Data Science
Social Sentiment Dashboard
Track opinion on a topic over time, with aspect breakdown
- Python
- Pandas
- Transformers
- Plotly
- +1
Source code · Report · Viva prep
Data science projects are judged on the questions you ask of the data as much as on the code. A strong one starts with a clear question, cleans the data in a way you can justify, and ends with a dashboard that answers the question for someone who has never opened a notebook.
Ready to build
Data Science
Track opinion on a topic over time, with aspect breakdown
Data Science
Statement parsing, auto-categorisation and spend forecasting
Data Science
Forecasts daily case counts with LSTM against classical baselines
Data Science
Explores vaccination progress by country, vaccine and population
Data Science
Classifies fishing behaviour from AIS vessel tracking data
Data Science
Compares a statistical and a deep forecaster on the same stock history
Data Science
Turns an exported chat file into activity stats, word clouds and mood
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Explores decades of US birth records and forecasts daily births
Data Science
Pulls comments via the YouTube Data API and charts audience mood
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A first NumPy and Pandas project on a small, clean dataset
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Forecasts which styles are rising from search and sales history
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Compares Netflix, Prime Video and Hotstar catalogues side by side
Data Science
State-wise unemployment trends and the effect of the COVID lockdown
Data Science
Multivariate LSTM forecasting of energy demand, benchmarked on ARIMA
Data Science
Predicts vehicle CO2 output and charts national emission trends
Data Science
Finds when and where pickups peak across a city
Data Science
RFM scoring and clustering to group shoppers by behaviour
Data Science
State and district crime trends from NCRB data with hotspot maps
Data Science
Density, growth and rank across every country in the world
Data Science
Breaks down Union Budget allocations and how they shift year to year
Data Science
Explores the Forbes list by country, industry, age and source
What you get
These kits include the raw and cleaned data, the analysis notebooks, a forecasting or modelling step with evaluation, and an interactive dashboard, all written up in a report that follows the usual problem, data, method, results and conclusion structure.
Your topic is not in the catalogue yet? We build to your problem statement too.
Ask about a custom buildQuestions
Python with Pandas, NumPy and scikit-learn for analysis, Prophet or statsmodels for forecasting, and Streamlit or Plotly for the dashboard.
It can be, if it goes beyond charts. Adding a predictive model, an evaluation of how good it is and an interactive dashboard turns an analysis into a project.
Yes. Swapping the dataset is covered as a free small change within your support window, as long as it has a similar shape.
Deadline approaching?
Send your abstract, rubric or guidelines document. You get a straight answer on scope, timeline and price within a day — no obligation.