │ ├── 18.sql │ ├── 19.sql │ ├── 20.sql │ ├── 21.sql │ ├── 22.sql │ ├── 23.sql │ ├── 24.sql │ ├── 25.sql │ └── 26.sql └── 3.Hard │ ├── 01.sql │ ├── 02.sql │ ├── 03.sql │ ├── 04.sql │ ├── 05.sql │ ├── 06.sql │ ├── 07.sql │ ├── 08.sql │ ├── 09.sql │ ├── 10.sql │ └── 11.sql └── Northwind_DB ├── 1.Easy ├── 01.sql ├── 02.sql ├── 03.sql ├── 04.sql ├── 05.sql ├── 06.sql ├── 07.sql ├── 08.sql └── 09.sql ├── 2.Medium ├── 01.sql ├── 02.sql ├── 03.sql └── 04.sql └── 3.Hard ├── 01.sql └── 02.sql /DataLemur/1.Easy/01 - 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