saturn

This dataset is a NASA meteorite landings catalogue covering 45,716 unique meteorite records with attributes including mass, classification, discovery year, and geographic coordinates. The most striking feature is the mass distribution: the median mass is just 32.6 g but the maximum reaches 60,000,000 g, producing extreme skew (skew=76.9) and over 7,000 statistical outliers — a handful of enormous meteorites are pulling the mean to 13,278 g. A second key finding is that 97.6% of records are classified as 'Found' rather than 'Fell', meaning nearly all entries are meteorites discovered on the ground rather than witnessed falling, which has strong implications for geographic and temporal bias in the data. The meteorite classification column (recclass) spans 466 types, dominated by ordinary chondrites (L6, H5, L5), and year of discovery shows a clear spike in the late 1990s–2000s likely tied to Antarctic collection campaigns.

This column contains UUIDs (universally unique identifiers) serving as a primary key, with all 45,716 values being exactly 36 characters long and fully unique — zero duplicates, zero nulls. Notably, all sampled top values share the prefix '00000000-0000-0000-', suggesting the UUID version/variant fields are zeroed out, which is atypical of standard UUID v4 generation and may indicate a custom or synthetic ID scheme. The allcaps_rate of 1.0 is consistent with hex characters but worth noting if downstream systems are case-sensitive.

This column is a Socrata-style row identifier, recognizable from the 'row-XXXX.XXXX-XXXX' format visible in all sampled values. Every value is exactly 18 characters long (len_min = len_max = len_mean = 18.0), and all 45,716 rows are unique with a duplicate_rate of 0.0 and null_rate of 0.0 — a perfect surrogate key. No surprises in the data; it is entirely consistent with an auto-generated system identifier from a Socrata open-data platform.

This column records the physical mass of objects in grams, almost certainly meteorite or asteroid specimen weights given the scale and distribution. The median is just 32.6 g while the mean explodes to 13,278 g and the maximum reaches 60,000,000 g (60 tonnes), indicating a tiny fraction of massive outliers dragging the distribution — skew of 76.9 and kurtosis of 6,796 confirm an extreme long tail. Fully 15.5% of rows (7,086) are flagged as outliers, meaning the bulk of specimens are small rocks while a handful of giants dominate the aggregate statistics.

GeoLocation stores geographic coordinates as serialized Python list strings in the format [None, '', '', None, False], representing what appears to be a structured geo-point object flattened to text. The most common value — '[None, '0.0', '0.0', None, False]' appearing 6,214 times — is almost certainly a null/unknown sentinel rather than a genuine equatorial location, masking true missingness beyond the 16% null rate. Duplicate rate is high at 55.5% (21,301 duplicates across 17,100 unique values), consistent with many records sharing the same geographic coordinates. The column should be parsed to extract numeric longitude and latitude fields rather than used as raw text.

This column captures whether a meteorite was discovered on the ground ('Found') versus observed falling ('Fell'), making it a binary classification label for meteorite recovery type. The distribution is severely imbalanced: 'Found' accounts for 97.6% of 45,716 records (44,609), while 'Fell' represents only 2.4% (1,107). The entropy ratio of 0.164 confirms near-minimum uncertainty, flagged explicitly as an imbalance alert. Any model using this as a target will require class-balancing techniques.

This column is a metadata field that contains exclusively the empty object literal '{ }' across all 45,716 rows, with zero nulls and a cardinality of 1. It carries no information whatsoever — entropy is 0.0 and top_rate is 1.0, meaning every single record is identical. This is almost certainly an unfilled placeholder or a defaulted JSON field that was never populated.

This column is a meteorite name-type classification flag, distinguishing between currently valid meteorite names ('Valid') and relict/superseded ones ('Relict'). The distribution is extremely imbalanced: 45,641 of 45,716 records (99.84%) are 'Valid', with only 75 'Relict' entries. The near-zero entropy (0.018) confirms this column carries almost no information variance, which triggered the imbalance alert.

This column contains proper names of geographic features — the top words ('range', 'hills', 'mountains', 'northwest', 'africa', 'grove', 'yamato', 'Queen Alexandra') are all typical components of named landforms or place names. Every one of the 45,716 rows has a distinct value (duplicate_rate 0.0, n_unique = 45,716) with zero nulls, making it a perfect natural identifier. The mean word count of 2.77 and median of 3.0 confirm multi-token names rather than single labels, while 'yamato' appearing 3,317 times as the top individual word suggests a large Antarctic or Japanese geographic sub-corpus driving partial lexical repetition even though full names are unique.

This column is a Unix timestamp named 'created_at', but every single one of its 45,716 non-null rows holds the identical value 1446143734 (approximately 2015-10-29 UTC), triggering a 'constant' alert. With n_unique of 1, std of 0.0, and IQR of 0.0, the column carries zero information variance — strongly suggesting a bulk-load default, a data pipeline bug, or a one-time snapshot import where timestamps were not properly captured. This is a critical data quality issue that renders the column useless as a temporal signal.

This column, named 'position', is a numeric field that is entirely constant — every one of its 45,716 non-null values is exactly 0.0 (zero_rate = 1.0, n_unique = 1). It carries zero information and would contribute nothing to any model or analysis. This is flagged as a constant alert, confirming it is safe to drop.

This column is a Unix epoch timestamp named `updated_at`, representing a last-modified datetime for each row. Every single one of the 45,716 non-null records holds the identical value 1446143734 (approximately 2015-10-29 UTC), meaning the column is a constant — it carries zero information variance. This strongly suggests a bulk data load or migration event where all rows were stamped with the same timestamp rather than tracking real update times.

The column 'created_meta' is likely a creation timestamp or metadata field associated with record provenance, but saturn classified it as 'unknown' kind and skipped all profiling, yielding zero stats and no uniqueness count. With 45,716 rows, zero nulls, and no further signal available, its actual dtype, distribution, and content cannot be assessed from this evidence alone.

The column 'updated_meta' was skipped by the profiler, yielding no stats, no uniqueness count, and no type resolution beyond 'unknown'. With 45,716 non-null rows and a null rate of 0.0, the column is fully populated, but its content, structure, and distribution are entirely opaque from the available evidence. The name suggests it may hold metadata update timestamps or serialized metadata objects (e.g., JSON blobs), but nothing in the evidence confirms this.

This column is almost certainly a row or entity identifier: it has 45,716 unique values across 45,716 rows with zero nulls and zero duplicates, indicating a perfect 1-to-1 mapping. Values run from 1 to 57,458, suggesting either a sparse sequential ID (gaps exist since max > n) or a pre-filtered subset of a larger table. The near-uniform distribution (kurtosis −1.16, skew 0.27, zero outliers) is consistent with a sequential or pseudo-random integer key rather than a meaningful numeric feature.

This column represents the recorded latitude of meteorite find/fall locations, with values ranging from -87.37° to +81.17° consistent with geographic latitude bounds. Surprising signals: the median of -71.5° indicates the majority of records are concentrated in high southern latitudes (likely Antarctic recovery sites), yet the Q3 is exactly 0.0°, suggesting a notable cluster at the equator or a placeholder zero — reinforced by a zero_rate of 16.8% that almost exactly matches the null_rate of 16%, implying zeros may be encoding missing coordinates rather than true equatorial finds. Kurtosis of -1.48 confirms a flat, bimodal-like distribution rather than a normal one.

This column represents the recorded longitude of meteorite landing or find locations, covering a range from -165.43° to 354.47°. The maximum value of 354.47 is surprising — valid WGS84 longitude should cap at 180°, suggesting some records use a 0–360° convention rather than the standard -180 to 180° range, which will cause mapping errors if not normalised. The zero_rate of ~16% mirrors the null_rate of 16%, strongly implying that zero-filled values are placeholder/missing entries rather than genuine equatorial coordinates at the prime meridian. Distribution is near-symmetric (skew -0.17, kurtosis -0.73) with a large IQR of 157.17, consistent with a globally spread geographic variable.

This column contains meteorite classification codes, identifying the mineralogical and petrologic type of each recovered meteorite specimen. The top 7 values (L6, H5, L5, H6, H4, LL5, LL6) are all ordinary chondrite classes and together account for the vast majority of records, with L6 alone representing 18.1% of the 45,716 rows. Despite 466 unique classes, the entropy ratio of 0.51 indicates moderate concentration — the long tail of rare classes (e.g., CM2 with only 416 occurrences) will create sparse dummy variables if one-hot encoded naively.

This column represents a calendar year, stored as full ISO-8601 timestamps normalised to January 1st of each year (e.g. '2003-01-01T00:00:00'), confirming the time component carries no information. Despite being profiled as categorical, it is effectively an annual time dimension spanning at least the range visible in the top values (1979–2006). Surprising: cardinality is 266 distinct values against only ~45 years visible in top values, suggesting either a much wider date range or some malformed/unexpected entries worth inspecting. The top year (2003) accounts for just 7.3% of rows, indicating a reasonably spread distribution rather than heavy concentration.