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Green on Paper — Python for Environmental Data and Green Claims

Beginner Python

What this course is

A government report says carbon dioxide emissions are down 15.5 percent, that tens of thousands of megawatts of renewable capacity have been added, that the recycling rate has reached 45.1 percent, that industry uses less water, that a city's air is 20 percent cleaner and that green projects cut 35.2 million tonnes a year. Every one of those numbers is arithmetically true, and every one misleads. This is the Academy edition of the LucidPlexus field book Green on Paper: seventeen lessons, one per chapter, with the book's figures and every Python example runnable on the page. It teaches Python from the first line by asking environmental data the questions a green claim raises, then teaches how to judge, chart and word an environmental number honestly.

You start with values, lists, loops and functions, then read, filter, total, group, join and date tables with pandas, convert units (tonnes, GWh, CO2-equivalent), and draw charts with matplotlib, each step on the question it answers: which years, capacity or output, whose average, which sector, better than what, claimed by whom. Then you find the 25 faults planted in the data, clean it in code with a record of every decision, and build the scorecard that sets each claim beside what the data says. The last lessons cover the ways a true number makes a misleading green claim, the reporting frameworks behind the numbers, and two checklists to keep beside the keyboard. Each lesson has a quiz and two Python practice challenges with automatic marking.

What this course proves

The certificate shows you can answer an environmental question from raw tables in Python, check and clean the data in a way anyone can rerun, test a claim more than one way, and chart and state the answer without distorting it. It is awarded when all lessons are complete, every lesson quiz is passed and the final project is approved.

Data

Every lesson, the practice and the final project use twelve tables about the Verdant Union, a fictional union of five countries with ten monitored cities: invented data built to behave like real environmental statistics, with 25 faults planted on purpose. Python reads each one as data/<name>.csv, for example pd.read_csv("data/air_quality.csv"). The tables come from three dataset pages:

The final project

A sustainability review of the Verdant Union's Green Progress Report 2024, end to end, in the career-project IDE in your browser: meet the twelve tables and reproduce the six claims, run the rule checks, clean with a log, rebuild the scorecard, test each claim another way, chart honestly, then write the honest version of the six claims and a one-page brief for a minister's office. It needs no Community membership and is reviewed by a person.

Community members can also take the track Green on Paper, which does the same work as one notebook for the whole book, with an automatic check for each chapter.

Start this course

What you'll learn

  • Write Python from the first line: values, lists, dictionaries, loops, functions, and reading a file
  • Read, filter, sort and total tables with pandas, and compute rates, percent changes, percentage points and per-person figures correctly
  • Group, reshape and join tables with groupby, pivot_table and merge without losing or multiplying rows
  • Work with dates and units: read mixed date formats, compare like seasons, convert tonnes, GWh and CO2-equivalent
  • Check data against rules, find duplicates, impossible values and missing rows, and clean on copies with a record of every decision
  • Rebuild a report's green claims as a scorecard and test each claim a second way
  • Draw honest charts with matplotlib: baselines from zero, reference lines, titles that state the finding
  • Recognize how a true number makes a misleading green claim, and write a claim that survives checking

17 lessons · 23.7 h

  1. Six Claims and the Data Behind Them Quiz 45 min
  2. Python from Zero Quiz 130 min
  3. Tables in pandas Quiz 120 min
  4. Filtering and Sorting Quiz 100 min
  5. Totals, Averages and Rates Quiz 95 min
  6. Grouping and Reshaping Quiz 80 min
  7. Joining Tables Quiz 95 min
  8. Time Quiz 100 min
  9. Units Quiz 95 min
  10. Checks Before You Believe Quiz 95 min
  11. Cleaning with a Record Quiz 120 min
  12. The Scorecard Quiz 85 min
  13. Charts That Tell the Truth Quiz 60 min
  14. Green on Paper Quiz 50 min
  15. Reporting Frameworks in Plain Language Quiz 65 min
  16. Ten Checks Before You Publish an Environmental Number Quiz 45 min
  17. Ten Ways a True Number Makes a Misleading Green Claim Quiz 40 min

How you earn the certificate

  1. Complete at least 100% of the lessons.
  2. Pass each of the 17 lesson quizzes with 70% or more. You can retake them.
  3. Build the final project, Green on Paper — the Verdant Union sustainability review, and have it approved by a reviewer.

Every certificate has a public link employers can use to check it, and you can add it to LinkedIn.

Who it's for

  • Sustainability officers, policy analysts and consultants handed environmental data and a claim to check
  • Journalists and NGO staff who check press releases, reports and pledges
  • Students and spreadsheet users who want to learn Python on data that matters

Before you start

  • None: the course teaches Python from the first line
  • A browser: everything runs in it, nothing to install
  • Some spreadsheet experience helps: lessons show many moves in a spreadsheet too