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- 1. Get the actors
- 2. Get list of actors names
- 3. Get an ordered list of movies
- 4. Get the first 10 movies in alphabetical order
- 5. Get films list third page
- 6. Get a list of movies sorted by multiple fields
- 7. Get the longest movie
- 8. Find long movies
- 9. Find long comedies
- 10. Classic movies
- 11. Find the actors by name
- 12. Find duplicate actor names
- 13. Find the most popular surname among actors
- 14. Get the languages list
- 15. Get the ordered list of languages
- 16. Get the sorted list of films with limit
- 17. Find stuff members by condition
- 18. Get the sorted list of films with condition
- 19. Find clients starting with the letter "A"
- 20. Find clients starting with the letter "A" (2)
- 21. Find customers full names
- 22. Find addresses using sub-query
- 23. Find addresses using JOIN
- 24. Find all the actors in the film
- 25. Find all films of an actor
- 26. Find clients who rented the film
- 27. Find all films where HENRY BERRY did not participate
- 28. Find the number of films in which the actor took part
- 29. Find actors more popular than HENRY BERRY
- 30. Find the distribution of films by category
- 31. Find the average length of a movie
- 32. Find minimum, maximum and average film duration
- 33. Find long movie categories
- 34. Find the minimal and maximal film rental cost
- 35. Find company stores details
- 36. Average film rental duration for each customer
- 37. Find the average length of a movie by category
- 38. The average cost of renting a movie by category
- 39. Find sad actors
- 40. Find the most diverse actors
- 41. Analyze monthly payment
- 42. Find the best month
- 43. Find the films never been rented
- 44. Find the most popular film
- 45. Analyze rental data for film
- 46. Find customers who did not return rented discs
- 47. Find average daily film rentals
- 48. Calculate daily income for the month
- 49. Find movie distribution by store
- 50. Find the distribution of customer activity
- 51. Find movie popularity rating
- 52. Quarterly earnings analysis
- 53. Find the countries with the most customers
- 54. Find film names by description
- 55. Find most active customers
- 56. Generate dates table
- 57. Calculate the number of days off in a month
- 58. Calculate factorial
- 59. Find the distribution by categories
- 60. Find the average client activity time
- 61. Find the average revenue
- 62. Find the store average revenue
- 63. Analyze monthly payments (2)
- 64. Calculate the area of a circle
- 65. Calculate circle perimeter
- 66. Find customer details
- 67. Find EMILY DEE fans
- 68. Clients who are not familiar with EMILY DEE films
- 69. Find the count of rented disks
- 70. Find the number of returns
- 71. Disc rental and return statistics
- 72. Find active customers
- 73. Find the least popular movies
- 74. Find the top spending customers
- 75. Find films with no available inventory
- 76. Find languages not represented in films
- 77. Find movies that have never been rented
- 78. Find movies with above-average rental rates
- 79. Find clients with a high number of rentals
- 80. Find movies with the highest replacement cost
- 81. Find movies with the highest replacement cost
- 82. Count the rental delays
- 83. Calculate the percentage of delays
- 84. Get movie cast lists
- 85. Extract address and domain from email
- 86. Get a list of actors - namesakes
- 87. Get a list of movies and their categories
- 88. Find film average rental time
- 89. Find movies with rental time below average
- 90. Movie rental prices by category
- 91. Get rolling payment amounts
- 92. Find the number of films in each category
- 93. Get list of clients
- 94. Analyze customer payments
- 95. Get a list of movie ratings
- 96. Find the most diverse clients
- 97. Find acting duets
- 98. Find film distribution
- 99. Find films that were out of stock
- 100. Payments analyze
- 101. Improve payments analyze
- 102. Get list of tables
- 103. Get table columns data
- 104. Get list of indexes
- 105. Distribution of clients by weekday
- 106. Find the distribution of clients by time of day
- 107. Improve distribution of clients by weekday
- 108. Movies without cast records
- 109. Movies without actors records
- 110. Find all the actors in the film
- 111. Find all actors never starred in adult only films
- 112. Analyze weekly rentals
- 113. Average rentals count
- 114. Find repeat rentals
- 115. Find the Horror films fans
- 116. Find the distribution of clients by country
- 117. Get the restricted films list
- 118. Get list of restricted films
- 119. Find never been delayed films
- 120. Find most delayed films
- 121. Create department table
- 122. Find adult only films about Database Administrator
- 123. Find films about Dogs or Cats
- 124. Clients whose first name is the last name of another client
- 125. Find clients who have met each other
- 126. Customers with matching name initials
- 127. Create new address record
- 128. Update the postal code
- 129. Update Canadian postal codes
- 130. Enter Woodridge postal code
- 131. Enter new staff record
- 132. Create customer addresses view
- 133. Find movies available in one store only
- 134. Find movies with no available copies
- 135. Staff performance analysis
- 136. Distribution of films by categories in JSON format
- 137. Generate a list of movies in JSON format
- 138. Remove customer records
- 139. Find addresses without postal code
- 140. Find an addresses with even postal codes
- 141. Category popularity analysis
- 142. Generate monthly bill
- 143. Build a overal email list
- 144. Build shared surnames list
- 145. Select clients without the letter "A"
- 146. Alter the staff table
- 147. Gap & Islands problem
- 148. Find customers who sow same films
- 149. Find films in several categories
- 150. Find last names with double letters
- 151. Analysis of the cost of film rental by category
- 152. Find rented films
- 153. Find films to share
- 154. Film distribution by category and store
- 155. Delete films records
- 1. Get airports data
- 2. Get a list of airports
- 3. Find long-range aircraft
- 4. Find Boeing aircraft
- 5. Get flights departed from Domodedovo
- 6. Get a list of aircraft from Domodedovo
- 7. Aircraft usage analysis
- 8. Find the aircraft without Business class
- 9. Get counts of seats by class
- 10. Get rows and seats count
- 11. Calculate the number of seats on flight
- 12. Get the list of destination airports
- 13. Get a list of airports with direct connections
- 14. Get a list of airports without direct connections
- 15. Get a list of no-show passengers
- 16. Get a list of passengers
- 17. Find the flight delay
- 18. Get flights statistics
- 19. Rate airports
- 20. Find a list of flight options
- 21. Find the fastest flight
- 22. Calculate the daily number of flights
- 23. Obtain a list of passengers
- 24. Find average flight occupancy
- 25. Find flight occupancy by fare
- 26. Get list of tables
- 27. Get information about the columns
- 28. Airports with one-way departures
- 29. Find airports relations
- 30. Find small airports
- 31. Get the passenger list
- 32. Get aircraft seat map
- 33. FInd the plane coordinates
- 34. Get a list of planes in the air
- 35. FInd the planes coordinates
- 36. Display a table of airports
- 37. Count departing passengers
- 38. Number of passengers with total
- 39. Display a table of departures
- 40. Get a list of airports with more than one direct flight
- 41. Distribution of flights by days of the week
- 42. Get list of tables (PostgreSQL)
- 1. Display a list of departments
- 2. Find non-Dollar/Euro countries
- 3. Show a sub-departments list (JOIN)
- 4. Get a list of sub-departments
- 5. Find foreign employees
- 6. Find employees by department
- 7. Find employee salary
- 8. Find employees with high salaries
- 9. Find employees with a salary above average
- 10. Find the department
- 11. Find employees works on the project
- 12. Staff availability report
- 13. Create a phonebook
- 14. Find all customers with unshipped orders
- 15. Find the number of employees
- 16. Find highly paid employees
- 17. Find employees by hire date
- 18. Get list of highly paid employees
- 19. Find highly paid employees
- 20. Reduced salaries
- 21. Find valuable employees
- 22. Find the salary ratio
- 23. Create a salary rating
- 24. Jobs without specific requirements
- 25. Orders shipped in the following month
- 26. Update project information
- 27. Find the median salary
- 28. Managed by Robert Nelson
- 29. Delete employee records
- 1. Product List
- 2. Filtered list of products
- 3. Ten heaviest products
- 4. Get list of tables (SQL Server)
- 5. Find customers with even numbers
- 6. Find customers by phone prefix
- 7. Find duplicate phone numbers
- 8. Get unique customers list
- 9. Get product category color counts
- 10. Top states by population
- 11. List of subcategories
- 12. List of categories
- 13. Root categories list
- 14. Subcategories count
- 15. Prepare mailing list
- 1. Sort the penguins
- 2. Find light weight penguins
- 3. Penguins list
- 4. Distribution penguins by islands
- 5. Find small penguins
- 6. Find small penguins species
- 7. Find small penguins species
- 8. Search by pattern
- 9. Flipper length to body mass rate
- 10. Penguins whose sex is unknown
- 11. Heavy chinstrap penguins
- 12. Penguins with absent data
- 13. Penguins and Islands
- 14. Count the penguins
- 15. Island with the minimum penguins mass
- 16. The most populated island
- 17. Penguins stats
- 18. Penguins stats table
- 19. Common penguin species
- 20. Delete records
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Write a SQL query to select the sex and body_mass_g columns from the little_penguins table, sorted so that penguins with the largest body mass are displayed first.
Use SQLite syntax to write your answer. Descriptions of tables are provided in the right pane.
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Querynomicon (SQLite)
A compact database for learning the basics of SQL.The Querynomicon database contains tables:
little_penguins - table of little penguins.
- speciesPenguin species.
- islandIsland of residence.
- bill_length_mmBill length, mm.
- bill_depth_mmBill depth, mm.
- flipper_length_mmFlipper length, mm.
- body_mass_gBody mass, g.
- sexSex.
| species | island | bill_length_mm | bill_depth_mm | flipper_length_mm | body_mass_g | sex |
|---|---|---|---|---|---|---|
| Gentoo | Biscoe | 52.1 | 17 | 230 | 5550 | MALE |
penguins - table of penguins.
- speciesPenguin species.
- islandIsland of residence.
- bill_length_mmBill length, mm.
- bill_depth_mmBill depth, mm.
- flipper_length_mmFlipper length, mm.
- body_mass_gBody mass, g.
- sexSex.
| species | island | bill_length_mm | bill_depth_mm | flipper_length_mm | body_mass_g | sex |
|---|---|---|---|---|---|---|
| Gentoo | Biscoe | 52.1 | 17 | 230 | 5550 | MALE |
staff - table of employees.
- identEmployee number.
- personalEmployee first name.
- familyEmployee last name.
- deptDepartment.
- ageAge.
| ident | personal | family | dept | age |
|---|---|---|---|---|
| 7 | Abram | Chokshi | gen | 23 |