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Python and SQL

SQL I

Day 1

595. Big Countries
596. Recyclable and Low Fat Products
597. Find Customer Referee
598. Customers Who Never Order

Day 2

1873. Calculate Special Bonus
1874. Swap Salary
1875. Delete Duplicate Emails

Day 3

1667. Fix Names in a Table
1668. Group Sold Products By The Date
1669. Patients With a Condition

Day 4

1965. Employees With Missing Information
1966. Rearrange Products Table
1967. Tree Node
1968. Second Highest Salary

Day 5

175. Combine Two Tables
176. Customer Who Visited but Did Not Make Any Transactions
177. Article Views I

Day 6

197. Rising Temperature
198. Sales Person

Day 7

1141. User Activity for the Past 30 Days I
1142. Daily Leads and Partners
1143. Find Followers Count

Day 8

586. Customer Placing the Largest Number of Orders
587. Game Play Analysis I
588. The Latest Login in 2020
589. Find Total Time Spent by Each Employee

Day 9

1393. Capital Gain/Loss
1394. Top Travellers
1395. Market Analysis I

Day 10

182. Duplicate Emails
183. Actors and Directors Who Cooperated At Least Three Times
184. Bank Account Summary II
185. Sales Analysis III

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