Assessfy Pvt. Ltd Beginner 5 milestones 100 marks

COVID-19 Time-Series Dashboard for Indian States

Target year: SE Sem 3-4 (Mini-Project-I) AICTE: 2 credits · ~50 hrs Bloom: Apply MU CBCS: DS403 Mini-Project 1A/1B

Real-world project · AICTE-aligned · AI-graded · Audit-ready certificate

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About this project

Pull 3 years of COVID-19 case + vaccination data from MoHFW/data.gov.in, clean + transform, build an interactive Streamlit dashboard with state-level comparisons, top-10 rankings, and a moving-average smoothing toggle. Cite data sources + freshness.

Course Learning Outcomes (CLOs):
CLO1: Apply data-wrangling techniques to messy government open data.
CLO2: Compute moving averages + percent-change + per-million normalization.
CLO3: Build an interactive dashboard with multiple linked filters.
CLO4: Cite + acknowledge public datasets correctly.

Industry/societal relevance: Indian govt + WHO + state health depts continually hire data analysts; foundational project for public-health-data roles.

Milestones

1. Data Acquisition + Cleaning

15 marks 5d

Pull CSVs from data.gov.in. Handle missing + duplicate state codes. Reshape long-vs-wide.

2. EDA + Insights

20 marks 10d

Plot state-wise peaks, vaccination coverage, deaths-per-million. Document 3 surprising findings.

3. Streamlit Multi-View

25 marks 14d

State multiselect, date range slider, metric toggle (cases / deaths / vaccinations). Linked plots.

4. Smoothing + Comparison

20 marks 10d

7-day + 28-day moving averages. Top-10 by metric. State A vs State B overlay.

5. Deploy + Report

20 marks 11d

Deploy on Streamlit Cloud. Submit live URL + 6-page report with screenshots + data-source citations.

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Skills you'll learn

Python (Pandas)Data cleaningTime-series visualizationStreamlitPublic open dataData citation hygiene

Tools used

Python 3.11PandasPlotlyStreamlitMoHFW + covid19india.org datasetsGitHub

Prerequisites

Python basics; intro statistics; spreadsheet experience

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COVID-19 Time-Series Dashboard for Indian States

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