Good Python data projects clean a real file, ask one question and answer it with a chart and a number: tidy a Netflix or HR dataset, analyse retail sales, study NSE prices or air quality, query SQLite from Python and scrape a practice site politely. Write the cleaning rules in your README.
Each idea uses a free dataset or practice site. Pair them with the data analytics projects for the SQL and dashboard side.
- 1Loadread, inspect, dtypes
- 2Cleanmissing, duplicates, types
- 3Exploregroupby, plots, tests
- 4Explainone chart, one number
- 5Sharenotebook plus README
Cleaning and exploration
Netflix titles cleaning and insights
Beginnerpandas
DataKaggle Netflix Movies and TV Shows
Stand-outDocumented rules for missing directors and mixed date formats
Messy HR CSV cleanup
Beginnerpandas
DataA messy CSV you build or download
Stand-outA cleaning log listing every rule and rows affected
Tips dataset visualisation
Beginnerpandas, seaborn
Dataseaborn tips dataset
Stand-outOne chart per question, each titled with its finding
Pharma sales analysis
Beginnerpandas, matplotlib
DataKaggle pharma sales data
Stand-outSeasonality and a stocking recommendation
Online retail analysis
Intermediatepandas
DataUCI Online Retail II
Stand-outCancellations handled explicitly and customer value tiers
IPL or cricket statistics explorer
Beginnerpandas
DataPublic IPL datasets on Kaggle
Stand-outA selection recommendation backed by numbers
Time series and finance
NSE stock price analysis
Intermediatepandas, yfinance
DataPublic price history (check usage terms)
Stand-outRolling returns, drawdowns and honest limits
Air-quality trends for Indian cities
Intermediatepandas
DataCPCB data via data.gov.in or Kaggle
Stand-outSeasonality with documented handling of missing readings
Vehicle sales over time
Intermediatepandas
DataKaggle vehicle sales data
Stand-outYear-over-year growth with holiday effects explained
Daily weather pipeline into SQLite
IntermediatePython, SQLite, cron
DataOpen-Meteo (free, no key)
Stand-outRuns on a schedule and survives API failures
SQL, scraping and sharing
Business questions with SQLite and Python
Beginnersqlite3, pandas
DataChinook sample database
Stand-outEvery answer as a function with a test
Book price scraper
Beginnerrequests, BeautifulSoup
Databooks.toscrape.com (made for practice)
Stand-outRespects robots.txt and rate limits; stores results in CSV
Fake jobs board scraper
Beginnerrequests, BeautifulSoup
Datarealpython.github.io/fake-jobs (practice site)
Stand-outCleaned output and a skills frequency chart
Music trends explorer
Beginnerpandas
DataKaggle Spotify datasets
Stand-outFeature-to-popularity analysis with caveats
Turn any idea into a portfolio piece
- Pick one idea and write the one-line goal first.
- Build the smallest version that works end to end.
- Add tests for the rules that could silently break.
- Deploy it so there is a live link or a one-command run.
- Write the README: what it does, how to run it, one number, one limit.
Frequently asked questions
What Python data analysis projects should I build?
One cleaning project, one exploratory analysis with charts, one time-series study and one SQL-plus-Python project.
Where can I find datasets for Python projects?
See free datasets for projects: Kaggle, UCI, data.gov.in and Hugging Face.
Is web scraping legal for projects?
Scrape only practice sites or pages whose terms allow it, respect robots.txt and rate limits, and never collect personal data.
How do I present a data analysis project?
One question, the cleaning rules, one chart, one number and the limits, in a notebook with a README.
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