Source: /home/coolhand/html/datavis/data_trove/data/urban/nyc_housing/nyc_housing_metrics_merged.csv
Saturn profiled 2,327 rows across 23 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/urban/nyc_housing/nyc_housing_metrics_merged.csv",
"--findings", "nyc_housing-nyc_housing_metrics_merged.json",
"--llm", "anthropic:claude-opus-4-7",
])This dataset covers 2,327 NYC census tracts with 23 columns describing housing tenure, rent burden, income, and rent levels across the five boroughs. The most urgent issue is data hygiene: median_gross_rent and median_household_income both contain a sentinel value of -666666666, which drags their means to roughly -41.5M and -36M respectively despite sensible medians (~$1,735 rent, ~$76,833 income) — these need to be filtered before any analysis. Beyond that, the substantive story is rent burden: pct_rent_burdened has a median of 50% with an IQR of 40.9–58.8, meaning half of NYC tracts have a majority of renters paying 30%+ of income on rent. Brooklyn (Kings) dominates the tract count at 35%, followed by Queens (31%) and the Bronx (15%), so any borough-level comparison should weight accordingly. The state column is constant (all 36, New York) and can be dropped.
citing: median_gross_rent · median_household_income · pct_rent_burdened · pct_severe_burden · pct_owner_occupied · county_name · state · total_households
saturn.schema() · 23 columns
| column | kind | n | null% | unique | alerts |
|---|---|---|---|---|---|
| total_renter_households | numeric | 2,327 | 0.0% | 1,418 | |
| rent_30_to_34_9_pct | numeric | 2,327 | 0.0% | 355 | high_skew outliers |
| rent_35_to_39_9_pct | numeric | 2,327 | 0.0% | 270 | high_skew |
| rent_40_to_49_9_pct | numeric | 2,327 | 0.0% | 322 | high_skew |
| rent_50_pct_or_more | numeric | 2,327 | 0.0% | 706 | |
| NAME | text | 2,327 | 0.0% | 2,327 | near_unique |
| state | numeric | 2,327 | 0.0% | 1 | constant |
| county | numeric | 2,327 | 0.0% | 5 | |
| tract | numeric | 2,327 | 0.0% | 1,530 | high_skew |
| county_name | categorical | 2,327 | 0.0% | 5 | |
| moderate_burden | numeric | 2,327 | 0.0% | 639 | |
| severe_burden | numeric | 2,327 | 0.0% | 706 | |
| pct_moderate_burden | numeric | 2,327 | 4.4% | 461 | |
| pct_severe_burden | numeric | 2,327 | 4.4% | 518 | |
| rent_burdened | numeric | 2,327 | 0.0% | 1,013 | |
| pct_rent_burdened | numeric | 2,327 | 4.4% | 596 | |
| median_gross_rent | numeric | 2,327 | 0.0% | 1,232 | high_skew outliers |
| median_household_income | numeric | 2,327 | 0.0% | 2,106 | high_skew outliers |
| total_households | numeric | 2,327 | 0.0% | 1,495 | |
| owner_occupied | numeric | 2,327 | 0.0% | 1,001 | outliers |
| renter_occupied | numeric | 2,327 | 0.0% | 1,418 | |
| pct_owner_occupied | numeric | 2,327 | 4.1% | 823 | |
| pct_renter_occupied | numeric | 2,327 | 4.1% | 823 |
| value | count | share |
|---|---|---|
| Brooklyn (Kings) | 805 | 34.6% |
| Queens | 725 | 31.2% |
| Bronx | 361 | 15.5% |
| Manhattan (New York) | 310 | 13.3% |
| Staten Island (Richmond) | 126 | 5.4% |
| bin | count |
|---|---|
| 0 – 2.5 | 8 |
| 2.5 – 5 | 3 |
| 5 – 7.5 | 1 |
| 7.5 – 10 | 5 |
| 10 – 12.5 | 7 |
| 12.5 – 15 | 8 |
| 15 – 17.5 | 12 |
| 17.5 – 20 | 14 |
| 20 – 22.5 | 14 |
| 22.5 – 25 | 24 |
| 25 – 27.5 | 35 |
| 27.5 – 30 | 42 |
| 30 – 32.5 | 53 |
| 32.5 – 35 | 80 |
| 35 – 37.5 | 91 |
| 37.5 – 40 | 119 |
| 40 – 42.5 | 129 |
| 42.5 – 45 | 144 |
| 45 – 47.5 | 146 |
| 47.5 – 50 | 177 |
| 50 – 52.5 | 139 |
| 52.5 – 55 | 178 |
| 55 – 57.5 | 162 |
| 57.5 – 60 | 131 |
| 60 – 62.5 | 117 |
| 62.5 – 65 | 97 |
| 65 – 67.5 | 60 |
| 67.5 – 70 | 57 |
| 70 – 72.5 | 54 |
| 72.5 – 75 | 28 |
| 75 – 77.5 | 20 |
| 77.5 – 80 | 25 |
| 80 – 82.5 | 8 |
| 82.5 – 85 | 4 |
| 85 – 87.5 | 12 |
| 87.5 – 90 | 5 |
| 90 – 92.5 | 5 |
| 92.5 – 95 | 3 |
| 95 – 97.5 | 0 |
| 97.5 – 100 | 8 |
| bin | count |
|---|---|
| 0 – 2.5 | 45 |
| 2.5 – 5 | 14 |
| 5 – 7.5 | 41 |
| 7.5 – 10 | 53 |
| 10 – 12.5 | 94 |
| 12.5 – 15 | 115 |
| 15 – 17.5 | 131 |
| 17.5 – 20 | 160 |
| 20 – 22.5 | 170 |
| 22.5 – 25 | 188 |
| 25 – 27.5 | 188 |
| 27.5 – 30 | 168 |
| 30 – 32.5 | 173 |
| 32.5 – 35 | 157 |
| 35 – 37.5 | 115 |
| 37.5 – 40 | 97 |
| 40 – 42.5 | 73 |
| 42.5 – 45 | 62 |
| 45 – 47.5 | 44 |
| 47.5 – 50 | 35 |
| 50 – 52.5 | 29 |
| 52.5 – 55 | 19 |
| 55 – 57.5 | 18 |
| 57.5 – 60 | 12 |
| 60 – 62.5 | 6 |
| 62.5 – 65 | 4 |
| 65 – 67.5 | 4 |
| 67.5 – 70 | 2 |
| 70 – 72.5 | 1 |
| 72.5 – 75 | 1 |
| 75 – 77.5 | 1 |
| 77.5 – 80 | 1 |
| 80 – 82.5 | 0 |
| 82.5 – 85 | 1 |
| 85 – 87.5 | 1 |
| 87.5 – 90 | 0 |
| 90 – 92.5 | 1 |
| 92.5 – 95 | 0 |
| 95 – 97.5 | 0 |
| 97.5 – 100 | 1 |
| bin | count |
|---|---|
| 0 – 2.5 | 141 |
| 2.5 – 5 | 86 |
| 5 – 7.5 | 71 |
| 7.5 – 10 | 63 |
| 10 – 12.5 | 86 |
| 12.5 – 15 | 65 |
| 15 – 17.5 | 72 |
| 17.5 – 20 | 88 |
| 20 – 22.5 | 98 |
| 22.5 – 25 | 88 |
| 25 – 27.5 | 79 |
| 27.5 – 30 | 67 |
| 30 – 32.5 | 70 |
| 32.5 – 35 | 56 |
| 35 – 37.5 | 76 |
| 37.5 – 40 | 68 |
| 40 – 42.5 | 59 |
| 42.5 – 45 | 72 |
| 45 – 47.5 | 58 |
| 47.5 – 50 | 54 |
| 50 – 52.5 | 70 |
| 52.5 – 55 | 59 |
| 55 – 57.5 | 55 |
| 57.5 – 60 | 39 |
| 60 – 62.5 | 44 |
| 62.5 – 65 | 40 |
| 65 – 67.5 | 52 |
| 67.5 – 70 | 34 |
| 70 – 72.5 | 40 |
| 72.5 – 75 | 47 |
| 75 – 77.5 | 32 |
| 77.5 – 80 | 48 |
| 80 – 82.5 | 31 |
| 82.5 – 85 | 27 |
| 85 – 87.5 | 26 |
| 87.5 – 90 | 24 |
| 90 – 92.5 | 23 |
| 92.5 – 95 | 8 |
| 95 – 97.5 | 6 |
| 97.5 – 100 | 9 |
| bin | count |
|---|---|
| 0 – 205.2 | 123 |
| 205.2 – 410.4 | 41 |
| 410.4 – 615.7 | 203 |
| 615.7 – 820.9 | 272 |
| 820.9 – 1026 | 269 |
| 1026 – 1231 | 237 |
| 1231 – 1437 | 215 |
| 1437 – 1642 | 221 |
| 1642 – 1847 | 162 |
| 1847 – 2052 | 134 |
| 2052 – 2257 | 94 |
| 2257 – 2463 | 101 |
| 2463 – 2668 | 66 |
| 2668 – 2873 | 39 |
| 2873 – 3078 | 35 |
| 3078 – 3284 | 24 |
| 3284 – 3489 | 22 |
| 3489 – 3694 | 8 |
| 3694 – 3899 | 7 |
| 3899 – 4104 | 9 |
| 4104 – 4310 | 13 |
| 4310 – 4515 | 9 |
| 4515 – 4720 | 5 |
| 4720 – 4925 | 5 |
| 4925 – 5131 | 3 |
| 5131 – 5336 | 2 |
| 5336 – 5541 | 2 |
| 5541 – 5746 | 0 |
| 5746 – 5952 | 1 |
| 5952 – 6157 | 1 |
| 6157 – 6362 | 0 |
| 6362 – 6567 | 0 |
| 6567 – 6772 | 1 |
| 6772 – 6978 | 2 |
| 6978 – 7183 | 0 |
| 7183 – 7388 | 0 |
| 7388 – 7593 | 0 |
| 7593 – 7799 | 0 |
| 7799 – 8004 | 0 |
| 8004 – 8209 | 1 |
| column | kind | null % |
|---|---|---|
| total_renter_households | numeric | 0.0% |
| rent_30_to_34_9_pct | numeric | 0.0% |
| rent_35_to_39_9_pct | numeric | 0.0% |
| rent_40_to_49_9_pct | numeric | 0.0% |
| rent_50_pct_or_more | numeric | 0.0% |
| NAME | text | 0.0% |
| state | numeric | 0.0% |
| county | numeric | 0.0% |
| tract | numeric | 0.0% |
| county_name | categorical | 0.0% |
| moderate_burden | numeric | 0.0% |
| severe_burden | numeric | 0.0% |
| pct_moderate_burden | numeric | 4.4% |
| pct_severe_burden | numeric | 4.4% |
| rent_burdened | numeric | 0.0% |
| pct_rent_burdened | numeric | 4.4% |
| median_gross_rent | numeric | 0.0% |
| median_household_income | numeric | 0.0% |
| total_households | numeric | 0.0% |
| owner_occupied | numeric | 0.0% |
| renter_occupied | numeric | 0.0% |
| pct_owner_occupied | numeric | 4.1% |
| pct_renter_occupied | numeric | 4.1% |
| total_renter_households | rent_30_to_34_9_pct | rent_35_to_39_9_pct | rent_40_to_49_9_pct | rent_50_pct_or_more | state | county | tract | moderate_burden | severe_burden | pct_moderate_burden | pct_severe_burden | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| total_renter_households | +1.00 | +0.76 | +0.73 | +0.76 | +0.84 | +nan | -0.18 | -0.23 | +0.89 | +0.84 | -0.03 | +0.07 |
| rent_30_to_34_9_pct | +0.76 | +1.00 | +0.55 | +0.57 | +0.56 | +nan | -0.14 | -0.18 | +0.87 | +0.56 | -0.04 | +0.09 |
| rent_35_to_39_9_pct | +0.73 | +0.55 | +1.00 | +0.60 | +0.61 | +nan | -0.13 | -0.12 | +0.81 | +0.61 | -0.01 | +0.04 |
| rent_40_to_49_9_pct | +0.76 | +0.57 | +0.60 | +1.00 | +0.62 | +nan | -0.15 | -0.15 | +0.85 | +0.62 | -0.02 | +0.03 |
| rent_50_pct_or_more | +0.84 | +0.56 | +0.61 | +0.62 | +1.00 | +nan | -0.32 | -0.21 | +0.70 | +1.00 | +0.03 | +0.11 |
| state | +nan | +nan | +nan | +nan | +nan | +nan | +nan | +nan | +nan | +nan | +nan | +nan |
| county | -0.18 | -0.14 | -0.13 | -0.15 | -0.32 | +nan | +1.00 | +0.18 | -0.16 | -0.32 | -0.14 | -0.07 |
| tract | -0.23 | -0.18 | -0.12 | -0.15 | -0.21 | +nan | +0.18 | +1.00 | -0.18 | -0.21 | -0.04 | -0.04 |
| moderate_burden | +0.89 | +0.87 | +0.81 | +0.85 | +0.70 | +nan | -0.16 | -0.18 | +1.00 | +0.70 | -0.03 | +0.06 |
| severe_burden | +0.84 | +0.56 | +0.61 | +0.62 | +1.00 | +nan | -0.32 | -0.21 | +0.70 | +1.00 | +0.03 | +0.11 |
| pct_moderate_burden | -0.03 | -0.04 | -0.01 | -0.02 | +0.03 | +nan | -0.14 | -0.04 | -0.03 | +0.03 | +1.00 | -0.26 |
| pct_severe_burden | +0.07 | +0.09 | +0.04 | +0.03 | +0.11 | +nan | -0.07 | -0.04 | +0.06 | +0.11 | -0.26 | +1.00 |
This column counts renter households per record, ranging from 0 to 8209 with a median of 726 and mean of 946. The distribution is right-skewed (skew 1.59, kurtosis 4.63) with 69 outliers (2.97%) on the high end and 4.38% zero values. No nulls, and 1418 unique values across 2327 rows suggests aggregation at a geographic or administrative unit.
Treatment: Log-transform before regression to tame the right skew, and decide whether zero-count rows should be modelled separately.
saturn.columns["total_renter_households"].stats
| stat | value |
|---|---|
| n | 2,327 |
| nulls | 0 (0.0%) |
| unique | 1,418 |
| min | 0 |
| max | 8,209 |
| mean | 946.1 |
| median | 726 |
| std | 815.4 |
| q1 | 346 |
| q3 | 1,357 |
| iqr | 1,011 |
| skew | 1.595 |
| kurtosis | 4.627 |
| n_outliers | 69 |
| outlier_rate | 0.02965 |
| zero_rate | 0.04383 |
total_renter_households. Vertical dash marks the median.
| bin | count |
|---|---|
| 0 – 205.2 | 349 |
| 205.2 – 410.4 | 358 |
| 410.4 – 615.7 | 292 |
| 615.7 – 820.9 | 268 |
| 820.9 – 1026 | 207 |
| 1026 – 1231 | 175 |
| 1231 – 1437 | 168 |
| 1437 – 1642 | 110 |
| 1642 – 1847 | 100 |
| 1847 – 2052 | 68 |
| 2052 – 2257 | 63 |
| 2257 – 2463 | 42 |
| 2463 – 2668 | 36 |
| 2668 – 2873 | 22 |
| 2873 – 3078 | 19 |
| 3078 – 3284 | 17 |
| 3284 – 3489 | 6 |
| 3489 – 3694 | 5 |
| 3694 – 3899 | 4 |
| 3899 – 4104 | 6 |
| 4104 – 4310 | 5 |
| 4310 – 4515 | 3 |
| 4515 – 4720 | 1 |
| 4720 – 4925 | 0 |
| 4925 – 5131 | 1 |
| 5131 – 5336 | 1 |
| 5336 – 5541 | 0 |
| 5541 – 5746 | 0 |
| 5746 – 5952 | 0 |
| 5952 – 6157 | 0 |
| 6157 – 6362 | 0 |
| 6362 – 6567 | 0 |
| 6567 – 6772 | 0 |
| 6772 – 6978 | 0 |
| 6978 – 7183 | 0 |
| 7183 – 7388 | 0 |
| 7388 – 7593 | 0 |
| 7593 – 7799 | 0 |
| 7799 – 8004 | 0 |
| 8004 – 8209 | 1 |
Likely a count of households paying 30%-34.9% of income on rent within some geographic unit, given the integer-like values, zero floor, and max of 1205. The distribution is heavily right-skewed (skew 2.76, kurtosis 13.86) with a median of 51 against a mean of 83.05, and 16.2% of rows are exactly zero. 124 outliers (5.33%) extend far above the Q3 of 116, consistent with a few large areas dominating.
Treatment: log1p-transform before modelling to tame the skew and zero inflation.
saturn.columns["rent_30_to_34_9_pct"].stats
| stat | value |
|---|---|
| n | 2,327 |
| nulls | 0 (0.0%) |
| unique | 355 |
| min | 0 |
| max | 1,205 |
| mean | 83.05 |
| median | 51 |
| std | 100.3 |
| q1 | 15 |
| q3 | 116 |
| iqr | 101 |
| skew | 2.755 |
| kurtosis | 13.86 |
| n_outliers | 124 |
| outlier_rate | 0.05329 |
| zero_rate | 0.1616 |
| alert: high_skew | skew=+2.76 |
| alert: outliers | 5.3% rows beyond 1.5 IQR |
rent_30_to_34_9_pct. Vertical dash marks the median.
| bin | count |
|---|---|
| 0 – 30.12 | 836 |
| 30.12 – 60.25 | 444 |
| 60.25 – 90.38 | 275 |
| 90.38 – 120.5 | 217 |
| 120.5 – 150.6 | 152 |
| 150.6 – 180.8 | 105 |
| 180.8 – 210.9 | 90 |
| 210.9 – 241 | 48 |
| 241 – 271.1 | 41 |
| 271.1 – 301.2 | 25 |
| 301.2 – 331.4 | 17 |
| 331.4 – 361.5 | 21 |
| 361.5 – 391.6 | 15 |
| 391.6 – 421.8 | 9 |
| 421.8 – 451.9 | 11 |
| 451.9 – 482 | 5 |
| 482 – 512.1 | 2 |
| 512.1 – 542.2 | 2 |
| 542.2 – 572.4 | 4 |
| 572.4 – 602.5 | 1 |
| 602.5 – 632.6 | 0 |
| 632.6 – 662.8 | 1 |
| 662.8 – 692.9 | 1 |
| 692.9 – 723 | 0 |
| 723 – 753.1 | 1 |
| 753.1 – 783.2 | 2 |
| 783.2 – 813.4 | 0 |
| 813.4 – 843.5 | 0 |
| 843.5 – 873.6 | 1 |
| 873.6 – 903.8 | 0 |
| 903.8 – 933.9 | 0 |
| 933.9 – 964 | 0 |
| 964 – 994.1 | 0 |
| 994.1 – 1024 | 0 |
| 1024 – 1054 | 0 |
| 1054 – 1084 | 0 |
| 1084 – 1115 | 0 |
| 1115 – 1145 | 0 |
| 1145 – 1175 | 0 |
| 1175 – 1205 | 1 |
Likely a count of households (or housing units) paying 35% to 39.9% of income on rent within some geographic unit. The distribution is heavily right-skewed (skew 2.40, kurtosis 9.27) with a median of 35 but a max of 633, and nearly 20% of rows are zero (zero_rate 0.196), suggesting many small areas have no households in this rent burden bracket. 110 outliers (4.7%) sit well above the Q3 of 83.
Treatment: Log1p-transform before regression to tame the right skew and zero inflation.
saturn.columns["rent_35_to_39_9_pct"].stats
| stat | value |
|---|---|
| n | 2,327 |
| nulls | 0 (0.0%) |
| unique | 270 |
| min | 0 |
| max | 633 |
| mean | 58.35 |
| median | 35 |
| std | 69.85 |
| q1 | 10 |
| q3 | 83 |
| iqr | 73 |
| skew | 2.395 |
| kurtosis | 9.275 |
| n_outliers | 110 |
| outlier_rate | 0.04727 |
| zero_rate | 0.1964 |
| alert: high_skew | skew=+2.40 |
rent_35_to_39_9_pct. Vertical dash marks the median.
| bin | count |
|---|---|
| 0 – 15.82 | 719 |
| 15.82 – 31.65 | 371 |
| 31.65 – 47.47 | 261 |
| 47.47 – 63.3 | 212 |
| 63.3 – 79.12 | 163 |
| 79.12 – 94.95 | 103 |
| 94.95 – 110.8 | 97 |
| 110.8 – 126.6 | 77 |
| 126.6 – 142.4 | 77 |
| 142.4 – 158.2 | 58 |
| 158.2 – 174.1 | 32 |
| 174.1 – 189.9 | 41 |
| 189.9 – 205.7 | 20 |
| 205.7 – 221.5 | 18 |
| 221.5 – 237.4 | 15 |
| 237.4 – 253.2 | 10 |
| 253.2 – 269 | 14 |
| 269 – 284.8 | 5 |
| 284.8 – 300.7 | 3 |
| 300.7 – 316.5 | 8 |
| 316.5 – 332.3 | 6 |
| 332.3 – 348.1 | 2 |
| 348.1 – 364 | 2 |
| 364 – 379.8 | 2 |
| 379.8 – 395.6 | 1 |
| 395.6 – 411.4 | 1 |
| 411.4 – 427.3 | 2 |
| 427.3 – 443.1 | 2 |
| 443.1 – 458.9 | 0 |
| 458.9 – 474.8 | 0 |
| 474.8 – 490.6 | 1 |
| 490.6 – 506.4 | 0 |
| 506.4 – 522.2 | 0 |
| 522.2 – 538 | 0 |
| 538 – 553.9 | 0 |
| 553.9 – 569.7 | 2 |
| 569.7 – 585.5 | 0 |
| 585.5 – 601.4 | 1 |
| 601.4 – 617.2 | 0 |
| 617.2 – 633 | 1 |
Likely a count of housing units paying rent in the 40-49.9% income bracket per geographic area. The distribution is heavily right-skewed (skew 2.14, kurtosis 7.14) with a median of 49 but a max of 740 and 111 outliers (4.77%), and 15.6% of rows are zero — consistent with small geographies sitting alongside dense ones.
Treatment: log1p-transform before modelling to tame the right skew and zero mass.
saturn.columns["rent_40_to_49_9_pct"].stats
| stat | value |
|---|---|
| n | 2,327 |
| nulls | 0 (0.0%) |
| unique | 322 |
| min | 0 |
| max | 740 |
| mean | 74.68 |
| median | 49 |
| std | 83.79 |
| q1 | 14 |
| q3 | 106 |
| iqr | 92 |
| skew | 2.137 |
| kurtosis | 7.139 |
| n_outliers | 111 |
| outlier_rate | 0.0477 |
| zero_rate | 0.1556 |
| alert: high_skew | skew=+2.14 |
rent_40_to_49_9_pct. Vertical dash marks the median.
| bin | count |
|---|---|
| 0 – 18.5 | 671 |
| 18.5 – 37 | 306 |
| 37 – 55.5 | 270 |
| 55.5 – 74 | 201 |
| 74 – 92.5 | 196 |
| 92.5 – 111 | 134 |
| 111 – 129.5 | 102 |
| 129.5 – 148 | 86 |
| 148 – 166.5 | 78 |
| 166.5 – 185 | 63 |
| 185 – 203.5 | 39 |
| 203.5 – 222 | 38 |
| 222 – 240.5 | 26 |
| 240.5 – 259 | 27 |
| 259 – 277.5 | 16 |
| 277.5 – 296 | 16 |
| 296 – 314.5 | 13 |
| 314.5 – 333 | 11 |
| 333 – 351.5 | 5 |
| 351.5 – 370 | 3 |
| 370 – 388.5 | 5 |
| 388.5 – 407 | 3 |
| 407 – 425.5 | 4 |
| 425.5 – 444 | 1 |
| 444 – 462.5 | 4 |
| 462.5 – 481 | 0 |
| 481 – 499.5 | 1 |
| 499.5 – 518 | 2 |
| 518 – 536.5 | 0 |
| 536.5 – 555 | 0 |
| 555 – 573.5 | 2 |
| 573.5 – 592 | 0 |
| 592 – 610.5 | 1 |
| 610.5 – 629 | 1 |
| 629 – 647.5 | 1 |
| 647.5 – 666 | 0 |
| 666 – 684.5 | 0 |
| 684.5 – 703 | 0 |
| 703 – 721.5 | 0 |
| 721.5 – 740 | 1 |
Counts of households spending 50% or more of income on rent, aggregated per geographic unit across 2327 rows with no nulls. The distribution is right-skewed (skew 1.60, kurtosis 3.44) with a median of 184 well below the mean of 253.18 and a max of 1918, and 6.27% of rows are zero. About 3.74% of values fall outside the Tukey fence.
Treatment: Log1p-transform before modelling to tame the right skew.
saturn.columns["rent_50_pct_or_more"].stats
| stat | value |
|---|---|
| n | 2,327 |
| nulls | 0 (0.0%) |
| unique | 706 |
| min | 0 |
| max | 1,918 |
| mean | 253.2 |
| median | 184 |
| std | 236.6 |
| q1 | 82 |
| q3 | 360 |
| iqr | 278 |
| skew | 1.603 |
| kurtosis | 3.435 |
| n_outliers | 87 |
| outlier_rate | 0.03739 |
| zero_rate | 0.06274 |
rent_50_pct_or_more. Vertical dash marks the median.
| bin | count |
|---|---|
| 0 – 47.95 | 368 |
| 47.95 – 95.9 | 293 |
| 95.9 – 143.9 | 290 |
| 143.9 – 191.8 | 249 |
| 191.8 – 239.8 | 186 |
| 239.8 – 287.7 | 175 |
| 287.7 – 335.7 | 122 |
| 335.7 – 383.6 | 114 |
| 383.6 – 431.6 | 101 |
| 431.6 – 479.5 | 83 |
| 479.5 – 527.5 | 62 |
| 527.5 – 575.4 | 45 |
| 575.4 – 623.4 | 48 |
| 623.4 – 671.3 | 31 |
| 671.3 – 719.2 | 41 |
| 719.2 – 767.2 | 28 |
| 767.2 – 815.2 | 15 |
| 815.2 – 863.1 | 12 |
| 863.1 – 911.1 | 14 |
| 911.1 – 959 | 7 |
| 959 – 1007 | 9 |
| 1007 – 1055 | 8 |
| 1055 – 1103 | 9 |
| 1103 – 1151 | 3 |
| 1151 – 1199 | 4 |
| 1199 – 1247 | 5 |
| 1247 – 1295 | 1 |
| 1295 – 1343 | 2 |
| 1343 – 1391 | 0 |
| 1391 – 1438 | 0 |
| 1438 – 1486 | 0 |
| 1486 – 1534 | 0 |
| 1534 – 1582 | 0 |
| 1582 – 1630 | 1 |
| 1630 – 1678 | 0 |
| 1678 – 1726 | 0 |
| 1726 – 1774 | 0 |
| 1774 – 1822 | 0 |
| 1822 – 1870 | 0 |
| 1870 – 1918 | 1 |
This column holds fully-qualified Census Tract names for New York City, every one of 2327 rows unique with zero nulls and tightly bounded length (38-46 chars, median 41). The vocabulary is formulaic: 'new', 'york', 'census', 'tract', 'county;' appear in essentially every row, with the borough split dominated by Kings (805), Queens (725), Bronx (361), and Richmond (126). Because each value is a one-to-one tract label, it functions as a geographic key rather than a modelling feature.
Treatment: Treat as a tract-level key; parse out borough or join to a geo table rather than feeding the raw string to a model.
saturn.columns["NAME"].stats
| stat | value |
|---|---|
| n | 2,327 |
| nulls | 0 (0.0%) |
| unique | 2,327 |
| len_min | 38 |
| len_max | 46 |
| len_mean | 41.65 |
| len_median | 41 |
| len_p95 | 46 |
| word_mean | 7.133 |
| word_median | 7 |
| n_empty | 0 |
| n_duplicates | 0 |
| duplicate_rate | 0 |
| vocab_size | 1,539 |
| readability_flesch_mean | 91.45 |
| 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 |
|---|---|
| 38 – 38 | 7 |
| 38 – 38 | 0 |
| 38 – 39 | 0 |
| 39 – 39 | 0 |
| 39 – 39 | 0 |
| 39 – 39 | 104 |
| 39 – 39 | 0 |
| 39 – 40 | 0 |
| 40 – 40 | 0 |
| 40 – 40 | 0 |
| 40 – 40 | 785 |
| 40 – 40 | 0 |
| 40 – 41 | 0 |
| 41 – 41 | 0 |
| 41 – 41 | 0 |
| 41 – 41 | 447 |
| 41 – 41 | 0 |
| 41 – 42 | 0 |
| 42 – 42 | 0 |
| 42 – 42 | 0 |
| 42 – 42 | 200 |
| 42 – 42 | 0 |
| 42 – 43 | 0 |
| 43 – 43 | 0 |
| 43 – 43 | 0 |
| 43 – 43 | 378 |
| 43 – 43 | 0 |
| 43 – 44 | 0 |
| 44 – 44 | 0 |
| 44 – 44 | 0 |
| 44 – 44 | 190 |
| 44 – 44 | 0 |
| 44 – 45 | 0 |
| 45 – 45 | 0 |
| 45 – 45 | 0 |
| 45 – 45 | 82 |
| 45 – 45 | 0 |
| 45 – 46 | 0 |
| 46 – 46 | 0 |
| 46 – 46 | 134 |
The column 'state' is numeric but holds the single value 36 across all 2327 rows, with zero variance and no nulls. It carries no information for modelling and likely encodes a fixed jurisdiction or pipeline stage code that was filtered upstream.
Treatment: Drop, constant column.
saturn.columns["state"].stats
| stat | value |
|---|---|
| n | 2,327 |
| nulls | 0 (0.0%) |
| unique | 1 |
| min | 36 |
| max | 36 |
| mean | 36 |
| median | 36 |
| std | 0 |
| q1 | 36 |
| q3 | 36 |
| iqr | 0 |
| skew | 0 |
| kurtosis | 0 |
| n_outliers | 0 |
| outlier_rate | 0 |
| zero_rate | 0 |
| alert: constant | only one distinct value |
state. Vertical dash marks the median.
| bin | count |
|---|---|
| 35.5 – 35.52 | 0 |
| 35.52 – 35.55 | 0 |
| 35.55 – 35.58 | 0 |
| 35.58 – 35.6 | 0 |
| 35.6 – 35.62 | 0 |
| 35.62 – 35.65 | 0 |
| 35.65 – 35.67 | 0 |
| 35.67 – 35.7 | 0 |
| 35.7 – 35.73 | 0 |
| 35.73 – 35.75 | 0 |
| 35.75 – 35.77 | 0 |
| 35.77 – 35.8 | 0 |
| 35.8 – 35.83 | 0 |
| 35.83 – 35.85 | 0 |
| 35.85 – 35.88 | 0 |
| 35.88 – 35.9 | 0 |
| 35.9 – 35.92 | 0 |
| 35.92 – 35.95 | 0 |
| 35.95 – 35.98 | 0 |
| 35.98 – 36 | 0 |
| 36 – 36.02 | 2327 |
| 36.02 – 36.05 | 0 |
| 36.05 – 36.08 | 0 |
| 36.08 – 36.1 | 0 |
| 36.1 – 36.12 | 0 |
| 36.12 – 36.15 | 0 |
| 36.15 – 36.17 | 0 |
| 36.17 – 36.2 | 0 |
| 36.2 – 36.23 | 0 |
| 36.23 – 36.25 | 0 |
| 36.25 – 36.27 | 0 |
| 36.27 – 36.3 | 0 |
| 36.3 – 36.33 | 0 |
| 36.33 – 36.35 | 0 |
| 36.35 – 36.38 | 0 |
| 36.38 – 36.4 | 0 |
| 36.4 – 36.42 | 0 |
| 36.42 – 36.45 | 0 |
| 36.45 – 36.48 | 0 |
| 36.48 – 36.5 | 0 |
Encoded county identifier stored as a numeric code, with only 5 distinct values across 2327 rows and no nulls. The values (min 5, max 85, median 47) look like sparse categorical codes rather than a continuous measurement, and the negative skew (-0.72) reflects uneven frequency across those 5 codes.
Treatment: Cast to categorical and one-hot or target-encode before modelling.
saturn.columns["county"].stats
| stat | value |
|---|---|
| n | 2,327 |
| nulls | 0 (0.0%) |
| unique | 5 |
| min | 5 |
| max | 85 |
| mean | 55 |
| median | 47 |
| std | 25.97 |
| q1 | 47 |
| q3 | 81 |
| iqr | 34 |
| skew | -0.72 |
| kurtosis | -0.4531 |
| n_outliers | 0 |
| outlier_rate | 0 |
| zero_rate | 0 |
county. Vertical dash marks the median.
| bin | count |
|---|---|
| 5 – 7 | 361 |
| 7 – 9 | 0 |
| 9 – 11 | 0 |
| 11 – 13 | 0 |
| 13 – 15 | 0 |
| 15 – 17 | 0 |
| 17 – 19 | 0 |
| 19 – 21 | 0 |
| 21 – 23 | 0 |
| 23 – 25 | 0 |
| 25 – 27 | 0 |
| 27 – 29 | 0 |
| 29 – 31 | 0 |
| 31 – 33 | 0 |
| 33 – 35 | 0 |
| 35 – 37 | 0 |
| 37 – 39 | 0 |
| 39 – 41 | 0 |
| 41 – 43 | 0 |
| 43 – 45 | 0 |
| 45 – 47 | 0 |
| 47 – 49 | 805 |
| 49 – 51 | 0 |
| 51 – 53 | 0 |
| 53 – 55 | 0 |
| 55 – 57 | 0 |
| 57 – 59 | 0 |
| 59 – 61 | 0 |
| 61 – 63 | 310 |
| 63 – 65 | 0 |
| 65 – 67 | 0 |
| 67 – 69 | 0 |
| 69 – 71 | 0 |
| 71 – 73 | 0 |
| 73 – 75 | 0 |
| 75 – 77 | 0 |
| 77 – 79 | 0 |
| 79 – 81 | 0 |
| 81 – 83 | 725 |
| 83 – 85 | 126 |
This is almost certainly a U.S. Census tract code stored as a numeric, with 1530 unique values across 2327 rows and no nulls. The distribution is severely right-skewed (skew 10.14, kurtosis 189.8) with a median of 30100 but a max of 990100, which is the expected pattern for tract codes rather than a true magnitude — values are categorical identifiers padded into a numeric range. The 63 flagged outliers (2.7%) are likely just tracts in higher-numbered county/state ranges, not data errors.
Treatment: Treat as a categorical geographic code; cast to zero-padded string and join to tract-level reference data rather than using as a numeric feature.
saturn.columns["tract"].stats
| stat | value |
|---|---|
| n | 2,327 |
| nulls | 0 (0.0%) |
| unique | 1,530 |
| min | 100 |
| max | 990,100 |
| mean | 4.225e+04 |
| median | 30,100 |
| std | 4.827e+04 |
| q1 | 15,200 |
| q3 | 5.79e+04 |
| iqr | 4.27e+04 |
| skew | 10.14 |
| kurtosis | 189.8 |
| n_outliers | 63 |
| outlier_rate | 0.02707 |
| zero_rate | 0 |
| alert: high_skew | skew=+10.14 |
tract. Vertical dash marks the median.
| bin | count |
|---|---|
| 100 – 2.485e+04 | 982 |
| 2.485e+04 – 4.96e+04 | 617 |
| 4.96e+04 – 7.435e+04 | 329 |
| 7.435e+04 – 9.91e+04 | 197 |
| 9.91e+04 – 1.238e+05 | 145 |
| 1.238e+05 – 1.486e+05 | 37 |
| 1.486e+05 – 1.734e+05 | 17 |
| 1.734e+05 – 1.981e+05 | 0 |
| 1.981e+05 – 2.228e+05 | 0 |
| 2.228e+05 – 2.476e+05 | 0 |
| 2.476e+05 – 2.724e+05 | 0 |
| 2.724e+05 – 2.971e+05 | 0 |
| 2.971e+05 – 3.218e+05 | 0 |
| 3.218e+05 – 3.466e+05 | 0 |
| 3.466e+05 – 3.714e+05 | 0 |
| 3.714e+05 – 3.961e+05 | 0 |
| 3.961e+05 – 4.208e+05 | 0 |
| 4.208e+05 – 4.456e+05 | 0 |
| 4.456e+05 – 4.704e+05 | 0 |
| 4.704e+05 – 4.951e+05 | 0 |
| 4.951e+05 – 5.198e+05 | 0 |
| 5.198e+05 – 5.446e+05 | 0 |
| 5.446e+05 – 5.694e+05 | 0 |
| 5.694e+05 – 5.941e+05 | 0 |
| 5.941e+05 – 6.188e+05 | 0 |
| 6.188e+05 – 6.436e+05 | 0 |
| 6.436e+05 – 6.684e+05 | 0 |
| 6.684e+05 – 6.931e+05 | 0 |
| 6.931e+05 – 7.178e+05 | 0 |
| 7.178e+05 – 7.426e+05 | 0 |
| 7.426e+05 – 7.674e+05 | 0 |
| 7.674e+05 – 7.921e+05 | 0 |
| 7.921e+05 – 8.168e+05 | 0 |
| 8.168e+05 – 8.416e+05 | 0 |
| 8.416e+05 – 8.664e+05 | 0 |
| 8.664e+05 – 8.911e+05 | 0 |
| 8.911e+05 – 9.158e+05 | 0 |
| 9.158e+05 – 9.406e+05 | 0 |
| 9.406e+05 – 9.654e+05 | 0 |
| 9.654e+05 – 9.901e+05 | 3 |
This column lists New York City borough/county names across 2327 rows, with exactly 5 unique values and no nulls. Distribution mirrors NYC borough sizes: Brooklyn (Kings) leads at 805 (34.6%), followed by Queens (725), Bronx (361), Manhattan (310), and Staten Island (126). Entropy ratio of 0.90 indicates a fairly balanced spread across the five categories with no extreme concentration.
Treatment: One-hot or target-encode for modelling.
saturn.columns["county_name"].stats
| stat | value |
|---|---|
| n | 2,327 |
| nulls | 0 (0.0%) |
| unique | 5 |
| top_value | Brooklyn (Kings) |
| top_rate | 0.3459 |
| cardinality | 5 |
| entropy | 2.086 |
| entropy_ratio | 0.8985 |
county_name.
| value | count | share |
|---|---|---|
| Brooklyn (Kings) | 805 | 34.6% |
| Queens | 725 | 31.2% |
| Bronx | 361 | 15.5% |
| Manhattan (New York) | 310 | 13.3% |
| Staten Island (Richmond) | 126 | 5.4% |
A non-negative integer count named 'moderate_burden', spanning 0 to 1732 with a median of 159 and mean of 216 across 2327 rows, no nulls. The distribution is right-skewed (skew 1.93, kurtosis 6.05) with 86 outliers (3.7%) and 6.4% zeros, suggesting a long tail of high-burden cases over a typical mid-hundreds bulk.
Treatment: Apply a log1p transform before regression to tame the right-skew and outliers.
saturn.columns["moderate_burden"].stats
| stat | value |
|---|---|
| n | 2,327 |
| nulls | 0 (0.0%) |
| unique | 639 |
| min | 0 |
| max | 1,732 |
| mean | 216.1 |
| median | 159 |
| std | 210.4 |
| q1 | 64 |
| q3 | 311 |
| iqr | 247 |
| skew | 1.934 |
| kurtosis | 6.052 |
| n_outliers | 86 |
| outlier_rate | 0.03696 |
| zero_rate | 0.06403 |
moderate_burden. Vertical dash marks the median.
| bin | count |
|---|---|
| 0 – 43.3 | 431 |
| 43.3 – 86.6 | 317 |
| 86.6 – 129.9 | 256 |
| 129.9 – 173.2 | 245 |
| 173.2 – 216.5 | 190 |
| 216.5 – 259.8 | 149 |
| 259.8 – 303.1 | 137 |
| 303.1 – 346.4 | 109 |
| 346.4 – 389.7 | 105 |
| 389.7 – 433 | 89 |
| 433 – 476.3 | 61 |
| 476.3 – 519.6 | 53 |
| 519.6 – 562.9 | 28 |
| 562.9 – 606.2 | 33 |
| 606.2 – 649.5 | 28 |
| 649.5 – 692.8 | 17 |
| 692.8 – 736.1 | 11 |
| 736.1 – 779.4 | 16 |
| 779.4 – 822.7 | 7 |
| 822.7 – 866 | 10 |
| 866 – 909.3 | 6 |
| 909.3 – 952.6 | 9 |
| 952.6 – 995.9 | 2 |
| 995.9 – 1039 | 0 |
| 1039 – 1082 | 3 |
| 1082 – 1126 | 6 |
| 1126 – 1169 | 1 |
| 1169 – 1212 | 0 |
| 1212 – 1256 | 1 |
| 1256 – 1299 | 1 |
| 1299 – 1342 | 1 |
| 1342 – 1386 | 0 |
| 1386 – 1429 | 0 |
| 1429 – 1472 | 0 |
| 1472 – 1516 | 0 |
| 1516 – 1559 | 3 |
| 1559 – 1602 | 0 |
| 1602 – 1645 | 1 |
| 1645 – 1689 | 0 |
| 1689 – 1732 | 1 |
Numeric count-like column 'severe_burden' with 2327 rows, no nulls, and 706 unique integer values ranging from 0 to 1918 (median 184, mean 253.18). The distribution is right-skewed (skew 1.60, kurtosis 3.44) with 6.27% zeros and 87 outliers (3.74%) above the upper whisker. The wide IQR (278) and std (236.60) relative to the median suggest substantial dispersion across units.
Treatment: Apply a log1p transform before regression to tame the right skew and outliers.
saturn.columns["severe_burden"].stats
| stat | value |
|---|---|
| n | 2,327 |
| nulls | 0 (0.0%) |
| unique | 706 |
| min | 0 |
| max | 1,918 |
| mean | 253.2 |
| median | 184 |
| std | 236.6 |
| q1 | 82 |
| q3 | 360 |
| iqr | 278 |
| skew | 1.603 |
| kurtosis | 3.435 |
| n_outliers | 87 |
| outlier_rate | 0.03739 |
| zero_rate | 0.06274 |
severe_burden. Vertical dash marks the median.
| bin | count |
|---|---|
| 0 – 47.95 | 368 |
| 47.95 – 95.9 | 293 |
| 95.9 – 143.9 | 290 |
| 143.9 – 191.8 | 249 |
| 191.8 – 239.8 | 186 |
| 239.8 – 287.7 | 175 |
| 287.7 – 335.7 | 122 |
| 335.7 – 383.6 | 114 |
| 383.6 – 431.6 | 101 |
| 431.6 – 479.5 | 83 |
| 479.5 – 527.5 | 62 |
| 527.5 – 575.4 | 45 |
| 575.4 – 623.4 | 48 |
| 623.4 – 671.3 | 31 |
| 671.3 – 719.2 | 41 |
| 719.2 – 767.2 | 28 |
| 767.2 – 815.2 | 15 |
| 815.2 – 863.1 | 12 |
| 863.1 – 911.1 | 14 |
| 911.1 – 959 | 7 |
| 959 – 1007 | 9 |
| 1007 – 1055 | 8 |
| 1055 – 1103 | 9 |
| 1103 – 1151 | 3 |
| 1151 – 1199 | 4 |
| 1199 – 1247 | 5 |
| 1247 – 1295 | 1 |
| 1295 – 1343 | 2 |
| 1343 – 1391 | 0 |
| 1391 – 1438 | 0 |
| 1438 – 1486 | 0 |
| 1486 – 1534 | 0 |
| 1534 – 1582 | 0 |
| 1582 – 1630 | 1 |
| 1630 – 1678 | 0 |
| 1678 – 1726 | 0 |
| 1726 – 1774 | 0 |
| 1774 – 1822 | 0 |
| 1822 – 1870 | 0 |
| 1870 – 1918 | 1 |
This is a percentage feature measuring the share of some population under moderate housing burden, ranging 0–100 with mean 22.74 and median 21.8. The distribution is right-skewed (skew 1.51, kurtosis 6.70) with 59 outliers (2.65%) and a 4.38% null rate. About 2.1% of rows are exact zeros and the IQR is tight at 12.3, so the upper tail past q3=28.2 stretches all the way to 100.
Treatment: Impute the ~4% nulls and consider a mild transform or winsorization to tame the right tail before modelling.
saturn.columns["pct_moderate_burden"].stats
| stat | value |
|---|---|
| n | 2,327 |
| nulls | 102 (4.4%) |
| unique | 461 |
| min | 0 |
| max | 100 |
| mean | 22.74 |
| median | 21.8 |
| std | 11.36 |
| q1 | 15.9 |
| q3 | 28.2 |
| iqr | 12.3 |
| skew | 1.509 |
| kurtosis | 6.704 |
| n_outliers | 59 |
| outlier_rate | 0.02652 |
| zero_rate | 0.02112 |
pct_moderate_burden. Vertical dash marks the median.
| bin | count |
|---|---|
| 0 – 2.5 | 55 |
| 2.5 – 5 | 24 |
| 5 – 7.5 | 49 |
| 7.5 – 10 | 78 |
| 10 – 12.5 | 108 |
| 12.5 – 15 | 160 |
| 15 – 17.5 | 213 |
| 17.5 – 20 | 251 |
| 20 – 22.5 | 238 |
| 22.5 – 25 | 240 |
| 25 – 27.5 | 193 |
| 27.5 – 30 | 172 |
| 30 – 32.5 | 129 |
| 32.5 – 35 | 79 |
| 35 – 37.5 | 71 |
| 37.5 – 40 | 41 |
| 40 – 42.5 | 31 |
| 42.5 – 45 | 24 |
| 45 – 47.5 | 14 |
| 47.5 – 50 | 12 |
| 50 – 52.5 | 6 |
| 52.5 – 55 | 4 |
| 55 – 57.5 | 4 |
| 57.5 – 60 | 6 |
| 60 – 62.5 | 0 |
| 62.5 – 65 | 3 |
| 65 – 67.5 | 3 |
| 67.5 – 70 | 5 |
| 70 – 72.5 | 0 |
| 72.5 – 75 | 1 |
| 75 – 77.5 | 1 |
| 77.5 – 80 | 1 |
| 80 – 82.5 | 1 |
| 82.5 – 85 | 1 |
| 85 – 87.5 | 0 |
| 87.5 – 90 | 1 |
| 90 – 92.5 | 2 |
| 92.5 – 95 | 1 |
| 95 – 97.5 | 0 |
| 97.5 – 100 | 3 |
A percentage metric (0–100 range) capturing the share of some population under severe burden, with a mean of 27.12 and median of 26.2 suggesting a fairly typical right-skewed distribution (skew 0.57). Spread is moderate (std 12.68, IQR 15.9) and only 1.35% of rows are flagged as outliers, though a max of 100.0 alongside a 1.98% zero rate hints at a few extreme records worth inspecting. Note the 4.38% null rate, which will need handling.
Treatment: Impute the 4.4% missing values and use as-is; mild skew does not require transformation.
saturn.columns["pct_severe_burden"].stats
| stat | value |
|---|---|
| n | 2,327 |
| nulls | 102 (4.4%) |
| unique | 518 |
| min | 0 |
| max | 100 |
| mean | 27.12 |
| median | 26.2 |
| std | 12.68 |
| q1 | 18.7 |
| q3 | 34.6 |
| iqr | 15.9 |
| skew | 0.5663 |
| kurtosis | 1.222 |
| n_outliers | 30 |
| outlier_rate | 0.01348 |
| zero_rate | 0.01978 |
pct_severe_burden. Vertical dash marks the median.
| bin | count |
|---|---|
| 0 – 2.5 | 45 |
| 2.5 – 5 | 14 |
| 5 – 7.5 | 41 |
| 7.5 – 10 | 53 |
| 10 – 12.5 | 94 |
| 12.5 – 15 | 115 |
| 15 – 17.5 | 131 |
| 17.5 – 20 | 160 |
| 20 – 22.5 | 170 |
| 22.5 – 25 | 188 |
| 25 – 27.5 | 188 |
| 27.5 – 30 | 168 |
| 30 – 32.5 | 173 |
| 32.5 – 35 | 157 |
| 35 – 37.5 | 115 |
| 37.5 – 40 | 97 |
| 40 – 42.5 | 73 |
| 42.5 – 45 | 62 |
| 45 – 47.5 | 44 |
| 47.5 – 50 | 35 |
| 50 – 52.5 | 29 |
| 52.5 – 55 | 19 |
| 55 – 57.5 | 18 |
| 57.5 – 60 | 12 |
| 60 – 62.5 | 6 |
| 62.5 – 65 | 4 |
| 65 – 67.5 | 4 |
| 67.5 – 70 | 2 |
| 70 – 72.5 | 1 |
| 72.5 – 75 | 1 |
| 75 – 77.5 | 1 |
| 77.5 – 80 | 1 |
| 80 – 82.5 | 0 |
| 82.5 – 85 | 1 |
| 85 – 87.5 | 1 |
| 87.5 – 90 | 0 |
| 90 – 92.5 | 1 |
| 92.5 – 95 | 0 |
| 95 – 97.5 | 0 |
| 97.5 – 100 | 1 |
Likely a count or dollar measure of rent-burdened households (or burden amount) per record, ranging from 0 to 3153 with a median of 358 and mean of 469.26. The distribution is right-skewed (skew 1.49, kurtosis 3.00) with 82 outliers (3.5%) and 4.7% exact zeros, so a long tail dominates the upper end.
Treatment: Apply a log1p transform before regression to tame the right skew and zero mass.
saturn.columns["rent_burdened"].stats
| stat | value |
|---|---|
| n | 2,327 |
| nulls | 0 (0.0%) |
| unique | 1,013 |
| min | 0 |
| max | 3,153 |
| mean | 469.3 |
| median | 358 |
| std | 415.3 |
| q1 | 164.5 |
| q3 | 670 |
| iqr | 505.5 |
| skew | 1.494 |
| kurtosis | 3.005 |
| n_outliers | 82 |
| outlier_rate | 0.03524 |
| zero_rate | 0.04727 |
rent_burdened. Vertical dash marks the median.
| bin | count |
|---|---|
| 0 – 78.83 | 310 |
| 78.83 – 157.7 | 256 |
| 157.7 – 236.5 | 264 |
| 236.5 – 315.3 | 231 |
| 315.3 – 394.1 | 190 |
| 394.1 – 473 | 180 |
| 473 – 551.8 | 147 |
| 551.8 – 630.6 | 113 |
| 630.6 – 709.4 | 108 |
| 709.4 – 788.2 | 75 |
| 788.2 – 867.1 | 91 |
| 867.1 – 945.9 | 73 |
| 945.9 – 1025 | 57 |
| 1025 – 1104 | 39 |
| 1104 – 1182 | 41 |
| 1182 – 1261 | 23 |
| 1261 – 1340 | 26 |
| 1340 – 1419 | 20 |
| 1419 – 1498 | 19 |
| 1498 – 1576 | 11 |
| 1576 – 1655 | 16 |
| 1655 – 1734 | 6 |
| 1734 – 1813 | 5 |
| 1813 – 1892 | 6 |
| 1892 – 1971 | 4 |
| 1971 – 2049 | 2 |
| 2049 – 2128 | 3 |
| 2128 – 2207 | 5 |
| 2207 – 2286 | 0 |
| 2286 – 2365 | 0 |
| 2365 – 2444 | 1 |
| 2444 – 2522 | 1 |
| 2522 – 2601 | 2 |
| 2601 – 2680 | 1 |
| 2680 – 2759 | 0 |
| 2759 – 2838 | 0 |
| 2838 – 2917 | 0 |
| 2917 – 2995 | 0 |
| 2995 – 3074 | 0 |
| 3074 – 3153 | 1 |
This is a numeric percentage indicating the share of rent-burdened households per record, ranging from 0 to 100 with a mean of 49.87 and median of 50.0. The distribution is nearly symmetric (skew -0.04) and reasonably tight around the middle (IQR 17.9, std 14.6), with 4.38% nulls and only 0.36% zeros. 62 outliers (2.79%) sit beyond the whiskers, but no severe tail or drift is evident.
Treatment: Impute the ~4% nulls and use as-is; no transform needed given near-symmetric bounded percentage.
saturn.columns["pct_rent_burdened"].stats
| stat | value |
|---|---|
| n | 2,327 |
| nulls | 102 (4.4%) |
| unique | 596 |
| min | 0 |
| max | 100 |
| mean | 49.87 |
| median | 50 |
| std | 14.62 |
| q1 | 40.9 |
| q3 | 58.8 |
| iqr | 17.9 |
| skew | -0.03839 |
| kurtosis | 0.7849 |
| n_outliers | 62 |
| outlier_rate | 0.02787 |
| zero_rate | 0.003596 |
pct_rent_burdened. Vertical dash marks the median.
| bin | count |
|---|---|
| 0 – 2.5 | 8 |
| 2.5 – 5 | 3 |
| 5 – 7.5 | 1 |
| 7.5 – 10 | 5 |
| 10 – 12.5 | 7 |
| 12.5 – 15 | 8 |
| 15 – 17.5 | 12 |
| 17.5 – 20 | 14 |
| 20 – 22.5 | 14 |
| 22.5 – 25 | 24 |
| 25 – 27.5 | 35 |
| 27.5 – 30 | 42 |
| 30 – 32.5 | 53 |
| 32.5 – 35 | 80 |
| 35 – 37.5 | 91 |
| 37.5 – 40 | 119 |
| 40 – 42.5 | 129 |
| 42.5 – 45 | 144 |
| 45 – 47.5 | 146 |
| 47.5 – 50 | 177 |
| 50 – 52.5 | 139 |
| 52.5 – 55 | 178 |
| 55 – 57.5 | 162 |
| 57.5 – 60 | 131 |
| 60 – 62.5 | 117 |
| 62.5 – 65 | 97 |
| 65 – 67.5 | 60 |
| 67.5 – 70 | 57 |
| 70 – 72.5 | 54 |
| 72.5 – 75 | 28 |
| 75 – 77.5 | 20 |
| 77.5 – 80 | 25 |
| 80 – 82.5 | 8 |
| 82.5 – 85 | 4 |
| 85 – 87.5 | 12 |
| 87.5 – 90 | 5 |
| 90 – 92.5 | 5 |
| 92.5 – 95 | 3 |
| 95 – 97.5 | 0 |
| 97.5 – 100 | 8 |
This is a numeric feature for median gross rent, with 2327 non-null values and 1232 unique levels. The middle of the distribution looks plausible (median 1735, IQR 1441.5–2049, max 3501), but the minimum is -666666666 and the mean is -41539608.8 with std 161182638.7, indicating sentinel values masquerading as numbers and producing severe negative skew (-3.62) and 289 outliers (12.4%).
Treatment: Replace the -666666666 sentinel with null before any modelling or aggregation.
saturn.columns["median_gross_rent"].stats
| stat | value |
|---|---|
| n | 2,327 |
| nulls | 0 (0.0%) |
| unique | 1,232 |
| min | -6.667e+08 |
| max | 3,501 |
| mean | -4.154e+07 |
| median | 1,735 |
| std | 1.612e+08 |
| q1 | 1442 |
| q3 | 2,049 |
| iqr | 607.5 |
| skew | -3.621 |
| kurtosis | 11.11 |
| n_outliers | 289 |
| outlier_rate | 0.1242 |
| zero_rate | 0 |
| alert: high_skew | skew=-3.62 |
| alert: outliers | 12.4% rows beyond 1.5 IQR |
median_gross_rent. Vertical dash marks the median.
| bin | count |
|---|---|
| -6.667e+08 – -6.5e+08 | 145 |
| -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 – -5.667e+08 | 0 |
| -5.667e+08 – -5.5e+08 | 0 |
| -5.5e+08 – -5.333e+08 | 0 |
| -5.333e+08 – -5.167e+08 | 0 |
| -5.167e+08 – -5e+08 | 0 |
| -5e+08 – -4.833e+08 | 0 |
| -4.833e+08 – -4.667e+08 | 0 |
| -4.667e+08 – -4.5e+08 | 0 |
| -4.5e+08 – -4.333e+08 | 0 |
| -4.333e+08 – -4.167e+08 | 0 |
| -4.167e+08 – -4e+08 | 0 |
| -4e+08 – -3.833e+08 | 0 |
| -3.833e+08 – -3.667e+08 | 0 |
| -3.667e+08 – -3.5e+08 | 0 |
| -3.5e+08 – -3.333e+08 | 0 |
| -3.333e+08 – -3.167e+08 | 0 |
| -3.167e+08 – -3e+08 | 0 |
| -3e+08 – -2.833e+08 | 0 |
| -2.833e+08 – -2.667e+08 | 0 |
| -2.667e+08 – -2.5e+08 | 0 |
| -2.5e+08 – -2.333e+08 | 0 |
| -2.333e+08 – -2.167e+08 | 0 |
| -2.167e+08 – -2e+08 | 0 |
| -2e+08 – -1.833e+08 | 0 |
| -1.833e+08 – -1.667e+08 | 0 |
| -1.667e+08 – -1.5e+08 | 0 |
| -1.5e+08 – -1.333e+08 | 0 |
| -1.333e+08 – -1.167e+08 | 0 |
| -1.167e+08 – -1e+08 | 0 |
| -1e+08 – -8.333e+07 | 0 |
| -8.333e+07 – -6.666e+07 | 0 |
| -6.666e+07 – -5e+07 | 0 |
| -5e+07 – -3.333e+07 | 0 |
| -3.333e+07 – -1.666e+07 | 0 |
| -1.666e+07 – 3501 | 2182 |
Median household income in dollars per record, fully populated across 2,327 rows with 2,106 unique values and a sensible median of 76,833 and IQR of 49,117. The mean of -36,017,397 and minimum of -666,666,666 are sentinel-coded missing values masquerading as numbers, which drag skew to -3.94 and kurtosis to 13.53. Roughly 8.9% of rows (208) are flagged as outliers, almost certainly the same sentinel contamination.
Treatment: Replace -666666666 sentinel with null, then consider log-transform or winsorisation before modelling.
saturn.columns["median_household_income"].stats
| stat | value |
|---|---|
| n | 2,327 |
| nulls | 0 (0.0%) |
| unique | 2,106 |
| min | -6.667e+08 |
| max | 250,001 |
| mean | -3.602e+07 |
| median | 76,833 |
| std | 1.509e+08 |
| q1 | 5.324e+04 |
| q3 | 1.024e+05 |
| iqr | 49,117 |
| skew | -3.94 |
| kurtosis | 13.53 |
| n_outliers | 208 |
| outlier_rate | 0.08939 |
| zero_rate | 0 |
| alert: high_skew | skew=-3.94 |
| alert: outliers | 8.9% rows beyond 1.5 IQR |
median_household_income. Vertical dash marks the median.
| bin | count |
|---|---|
| -6.667e+08 – -6.5e+08 | 126 |
| -6.5e+08 – -6.333e+08 | 0 |
| -6.333e+08 – -6.166e+08 | 0 |
| -6.166e+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 – -4.999e+08 | 0 |
| -4.999e+08 – -4.833e+08 | 0 |
| -4.833e+08 – -4.666e+08 | 0 |
| -4.666e+08 – -4.499e+08 | 0 |
| -4.499e+08 – -4.332e+08 | 0 |
| -4.332e+08 – -4.166e+08 | 0 |
| -4.166e+08 – -3.999e+08 | 0 |
| -3.999e+08 – -3.832e+08 | 0 |
| -3.832e+08 – -3.666e+08 | 0 |
| -3.666e+08 – -3.499e+08 | 0 |
| -3.499e+08 – -3.332e+08 | 0 |
| -3.332e+08 – -3.165e+08 | 0 |
| -3.165e+08 – -2.999e+08 | 0 |
| -2.999e+08 – -2.832e+08 | 0 |
| -2.832e+08 – -2.665e+08 | 0 |
| -2.665e+08 – -2.498e+08 | 0 |
| -2.498e+08 – -2.332e+08 | 0 |
| -2.332e+08 – -2.165e+08 | 0 |
| -2.165e+08 – -1.998e+08 | 0 |
| -1.998e+08 – -1.832e+08 | 0 |
| -1.832e+08 – -1.665e+08 | 0 |
| -1.665e+08 – -1.498e+08 | 0 |
| -1.498e+08 – -1.331e+08 | 0 |
| -1.331e+08 – -1.165e+08 | 0 |
| -1.165e+08 – -9.979e+07 | 0 |
| -9.979e+07 – -8.311e+07 | 0 |
| -8.311e+07 – -6.644e+07 | 0 |
| -6.644e+07 – -4.977e+07 | 0 |
| -4.977e+07 – -3.31e+07 | 0 |
| -3.31e+07 – -1.642e+07 | 0 |
| -1.642e+07 – 2.5e+05 | 2201 |
Counts of households per record, ranging from 0 to 8209 with a median of 1252 and mean of 1410.7. The distribution is right-skewed (skew 1.48, kurtosis 4.38) with 70 outliers (3.0%) on the high end, and 4.1% of rows are zero, which may indicate unpopulated or placeholder areas.
Treatment: Log-transform or winsorize before modelling and decide whether zero-household rows should be filtered.
saturn.columns["total_households"].stats
| stat | value |
|---|---|
| n | 2,327 |
| nulls | 0 (0.0%) |
| unique | 1,495 |
| min | 0 |
| max | 8,209 |
| mean | 1411 |
| median | 1,252 |
| std | 923.3 |
| q1 | 773.5 |
| q3 | 1,850 |
| iqr | 1076 |
| skew | 1.479 |
| kurtosis | 4.377 |
| n_outliers | 70 |
| outlier_rate | 0.03008 |
| zero_rate | 0.04125 |
total_households. Vertical dash marks the median.
| bin | count |
|---|---|
| 0 – 205.2 | 123 |
| 205.2 – 410.4 | 41 |
| 410.4 – 615.7 | 203 |
| 615.7 – 820.9 | 272 |
| 820.9 – 1026 | 269 |
| 1026 – 1231 | 237 |
| 1231 – 1437 | 215 |
| 1437 – 1642 | 221 |
| 1642 – 1847 | 162 |
| 1847 – 2052 | 134 |
| 2052 – 2257 | 94 |
| 2257 – 2463 | 101 |
| 2463 – 2668 | 66 |
| 2668 – 2873 | 39 |
| 2873 – 3078 | 35 |
| 3078 – 3284 | 24 |
| 3284 – 3489 | 22 |
| 3489 – 3694 | 8 |
| 3694 – 3899 | 7 |
| 3899 – 4104 | 9 |
| 4104 – 4310 | 13 |
| 4310 – 4515 | 9 |
| 4515 – 4720 | 5 |
| 4720 – 4925 | 5 |
| 4925 – 5131 | 3 |
| 5131 – 5336 | 2 |
| 5336 – 5541 | 2 |
| 5541 – 5746 | 0 |
| 5746 – 5952 | 1 |
| 5952 – 6157 | 1 |
| 6157 – 6362 | 0 |
| 6362 – 6567 | 0 |
| 6567 – 6772 | 1 |
| 6772 – 6978 | 2 |
| 6978 – 7183 | 0 |
| 7183 – 7388 | 0 |
| 7388 – 7593 | 0 |
| 7593 – 7799 | 0 |
| 7799 – 8004 | 0 |
| 8004 – 8209 | 1 |
Despite the boolean-sounding name 'owner_occupied', this is a numeric count column with 1001 unique values ranging from 0 to 3052 and a mean of 464.6 — likely a tally of owner-occupied units per record (e.g., per tract or block). The distribution is right-skewed (skew 1.76, kurtosis 4.25) with 143 outliers (6.1%) and 7.2% zeros. No nulls are present.
Treatment: Log-transform (log1p to handle the 7% zeros) before modelling to tame the right skew.
saturn.columns["owner_occupied"].stats
| stat | value |
|---|---|
| n | 2,327 |
| nulls | 0 (0.0%) |
| unique | 1,001 |
| min | 0 |
| max | 3,052 |
| mean | 464.6 |
| median | 371 |
| std | 422.6 |
| q1 | 177 |
| q3 | 608 |
| iqr | 431 |
| skew | 1.761 |
| kurtosis | 4.254 |
| n_outliers | 143 |
| outlier_rate | 0.06145 |
| zero_rate | 0.0722 |
| alert: outliers | 6.1% rows beyond 1.5 IQR |
owner_occupied. Vertical dash marks the median.
| bin | count |
|---|---|
| 0 – 76.3 | 343 |
| 76.3 – 152.6 | 175 |
| 152.6 – 228.9 | 191 |
| 228.9 – 305.2 | 236 |
| 305.2 – 381.5 | 258 |
| 381.5 – 457.8 | 245 |
| 457.8 – 534.1 | 167 |
| 534.1 – 610.4 | 134 |
| 610.4 – 686.7 | 98 |
| 686.7 – 763 | 69 |
| 763 – 839.3 | 61 |
| 839.3 – 915.6 | 49 |
| 915.6 – 991.9 | 53 |
| 991.9 – 1068 | 43 |
| 1068 – 1144 | 33 |
| 1144 – 1221 | 21 |
| 1221 – 1297 | 20 |
| 1297 – 1373 | 28 |
| 1373 – 1450 | 16 |
| 1450 – 1526 | 18 |
| 1526 – 1602 | 9 |
| 1602 – 1679 | 13 |
| 1679 – 1755 | 9 |
| 1755 – 1831 | 8 |
| 1831 – 1908 | 5 |
| 1908 – 1984 | 2 |
| 1984 – 2060 | 4 |
| 2060 – 2136 | 3 |
| 2136 – 2213 | 3 |
| 2213 – 2289 | 1 |
| 2289 – 2365 | 2 |
| 2365 – 2442 | 2 |
| 2442 – 2518 | 3 |
| 2518 – 2594 | 0 |
| 2594 – 2670 | 3 |
| 2670 – 2747 | 0 |
| 2747 – 2823 | 1 |
| 2823 – 2899 | 0 |
| 2899 – 2976 | 0 |
| 2976 – 3052 | 1 |
Counts of renter-occupied units per record, ranging from 0 to 8209 with a median of 726 and mean of 946. The distribution is right-skewed (skew 1.59, kurtosis 4.63) with 69 outliers (2.97%) and 4.38% zeros, consistent with area-level housing tallies rather than a per-household flag.
Treatment: log-transform or scale before regression to tame the right skew.
saturn.columns["renter_occupied"].stats
| stat | value |
|---|---|
| n | 2,327 |
| nulls | 0 (0.0%) |
| unique | 1,418 |
| min | 0 |
| max | 8,209 |
| mean | 946.1 |
| median | 726 |
| std | 815.4 |
| q1 | 346 |
| q3 | 1,357 |
| iqr | 1,011 |
| skew | 1.595 |
| kurtosis | 4.627 |
| n_outliers | 69 |
| outlier_rate | 0.02965 |
| zero_rate | 0.04383 |
renter_occupied. Vertical dash marks the median.
| bin | count |
|---|---|
| 0 – 205.2 | 349 |
| 205.2 – 410.4 | 358 |
| 410.4 – 615.7 | 292 |
| 615.7 – 820.9 | 268 |
| 820.9 – 1026 | 207 |
| 1026 – 1231 | 175 |
| 1231 – 1437 | 168 |
| 1437 – 1642 | 110 |
| 1642 – 1847 | 100 |
| 1847 – 2052 | 68 |
| 2052 – 2257 | 63 |
| 2257 – 2463 | 42 |
| 2463 – 2668 | 36 |
| 2668 – 2873 | 22 |
| 2873 – 3078 | 19 |
| 3078 – 3284 | 17 |
| 3284 – 3489 | 6 |
| 3489 – 3694 | 5 |
| 3694 – 3899 | 4 |
| 3899 – 4104 | 6 |
| 4104 – 4310 | 5 |
| 4310 – 4515 | 3 |
| 4515 – 4720 | 1 |
| 4720 – 4925 | 0 |
| 4925 – 5131 | 1 |
| 5131 – 5336 | 1 |
| 5336 – 5541 | 0 |
| 5541 – 5746 | 0 |
| 5746 – 5952 | 0 |
| 5952 – 6157 | 0 |
| 6157 – 6362 | 0 |
| 6362 – 6567 | 0 |
| 6567 – 6772 | 0 |
| 6772 – 6978 | 0 |
| 6978 – 7183 | 0 |
| 7183 – 7388 | 0 |
| 7388 – 7593 | 0 |
| 7593 – 7799 | 0 |
| 7799 – 8004 | 0 |
| 8004 – 8209 | 1 |
Percentage of owner-occupied housing per record, ranging the full 0-100 scale with a mean of 37.5 and median of 34.4. The distribution is wide (std 25.7, IQR 39.7) and slightly right-skewed (0.39) with negative kurtosis (-0.85), indicating a flat, near-uniform spread rather than a tight central mass. About 3.2% of rows are exactly zero and 4.1% are null, but no statistical outliers were flagged.
Treatment: Use as-is as a bounded percentage feature; impute the 4% nulls with the median or a missingness flag.
saturn.columns["pct_owner_occupied"].stats
| stat | value |
|---|---|
| n | 2,327 |
| nulls | 96 (4.1%) |
| unique | 823 |
| min | 0 |
| max | 100 |
| mean | 37.51 |
| median | 34.4 |
| std | 25.65 |
| q1 | 16.4 |
| q3 | 56.1 |
| iqr | 39.7 |
| skew | 0.3948 |
| kurtosis | -0.854 |
| n_outliers | 0 |
| outlier_rate | 0 |
| zero_rate | 0.03227 |
pct_owner_occupied. Vertical dash marks the median.
| bin | count |
|---|---|
| 0 – 2.5 | 141 |
| 2.5 – 5 | 86 |
| 5 – 7.5 | 71 |
| 7.5 – 10 | 63 |
| 10 – 12.5 | 86 |
| 12.5 – 15 | 65 |
| 15 – 17.5 | 72 |
| 17.5 – 20 | 88 |
| 20 – 22.5 | 98 |
| 22.5 – 25 | 88 |
| 25 – 27.5 | 79 |
| 27.5 – 30 | 67 |
| 30 – 32.5 | 70 |
| 32.5 – 35 | 56 |
| 35 – 37.5 | 76 |
| 37.5 – 40 | 68 |
| 40 – 42.5 | 59 |
| 42.5 – 45 | 72 |
| 45 – 47.5 | 58 |
| 47.5 – 50 | 54 |
| 50 – 52.5 | 70 |
| 52.5 – 55 | 59 |
| 55 – 57.5 | 55 |
| 57.5 – 60 | 39 |
| 60 – 62.5 | 44 |
| 62.5 – 65 | 40 |
| 65 – 67.5 | 52 |
| 67.5 – 70 | 34 |
| 70 – 72.5 | 40 |
| 72.5 – 75 | 47 |
| 75 – 77.5 | 32 |
| 77.5 – 80 | 48 |
| 80 – 82.5 | 31 |
| 82.5 – 85 | 27 |
| 85 – 87.5 | 26 |
| 87.5 – 90 | 24 |
| 90 – 92.5 | 23 |
| 92.5 – 95 | 8 |
| 95 – 97.5 | 6 |
| 97.5 – 100 | 9 |
Numeric percentage of renter-occupied units, ranging the full 0–100 with mean 62.5 and median 65.6, suggesting these records skew toward rental-heavy geographies. Spread is wide (std 25.7, IQR 39.7) and the distribution is mildly left-skewed (-0.39) and flat (kurtosis -0.85), so no outliers were flagged. About 4.1% of rows are null and only 0.27% are exact zeros, with 823 distinct values across 2,327 rows.
Treatment: Use as-is as a bounded percentage feature; impute the 4.1% nulls before modelling.
saturn.columns["pct_renter_occupied"].stats
| stat | value |
|---|---|
| n | 2,327 |
| nulls | 96 (4.1%) |
| unique | 823 |
| min | 0 |
| max | 100 |
| mean | 62.49 |
| median | 65.6 |
| std | 25.65 |
| q1 | 43.9 |
| q3 | 83.6 |
| iqr | 39.7 |
| skew | -0.3948 |
| kurtosis | -0.854 |
| n_outliers | 0 |
| outlier_rate | 0 |
| zero_rate | 0.002689 |
pct_renter_occupied. Vertical dash marks the median.
| bin | count |
|---|---|
| 0 – 2.5 | 9 |
| 2.5 – 5 | 6 |
| 5 – 7.5 | 7 |
| 7.5 – 10 | 23 |
| 10 – 12.5 | 24 |
| 12.5 – 15 | 26 |
| 15 – 17.5 | 27 |
| 17.5 – 20 | 32 |
| 20 – 22.5 | 47 |
| 22.5 – 25 | 31 |
| 25 – 27.5 | 48 |
| 27.5 – 30 | 40 |
| 30 – 32.5 | 34 |
| 32.5 – 35 | 50 |
| 35 – 37.5 | 39 |
| 37.5 – 40 | 46 |
| 40 – 42.5 | 41 |
| 42.5 – 45 | 53 |
| 45 – 47.5 | 57 |
| 47.5 – 50 | 72 |
| 50 – 52.5 | 54 |
| 52.5 – 55 | 54 |
| 55 – 57.5 | 73 |
| 57.5 – 60 | 62 |
| 60 – 62.5 | 69 |
| 62.5 – 65 | 72 |
| 65 – 67.5 | 60 |
| 67.5 – 70 | 65 |
| 70 – 72.5 | 72 |
| 72.5 – 75 | 75 |
| 75 – 77.5 | 91 |
| 77.5 – 80 | 94 |
| 80 – 82.5 | 92 |
| 82.5 – 85 | 73 |
| 85 – 87.5 | 64 |
| 87.5 – 90 | 83 |
| 90 – 92.5 | 65 |
| 92.5 – 95 | 71 |
| 95 – 97.5 | 83 |
| 97.5 – 100 | 147 |
click to copy
@misc{saturn-nyc-housing-nyc-housing-metrics-merged-2026,
author = {Steuber, Luke},
title = {Saturn reading: nyc housing nyc housing metrics merged},
year ={2026},
howpublished = {\url{https://dr.eamer.dev/saturn/view/nyc_housing-nyc_housing_metrics_merged}},
note = {Profiled with saturn-dissect v0.2.0, prompt saturn-insight-v2, model anthropic:claude-opus-4-7},
}
Steuber, L. (2026). Saturn reading: nyc housing nyc housing metrics merged. Source: /home/coolhand/html/datavis/data_trove/data/urban/nyc_housing/nyc_housing_metrics_merged.csv. Profiled with saturn-dissect v0.2.0 (saturn-insight-v2, anthropic:claude-opus-4-7). Retrieved from https://dr.eamer.dev/saturn/view/nyc_housing-nyc_housing_metrics_merged