Data Analytics · Guided project
Placement Data Analysis with SQL and pandas — Guided Project
Analyse a placement dataset with SQL and Python to answer what really drives offers — CGPA, branch, internships or skills — and present it as a short report.
- Intermediate
- ~5 hours
- 5 steps
The brief
Use a public campus placement dataset (or anonymised data from your placement cell, with permission). Load it into MySQL or PostgreSQL and answer questions with SQL, then use pandas for deeper analysis and charts. Be careful to describe relationships honestly — correlation, not causation.
Skills you will use: SQL GROUP BY & window functions · pandas · Charts · Honest interpretation
Build it
Step by step
Tick each step as you finish it. 0 of 5 done.
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Step 1Load the data
Create a table, import the CSV and check row counts, types and missing values.
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Step 2SQL questions
Placement rate by branch, median package by CGPA band, top 3 recruiters per branch using DENSE_RANK.
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Step 3pandas analysis
Compare placed vs not placed on internships, CGPA and certifications; build a pivot table and two charts.
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Step 4Check your claims
For each finding, note sample size and whether another factor could explain it.
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Step 5Report
A notebook or two-page PDF: questions, method, findings with charts, limitations, advice for juniors.
Self-review before you call it done
Tick each point once your project really meets it. These are the things an interviewer will look for.
Check all 4 points, then mark the project as finished.
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