Explore ESG & Climate Data
Load the ESG & Financial Performance dataset (1,000 companies × 11 years, 16 columns) to understand how companies perform on Environmental, Social, and Governance metrics alongside their financials.
Explore ESG & Climate Data
Python / R • Step 1
Load the ESG & Financial Performance dataset (1,000 companies × 11 years, 16 columns) to understand how companies perform on Environmental, Social, and Governance metrics alongside their financials.
Learning Objectives
- →Understand ESG scoring frameworks (E, S, G pillars)
- →Load and merge ESG datasets from multiple sources
- →Identify sector-level ESG trends
Dataset
View on Kaggle1,000 companies × 11 years — ESG pillar scores + financials (Revenue, MarketCap, GrowthRate, CarbonEmissions).
*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/company_esg_financial_dataset.csv"))
print(df.shape)
print(df.columns.tolist()) Running locally? The file inside the Kaggle download is already named company_esg_financial_dataset.csv — drop it into the notebook's working directory and the code above runs unchanged (swap open_url(...) for "company_esg_financial_dataset.csv").
Dataset Columns
CompanyIDCompanyNameIndustryRegionYearRevenueProfitMarginMarketCapGrowthRateESG_OverallESG_EnvironmentalESG_SocialESG_GovernanceCarbonEmissionsWaterUsageEnergyConsumptionCode Language
- 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
Shape: Columns:
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