Model Carbon Footprint
Build a carbon footprint model that estimates emissions from operational data — energy use, transport, supply chain activities.
2
Model Carbon Footprint
python • Step 2
Build a carbon footprint model that estimates emissions from operational data — energy use, transport, supply chain activities.
carbon_accountingregressionlifecycle_analysis
Learning Objectives
- →Calculate carbon footprint using emission factors
- →Model the relationship between operational metrics and emissions
- →Identify the largest emission hotspots
Dataset
View on Kaggle Matches Kaggle
UNFCCC GHG inventory 1990-2017 — country_or_area, year, value, category.
*bleep* Load the dataset in the browser terminal:
from pyodide.http import open_url
import pandas as pd
df = pd.read_csv(open_url("/datasets/greenhouse_gas_inventory_data_data.csv"))
print(df.shape)
print(df.columns.tolist()) Running locally? The file inside the Kaggle download is already named greenhouse_gas_inventory_data_data.csv — drop it into the notebook's working directory and the code above runs unchanged (swap open_url(...) for "greenhouse_gas_inventory_data_data.csv").
Dataset Columns
country_or_areayearvaluecategory- Write your solution in the Try It Yourself editor below — matplotlib/seaborn figures and pandas tables render inline.
- Stuck? Expand a section and click ↑ Send to editor to stack its snippet into the editor, notebook-style.
- Hit ▶ Run (or ⌘↵) — once your output matches the expected result, the step is marked solved.
- Use ↺ Reset to restore the starter code at any time.
Try It Yourself
Python
Loading editor...
*bleep* Output will appear here after running your code. Figures from matplotlib/seaborn render inline.
Expected output:
Shape: Columns:
0/2
Export to GitHub
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