Tracks/Strings and dates
Strings and dates
LIKE, EXTRACT, and everyday text/date helpers.
string functions
date functions
EXTRACT
LIKE
BETWEEN
0/77 solved
- 1—008. Employees Hired After 2022easy
- 2—018. Customer Name Searcheasy
- 3—019. Orders in a Price Rangeeasy
- 4—022. Uppercase Product Nameseasy
- 5—023. Extract Order Yeareasy
- 6—030. Monthly Order Counteasy
- 7—101. String Length Functioneasy
- 8—102. UPPER and LOWER String Functionseasy
- 9—103. Trim Leading and Trailing Whitespaceeasy
- 10—104. Concatenate First and Last Nameeasy
- 11—105. Extract Category Code from SKUeasy
- 12—106. Replace Words in Review Texteasy
- 13—107. Filter Orders by Dateeasy
- 14—108. Extract Year from Hire Dateeasy
- 15—109. Find Orders Placed in Septembereasy
- 16—110. Calculate Project Duration in Dayseasy
- 17—120. Filter Employees by Salary Rangeeasy
- 18—123. Find Gmail Customers Using LIKEeasy
- 19—124. Match Employee Codes with _ Wildcardeasy
- 20—125. Find Products NOT Starting with Seasy
- 21—131. Most Recent Hire Date per Departmenteasy
- 22—132. First Product Name Alphabetically per Categoryeasy
- 23—153. Group Orders by Month Using DATE_TRUNCeasy
- 24—154. Find Active Subscriptions After a Dateeasy
- 25—155. Pad Invoice Numbers with LPADeasy
- 26—156. Reverse Strings and Detect Palindromeseasy
- 27—157. Find the Position of @ in Email Addresseseasy
- 28—158. CHAR_LENGTH vs LENGTH on Messageseasy
- 29—305. Extract Day of Week from Order Dateeasy
- 30—308. Products Whose Name Starts with 'A'easy
- 31—310. Filter Orders by a Specific Dateeasy
- 32—314. Customers with Long Nameseasy
- 33—315. Uppercase Product Nameseasy
- 34—318. Count Orders Grouped by Year and Montheasy
- 35—319. Orders in a Date Range (BETWEEN)easy
- 36—324. Format Order IDs with Zero-Paddingeasy
- 37—042. Combined List: Employees and Customers Named Alexmedium
- 38—046. Month-over-Month Revenue Changemedium
- 39—047. Preview Next Month Revenue with LEADmedium
- 40—054. Year-over-Year Order Revenue Growthmedium
- 41—057. Employee Tenure in Full Yearsmedium
- 42—058. Monthly New Customer Signupsmedium
- 43—067. Extract Email Domainmedium
- 44—069. 7-Day Rolling Active Usersmedium
- 45—073. Orders from Last Quartermedium
- 46—074. Products per Category as Comma-Separated Listmedium
- 47—075. Average Days Between Customer Ordersmedium
- 48—076. Monthly Order Completion Ratemedium
- 49—079. Customer Cohort by First Order Monthmedium
- 50—080. 3-Month Moving Average Revenuemedium
- 51—082. Retained Customers: Ordered in Both Month 1 and Month 2medium
- 52—088. Fulfilled Orders Percentage per Monthmedium
- 53—090. Customers Who Ordered Every Month of 2026medium
- 54—184. Comma-Separated Employee List Per Departmentmedium
- 55—187. Filter Users by Email Pattern Using REGEXPmedium
- 56—188. Extract Email Domain Using SPLIT_PARTmedium
- 57—189. Subscription Expiry and Days Remainingmedium
- 58—190. Fill Date Gaps Using GENERATE_SERIESmedium
- 59—205. Weekly Sales Totals Using DATE_TRUNCmedium
- 60—240. Aggregate Orders by Weekday vs Weekendmedium
- 61—241. Count Orders by Hour of Daymedium
- 62—244. Email Domain Frequency Analysismedium
- 63—245. Phone Number Format Validation with SIMILAR TOmedium
- 64—265. Month-End Date Calculationmedium
- 65—266. Assign Sales to Fiscal Year Quartersmedium
- 66—267. Count Business Days Between Two Datesmedium
- 67—268. Calculate Age in Years from Birthdatemedium
- 68—338. Total Revenue by Day of Weekmedium
- 69—342. Customer Order Gap Alert (30–60 Days)medium
- 70—344. Top Salesperson Each Quartermedium
- 71—359. Region × Quarter Revenue Pivot Matrixmedium
- 72—370. Peak Order Hour per Daymedium
- 73—092. Longest Consecutive Login Streakhard
- 74—095. Session Identification from Login Eventshard
- 75—096. Churned vs Retained Customershard
- 76—097. Cohort Retention Matrix (Months 0–3)hard
- 77—298. String Parsing: Extract Structured Data from Concatenated Fieldhard