Truck Speed Data Analysis Challenge
Budget: $25 – $50 USD
I’m looking for the sharpest analytical mind to dive into a set of truck-speed readings and surface clear, data-driven insights. This is a straight data analysis contest—no simulations, no lengthy theoretical papers—just solid, evidence-based findings that reveal how these trucks really move.
What you’ll receive from me
• A CSV file containing timestamped speed logs for a fleet of trucks (columns: TruckID, Time, GPS_Lat, GPS_Lon, Speed_kph).
• A short note outlining collection conditions and any known anomalies.
What I expect in your submission
1. Clean, well-documented analysis code (Python, R or MATLAB are all fine—use pandas, NumPy, ggplot, seaborn or similar as you prefer).
2. A concise report (PDF or Jupyter Notebook) that includes:
• Key descriptive stats (mean, median, max, percentiles) for overall and per-truck speeds.
• Identification of outliers or speed-limit violations, with brief commentary on possible causes.
• Clear visualisations—at minimum a distribution plot, a time-series sample, and a heat map or equivalent showing speed versus location.
• Actionable recommendations (e.g., route optimisation, safety advisories) grounded in your findings.
Winning criteria
• Accuracy and clarity of insights.
• Quality and readability of code.
• Visual impact and interpretability of charts.
• Practical value of recommendations.
Keep the report focused—no filler—just data cleaning, analysis, visuals, and takeaways. Impress me with sharp thinking and clean presentation, and the prize is yours.
What you’ll receive from me
• A CSV file containing timestamped speed logs for a fleet of trucks (columns: TruckID, Time, GPS_Lat, GPS_Lon, Speed_kph).
• A short note outlining collection conditions and any known anomalies.
What I expect in your submission
1. Clean, well-documented analysis code (Python, R or MATLAB are all fine—use pandas, NumPy, ggplot, seaborn or similar as you prefer).
2. A concise report (PDF or Jupyter Notebook) that includes:
• Key descriptive stats (mean, median, max, percentiles) for overall and per-truck speeds.
• Identification of outliers or speed-limit violations, with brief commentary on possible causes.
• Clear visualisations—at minimum a distribution plot, a time-series sample, and a heat map or equivalent showing speed versus location.
• Actionable recommendations (e.g., route optimisation, safety advisories) grounded in your findings.
Winning criteria
• Accuracy and clarity of insights.
• Quality and readability of code.
• Visual impact and interpretability of charts.
• Practical value of recommendations.
Keep the report focused—no filler—just data cleaning, analysis, visuals, and takeaways. Impress me with sharp thinking and clean presentation, and the prize is yours.