Fiddling around with DataFusion, pandas, and PyArrow.
Problem # | Title | Difficulty | PyArrow | DataFusion | pandas |
---|---|---|---|---|---|
1757 | Recyclable and Low Fat Products | Easy | ✅ | ❌ | ✅ |
584 | Find Customer Referee | Easy | ✅ | ✅ | ✅ |
595 | Big Countries | Easy | ✅ | ✅ | ✅ |
1148 | Article Views I | Easy | ✅ | ❌ | ✅ |
1683 | Invalid Tweets | Easy | ✅ | ❌ | ✅ |
Problem # | Title | Difficulty | PyArrow | DataFusion | pandas |
---|---|---|---|---|---|
1378 | Replace Employee ID With The Unique Identifier | Easy | ✅ | ✅ | ✅ |
1068 | Product Sales Analysis I | Easy | ✅ | ❌ | ✅ |
1581 | Customer Who Visited but Did Not Make Any Transactions | Easy | ✅ | ❌ | ✅ |
197 | Rising Temperature | Easy | ✅ | ❌ | ✅ |
1661 | Average Time of Process per Machine | Easy | ✅ | ❌ | ✅ |
577 | Employee Bonus | Easy | ✅ | ❌ | ❌ |
1280 | Students and Examinations | Easy | ✅ | ❌ | ❌ |
570 | Managers with at Least 5 Direct Reports | Medium | ✅ | ❌ | ❌ |
1934 | Confirmation Rate | Medium | ✅ | ❌ | ❌ |
Problem # | Title | Difficulty | PyArrow | DataFusion | pandas |
---|---|---|---|---|---|
620 | Not Boring Movies | Easy | ✅ | ✅ | ❌ |
1251 | Average Selling Price | Easy | ✅ | ❌ | ❌ |
1075 | Project Employees I | Easy | ✅ | ❌ | ❌ |
1633 | Percentage of Users Attended a Contest | Easy | ✅ | ❌ | ❌ |
1211 | Queries Quality and Percentage | Easy | ✅ | ❌ | ❌ |
1193 | Monthly Transactions I | Medium | ✅ | ❌ | ❌ |
1174 | Immediate Food Delivery II | Medium | ✅ | ❌ | ❌ |
550 | Game Play Analysis IV | Medium | ✅ | ❌ | ❌ |
Problem # | Title | Difficulty | PyArrow | DataFusion | pandas |
---|---|---|---|---|---|
2356 | Number of Unique Subjects Taught by Each Teacher | Easy | ✅ | ❌ | ❌ |
1141 | User Activity for the Past 30 Days I | Easy | ✅ | ❌ | ❌ |
1070 | Product Sales Analysis III | Medium | ✅ | ❌ | ❌ |
596 | Classes More Than 5 Students | Easy | ✅ | ❌ | ❌ |
1729 | Find Followers Count | Easy | ✅ | ❌ | ❌ |
619 | Biggest Single Number | Easy | ✅ | ❌ | ❌ |
1045 | Customers Who Bought All Products | Medium | ✅ | ❌ | ❌ |
Problem # | Title | Difficulty | PyArrow | DataFusion | pandas |
---|---|---|---|---|---|
1731 | The Number of Employees Which Report to Each Employee | Easy | ✅ | ❌ | ❌ |
1789 | Primary Department for Each Employee | Easy | ✅ | ❌ | ❌ |
610 | Triangle Judgement | Easy | ✅ | ❌ | ❌ |
180 | Consecutive Numbers | Medium | ✅ | ❌ | ✅ |
1164 | Product Price at a Given Date | Medium | ✅ | ❌ | ❌ |
1204 | Last Person to Fit in the Bus | Medium | ✅ | ❌ | ❌ |
1907 | Count Salary Categories | Medium | ✅ | ❌ | ❌ |
Problem # | Title | Difficulty | PyArrow | DataFusion | pandas |
---|---|---|---|---|---|
1978 | Employees Whose Manager Left the Company | Easy | ✅ | ❌ | ❌ |
626 | Exchange Seats | Medium | ✅ | ❌ | ❌ |
1341 | Movie Rating | Medium | ✅ | ❌ | ❌ |
1321 | Restaurant Growth | Medium | ❌ | ✅ | ✅ |
602 | Friend Requests II: Who Has the Most Friends | Medium | ✅ | ❌ | ❌ |
585 | Investments in 2016 | Medium | ✅ | ❌ | ❌ |
185 | Department Top Three Salaries | Hard | ✅ | ❌ | ❌ |
Problem # | Title | Difficulty | PyArrow | DataFusion | pandas |
---|---|---|---|---|---|
1667 | Fix Names in a Table | Easy | ✅ | ❌ | ❌ |
1527 | Patients With a Condition | Easy | ✅ | ❌ | ❌ |
196 | Delete Duplicate Emails | Easy | ✅ | ❌ | ❌ |
176 | Second Highest Salary | Medium | ✅ | ✅ | ✅ |
1484 | Group Sold Products By The Date | Easy | ❌ | ✅ | ❌ |
1327 | List the Products Ordered in a Period | Easy | ✅ | ❌ | ❌ |
1517 | Find Users With Valid E-Mails | Easy | ✅ | ❌ | ❌ |