Datasets / United States · public schools · school locations
United States · public schools directory coverage
Counts describe source directory records, not school quality or complete worldwide coverage. Smaller groups are retained as Other when needed.
How it decided
United States · public schools · school locations: 102,178 rows, 16 columns. The directory identifier and region classify source records; missing coordinates are still counted.
102,178 rows in, 16 out across 2 columns. Counts describe source directory records, not school quality or complete worldwide coverage. Smaller groups are retained as Other when needed.
bar. A count comparison describes coverage without inventing achievement scores or attendance boundaries.
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('region', dropna=False).size().reset_index(name='schools').rename(columns={'region':'group'})
result = result.sort_values('schools', ascending=False).reset_index(drop=True)
if len(result) > 15:
result = pd.concat([result.head(15), pd.DataFrame([{'group':'Other','schools':int(result.iloc[15:]['schools'].sum())}])], ignore_index=True)What it charted
16 rows out of 102,178, 2 columns. First 8 shown.
| group | schools |
|---|---|
| CA | 10407 |
| TX | 9774 |
| NY | 4865 |
| IL | 4439 |
| FL | 4312 |
| OH | 3611 |
| MI | 3508 |
| PA | 2949 |