Renewable share of electricity by region
Every region's share climbs, but from different bases: the lines do not cross so much as converge on different ceilings.
How it decided
Energy transition: 40 rows, 9 columns. year, region and renewable_share_pct.
40 rows in, 40 out across 3 columns. Every region's share climbs, but from different bases: the lines do not cross so much as converge on different ceilings.
bar. One measure over time per region: a line each. An area would sum shares that do not add to a meaningful total.
Palette, spacing, axis titles and legend placement applied. 0 issues found.
The transformation
This is the code, not a description of it — the chart above was drawn from what it returns, and the notebook download runs the same lines against the same file.
result = df.groupby(["year", "region"], as_index=False)["renewable_share_pct"].mean()What it charted
40 rows out of 40, 3 columns. First 8 shown.
| year | region | renewable_share_pct |
|---|---|---|
| 2016 | Asia Pacific | 44.9 |
| 2016 | Europe | 47.2 |
| 2016 | Latin America | 42.3 |
| 2016 | North America | 48.6 |
| 2017 | Asia Pacific | 44.0 |
| 2017 | Europe | 46.9 |
| 2017 | Latin America | 41.9 |
| 2017 | North America | 49.5 |