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Project overview
In this project, you’ll take on the role of a data analyst tasked with exploring a dataset on westbound traffic on the I-94 Interstate highway. Applying skills in exploratory data visualization using Python libraries like pandas, Matplotlib, and Seaborn, you’ll analyze traffic volume data recorded by a station midway between Minneapolis and Saint Paul.
Your objective is to determine key indicators of heavy traffic on I-94, which could include weather type, time of day, or day of the week. By examining traffic volume patterns across various conditions, you’ll uncover insights to characterize peak congestion times on this busy highway. This project will strengthen your ability to combine and apply data visualization techniques to extract meaningful findings from real-world data.
Objective: Use exploratory data visualization to identify the primary factors contributing to heavy westbound traffic on I-94 based on weather, time, and day of week indicators.
Key skill required
To complete this project, it's recommended to build these foundational skills in Python
- Plotting various graph types using the Matplotlib library
- Visualizing and interpreting time series, correlations, and frequency distributions
- Generating and comparing graphs using pandas and grid charts
- Building relational plots using seaborn to represent multiple variables
Projects steps
Step 1: The I-94 Traffic Dataset
Step 2: Analyzing Traffic Volume
Step 3: Traffic Volume: Day vs. Night
Step 4: Traffic Volume: Day vs. Night (II)
Step 5: Time Indicators
Step 6: Time Indicators (II)
Step 7: Time Indicators (III)
Step 8: Weather Indicators
Step 9: Weather Types
Step 10: Next Steps
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