data trove veteran population by county

Overview

Source: /home/coolhand/html/datavis/data_trove/demographic/veterans/military_firearm_veterans.csv

Saturn profiled 49 rows across 5 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).

NAME categorical label

This column contains U.S. state names, with 49 unique values across 49 rows and zero nulls — consistent with a near-complete list of U.S. states (50 states minus one, or possibly including a territory/district instead). Every value appears exactly once (top_rate = 0.0204, i.e., 1/49), yielding a maximum entropy_ratio of 1.0, which flags as a long-tail alert but is actually a perfectly uniform identifier distribution. The missing 50th entry is worth investigating — one state may be absent or replaced by a non-standard entry.

Treatment: Use as a join key or group-by label; audit for the missing 50th U.S. state before aggregation.

state categorical label

This column contains US state names, with exactly 49 rows and 49 unique values — meaning every row is a distinct state (notably, only 49 of the 50 US states are present, so one state is missing from the dataset). The entropy ratio of 1.0 and uniform frequency of 1 per state confirm perfect cardinality with zero repetition, making this a de facto identifier rather than a grouping variable. The 'long_tail' alert is technically a misnomer here: all values occur exactly once, so there is no skew whatsoever.

Treatment: Use as a row label or join key; do not one-hot encode with cardinality 49 without dimensionality reduction — consider mapping to regions or numeric features instead.

veteran_population numeric feature

This column represents the veteran population count for each of 49 geographic units (likely U.S. states or territories, given the count). All 49 rows are unique and non-null, consistent with one record per jurisdiction. The distribution is remarkably symmetric (skew ≈ -0.04) and platykurtic (kurtosis ≈ -1.34), meaning values are spread broadly and uniformly across a wide range from 61,090 to 1,786,891 with no outliers — an unusual flatness for a population variable, which typically skews right.

Treatment: Use as-is or normalize per total state population to create a veteran rate before modelling.

total_population numeric feature

This column represents total population counts for 49 distinct geographic units (likely US states or similar administrative regions), with every row populated and fully unique. Values span from 548,984 to 39,227,468 with a mean of ~18.8M and median of ~19.6M, suggesting a reasonably balanced distribution — the near-zero skew (0.10) and platykurtic kurtosis (-1.16) confirm a flat, spread-out distribution rather than a peaked one. The wide IQR of ~20.4M and std of ~12.2M reflect the natural size heterogeneity across regions, and notably there are zero detected outliers despite this spread.

Treatment: Use as-is or consider per-capita normalization when combining with other count-based columns.

veteran_percentage numeric feature

This column represents veteran percentage figures across 49 fully distinct, non-null records — likely a rate or share (%) of veterans in some population unit such as counties, districts, or organizations. The distribution is severely right-skewed (skew = 5.79, kurtosis = 34.86): the median is only 5.08 while the mean is pulled to 14.92 by extreme outliers. Most strikingly, the maximum value is 277.05, which exceeds 100% and is physically impossible for a percentage, strongly suggesting data quality issues — either unit errors (e.g., per-thousand rates mixed with percentages) or data entry errors among the 8 flagged outliers (outlier rate = 16.3%).

Treatment: Investigate and correct values exceeding 100 before use; consider log-transform or winsorization after cleaning to address skew.