Day 14✅Of 100DaysOfSQL challenges
Wrote a SQL query that filters hackers by challenge count.
Keeps those with the highest count
Keeps those with a unique count
Removes repeated non-max counts
Nested logic + CTE = brain workout 😅
#SQL#100DaysOfSQL#DataSkills
Day 12✅ Of 100DaysOfSQL challenge
Solved yet another question of Basic joins.
Challenge :Mask names for grade<8,sort by grade desc ,then name or marks based on grade.
#SQL#DataCommunity#100DaysOfSQL
Day 10✅ Of 100DaysOfSQL challenge
Today I solved an interesting question , Find the median of the lat_n column that divides the data into 2 halves . I have explored row_number(),over(), and subquery .
If you are into data field let's connect.
#DataCommunity#SQL#100DaysOfSQL
Day 9✅ Of 100DaysOfSQL challenge
😥Missed posts few days due my college project submission crunch, but the streak lives on!
Today’s challenge: mastering Aggregation .
Let’s keep pushing!
#SQL#DataChallenge
Day ✅8 Of 100DaysOfSQL challenges
Today I solved a sql question on basic aggregation ,calculated the amount of error and round up to the next integer.
#SQL#DataCommunity#100DaysOfCode
Day ✅6 & 7Of 100DaysOfSQL challenge
Solved a binary tree node challenge using advanced SELECT logic.
Practiced basic aggregation (SUM) today.
Learning daily, posting consistently—even if a day late 😉
#SQLChallenge#DataJourney#DataCommunity
Day✅5 of 100DaysOfSQL challenge! Just solved an advanced select problem on Had to generate 2 result sets:
1) alphabetized list of names with profession's 1st letter in parentheses.
2) occupation counts in ascending order, formatted with a twist!
#SQL#DataCommunity#SkilledUp
Day✅4 Of 100 DaysOfSQL challenge
Tackeled yet another advanced sql query .Arrange the same occupation people in same column
Approach
CTE → assigns a row number to each name within their occupation.
MAX(CASE) → pivots those rows into columns, grouping them by row number. #SQL
Day 2✅ Of 100 DaysOfSQL challenges
Today I explored JOIN, GROUP BY, and COUNT(DISTINCT) to summarize company-wise employee hierarchy. Used MAX(founder) to safely pull non-grouped data.
#SQL#Data#Datacommunity #100DaysOfSQL
Day ✅1 of 100 DaysOfSQL
Started with basic select exploring filtering with WHERE ,sorting with ORDER by and REGEXP for pattern matching
#DataEnthusiast#SQL
Hey guys I am starting #100DaysOfSQL today! 🎯
Why?
To sharpen my skills, share insights, and connect with fellow data enthusiasts. Expect dashboards, dry-run logic, query breakdowns, and real-world use cases.
Let’s make SQL storytelling fun. Join me? #DataCommunity#SQL
Hello everyone 👋,
Sharing my recent project where I explored e-commerce churn data. I used Python (pandas) for EDA and then built an interactive Power BI dashboard.
Dataset: Kaggle
Tools: Python, Power BI
#DataAnalytics#PowerBI#Python#EDA#ChurnAnalysis
160GFG Challenge Completed✅
What started as a challenge became a habit—160 days of problem-solving, debugging, and leveling up my DSA skills!
Thank you @geeksforgeeks .
#160gfgchallenge#womenintech
Day 160✅Of 160gfg Challenge
Problem-Unique Number II
Approach-Similar to the Unique Number I problem,in todays problem just store the answer in array, sort the answer array and return it.
#160gfgchallenge@geeksforgeeks#womenintech
Day 159✅Of 160gfg Challenge
Problem-Unique Number I
Approach-Create a HashMap and track the occurence of each element . The element in map whose value ==1 return that element.
#160gfgchallenge@geeksforgeeks#womenintech
Day 158✅Of 160gfg Challenge
Problem-Missing in Array
Approach-Sort the Array, traverse the array and check if arr[i]!=i+1 return i+1, else if(i==n-1) return arr[i]+1.
#160gfgchallenge@geeksforgeeks#womenintech
Day 157✅Of 160gfg Challenge
Problem-Find Only Repetitive Elements
Approach-Use the hashmap to store the Occurences of the element . Then traverse through the map if the occurence of element is greater than 1 return that element
#160gfgchallenge@geeksforgeeks#womenintech
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