saturn

This dataset tracks SNAP (food stamp) program enrollment across 20 U.S. states, capturing estimated eligible populations, actual participants, and the resulting coverage gap. Two things stand out immediately: first, the enrollment rate and gap percentage are constant across all states (67% enrolled, 33% gap), suggesting these are summary-level figures rather than state-specific calculations — they should not be used for cross-state comparison. Second, the three population-count columns (eligible, participants, gap) are all heavily right-skewed with 2 outliers each, pointing to a small number of very large states — likely California and/or Florida — that dwarf the rest and will dominate any totals-based analysis.

This column represents estimated counts of SNAP-eligible individuals, likely at a geographic unit level (e.g., county or district). Values span a wide range from 75,227 to 4,685,272, with a median of 507,917 well below the mean of 857,172.75 — a classic signature of population-size data. The distribution is heavily right-skewed (skew = 2.42, kurtosis = 5.58) with 2 outliers (10% of rows), almost certainly large urban jurisdictions pulling the tail sharply upward.

snap_gap is a numeric column likely representing some form of gap or interval measurement (e.g., a time delta, distance, or capacity gap between snapshots). With only 20 rows and 20 unique values, every observation is distinct. The distribution is heavily right-skewed (skew = 2.42, kurtosis = 5.58): the median is 167,613 while the mean is pulled to 282,866 by a long upper tail, and 2 outliers (10% of rows) push up to a maximum of 1,546,138 — roughly 25× the minimum of 24,824. The IQR of 222,841 spans a wide range relative to Q1 of 61,204, signalling high dispersion.

This column represents estimated SNAP (Supplemental Nutrition Assistance Program) participant counts, likely at the state or large geographic-unit level given the scale of values ranging from 50,403 to 3,139,134. With only 20 rows and 20 unique values, each record appears to represent a distinct entity (e.g., a U.S. state or territory). The distribution is heavily right-skewed (skew = 2.42, kurtosis = 5.58) with 2 outliers (10% of the dataset), suggesting a small number of very large states—likely California or Texas—dominate the upper tail, while the median (340,304) sits well below the mean (574,306).

This column represents a SNAP (Supplemental Nutrition Assistance Program) enrollment rate, likely expressed as a percentage. Every single one of the 20 rows holds the identical value of 67.0, with zero variance, zero IQR, and a standard deviation of 0.0 — the column is perfectly constant. This is a strong signal that the value was hardcoded, imputed with a single figure, or the dataset captures a single geographic/temporal stratum where this rate was applied uniformly. It carries no predictive or descriptive information across rows.

This column appears to represent a snapshot gap percentage, likely a configuration or policy parameter defining some threshold or interval (e.g., 33%). Across all 20 rows the value is identically 33.0 with zero variance, zero nulls, and a single unique value — making it a degenerate constant with no discriminative power whatsoever.

This column contains US state (and territory) names, with exactly 20 unique values across 20 rows — every row holds a distinct state name, yielding a perfect entropy ratio of 1.0 and a top_rate of 0.05. The dataset appears to be a small, deduplicated lookup or summary table with one row per geographic unit rather than a transactional dataset. The 'long_tail' alert is a statistical artifact of the perfectly uniform distribution, not a genuine skew concern.