How to use the Practice Datasets for Data Analysis
- 1. Pick a datasetRetail sales, HR, student marks, e-commerce orders or daily website traffic.
- 2. Set size and seedChoose rows, a seed number, and whether to add messy values to clean.
- 3. Download and analyseGet the CSV with a preview and practice questions to try.
What is in each dataset
- Retail sales: order date, region, product, category, price, quantity, discount, total and payment mode. Good for pivots, SUMIFS and monthly trends.
- Employees (HR): department, city, join date, experience, CTC, rating and whether they left. Good for attrition analysis.
- Student marks: attendance, study hours and four subject scores. Good for correlation and pass-rate questions.
- E-commerce orders: order value, delivery days, status, traffic source and rating. Good for return-rate and funnel questions.
- Website traffic: daily sessions, users, bounce rate and conversions for a year from 1 January 2025. Good for time series.
Each dataset comes with four questions to answer, so you practise thinking like an analyst, not just clicking.
Honest note and worked example
This data is synthetic. It is made in your browser by a seeded random generator with simple built-in relationships, such as CTC rising with experience or ratings dropping with slow delivery. It is not real company, customer or student data, and you should not quote it as facts.
Worked example: choose Retail sales, 500 rows and seed 42 and you get a file named sales-500-rows-seed42.csv with 500 rows × 10 columns. Anyone who uses the same three settings gets exactly the same file, so a teacher can give a whole class one dataset by sharing the seed.
Tick messy data to practise cleaning. About 2% of rows are duplicated, about 4% of rows get a blank cell, and some text gets extra spaces and capital letters. Clean it with TRIM, Remove Duplicates and filters in Excel, or with drop_duplicates() and fillna() in pandas, before you analyse.
Frequently asked questions
Is this real data?
No. It is realistic-looking synthetic data made for practice. Use public data portals when you need real figures.
Can I use it in a portfolio project?
Yes, as long as you say it is synthetic practice data. Real public datasets impress recruiters more for final portfolio pieces.
Which tools can open the CSV?
Excel, Google Sheets, Power BI, Tableau, SQL databases and Python pandas all read it directly.
Are the datasets free?
Yes, all free. Generating your first dataset asks for your name and WhatsApp number once. After that, every download and every Uncodemy tool opens without the form.