This guide will walk you through the process of running scripts and updating the CSV data model for EVs in Australia, along with additional resources for understanding the EV adoption trends and charging infrastructure.
- Data Source: Fuel Economy Data
- Script: Download the provided Python script and run it to fetch the EV data for Australia.
- Command to run:
python3 get_ev_list_australia.py
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Use the sales data (by model, etc.) to find the most popular EVs and add this information to the CSV/Data Model for each vehicle type.
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Run the following scripts:
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EV Sales Analysis: Split by AC & DC charging
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Sales by type of EV & Charging Infrastructure:
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- Add the connector type (plug type) for each vehicle to the CSV Data Model.
- You may need to use tools like co-pilot or other sources to gather these details into a list.
- The final CSV model should include both current fields and new fields for each vehicle type.
Current fields (these may need renaming to match the existing schema):
_id,model_release_year,make,model,variant,fuel_type,energy_consumption_whkm,electric_range_km
New fields to include:
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battery_capacity_kwh: Total capacity of the vehicle's battery (kWh) -
charge_rate_acceptance_kw: Maximum rate at which the vehicle can accept a charge (kW) -
charger_power_output_kw: The power output capacity of the charger (kW) -
charger_type: Type of charger (AC/DC) -
efficiency: Charging efficiency (%) -
desired_charge_level_kwh: Target charge level (kWh) -
Example usage:
battery_capacity_kwh = 75 # kWh current_battery_level_kwh = 20 # kWh charge_rate_acceptance_kw = 50 # kW charger_power_output_kw = 100 # kW charger_type = "DC" # AC or DC efficiency = 90 # % desired_charge_level_kwh = 60 # kWh
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Fields for vehicle types:
ac_v2g: "no"dc_v2g: "no"
- Once the CSV Data Model is updated, use it to create PowerBI dashboards.
- This step will need to be done manually using PowerBI's interface.
- After the new fields are added, update the documentation to reflect the changes in the data model and ensure consistency.
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GitHub Repository: EVAT-Data-Science - Personal Work (John Collins)
- This repository contains various scripts and data models used for EV adoption and sales analysis.
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Onboarding Pack: The onboarding video contains additional information. It is highly recommended to watch the video to understand what was presented last trimester.
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Interactive Map: There is a useful map relating to EV charging stations, which can be compared to the data in the video.
- Map: Interactive: EV Charging Stations Across the U.S. Mapped
- Action: Compare this map to the data in the PowerPoint presentation to gain insights on the location and availability of charging stations across the U.S
- Project Dashboard: Access the ON TRACK SUBMISSION LINK for the latest updates on the EV analysis and project progress.
The final CSV data model should include detailed information about each EV, including its make, model, charging details, and connector type.
By following these steps, you'll be able to update the EV data model and develop comprehensive insights for EV adoption trends and infrastructure in Australia and beyond.