Mini Project
Data Science
Personal Finance Analytics
Statement parsing, auto-categorisation and spend forecasting
- Python
- Pandas
- Prophet
- Streamlit
- +2
₹2,299₹3,999
4.5/198 reviews
Data Science · Mini Project
US Presidents Height Distribution Analysis
A first NumPy and Pandas project on a small, clean dataset
1-2 weeks build
Overview
An introductory analytics kit built around the heights of US presidents. It covers loading a CSV, computing mean, median, spread and percentiles with NumPy, and plotting histograms, box plots and a height-by-order line chart. A short section compares heights with election outcomes and explains why a sample this small cannot support strong conclusions.
What makes it stand up
- 01Descriptive statistics written with NumPy aggregations
- 02Histogram, box plot and KDE of the distribution
- 03Height by presidency order with a rolling average
- 04Simple comparison against election results
- 05Report section on sample size and its limits
Module breakdown
- 01
Loading
Reads the CSV and checks types and missing values.
- 02
Statistics
Mean, median, standard deviation and quartiles.
- 03
Distribution plots
Histogram, box plot and density curve.
- 04
Trends
Heights across presidencies with a rolling mean.
- 05
Interpretation
Notebook write-up of findings and caveats.
After this, you will be able to
- Explain mean versus median and when each misleads
- Read a box plot aloud, including its whiskers and outliers
- Defend why the sample is too small for causal claims
Technology stack
- Python
- NumPy
- Pandas
- Matplotlib
- Seaborn
- Level
- Mini Project
- Domain
- Data Science
- Build time
- 1-2 weeks
- Difficulty
You receive
- Complete, commented source code
- 60-90 page project report (IEEE format)
- Editable presentation deck
- Architecture, ER and UML diagrams
- Local setup and deployment guide
- Sample dataset or seed data
- Viva question bank with answers
- One 45-minute walkthrough call
- 30 days of doubt-clearing support