Source: /home/coolhand/html/datavis/data_trove/data/geographic/scars/master_dataset.csv
Saturn profiled 3,221 rows across 20 columns. The stats below are deterministic and machine-readable; the prose is a language-model interpretation of those stats (opt-in, added after the fact, never sees raw rows).
!pip install saturn-dissect
import subprocess
subprocess.run([
"saturn", "analyze", "/home/coolhand/html/datavis/data_trove/data/geographic/scars/master_dataset.csv",
"--findings", "scars-master_dataset.json",
"--llm", "anthropic:claude-opus-4-7",
])This is a county-level US dataset of 3,221 rows and 20 columns combining demographics (population by race, poverty, income), 2016 and 2020 presidential vote shares, and geographic identifiers (FIPS, state, county). Two data-quality issues stand out and should be addressed first: median_household_income contains sentinel/error values that pull its minimum to -666,666,666 and yield a negative mean, and margin_2016 is stored as text percentages (e.g. '15.17%') while margin_2020 is numeric, so the two election cycles aren't directly comparable without cleaning. The political columns themselves are well-formed and show a Republican-leaning county distribution (mean republican_pct_2020 ≈ 0.65 vs democratic_pct_2020 ≈ 0.33). Population and demographic counts are heavily right-skewed with many outliers, as expected when mixing rural counties with metros up to ~10M people, so log scales or per-capita rates (already provided as pct_white, pct_black, pct_hispanic) will be more informative than raw counts.
citing: median_household_income · margin_2016 · margin_2020 · republican_pct_2020 · democratic_pct_2020 · total_population · pct_white · pct_black · pct_hispanic · poverty_rate
saturn.schema() · 20 columns
| column | kind | n | null% | unique | alerts |
|---|---|---|---|---|---|
| NAME | text | 3,221 | 0.0% | 3,221 | near_unique |
| total_population | numeric | 3,221 | 0.0% | 3,160 | high_skew outliers |
| black_population | numeric | 3,221 | 0.0% | 2,066 | high_skew outliers |
| white_population | numeric | 3,221 | 0.0% | 3,143 | high_skew outliers |
| hispanic_population | numeric | 3,221 | 0.0% | 2,331 | high_skew outliers |
| state | numeric | 3,221 | 0.0% | 52 | |
| county | numeric | 3,221 | 0.0% | 326 | high_skew outliers |
| FIPS | numeric | 3,221 | 0.0% | 3,221 | |
| pct_black | numeric | 3,221 | 0.0% | 3,128 | high_skew outliers |
| pct_white | numeric | 3,221 | 0.0% | 3,218 | |
| pct_hispanic | numeric | 3,221 | 0.0% | 3,205 | high_skew outliers |
| poverty_rate | numeric | 3,221 | 0.0% | 3,219 | high_skew |
| below_poverty_level | numeric | 3,221 | 0.0% | 2,824 | high_skew outliers |
| median_household_income | numeric | 3,221 | 0.0% | 3,099 | high_skew outliers |
| margin_2020 | numeric | 3,221 | 3.4% | 3,112 | |
| democratic_pct_2020 | numeric | 3,221 | 3.4% | 3,111 | |
| republican_pct_2020 | numeric | 3,221 | 3.4% | 3,111 | |
| margin_2016 | text | 3,221 | 2.6% | 2,554 | one_word allcaps short_text |
| democratic_pct_2016 | numeric | 3,221 | 2.6% | 3,111 | |
| republican_pct_2016 | numeric | 3,221 | 2.6% | 3,111 |
| bin | count |
|---|---|
| 0.05397 – 0.07667 | 1 |
| 0.07667 – 0.09937 | 2 |
| 0.09937 – 0.1221 | 2 |
| 0.1221 – 0.1448 | 6 |
| 0.1448 – 0.1675 | 6 |
| 0.1675 – 0.1901 | 15 |
| 0.1901 – 0.2128 | 5 |
| 0.2128 – 0.2355 | 13 |
| 0.2355 – 0.2582 | 12 |
| 0.2582 – 0.2809 | 25 |
| 0.2809 – 0.3036 | 26 |
| 0.3036 – 0.3263 | 32 |
| 0.3263 – 0.349 | 32 |
| 0.349 – 0.3717 | 40 |
| 0.3717 – 0.3944 | 46 |
| 0.3944 – 0.4171 | 52 |
| 0.4171 – 0.4398 | 64 |
| 0.4398 – 0.4625 | 78 |
| 0.4625 – 0.4852 | 61 |
| 0.4852 – 0.5079 | 78 |
| 0.5079 – 0.5306 | 66 |
| 0.5306 – 0.5533 | 97 |
| 0.5533 – 0.576 | 126 |
| 0.576 – 0.5987 | 122 |
| 0.5987 – 0.6214 | 139 |
| 0.6214 – 0.6441 | 143 |
| 0.6441 – 0.6668 | 154 |
| 0.6668 – 0.6895 | 173 |
| 0.6895 – 0.7122 | 176 |
| 0.7122 – 0.7349 | 200 |
| 0.7349 – 0.7576 | 213 |
| 0.7576 – 0.7802 | 195 |
| 0.7802 – 0.8029 | 203 |
| 0.8029 – 0.8256 | 169 |
| 0.8256 – 0.8483 | 132 |
| 0.8483 – 0.871 | 103 |
| 0.871 – 0.8937 | 65 |
| 0.8937 – 0.9164 | 27 |
| 0.9164 – 0.9391 | 9 |
| 0.9391 – 0.9618 | 4 |
| bin | count |
|---|---|
| -0.8675 – -0.8226 | 1 |
| -0.8226 – -0.7776 | 2 |
| -0.7776 – -0.7326 | 3 |
| -0.7326 – -0.6877 | 5 |
| -0.6877 – -0.6427 | 8 |
| -0.6427 – -0.5978 | 12 |
| -0.5978 – -0.5528 | 6 |
| -0.5528 – -0.5078 | 12 |
| -0.5078 – -0.4629 | 14 |
| -0.4629 – -0.4179 | 22 |
| -0.4179 – -0.373 | 28 |
| -0.373 – -0.328 | 33 |
| -0.328 – -0.283 | 29 |
| -0.283 – -0.2381 | 46 |
| -0.2381 – -0.1931 | 41 |
| -0.1931 – -0.1482 | 54 |
| -0.1482 – -0.1032 | 63 |
| -0.1032 – -0.05823 | 67 |
| -0.05823 – -0.01327 | 69 |
| -0.01327 – 0.03169 | 73 |
| 0.03169 – 0.07665 | 70 |
| 0.07665 – 0.1216 | 90 |
| 0.1216 – 0.1666 | 131 |
| 0.1666 – 0.2115 | 117 |
| 0.2115 – 0.2565 | 129 |
| 0.2565 – 0.3015 | 141 |
| 0.3015 – 0.3464 | 159 |
| 0.3464 – 0.3914 | 165 |
| 0.3914 – 0.4363 | 181 |
| 0.4363 – 0.4813 | 206 |
| 0.4813 – 0.5263 | 195 |
| 0.5263 – 0.5712 | 197 |
| 0.5712 – 0.6162 | 213 |
| 0.6162 – 0.6611 | 175 |
| 0.6611 – 0.7061 | 140 |
| 0.7061 – 0.7511 | 102 |
| 0.7511 – 0.796 | 69 |
| 0.796 – 0.841 | 29 |
| 0.841 – 0.8859 | 11 |
| 0.8859 – 0.9309 | 4 |
| bin | count |
|---|---|
| 3.29 – 5.708 | 2 |
| 5.708 – 8.125 | 1 |
| 8.125 – 10.54 | 4 |
| 10.54 – 12.96 | 2 |
| 12.96 – 15.38 | 10 |
| 15.38 – 17.8 | 6 |
| 17.8 – 20.21 | 4 |
| 20.21 – 22.63 | 7 |
| 22.63 – 25.05 | 12 |
| 25.05 – 27.47 | 12 |
| 27.47 – 29.89 | 7 |
| 29.89 – 32.3 | 4 |
| 32.3 – 34.72 | 10 |
| 34.72 – 37.14 | 13 |
| 37.14 – 39.56 | 24 |
| 39.56 – 41.97 | 18 |
| 41.97 – 44.39 | 24 |
| 44.39 – 46.81 | 30 |
| 46.81 – 49.23 | 24 |
| 49.23 – 51.64 | 34 |
| 51.64 – 54.06 | 33 |
| 54.06 – 56.48 | 37 |
| 56.48 – 58.9 | 58 |
| 58.9 – 61.32 | 43 |
| 61.32 – 63.73 | 69 |
| 63.73 – 66.15 | 72 |
| 66.15 – 68.57 | 77 |
| 68.57 – 70.99 | 76 |
| 70.99 – 73.4 | 88 |
| 73.4 – 75.82 | 100 |
| 75.82 – 78.24 | 98 |
| 78.24 – 80.66 | 143 |
| 80.66 – 83.08 | 132 |
| 83.08 – 85.49 | 163 |
| 85.49 – 87.91 | 191 |
| 87.91 – 90.33 | 246 |
| 90.33 – 92.75 | 302 |
| 92.75 – 95.16 | 453 |
| 95.16 – 97.58 | 525 |
| 97.58 – 100 | 67 |
| bin | count |
|---|---|
| 0 – 1.655 | 2 |
| 1.655 – 3.31 | 9 |
| 3.31 – 4.964 | 48 |
| 4.964 – 6.619 | 123 |
| 6.619 – 8.274 | 212 |
| 8.274 – 9.929 | 317 |
| 9.929 – 11.58 | 378 |
| 11.58 – 13.24 | 392 |
| 13.24 – 14.89 | 353 |
| 14.89 – 16.55 | 338 |
| 16.55 – 18.2 | 235 |
| 18.2 – 19.86 | 192 |
| 19.86 – 21.51 | 157 |
| 21.51 – 23.17 | 108 |
| 23.17 – 24.82 | 77 |
| 24.82 – 26.48 | 53 |
| 26.48 – 28.13 | 41 |
| 28.13 – 29.79 | 37 |
| 29.79 – 31.44 | 29 |
| 31.44 – 33.1 | 13 |
| 33.1 – 34.75 | 10 |
| 34.75 – 36.41 | 11 |
| 36.41 – 38.06 | 7 |
| 38.06 – 39.72 | 2 |
| 39.72 – 41.37 | 8 |
| 41.37 – 43.03 | 6 |
| 43.03 – 44.68 | 7 |
| 44.68 – 46.33 | 11 |
| 46.33 – 47.99 | 6 |
| 47.99 – 49.64 | 9 |
| 49.64 – 51.3 | 8 |
| 51.3 – 52.95 | 5 |
| 52.95 – 54.61 | 6 |
| 54.61 – 56.26 | 2 |
| 56.26 – 57.92 | 2 |
| 57.92 – 59.57 | 3 |
| 59.57 – 61.23 | 1 |
| 61.23 – 62.88 | 1 |
| 62.88 – 64.54 | 0 |
| 64.54 – 66.19 | 2 |
| bin | count |
|---|---|
| -6.667e+08 – -6.5e+08 | 1 |
| -6.5e+08 – -6.333e+08 | 0 |
| -6.333e+08 – -6.167e+08 | 0 |
| -6.167e+08 – -6e+08 | 0 |
| -6e+08 – -5.833e+08 | 0 |
| -5.833e+08 – -5.666e+08 | 0 |
| -5.666e+08 – -5.5e+08 | 0 |
| -5.5e+08 – -5.333e+08 | 0 |
| -5.333e+08 – -5.166e+08 | 0 |
| -5.166e+08 – -5e+08 | 0 |
| -5e+08 – -4.833e+08 | 0 |
| -4.833e+08 – -4.666e+08 | 0 |
| -4.666e+08 – -4.5e+08 | 0 |
| -4.5e+08 – -4.333e+08 | 0 |
| -4.333e+08 – -4.166e+08 | 0 |
| -4.166e+08 – -3.999e+08 | 0 |
| -3.999e+08 – -3.833e+08 | 0 |
| -3.833e+08 – -3.666e+08 | 0 |
| -3.666e+08 – -3.499e+08 | 0 |
| -3.499e+08 – -3.333e+08 | 0 |
| -3.333e+08 – -3.166e+08 | 0 |
| -3.166e+08 – -2.999e+08 | 0 |
| -2.999e+08 – -2.832e+08 | 0 |
| -2.832e+08 – -2.666e+08 | 0 |
| -2.666e+08 – -2.499e+08 | 0 |
| -2.499e+08 – -2.332e+08 | 0 |
| -2.332e+08 – -2.166e+08 | 0 |
| -2.166e+08 – -1.999e+08 | 0 |
| -1.999e+08 – -1.832e+08 | 0 |
| -1.832e+08 – -1.666e+08 | 0 |
| -1.666e+08 – -1.499e+08 | 0 |
| -1.499e+08 – -1.332e+08 | 0 |
| -1.332e+08 – -1.165e+08 | 0 |
| -1.165e+08 – -9.987e+07 | 0 |
| -9.987e+07 – -8.32e+07 | 0 |
| -8.32e+07 – -6.653e+07 | 0 |
| -6.653e+07 – -4.986e+07 | 0 |
| -4.986e+07 – -3.319e+07 | 0 |
| -3.319e+07 – -1.652e+07 | 0 |
| -1.652e+07 – 1.471e+05 | 3220 |
| column | kind | null % |
|---|---|---|
| NAME | text | 0.0% |
| total_population | numeric | 0.0% |
| black_population | numeric | 0.0% |
| white_population | numeric | 0.0% |
| hispanic_population | numeric | 0.0% |
| state | numeric | 0.0% |
| county | numeric | 0.0% |
| FIPS | numeric | 0.0% |
| pct_black | numeric | 0.0% |
| pct_white | numeric | 0.0% |
| pct_hispanic | numeric | 0.0% |
| poverty_rate | numeric | 0.0% |
| below_poverty_level | numeric | 0.0% |
| median_household_income | numeric | 0.0% |
| margin_2020 | numeric | 3.4% |
| democratic_pct_2020 | numeric | 3.4% |
| republican_pct_2020 | numeric | 3.4% |
| margin_2016 | text | 2.6% |
| democratic_pct_2016 | numeric | 2.6% |
| republican_pct_2016 | numeric | 2.6% |
| total_population | black_population | white_population | hispanic_population | state | county | FIPS | pct_black | pct_white | pct_hispanic | poverty_rate | below_poverty_level | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| total_population | +1.00 | +0.69 | +0.98 | +0.88 | -0.06 | -0.10 | -0.06 | +0.04 | -0.19 | +0.08 | -0.15 | +0.93 |
| black_population | +0.69 | +1.00 | +0.63 | +0.44 | -0.01 | -0.03 | -0.01 | +0.27 | -0.29 | +0.01 | -0.04 | +0.77 |
| white_population | +0.98 | +0.63 | +1.00 | +0.86 | -0.06 | -0.11 | -0.06 | +0.01 | -0.12 | +0.07 | -0.17 | +0.89 |
| hispanic_population | +0.88 | +0.44 | +0.86 | +1.00 | -0.06 | -0.07 | -0.06 | -0.01 | -0.15 | +0.22 | -0.02 | +0.86 |
| state | -0.06 | -0.01 | -0.06 | -0.06 | +1.00 | +0.07 | +1.00 | -0.07 | +0.02 | +0.37 | +0.22 | -0.05 |
| county | -0.10 | -0.03 | -0.11 | -0.07 | +0.07 | +1.00 | +0.07 | +0.09 | -0.07 | +0.07 | +0.11 | -0.08 |
| FIPS | -0.06 | -0.01 | -0.06 | -0.06 | +1.00 | +0.07 | +1.00 | -0.07 | +0.02 | +0.37 | +0.22 | -0.05 |
| pct_black | +0.04 | +0.27 | +0.01 | -0.01 | -0.07 | +0.09 | -0.07 | +1.00 | -0.79 | -0.02 | +0.39 | +0.10 |
| pct_white | -0.19 | -0.29 | -0.12 | -0.15 | +0.02 | -0.07 | +0.02 | -0.79 | +1.00 | -0.24 | -0.48 | -0.23 |
| pct_hispanic | +0.08 | +0.01 | +0.07 | +0.22 | +0.37 | +0.07 | +0.37 | -0.02 | -0.24 | +1.00 | +0.53 | +0.14 |
| poverty_rate | -0.15 | -0.04 | -0.17 | -0.02 | +0.22 | +0.11 | +0.22 | +0.39 | -0.48 | +0.53 | +1.00 | -0.01 |
| below_poverty_level | +0.93 | +0.77 | +0.89 | +0.86 | -0.05 | -0.08 | -0.05 | +0.10 | -0.23 | +0.14 | -0.01 | +1.00 |
This column appears to hold US county names with state qualifiers — 'county,' appears in 3,007 of 3,221 rows, followed by state tokens like Texas (256), Virginia (189), and Georgia (159). Every value is unique (n_unique = 3221, duplicate_rate = 0.0) with no nulls, and lengths cluster tightly around 24 characters (min 16, max 42), consistent with a canonical 'X County, ST' format. The near_unique alert confirms this behaves as an identifier rather than a categorical feature.
Treatment: Use as a join key to county-level reference tables; do not feed as a categorical feature.
saturn.columns["NAME"].stats
| stat | value |
|---|---|
| n | 3,221 |
| nulls | 0 (0.0%) |
| unique | 3,221 |
| len_min | 16 |
| len_max | 42 |
| len_mean | 24.27 |
| len_median | 24 |
| len_p95 | 31 |
| word_mean | 3.243 |
| word_median | 3 |
| n_empty | 0 |
| n_duplicates | 0 |
| duplicate_rate | 0 |
| vocab_size | 1,983 |
| readability_flesch_mean | 7.581 |
| emoji_rate | 0 |
| url_rate | 0 |
| one_word_rate | 0 |
| allcaps_rate | 0 |
| boilerplate_rate | 0 |
| alert: near_unique | 100.0% of rows are unique strings |
NAME.
| chars | count |
|---|---|
| 16 – 17 | 3 |
| 17 – 17 | 23 |
| 17 – 18 | 0 |
| 18 – 19 | 72 |
| 19 – 19 | 121 |
| 19 – 20 | 0 |
| 20 – 21 | 190 |
| 21 – 21 | 264 |
| 21 – 22 | 0 |
| 22 – 22 | 407 |
| 22 – 23 | 420 |
| 23 – 24 | 0 |
| 24 – 24 | 363 |
| 24 – 25 | 320 |
| 25 – 26 | 0 |
| 26 – 26 | 240 |
| 26 – 27 | 233 |
| 27 – 28 | 0 |
| 28 – 28 | 153 |
| 28 – 29 | 0 |
| 29 – 30 | 142 |
| 30 – 30 | 86 |
| 30 – 31 | 0 |
| 31 – 32 | 81 |
| 32 – 32 | 41 |
| 32 – 33 | 0 |
| 33 – 34 | 28 |
| 34 – 34 | 16 |
| 34 – 35 | 0 |
| 35 – 36 | 10 |
| 36 – 36 | 4 |
| 36 – 37 | 0 |
| 37 – 37 | 0 |
| 37 – 38 | 1 |
| 38 – 39 | 0 |
| 39 – 39 | 1 |
| 39 – 40 | 0 |
| 40 – 41 | 0 |
| 41 – 41 | 1 |
| 41 – 42 | 1 |
Likely a county- or area-level total population count, given 3,221 rows with no nulls and a minimum of 117 alongside a maximum of 10,040,682. The distribution is severely right-skewed (skew 13.67, kurtosis 311.9) with the mean (102,398) nearly four times the median (25,981) and 441 outliers (13.7%). A few mega-population areas dominate while most are small.
Treatment: log-transform before modelling to tame the heavy right tail.
saturn.columns["total_population"].stats
| stat | value |
|---|---|
| n | 3,221 |
| nulls | 0 (0.0%) |
| unique | 3,160 |
| min | 117 |
| max | 1.004e+07 |
| mean | 1.024e+05 |
| median | 25,981 |
| std | 3.283e+05 |
| q1 | 11,125 |
| q3 | 66,969 |
| iqr | 55,844 |
| skew | 13.67 |
| kurtosis | 311.9 |
| n_outliers | 441 |
| outlier_rate | 0.1369 |
| zero_rate | 0 |
| alert: high_skew | skew=+13.67 |
| alert: outliers | 13.7% rows beyond 1.5 IQR |
total_population. Vertical dash marks the median.
| bin | count |
|---|---|
| 117 – 2.511e+05 | 2946 |
| 2.511e+05 – 5.021e+05 | 135 |
| 5.021e+05 – 7.532e+05 | 53 |
| 7.532e+05 – 1.004e+06 | 42 |
| 1.004e+06 – 1.255e+06 | 12 |
| 1.255e+06 – 1.506e+06 | 9 |
| 1.506e+06 – 1.757e+06 | 6 |
| 1.757e+06 – 2.008e+06 | 3 |
| 2.008e+06 – 2.259e+06 | 4 |
| 2.259e+06 – 2.51e+06 | 2 |
| 2.51e+06 – 2.761e+06 | 3 |
| 2.761e+06 – 3.012e+06 | 0 |
| 3.012e+06 – 3.263e+06 | 1 |
| 3.263e+06 – 3.514e+06 | 1 |
| 3.514e+06 – 3.765e+06 | 0 |
| 3.765e+06 – 4.016e+06 | 0 |
| 4.016e+06 – 4.267e+06 | 0 |
| 4.267e+06 – 4.518e+06 | 1 |
| 4.518e+06 – 4.769e+06 | 1 |
| 4.769e+06 – 5.02e+06 | 0 |
| 5.02e+06 – 5.271e+06 | 1 |
| 5.271e+06 – 5.522e+06 | 0 |
| 5.522e+06 – 5.773e+06 | 0 |
| 5.773e+06 – 6.024e+06 | 0 |
| 6.024e+06 – 6.275e+06 | 0 |
| 6.275e+06 – 6.526e+06 | 0 |
| 6.526e+06 – 6.777e+06 | 0 |
| 6.777e+06 – 7.029e+06 | 0 |
| 7.029e+06 – 7.28e+06 | 0 |
| 7.28e+06 – 7.531e+06 | 0 |
| 7.531e+06 – 7.782e+06 | 0 |
| 7.782e+06 – 8.033e+06 | 0 |
| 8.033e+06 – 8.284e+06 | 0 |
| 8.284e+06 – 8.535e+06 | 0 |
| 8.535e+06 – 8.786e+06 | 0 |
| 8.786e+06 – 9.037e+06 | 0 |
| 9.037e+06 – 9.288e+06 | 0 |
| 9.288e+06 – 9.539e+06 | 0 |
| 9.539e+06 – 9.79e+06 | 0 |
| 9.79e+06 – 1.004e+07 | 1 |
Numeric count of Black residents per record (likely US county-level given n=3221), ranging from 0 to 1,202,260 with a median of just 859. The distribution is extremely right-skewed (skew 10.46, kurtosis 148.2) with 13.6% flagged as outliers and a std (54,952) over four times the mean (12,914), reflecting a few major metros dominating a long tail of small counties. About 2.8% of rows are zero and there are no nulls.
Treatment: Log-transform (log1p) before modelling or normalise as a share of total population.
saturn.columns["black_population"].stats
| stat | value |
|---|---|
| n | 3,221 |
| nulls | 0 (0.0%) |
| unique | 2,066 |
| min | 0 |
| max | 1.202e+06 |
| mean | 1.291e+04 |
| median | 859 |
| std | 5.495e+04 |
| q1 | 114 |
| q3 | 5,553 |
| iqr | 5,439 |
| skew | 10.46 |
| kurtosis | 148.2 |
| n_outliers | 438 |
| outlier_rate | 0.136 |
| zero_rate | 0.02825 |
| alert: high_skew | skew=+10.46 |
| alert: outliers | 13.6% rows beyond 1.5 IQR |
black_population. Vertical dash marks the median.
| bin | count |
|---|---|
| 0 – 3.006e+04 | 2968 |
| 3.006e+04 – 6.011e+04 | 108 |
| 6.011e+04 – 9.017e+04 | 41 |
| 9.017e+04 – 1.202e+05 | 33 |
| 1.202e+05 – 1.503e+05 | 12 |
| 1.503e+05 – 1.803e+05 | 14 |
| 1.803e+05 – 2.104e+05 | 8 |
| 2.104e+05 – 2.405e+05 | 3 |
| 2.405e+05 – 2.705e+05 | 7 |
| 2.705e+05 – 3.006e+05 | 6 |
| 3.006e+05 – 3.306e+05 | 2 |
| 3.306e+05 – 3.607e+05 | 2 |
| 3.607e+05 – 3.907e+05 | 2 |
| 3.907e+05 – 4.208e+05 | 2 |
| 4.208e+05 – 4.508e+05 | 0 |
| 4.508e+05 – 4.809e+05 | 2 |
| 4.809e+05 – 5.11e+05 | 2 |
| 5.11e+05 – 5.41e+05 | 0 |
| 5.41e+05 – 5.711e+05 | 2 |
| 5.711e+05 – 6.011e+05 | 1 |
| 6.011e+05 – 6.312e+05 | 0 |
| 6.312e+05 – 6.612e+05 | 1 |
| 6.612e+05 – 6.913e+05 | 1 |
| 6.913e+05 – 7.214e+05 | 0 |
| 7.214e+05 – 7.514e+05 | 0 |
| 7.514e+05 – 7.815e+05 | 0 |
| 7.815e+05 – 8.115e+05 | 2 |
| 8.115e+05 – 8.416e+05 | 0 |
| 8.416e+05 – 8.716e+05 | 0 |
| 8.716e+05 – 9.017e+05 | 1 |
| 9.017e+05 – 9.318e+05 | 0 |
| 9.318e+05 – 9.618e+05 | 0 |
| 9.618e+05 – 9.919e+05 | 0 |
| 9.919e+05 – 1.022e+06 | 0 |
| 1.022e+06 – 1.052e+06 | 0 |
| 1.052e+06 – 1.082e+06 | 0 |
| 1.082e+06 – 1.112e+06 | 0 |
| 1.112e+06 – 1.142e+06 | 0 |
| 1.142e+06 – 1.172e+06 | 0 |
| 1.172e+06 – 1.202e+06 | 1 |
Counts of the white population per record (likely US counties given n=3221), ranging from 58 to 4,795,186 with a median of 21,282 but a mean of 72,000. The distribution is extremely right-skewed (skew 10.35, kurtosis 175.65) with 407 outliers (12.6%), reflecting a few very populous counties dwarfing the rest. No nulls or zeros, and near-unique values (3143/3221).
Treatment: log-transform before regression to tame the heavy right skew.
saturn.columns["white_population"].stats
| stat | value |
|---|---|
| n | 3,221 |
| nulls | 0 (0.0%) |
| unique | 3,143 |
| min | 58 |
| max | 4.795e+06 |
| mean | 7.2e+04 |
| median | 21,282 |
| std | 1.918e+05 |
| q1 | 8,855 |
| q3 | 56,553 |
| iqr | 47,698 |
| skew | 10.35 |
| kurtosis | 175.7 |
| n_outliers | 407 |
| outlier_rate | 0.1264 |
| zero_rate | 0 |
| alert: high_skew | skew=+10.35 |
| alert: outliers | 12.6% rows beyond 1.5 IQR |
white_population. Vertical dash marks the median.
| bin | count |
|---|---|
| 58 – 1.199e+05 | 2795 |
| 1.199e+05 – 2.398e+05 | 216 |
| 2.398e+05 – 3.597e+05 | 74 |
| 3.597e+05 – 4.796e+05 | 47 |
| 4.796e+05 – 5.994e+05 | 29 |
| 5.994e+05 – 7.193e+05 | 24 |
| 7.193e+05 – 8.392e+05 | 6 |
| 8.392e+05 – 9.591e+05 | 9 |
| 9.591e+05 – 1.079e+06 | 3 |
| 1.079e+06 – 1.199e+06 | 3 |
| 1.199e+06 – 1.319e+06 | 4 |
| 1.319e+06 – 1.439e+06 | 3 |
| 1.439e+06 – 1.558e+06 | 1 |
| 1.558e+06 – 1.678e+06 | 0 |
| 1.678e+06 – 1.798e+06 | 1 |
| 1.798e+06 – 1.918e+06 | 1 |
| 1.918e+06 – 2.038e+06 | 0 |
| 2.038e+06 – 2.158e+06 | 0 |
| 2.158e+06 – 2.278e+06 | 1 |
| 2.278e+06 – 2.398e+06 | 0 |
| 2.398e+06 – 2.518e+06 | 0 |
| 2.518e+06 – 2.637e+06 | 0 |
| 2.637e+06 – 2.757e+06 | 1 |
| 2.757e+06 – 2.877e+06 | 1 |
| 2.877e+06 – 2.997e+06 | 0 |
| 2.997e+06 – 3.117e+06 | 0 |
| 3.117e+06 – 3.237e+06 | 0 |
| 3.237e+06 – 3.357e+06 | 1 |
| 3.357e+06 – 3.477e+06 | 0 |
| 3.477e+06 – 3.596e+06 | 0 |
| 3.596e+06 – 3.716e+06 | 0 |
| 3.716e+06 – 3.836e+06 | 0 |
| 3.836e+06 – 3.956e+06 | 0 |
| 3.956e+06 – 4.076e+06 | 0 |
| 4.076e+06 – 4.196e+06 | 0 |
| 4.196e+06 – 4.316e+06 | 0 |
| 4.316e+06 – 4.436e+06 | 0 |
| 4.436e+06 – 4.555e+06 | 0 |
| 4.555e+06 – 4.675e+06 | 0 |
| 4.675e+06 – 4.795e+06 | 1 |
Counts of Hispanic population per record (likely county- or tract-level given n=3221), ranging from 0 to 4,851,344 with a median of just 1,209. The distribution is extraordinarily right-skewed (skew 22.75, kurtosis 744.79) and 15.3% of rows flag as outliers, indicating a handful of very large jurisdictions dwarf the rest. Mean (19,427) sits far above the Q3 of 5,875, confirming a long heavy tail.
Treatment: Apply a log1p transform before modelling to tame the heavy right tail.
saturn.columns["hispanic_population"].stats
| stat | value |
|---|---|
| n | 3,221 |
| nulls | 0 (0.0%) |
| unique | 2,331 |
| min | 0 |
| max | 4.851e+06 |
| mean | 1.943e+04 |
| median | 1,209 |
| std | 1.251e+05 |
| q1 | 377 |
| q3 | 5,875 |
| iqr | 5,498 |
| skew | 22.75 |
| kurtosis | 744.8 |
| n_outliers | 492 |
| outlier_rate | 0.1527 |
| zero_rate | 0.004967 |
| alert: high_skew | skew=+22.75 |
| alert: outliers | 15.3% rows beyond 1.5 IQR |
hispanic_population. Vertical dash marks the median.
| bin | count |
|---|---|
| 0 – 1.213e+05 | 3124 |
| 1.213e+05 – 2.426e+05 | 55 |
| 2.426e+05 – 3.639e+05 | 13 |
| 3.639e+05 – 4.851e+05 | 9 |
| 4.851e+05 – 6.064e+05 | 4 |
| 6.064e+05 – 7.277e+05 | 3 |
| 7.277e+05 – 8.49e+05 | 2 |
| 8.49e+05 – 9.703e+05 | 0 |
| 9.703e+05 – 1.092e+06 | 2 |
| 1.092e+06 – 1.213e+06 | 4 |
| 1.213e+06 – 1.334e+06 | 1 |
| 1.334e+06 – 1.455e+06 | 1 |
| 1.455e+06 – 1.577e+06 | 0 |
| 1.577e+06 – 1.698e+06 | 0 |
| 1.698e+06 – 1.819e+06 | 0 |
| 1.819e+06 – 1.941e+06 | 1 |
| 1.941e+06 – 2.062e+06 | 1 |
| 2.062e+06 – 2.183e+06 | 0 |
| 2.183e+06 – 2.304e+06 | 0 |
| 2.304e+06 – 2.426e+06 | 0 |
| 2.426e+06 – 2.547e+06 | 0 |
| 2.547e+06 – 2.668e+06 | 0 |
| 2.668e+06 – 2.79e+06 | 0 |
| 2.79e+06 – 2.911e+06 | 0 |
| 2.911e+06 – 3.032e+06 | 0 |
| 3.032e+06 – 3.153e+06 | 0 |
| 3.153e+06 – 3.275e+06 | 0 |
| 3.275e+06 – 3.396e+06 | 0 |
| 3.396e+06 – 3.517e+06 | 0 |
| 3.517e+06 – 3.639e+06 | 0 |
| 3.639e+06 – 3.76e+06 | 0 |
| 3.76e+06 – 3.881e+06 | 0 |
| 3.881e+06 – 4.002e+06 | 0 |
| 4.002e+06 – 4.124e+06 | 0 |
| 4.124e+06 – 4.245e+06 | 0 |
| 4.245e+06 – 4.366e+06 | 0 |
| 4.366e+06 – 4.487e+06 | 0 |
| 4.487e+06 – 4.609e+06 | 0 |
| 4.609e+06 – 4.73e+06 | 0 |
| 4.73e+06 – 4.851e+06 | 1 |
Stored as numeric but with only 52 unique integer values across 3221 rows ranging 1–72 with no nulls or zeros, this is almost certainly a FIPS-style state code rather than a true quantity. The near-symmetric spread (skew 0.157, kurtosis -0.626, mean 31.28 vs median 30) reflects roughly uniform coverage of US states/territories, not a meaningful distribution. The max of 72 is consistent with FIPS codes that extend past 50 to cover territories.
Treatment: Cast to categorical and one-hot or target-encode before modelling.
saturn.columns["state"].stats
| stat | value |
|---|---|
| n | 3,221 |
| nulls | 0 (0.0%) |
| unique | 52 |
| min | 1 |
| max | 72 |
| mean | 31.28 |
| median | 30 |
| std | 16.28 |
| q1 | 19 |
| q3 | 46 |
| iqr | 27 |
| skew | 0.157 |
| kurtosis | -0.6261 |
| n_outliers | 0 |
| outlier_rate | 0 |
| zero_rate | 0 |
state. Vertical dash marks the median.
| bin | count |
|---|---|
| 1 – 2.775 | 97 |
| 2.775 – 4.55 | 15 |
| 4.55 – 6.325 | 133 |
| 6.325 – 8.1 | 64 |
| 8.1 – 9.875 | 8 |
| 9.875 – 11.65 | 4 |
| 11.65 – 13.42 | 226 |
| 13.42 – 15.2 | 5 |
| 15.2 – 16.98 | 44 |
| 16.98 – 18.75 | 194 |
| 18.75 – 20.52 | 204 |
| 20.52 – 22.3 | 184 |
| 22.3 – 24.07 | 40 |
| 24.07 – 25.85 | 14 |
| 25.85 – 27.62 | 170 |
| 27.62 – 29.4 | 197 |
| 29.4 – 31.17 | 149 |
| 31.17 – 32.95 | 17 |
| 32.95 – 34.73 | 31 |
| 34.73 – 36.5 | 95 |
| 36.5 – 38.27 | 153 |
| 38.27 – 40.05 | 165 |
| 40.05 – 41.82 | 36 |
| 41.82 – 43.6 | 67 |
| 43.6 – 45.38 | 51 |
| 45.38 – 47.15 | 161 |
| 47.15 – 48.92 | 254 |
| 48.92 – 50.7 | 43 |
| 50.7 – 52.47 | 133 |
| 52.47 – 54.25 | 94 |
| 54.25 – 56.02 | 95 |
| 56.02 – 57.8 | 0 |
| 57.8 – 59.57 | 0 |
| 59.57 – 61.35 | 0 |
| 61.35 – 63.12 | 0 |
| 63.12 – 64.9 | 0 |
| 64.9 – 66.67 | 0 |
| 66.67 – 68.45 | 0 |
| 68.45 – 70.22 | 0 |
| 70.22 – 72 | 78 |
Stored as numeric, but with 326 unique integer values from 1 to 840 across 3221 rows and zero nulls, this is almost certainly a county FIPS or county-code identifier rather than a measurement. The heavy right skew (2.87) and kurtosis (11.6) flagged as outliers simply reflect that codes are not uniformly distributed — 178 'outliers' here are real codes, not anomalies. Treating mean=102.8 or std=106.6 as meaningful would be misleading.
Treatment: Cast to categorical/string code and join to a county lookup; do not use as a continuous feature.
saturn.columns["county"].stats
| stat | value |
|---|---|
| n | 3,221 |
| nulls | 0 (0.0%) |
| unique | 326 |
| min | 1 |
| max | 840 |
| mean | 102.8 |
| median | 79 |
| std | 106.6 |
| q1 | 35 |
| q3 | 133 |
| iqr | 98 |
| skew | 2.868 |
| kurtosis | 11.64 |
| n_outliers | 178 |
| outlier_rate | 0.05526 |
| zero_rate | 0 |
| alert: high_skew | skew=+2.87 |
| alert: outliers | 5.5% rows beyond 1.5 IQR |
county. Vertical dash marks the median.
| bin | count |
|---|---|
| 1 – 21.98 | 531 |
| 21.98 – 42.95 | 418 |
| 42.95 – 63.93 | 411 |
| 63.93 – 84.9 | 345 |
| 84.9 – 105.9 | 352 |
| 105.9 – 126.9 | 279 |
| 126.9 – 147.8 | 234 |
| 147.8 – 168.8 | 166 |
| 168.8 – 189.8 | 138 |
| 189.8 – 210.8 | 70 |
| 210.8 – 231.7 | 45 |
| 231.7 – 252.7 | 25 |
| 252.7 – 273.7 | 22 |
| 273.7 – 294.7 | 23 |
| 294.7 – 315.6 | 22 |
| 315.6 – 336.6 | 13 |
| 336.6 – 357.6 | 11 |
| 357.6 – 378.6 | 10 |
| 378.6 – 399.5 | 11 |
| 399.5 – 420.5 | 10 |
| 420.5 – 441.5 | 11 |
| 441.5 – 462.5 | 10 |
| 462.5 – 483.4 | 11 |
| 483.4 – 504.4 | 10 |
| 504.4 – 525.4 | 7 |
| 525.4 – 546.4 | 2 |
| 546.4 – 567.3 | 1 |
| 567.3 – 588.3 | 2 |
| 588.3 – 609.3 | 3 |
| 609.3 – 630.2 | 3 |
| 630.2 – 651.2 | 2 |
| 651.2 – 672.2 | 2 |
| 672.2 – 693.2 | 5 |
| 693.2 – 714.2 | 2 |
| 714.2 – 735.1 | 3 |
| 735.1 – 756.1 | 2 |
| 756.1 – 777.1 | 3 |
| 777.1 – 798.1 | 1 |
| 798.1 – 819 | 2 |
| 819 – 840 | 3 |
FIPS is the standard U.S. Federal Information Processing Standards county code, with all 3221 rows unique and no nulls. Values span 1001 to 72153, consistent with state-prefixed county identifiers (Alabama through Puerto Rico), and the distribution is near-symmetric (skew 0.157) with no outliers flagged.
Treatment: Treat as a categorical key; left-join on this code rather than using as a numeric feature.
saturn.columns["FIPS"].stats
| stat | value |
|---|---|
| n | 3,221 |
| nulls | 0 (0.0%) |
| unique | 3,221 |
| min | 1,001 |
| max | 72,153 |
| mean | 3.138e+04 |
| median | 30,023 |
| std | 1.63e+04 |
| q1 | 19,031 |
| q3 | 46,105 |
| iqr | 27,074 |
| skew | 0.1569 |
| kurtosis | -0.6308 |
| n_outliers | 0 |
| outlier_rate | 0 |
| zero_rate | 0 |
FIPS. Vertical dash marks the median.
| bin | count |
|---|---|
| 1001 – 2780 | 97 |
| 2780 – 4559 | 15 |
| 4559 – 6337 | 133 |
| 6337 – 8116 | 59 |
| 8116 – 9895 | 13 |
| 9895 – 1.167e+04 | 4 |
| 1.167e+04 – 1.345e+04 | 226 |
| 1.345e+04 – 1.523e+04 | 5 |
| 1.523e+04 – 1.701e+04 | 49 |
| 1.701e+04 – 1.879e+04 | 189 |
| 1.879e+04 – 2.057e+04 | 204 |
| 2.057e+04 – 2.235e+04 | 184 |
| 2.235e+04 – 2.413e+04 | 39 |
| 2.413e+04 – 2.59e+04 | 15 |
| 2.59e+04 – 2.768e+04 | 170 |
| 2.768e+04 – 2.946e+04 | 196 |
| 2.946e+04 – 3.124e+04 | 150 |
| 3.124e+04 – 3.302e+04 | 27 |
| 3.302e+04 – 3.48e+04 | 21 |
| 3.48e+04 – 3.658e+04 | 95 |
| 3.658e+04 – 3.836e+04 | 153 |
| 3.836e+04 – 4.013e+04 | 155 |
| 4.013e+04 – 4.191e+04 | 46 |
| 4.191e+04 – 4.369e+04 | 67 |
| 4.369e+04 – 4.547e+04 | 51 |
| 4.547e+04 – 4.725e+04 | 161 |
| 4.725e+04 – 4.903e+04 | 268 |
| 4.903e+04 – 5.081e+04 | 29 |
| 5.081e+04 – 5.259e+04 | 133 |
| 5.259e+04 – 5.436e+04 | 94 |
| 5.436e+04 – 5.614e+04 | 95 |
| 5.614e+04 – 5.792e+04 | 0 |
| 5.792e+04 – 5.97e+04 | 0 |
| 5.97e+04 – 6.148e+04 | 0 |
| 6.148e+04 – 6.326e+04 | 0 |
| 6.326e+04 – 6.504e+04 | 0 |
| 6.504e+04 – 6.682e+04 | 0 |
| 6.682e+04 – 6.86e+04 | 0 |
| 6.86e+04 – 7.037e+04 | 0 |
| 7.037e+04 – 7.215e+04 | 78 |
This is a numeric percentage of Black population per record (likely a county or tract), ranging from 0 to 87.79 with a median of just 2.38% but a mean of 9.08%. The distribution is heavily right-skewed (skew 2.33, kurtosis 5.45) with 422 outliers (13.1%) and 2.8% exact zeros, indicating a long tail of high-percentage areas above an otherwise low-share majority. No nulls, and 3,128 of 3,221 values are unique.
Treatment: Apply a log1p or similar transform before regression to tame the right skew.
saturn.columns["pct_black"].stats
| stat | value |
|---|---|
| n | 3,221 |
| nulls | 0 (0.0%) |
| unique | 3,128 |
| min | 0 |
| max | 87.79 |
| mean | 9.085 |
| median | 2.383 |
| std | 14.5 |
| q1 | 0.6919 |
| q3 | 10.21 |
| iqr | 9.513 |
| skew | 2.326 |
| kurtosis | 5.451 |
| n_outliers | 422 |
| outlier_rate | 0.131 |
| zero_rate | 0.02825 |
| alert: high_skew | skew=+2.33 |
| alert: outliers | 13.1% rows beyond 1.5 IQR |
pct_black. Vertical dash marks the median.
| bin | count |
|---|---|
| 0 – 2.195 | 1568 |
| 2.195 – 4.39 | 402 |
| 4.39 – 6.584 | 218 |
| 6.584 – 8.779 | 153 |
| 8.779 – 10.97 | 112 |
| 10.97 – 13.17 | 86 |
| 13.17 – 15.36 | 70 |
| 15.36 – 17.56 | 54 |
| 17.56 – 19.75 | 46 |
| 19.75 – 21.95 | 48 |
| 21.95 – 24.14 | 36 |
| 24.14 – 26.34 | 42 |
| 26.34 – 28.53 | 36 |
| 28.53 – 30.73 | 41 |
| 30.73 – 32.92 | 34 |
| 32.92 – 35.12 | 32 |
| 35.12 – 37.31 | 28 |
| 37.31 – 39.51 | 19 |
| 39.51 – 41.7 | 25 |
| 41.7 – 43.9 | 25 |
| 43.9 – 46.09 | 18 |
| 46.09 – 48.28 | 17 |
| 48.28 – 50.48 | 14 |
| 50.48 – 52.67 | 9 |
| 52.67 – 54.87 | 13 |
| 54.87 – 57.06 | 11 |
| 57.06 – 59.26 | 13 |
| 59.26 – 61.45 | 7 |
| 61.45 – 63.65 | 8 |
| 63.65 – 65.84 | 4 |
| 65.84 – 68.04 | 1 |
| 68.04 – 70.23 | 6 |
| 70.23 – 72.43 | 8 |
| 72.43 – 74.62 | 5 |
| 74.62 – 76.82 | 2 |
| 76.82 – 79.01 | 5 |
| 79.01 – 81.21 | 1 |
| 81.21 – 83.4 | 1 |
| 83.4 – 85.6 | 1 |
| 85.6 – 87.79 | 2 |
This column reports the percentage of a population that is white, ranging from 3.29 to 100.0 with a mean of 81.20 and median of 87.66. The distribution is heavily left-skewed (skew -1.56) with 145 low-end outliers (4.5% outlier rate), indicating most records are predominantly white but a long tail of diverse populations exists. No nulls or zeros are present, and near-unique values across 3221 rows suggest one row per geographic unit.
Treatment: Consider a logit or reflected-log transform to address the strong left skew before modelling.
saturn.columns["pct_white"].stats
| stat | value |
|---|---|
| n | 3,221 |
| nulls | 0 (0.0%) |
| unique | 3,218 |
| min | 3.29 |
| max | 100 |
| mean | 81.2 |
| median | 87.66 |
| std | 17.35 |
| q1 | 73.62 |
| q3 | 93.99 |
| iqr | 20.37 |
| skew | -1.562 |
| kurtosis | 2.301 |
| n_outliers | 145 |
| outlier_rate | 0.04502 |
| zero_rate | 0 |
pct_white. Vertical dash marks the median.
| bin | count |
|---|---|
| 3.29 – 5.708 | 2 |
| 5.708 – 8.125 | 1 |
| 8.125 – 10.54 | 4 |
| 10.54 – 12.96 | 2 |
| 12.96 – 15.38 | 10 |
| 15.38 – 17.8 | 6 |
| 17.8 – 20.21 | 4 |
| 20.21 – 22.63 | 7 |
| 22.63 – 25.05 | 12 |
| 25.05 – 27.47 | 12 |
| 27.47 – 29.89 | 7 |
| 29.89 – 32.3 | 4 |
| 32.3 – 34.72 | 10 |
| 34.72 – 37.14 | 13 |
| 37.14 – 39.56 | 24 |
| 39.56 – 41.97 | 18 |
| 41.97 – 44.39 | 24 |
| 44.39 – 46.81 | 30 |
| 46.81 – 49.23 | 24 |
| 49.23 – 51.64 | 34 |
| 51.64 – 54.06 | 33 |
| 54.06 – 56.48 | 37 |
| 56.48 – 58.9 | 58 |
| 58.9 – 61.32 | 43 |
| 61.32 – 63.73 | 69 |
| 63.73 – 66.15 | 72 |
| 66.15 – 68.57 | 77 |
| 68.57 – 70.99 | 76 |
| 70.99 – 73.4 | 88 |
| 73.4 – 75.82 | 100 |
| 75.82 – 78.24 | 98 |
| 78.24 – 80.66 | 143 |
| 80.66 – 83.08 | 132 |
| 83.08 – 85.49 | 163 |
| 85.49 – 87.91 | 191 |
| 87.91 – 90.33 | 246 |
| 90.33 – 92.75 | 302 |
| 92.75 – 95.16 | 453 |
| 95.16 – 97.58 | 525 |
| 97.58 – 100 | 67 |
This is a numeric percentage of Hispanic population per row, ranging 0 to 99.996 with a median of just 4.52 but a mean of 11.74, indicating a long right tail. Skew of 3.11 and kurtosis of 9.89 confirm heavy concentration at low values with 420 outliers (13.0% of rows) stretching toward 100. Near-zero null rate (0.0) and only 0.5% exact zeros suggest the values are continuously measured rather than sparsely populated.
Treatment: Apply a log1p or similar transform before modelling to tame the right skew and outliers.
saturn.columns["pct_hispanic"].stats
| stat | value |
|---|---|
| n | 3,221 |
| nulls | 0 (0.0%) |
| unique | 3,205 |
| min | 0 |
| max | 100 |
| mean | 11.74 |
| median | 4.516 |
| std | 19.4 |
| q1 | 2.363 |
| q3 | 10.66 |
| iqr | 8.294 |
| skew | 3.113 |
| kurtosis | 9.888 |
| n_outliers | 420 |
| outlier_rate | 0.1304 |
| zero_rate | 0.004967 |
| alert: high_skew | skew=+3.11 |
| alert: outliers | 13.0% rows beyond 1.5 IQR |
pct_hispanic. Vertical dash marks the median.
| bin | count |
|---|---|
| 0 – 2.5 | 882 |
| 2.5 – 5 | 850 |
| 5 – 7.5 | 412 |
| 7.5 – 10 | 213 |
| 10 – 12.5 | 148 |
| 12.5 – 15 | 102 |
| 15 – 17.5 | 75 |
| 17.5 – 20 | 64 |
| 20 – 22.5 | 45 |
| 22.5 – 25 | 49 |
| 25 – 27.5 | 39 |
| 27.5 – 30 | 30 |
| 30 – 32.5 | 26 |
| 32.5 – 35 | 18 |
| 35 – 37.5 | 17 |
| 37.5 – 40 | 15 |
| 40 – 42.5 | 17 |
| 42.5 – 45 | 15 |
| 45 – 47.5 | 12 |
| 47.5 – 50 | 10 |
| 50 – 52.5 | 12 |
| 52.5 – 55 | 12 |
| 55 – 57.5 | 9 |
| 57.5 – 60 | 12 |
| 60 – 62.5 | 10 |
| 62.5 – 65 | 9 |
| 65 – 67.5 | 3 |
| 67.5 – 70 | 6 |
| 70 – 72.5 | 3 |
| 72.5 – 75 | 3 |
| 75 – 77.5 | 0 |
| 77.5 – 80 | 3 |
| 80 – 82.5 | 4 |
| 82.5 – 85 | 5 |
| 85 – 87.5 | 1 |
| 87.5 – 90 | 3 |
| 90 – 92.5 | 4 |
| 92.5 – 95 | 5 |
| 95 – 97.5 | 8 |
| 97.5 – 100 | 70 |
Continuous percentage values ranging from 0 to 66.19 with mean 15.38 and median 13.81, almost certainly a county- or area-level poverty rate. Distribution is right-skewed (skew 2.11, kurtosis 6.92) with 143 high-end outliers (4.4%) stretching well beyond Q3 of 18.25. Near-unique values across 3,221 rows (3,219 distinct) and effectively no zeros or nulls.
Treatment: Log- or Box-Cox-transform before regression to tame the right skew.
saturn.columns["poverty_rate"].stats
| stat | value |
|---|---|
| n | 3,221 |
| nulls | 0 (0.0%) |
| unique | 3,219 |
| min | 0 |
| max | 66.19 |
| mean | 15.38 |
| median | 13.81 |
| std | 7.97 |
| q1 | 10.34 |
| q3 | 18.25 |
| iqr | 7.91 |
| skew | 2.111 |
| kurtosis | 6.922 |
| n_outliers | 143 |
| outlier_rate | 0.0444 |
| zero_rate | 0.0003105 |
| alert: high_skew | skew=+2.11 |
poverty_rate. Vertical dash marks the median.
| bin | count |
|---|---|
| 0 – 1.655 | 2 |
| 1.655 – 3.31 | 9 |
| 3.31 – 4.964 | 48 |
| 4.964 – 6.619 | 123 |
| 6.619 – 8.274 | 212 |
| 8.274 – 9.929 | 317 |
| 9.929 – 11.58 | 378 |
| 11.58 – 13.24 | 392 |
| 13.24 – 14.89 | 353 |
| 14.89 – 16.55 | 338 |
| 16.55 – 18.2 | 235 |
| 18.2 – 19.86 | 192 |
| 19.86 – 21.51 | 157 |
| 21.51 – 23.17 | 108 |
| 23.17 – 24.82 | 77 |
| 24.82 – 26.48 | 53 |
| 26.48 – 28.13 | 41 |
| 28.13 – 29.79 | 37 |
| 29.79 – 31.44 | 29 |
| 31.44 – 33.1 | 13 |
| 33.1 – 34.75 | 10 |
| 34.75 – 36.41 | 11 |
| 36.41 – 38.06 | 7 |
| 38.06 – 39.72 | 2 |
| 39.72 – 41.37 | 8 |
| 41.37 – 43.03 | 6 |
| 43.03 – 44.68 | 7 |
| 44.68 – 46.33 | 11 |
| 46.33 – 47.99 | 6 |
| 47.99 – 49.64 | 9 |
| 49.64 – 51.3 | 8 |
| 51.3 – 52.95 | 5 |
| 52.95 – 54.61 | 6 |
| 54.61 – 56.26 | 2 |
| 56.26 – 57.92 | 2 |
| 57.92 – 59.57 | 3 |
| 59.57 – 61.23 | 1 |
| 61.23 – 62.88 | 1 |
| 62.88 – 64.54 | 0 |
| 64.54 – 66.19 | 2 |
This column appears to be a count of residents below the poverty level per geographic unit, ranging from 0 to 1,401,656 with a median of 3,831. The distribution is severely right-skewed (skew 15.1, kurtosis 360.7) with the mean (13,136) more than three times the median and 351 outliers (10.9% of rows). Standard deviation (44,284) dwarfs the IQR (8,390), consistent with a few very large jurisdictions dominating the tail.
Treatment: Log-transform (or normalize per population) before modelling to tame the heavy right tail.
saturn.columns["below_poverty_level"].stats
| stat | value |
|---|---|
| n | 3,221 |
| nulls | 0 (0.0%) |
| unique | 2,824 |
| min | 0 |
| max | 1.402e+06 |
| mean | 1.314e+04 |
| median | 3,831 |
| std | 4.428e+04 |
| q1 | 1,547 |
| q3 | 9,937 |
| iqr | 8,390 |
| skew | 15.11 |
| kurtosis | 360.7 |
| n_outliers | 351 |
| outlier_rate | 0.109 |
| zero_rate | 0.0003105 |
| alert: high_skew | skew=+15.11 |
| alert: outliers | 10.9% rows beyond 1.5 IQR |
below_poverty_level. Vertical dash marks the median.
| bin | count |
|---|---|
| 0 – 3.504e+04 | 2980 |
| 3.504e+04 – 7.008e+04 | 136 |
| 7.008e+04 – 1.051e+05 | 50 |
| 1.051e+05 – 1.402e+05 | 19 |
| 1.402e+05 – 1.752e+05 | 7 |
| 1.752e+05 – 2.102e+05 | 8 |
| 2.102e+05 – 2.453e+05 | 3 |
| 2.453e+05 – 2.803e+05 | 2 |
| 2.803e+05 – 3.154e+05 | 3 |
| 3.154e+05 – 3.504e+05 | 2 |
| 3.504e+05 – 3.855e+05 | 5 |
| 3.855e+05 – 4.205e+05 | 0 |
| 4.205e+05 – 4.555e+05 | 1 |
| 4.555e+05 – 4.906e+05 | 1 |
| 4.906e+05 – 5.256e+05 | 0 |
| 5.256e+05 – 5.607e+05 | 1 |
| 5.607e+05 – 5.957e+05 | 0 |
| 5.957e+05 – 6.307e+05 | 0 |
| 6.307e+05 – 6.658e+05 | 0 |
| 6.658e+05 – 7.008e+05 | 1 |
| 7.008e+05 – 7.359e+05 | 1 |
| 7.359e+05 – 7.709e+05 | 0 |
| 7.709e+05 – 8.06e+05 | 0 |
| 8.06e+05 – 8.41e+05 | 0 |
| 8.41e+05 – 8.76e+05 | 0 |
| 8.76e+05 – 9.111e+05 | 0 |
| 9.111e+05 – 9.461e+05 | 0 |
| 9.461e+05 – 9.812e+05 | 0 |
| 9.812e+05 – 1.016e+06 | 0 |
| 1.016e+06 – 1.051e+06 | 0 |
| 1.051e+06 – 1.086e+06 | 0 |
| 1.086e+06 – 1.121e+06 | 0 |
| 1.121e+06 – 1.156e+06 | 0 |
| 1.156e+06 – 1.191e+06 | 0 |
| 1.191e+06 – 1.226e+06 | 0 |
| 1.226e+06 – 1.261e+06 | 0 |
| 1.261e+06 – 1.297e+06 | 0 |
| 1.297e+06 – 1.332e+06 | 0 |
| 1.332e+06 – 1.367e+06 | 0 |
| 1.367e+06 – 1.402e+06 | 1 |
Median household income per record (n=3221, 3099 unique, no nulls) with a typical value near the median of 52380 and IQR of 16300. The mean of -152820 and min of -666666666 betray a sentinel value masquerading as data, producing extreme skew (-56.73) and kurtosis (3215.99) plus 182 flagged outliers. Once those sentinels are removed, the q1/q3 range of 44939-61239 looks like plausible US county-level income.
Treatment: Replace the -666666666 sentinel with null, then consider winsorizing or log-transforming before modelling.
saturn.columns["median_household_income"].stats
| stat | value |
|---|---|
| n | 3,221 |
| nulls | 0 (0.0%) |
| unique | 3,099 |
| min | -6.667e+08 |
| max | 147,111 |
| mean | -1.528e+05 |
| median | 52,380 |
| std | 1.175e+07 |
| q1 | 44,939 |
| q3 | 61,239 |
| iqr | 16,300 |
| skew | -56.73 |
| kurtosis | 3216 |
| n_outliers | 182 |
| outlier_rate | 0.0565 |
| zero_rate | 0 |
| alert: high_skew | skew=-56.73 |
| alert: outliers | 5.7% rows beyond 1.5 IQR |
median_household_income. Vertical dash marks the median.
| bin | count |
|---|---|
| -6.667e+08 – -6.5e+08 | 1 |
| -6.5e+08 – -6.333e+08 | 0 |
| -6.333e+08 – -6.167e+08 | 0 |
| -6.167e+08 – -6e+08 | 0 |
| -6e+08 – -5.833e+08 | 0 |
| -5.833e+08 – -5.666e+08 | 0 |
| -5.666e+08 – -5.5e+08 | 0 |
| -5.5e+08 – -5.333e+08 | 0 |
| -5.333e+08 – -5.166e+08 | 0 |
| -5.166e+08 – -5e+08 | 0 |
| -5e+08 – -4.833e+08 | 0 |
| -4.833e+08 – -4.666e+08 | 0 |
| -4.666e+08 – -4.5e+08 | 0 |
| -4.5e+08 – -4.333e+08 | 0 |
| -4.333e+08 – -4.166e+08 | 0 |
| -4.166e+08 – -3.999e+08 | 0 |
| -3.999e+08 – -3.833e+08 | 0 |
| -3.833e+08 – -3.666e+08 | 0 |
| -3.666e+08 – -3.499e+08 | 0 |
| -3.499e+08 – -3.333e+08 | 0 |
| -3.333e+08 – -3.166e+08 | 0 |
| -3.166e+08 – -2.999e+08 | 0 |
| -2.999e+08 – -2.832e+08 | 0 |
| -2.832e+08 – -2.666e+08 | 0 |
| -2.666e+08 – -2.499e+08 | 0 |
| -2.499e+08 – -2.332e+08 | 0 |
| -2.332e+08 – -2.166e+08 | 0 |
| -2.166e+08 – -1.999e+08 | 0 |
| -1.999e+08 – -1.832e+08 | 0 |
| -1.832e+08 – -1.666e+08 | 0 |
| -1.666e+08 – -1.499e+08 | 0 |
| -1.499e+08 – -1.332e+08 | 0 |
| -1.332e+08 – -1.165e+08 | 0 |
| -1.165e+08 – -9.987e+07 | 0 |
| -9.987e+07 – -8.32e+07 | 0 |
| -8.32e+07 – -6.653e+07 | 0 |
| -6.653e+07 – -4.986e+07 | 0 |
| -4.986e+07 – -3.319e+07 | 0 |
| -3.319e+07 – -1.652e+07 | 0 |
| -1.652e+07 – 1.471e+05 | 3220 |
Numeric margin values for 2020, almost entirely unique across 3,221 rows (3,112 distinct), ranging from -0.87 to 0.93 with a mean of 0.317 and median 0.384. The distribution is left-skewed (skew -0.82), suggesting most observations cluster on the positive side while a tail of negative margins pulls the mean down. About 3.4% of rows are null and only 1.5% are flagged as outliers, with no zero values at all.
Treatment: Use directly as a signed numeric feature; impute the 3.4% nulls and retain sign since negatives are meaningful.
saturn.columns["margin_2020"].stats
| stat | value |
|---|---|
| n | 3,221 |
| nulls | 109 (3.4%) |
| unique | 3,112 |
| min | -0.8675 |
| max | 0.9309 |
| mean | 0.317 |
| median | 0.3844 |
| std | 0.321 |
| q1 | 0.1348 |
| q3 | 0.5662 |
| iqr | 0.4314 |
| skew | -0.8212 |
| kurtosis | 0.2286 |
| n_outliers | 48 |
| outlier_rate | 0.01542 |
| zero_rate | 0 |
margin_2020. Vertical dash marks the median.
| bin | count |
|---|---|
| -0.8675 – -0.8226 | 1 |
| -0.8226 – -0.7776 | 2 |
| -0.7776 – -0.7326 | 3 |
| -0.7326 – -0.6877 | 5 |
| -0.6877 – -0.6427 | 8 |
| -0.6427 – -0.5978 | 12 |
| -0.5978 – -0.5528 | 6 |
| -0.5528 – -0.5078 | 12 |
| -0.5078 – -0.4629 | 14 |
| -0.4629 – -0.4179 | 22 |
| -0.4179 – -0.373 | 28 |
| -0.373 – -0.328 | 33 |
| -0.328 – -0.283 | 29 |
| -0.283 – -0.2381 | 46 |
| -0.2381 – -0.1931 | 41 |
| -0.1931 – -0.1482 | 54 |
| -0.1482 – -0.1032 | 63 |
| -0.1032 – -0.05823 | 67 |
| -0.05823 – -0.01327 | 69 |
| -0.01327 – 0.03169 | 73 |
| 0.03169 – 0.07665 | 70 |
| 0.07665 – 0.1216 | 90 |
| 0.1216 – 0.1666 | 131 |
| 0.1666 – 0.2115 | 117 |
| 0.2115 – 0.2565 | 129 |
| 0.2565 – 0.3015 | 141 |
| 0.3015 – 0.3464 | 159 |
| 0.3464 – 0.3914 | 165 |
| 0.3914 – 0.4363 | 181 |
| 0.4363 – 0.4813 | 206 |
| 0.4813 – 0.5263 | 195 |
| 0.5263 – 0.5712 | 197 |
| 0.5712 – 0.6162 | 213 |
| 0.6162 – 0.6611 | 175 |
| 0.6611 – 0.7061 | 140 |
| 0.7061 – 0.7511 | 102 |
| 0.7511 – 0.796 | 69 |
| 0.796 – 0.841 | 29 |
| 0.841 – 0.8859 | 11 |
| 0.8859 – 0.9309 | 4 |
This is the share of votes cast for the Democratic candidate in 2020, recorded per row (likely county-level given n=3221). Values range from 0.031 to 0.921 with a median of 0.300 and mean of 0.333, indicating most units lean Republican while a long right tail of heavily Democratic units pulls the mean up (skew 0.83). About 3.4% of rows are null and 49 outliers (1.6%) sit beyond the whiskers; no zeros are present.
Treatment: Use as-is as a proportion feature; impute the 3.4% nulls or drop those rows before modelling.
saturn.columns["democratic_pct_2020"].stats
| stat | value |
|---|---|
| n | 3,221 |
| nulls | 109 (3.4%) |
| unique | 3,111 |
| min | 0.03091 |
| max | 0.9215 |
| mean | 0.3327 |
| median | 0.2998 |
| std | 0.1598 |
| q1 | 0.2091 |
| q3 | 0.4236 |
| iqr | 0.2145 |
| skew | 0.8326 |
| kurtosis | 0.2523 |
| n_outliers | 49 |
| outlier_rate | 0.01575 |
| zero_rate | 0 |
democratic_pct_2020. Vertical dash marks the median.
| bin | count |
|---|---|
| 0.03091 – 0.05317 | 5 |
| 0.05317 – 0.07544 | 11 |
| 0.07544 – 0.0977 | 31 |
| 0.0977 – 0.12 | 76 |
| 0.12 – 0.1422 | 104 |
| 0.1422 – 0.1645 | 145 |
| 0.1645 – 0.1868 | 182 |
| 0.1868 – 0.209 | 224 |
| 0.209 – 0.2313 | 192 |
| 0.2313 – 0.2536 | 199 |
| 0.2536 – 0.2758 | 200 |
| 0.2758 – 0.2981 | 174 |
| 0.2981 – 0.3204 | 164 |
| 0.3204 – 0.3426 | 158 |
| 0.3426 – 0.3649 | 130 |
| 0.3649 – 0.3871 | 132 |
| 0.3871 – 0.4094 | 121 |
| 0.4094 – 0.4317 | 125 |
| 0.4317 – 0.4539 | 84 |
| 0.4539 – 0.4762 | 79 |
| 0.4762 – 0.4985 | 66 |
| 0.4985 – 0.5207 | 73 |
| 0.5207 – 0.543 | 67 |
| 0.543 – 0.5653 | 58 |
| 0.5653 – 0.5875 | 50 |
| 0.5875 – 0.6098 | 42 |
| 0.6098 – 0.6321 | 42 |
| 0.6321 – 0.6543 | 34 |
| 0.6543 – 0.6766 | 28 |
| 0.6766 – 0.6988 | 29 |
| 0.6988 – 0.7211 | 22 |
| 0.7211 – 0.7434 | 14 |
| 0.7434 – 0.7656 | 13 |
| 0.7656 – 0.7879 | 7 |
| 0.7879 – 0.8102 | 8 |
| 0.8102 – 0.8324 | 11 |
| 0.8324 – 0.8547 | 5 |
| 0.8547 – 0.877 | 3 |
| 0.877 – 0.8992 | 3 |
| 0.8992 – 0.9215 | 1 |
This is the 2020 Republican vote share by what looks like a U.S. county-level unit, with 3221 rows and a mean of 0.65 and median 0.68. The distribution is left-skewed (skew -0.81) toward strongly Republican counties, ranging from 0.054 to 0.962, and 3.38% of rows are null. Only 47 outliers (1.5%) and near-unique values (3111 distinct) are consistent with continuous geographic shares.
Treatment: Use as-is as a continuous feature; impute or drop the 3.38% missing rows before modelling.
saturn.columns["republican_pct_2020"].stats
| stat | value |
|---|---|
| n | 3,221 |
| nulls | 109 (3.4%) |
| unique | 3,111 |
| min | 0.05397 |
| max | 0.9618 |
| mean | 0.6497 |
| median | 0.6829 |
| std | 0.1613 |
| q1 | 0.5576 |
| q3 | 0.7747 |
| iqr | 0.2171 |
| skew | -0.8091 |
| kurtosis | 0.2063 |
| n_outliers | 47 |
| outlier_rate | 0.0151 |
| zero_rate | 0 |
republican_pct_2020. Vertical dash marks the median.
| bin | count |
|---|---|
| 0.05397 – 0.07667 | 1 |
| 0.07667 – 0.09937 | 2 |
| 0.09937 – 0.1221 | 2 |
| 0.1221 – 0.1448 | 6 |
| 0.1448 – 0.1675 | 6 |
| 0.1675 – 0.1901 | 15 |
| 0.1901 – 0.2128 | 5 |
| 0.2128 – 0.2355 | 13 |
| 0.2355 – 0.2582 | 12 |
| 0.2582 – 0.2809 | 25 |
| 0.2809 – 0.3036 | 26 |
| 0.3036 – 0.3263 | 32 |
| 0.3263 – 0.349 | 32 |
| 0.349 – 0.3717 | 40 |
| 0.3717 – 0.3944 | 46 |
| 0.3944 – 0.4171 | 52 |
| 0.4171 – 0.4398 | 64 |
| 0.4398 – 0.4625 | 78 |
| 0.4625 – 0.4852 | 61 |
| 0.4852 – 0.5079 | 78 |
| 0.5079 – 0.5306 | 66 |
| 0.5306 – 0.5533 | 97 |
| 0.5533 – 0.576 | 126 |
| 0.576 – 0.5987 | 122 |
| 0.5987 – 0.6214 | 139 |
| 0.6214 – 0.6441 | 143 |
| 0.6441 – 0.6668 | 154 |
| 0.6668 – 0.6895 | 173 |
| 0.6895 – 0.7122 | 176 |
| 0.7122 – 0.7349 | 200 |
| 0.7349 – 0.7576 | 213 |
| 0.7576 – 0.7802 | 195 |
| 0.7802 – 0.8029 | 203 |
| 0.8029 – 0.8256 | 169 |
| 0.8256 – 0.8483 | 132 |
| 0.8483 – 0.871 | 103 |
| 0.871 – 0.8937 | 65 |
| 0.8937 – 0.9164 | 27 |
| 0.9164 – 0.9391 | 9 |
| 0.9391 – 0.9618 | 4 |
This column stores a 2016 margin as a short percentage string (e.g. '15.17%', '26.55%'), with lengths capped at 5-6 characters and exactly one 'word' per row. Despite the percent formatting it's stored as text, and 18.6% of values are duplicates with '15.17%' alone appearing 29 times — worth checking whether that's a placeholder or genuine repeat. Null rate is 2.58% and there are 2554 unique values across 3221 rows.
Treatment: Strip the '%' and cast to float before any numeric analysis.
saturn.columns["margin_2016"].stats
| stat | value |
|---|---|
| n | 3,221 |
| nulls | 83 (2.6%) |
| unique | 2,554 |
| len_min | 5 |
| len_max | 6 |
| len_mean | 5.896 |
| len_median | 6 |
| len_p95 | 6 |
| word_mean | 1 |
| word_median | 1 |
| n_empty | 0 |
| n_duplicates | 584 |
| duplicate_rate | 0.1861 |
| vocab_size | 2,554 |
| readability_flesch_mean | 121.2 |
| emoji_rate | 0 |
| url_rate | 0 |
| one_word_rate | 1 |
| allcaps_rate | 1 |
| boilerplate_rate | 0 |
| alert: one_word | 100.0% rows are a single word |
| alert: allcaps | 100.0% rows are all-caps |
| alert: short_text | 95th-percentile length under 20 chars |
margin_2016.
| chars | count |
|---|---|
| 5 – 5 | 327 |
| 5 – 5 | 0 |
| 5 – 5 | 0 |
| 5 – 5 | 0 |
| 5 – 5 | 0 |
| 5 – 5 | 0 |
| 5 – 5 | 0 |
| 5 – 5 | 0 |
| 5 – 5 | 0 |
| 5 – 5 | 0 |
| 5 – 5 | 0 |
| 5 – 5 | 0 |
| 5 – 5 | 0 |
| 5 – 5 | 0 |
| 5 – 5 | 0 |
| 5 – 5 | 0 |
| 5 – 5 | 0 |
| 5 – 5 | 0 |
| 5 – 5 | 0 |
| 5 – 6 | 0 |
| 6 – 6 | 0 |
| 6 – 6 | 0 |
| 6 – 6 | 0 |
| 6 – 6 | 0 |
| 6 – 6 | 0 |
| 6 – 6 | 0 |
| 6 – 6 | 0 |
| 6 – 6 | 0 |
| 6 – 6 | 0 |
| 6 – 6 | 0 |
| 6 – 6 | 0 |
| 6 – 6 | 0 |
| 6 – 6 | 0 |
| 6 – 6 | 0 |
| 6 – 6 | 0 |
| 6 – 6 | 0 |
| 6 – 6 | 0 |
| 6 – 6 | 0 |
| 6 – 6 | 0 |
| 6 – 6 | 2811 |
Share of the 2016 vote going Democratic, recorded per row (likely county-level given n=3221). Values range from 0.031 to 0.928 with a mean of 0.317 and median 0.286, and the right skew of 0.94 reflects a long tail of heavily Democratic jurisdictions amid a mass of Republican-leaning ones. About 2.6% of rows are null and 75 high-side outliers (2.4%) sit above the IQR fence.
Treatment: Use as-is as a proportion feature; impute or drop the 2.6% nulls before modelling.
saturn.columns["democratic_pct_2016"].stats
| stat | value |
|---|---|
| n | 3,221 |
| nulls | 83 (2.6%) |
| unique | 3,111 |
| min | 0.03145 |
| max | 0.9285 |
| mean | 0.3174 |
| median | 0.2861 |
| std | 0.1527 |
| q1 | 0.2054 |
| q3 | 0.3982 |
| iqr | 0.1928 |
| skew | 0.9371 |
| kurtosis | 0.666 |
| n_outliers | 75 |
| outlier_rate | 0.0239 |
| zero_rate | 0 |
democratic_pct_2016. Vertical dash marks the median.
| bin | count |
|---|---|
| 0.03145 – 0.05387 | 8 |
| 0.05387 – 0.0763 | 16 |
| 0.0763 – 0.09872 | 52 |
| 0.09872 – 0.1211 | 74 |
| 0.1211 – 0.1436 | 116 |
| 0.1436 – 0.166 | 146 |
| 0.166 – 0.1884 | 203 |
| 0.1884 – 0.2109 | 226 |
| 0.2109 – 0.2333 | 240 |
| 0.2333 – 0.2557 | 218 |
| 0.2557 – 0.2781 | 200 |
| 0.2781 – 0.3006 | 205 |
| 0.3006 – 0.323 | 153 |
| 0.323 – 0.3454 | 147 |
| 0.3454 – 0.3678 | 153 |
| 0.3678 – 0.3903 | 150 |
| 0.3903 – 0.4127 | 106 |
| 0.4127 – 0.4351 | 111 |
| 0.4351 – 0.4575 | 77 |
| 0.4575 – 0.48 | 78 |
| 0.48 – 0.5024 | 56 |
| 0.5024 – 0.5248 | 72 |
| 0.5248 – 0.5472 | 45 |
| 0.5472 – 0.5697 | 42 |
| 0.5697 – 0.5921 | 36 |
| 0.5921 – 0.6145 | 36 |
| 0.6145 – 0.6369 | 34 |
| 0.6369 – 0.6594 | 25 |
| 0.6594 – 0.6818 | 30 |
| 0.6818 – 0.7042 | 16 |
| 0.7042 – 0.7266 | 12 |
| 0.7266 – 0.7491 | 12 |
| 0.7491 – 0.7715 | 14 |
| 0.7715 – 0.7939 | 9 |
| 0.7939 – 0.8163 | 6 |
| 0.8163 – 0.8388 | 4 |
| 0.8388 – 0.8612 | 4 |
| 0.8612 – 0.8836 | 3 |
| 0.8836 – 0.906 | 2 |
| 0.906 – 0.9285 | 1 |
This column captures the Republican vote share by unit (likely US county) in the 2016 election, expressed as a proportion between 0.041 and 0.953. The distribution is left-skewed (skew -0.81) with a median of 0.666 above the mean of 0.635, indicating most units leaned Republican while a smaller tail of strongly Democratic units pulls the mean down. Near-unique values (3111 of 3221) and a 2.58% null rate are consistent with one row per geographic unit.
Treatment: Use as-is as a proportion feature; impute or drop the ~2.6% nulls before modelling.
saturn.columns["republican_pct_2016"].stats
| stat | value |
|---|---|
| n | 3,221 |
| nulls | 83 (2.6%) |
| unique | 3,111 |
| min | 0.04122 |
| max | 0.9527 |
| mean | 0.6354 |
| median | 0.6656 |
| std | 0.1559 |
| q1 | 0.5463 |
| q3 | 0.7503 |
| iqr | 0.2041 |
| skew | -0.8145 |
| kurtosis | 0.3566 |
| n_outliers | 62 |
| outlier_rate | 0.01976 |
| zero_rate | 0 |
republican_pct_2016. Vertical dash marks the median.
| bin | count |
|---|---|
| 0.04122 – 0.06401 | 1 |
| 0.06401 – 0.0868 | 1 |
| 0.0868 – 0.1096 | 5 |
| 0.1096 – 0.1324 | 2 |
| 0.1324 – 0.1552 | 6 |
| 0.1552 – 0.1779 | 11 |
| 0.1779 – 0.2007 | 7 |
| 0.2007 – 0.2235 | 17 |
| 0.2235 – 0.2463 | 17 |
| 0.2463 – 0.2691 | 17 |
| 0.2691 – 0.2919 | 23 |
| 0.2919 – 0.3147 | 32 |
| 0.3147 – 0.3375 | 34 |
| 0.3375 – 0.3602 | 30 |
| 0.3602 – 0.383 | 43 |
| 0.383 – 0.4058 | 41 |
| 0.4058 – 0.4286 | 64 |
| 0.4286 – 0.4514 | 71 |
| 0.4514 – 0.4742 | 63 |
| 0.4742 – 0.497 | 89 |
| 0.497 – 0.5198 | 78 |
| 0.5198 – 0.5425 | 115 |
| 0.5425 – 0.5653 | 116 |
| 0.5653 – 0.5881 | 147 |
| 0.5881 – 0.6109 | 147 |
| 0.6109 – 0.6337 | 156 |
| 0.6337 – 0.6565 | 165 |
| 0.6565 – 0.6793 | 193 |
| 0.6793 – 0.7021 | 190 |
| 0.7021 – 0.7249 | 215 |
| 0.7249 – 0.7476 | 223 |
| 0.7476 – 0.7704 | 213 |
| 0.7704 – 0.7932 | 187 |
| 0.7932 – 0.816 | 142 |
| 0.816 – 0.8388 | 113 |
| 0.8388 – 0.8616 | 74 |
| 0.8616 – 0.8844 | 49 |
| 0.8844 – 0.9072 | 29 |
| 0.9072 – 0.9299 | 9 |
| 0.9299 – 0.9527 | 3 |
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@misc{saturn-scars-master-dataset-2026,
author = {Steuber, Luke},
title = {Saturn reading: scars master dataset},
year ={2026},
howpublished = {\url{https://dr.eamer.dev/saturn/view/scars-master_dataset}},
note = {Profiled with saturn-dissect v0.2.0, prompt saturn-insight-v2, model anthropic:claude-opus-4-7},
}
Steuber, L. (2026). Saturn reading: scars master dataset. Source: /home/coolhand/html/datavis/data_trove/data/geographic/scars/master_dataset.csv. Profiled with saturn-dissect v0.2.0 (saturn-insight-v2, anthropic:claude-opus-4-7). Retrieved from https://dr.eamer.dev/saturn/view/scars-master_dataset