Voluntary Carbon Offset Market
Analyze voluntary carbon offset projects by methodology, vintage, issuance, retirement, and price. Identify which projects are undersubscribed or overpriced.
3
Voluntary Carbon Offset Market
python • Step 3
Analyze voluntary carbon offset projects by methodology, vintage, issuance, retirement, and price. Identify which projects are undersubscribed or overpriced.
pandasedafinanceclimate
Learning Objectives
- →Explore carbon offset issuance, retirement, and prices by methodology
- →Compute utilization rate (retired / issued)
- →Compare average prices across methodologies
- →Understand additionality and vintage risk
Dataset
View on data.worlddata.world filename
Lab path (browser)
Carbon offset project metadata, methodologies, and issuances.
*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/carbon_offset_projects.csv"))
print(df.shape)
print(df.columns.tolist()) Running locally? data.world ships offset_projects.csv. Point read_csv at that path and everything else works unchanged.
Dataset Columns
project_idmethodologyvintageissuance_tco2eretired_tco2eprice_usdcountry- 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:
methodology issuance_tco2e retired_tco2e unsold_tco2e price_usd utilization_rate
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