data trove noaa atmospheric weather alerts

This column contains National Weather Service alert/advisory event type names, serving as a categorical label for meteorological warning events. With 35 unique values across 571 rows, it covers a meaningful range of weather phenomena. 'Small Craft Advisory' dominates at 26.5% (149 occurrences), while the top 4 event types together account for the majority of records — suggesting a skewed distribution toward marine and winter/wind events. Entropy ratio of 0.72 indicates moderate-to-high diversity, but the heavy concentration in a few categories is worth noting for class-imbalance handling in any classification task. Treatment: One-hot encode or target-encode for modelling; be aware of class imbalance with 'Small Craft Advisory' at 26.5% and many tail categories. high · anthropic:default

n

571

nulls

8 (1.4%)

unique

35

top_value

Small Craft Advisory

top_rate

0.2647

cardinality

35

entropy

3.699

entropy_ratio

0.7212

This column contains NWS (National Weather Service) alert headlines — structured text strings describing weather advisory type, issuance timestamp, expiry, and issuing office. Despite appearing categorical, the entropy ratio of 0.943 and 305 unique values out of 571 records signal near free-text behaviour, with a long-tail alert confirming most headlines appear only once or a handful of times. The most frequent value ('Small Craft Advisory issued February 17…') appears only 19 times (top_rate ≈ 3.4%), indicating very little repetition across the dataset. Treatment: Parse structured subfields (alert type, issue time, expiry time, NWS office) via regex before modelling; do not use raw string as a categorical feature. high · anthropic:default

n

571

nulls

9 (1.6%)

unique

305

top_value

Small Craft Advisory issued February 17 at 4:12AM AKST until February 18 at 5:00PM AKST by NWS Anchorage AK

top_rate

0.03381

cardinality

305

entropy

7.782

entropy_ratio

0.943

This column contains full-text NWS (National Weather Service) alert and forecast descriptions — multi-line, structured prose covering marine, fire weather, wind, and winter storm warnings across various US regions. With 527 unique values out of 571 rows and an entropy ratio of 0.9945, nearly every entry is distinct, making this essentially free text. The long-tail alert and the presence of duplicate entries (e.g., the same Southeast Alaska marine forecast appearing 4 times) suggest periodic reissue of templated advisories rather than purely unique records, which may indicate time-series duplication worth investigating. Treatment: Tokenize and embed (e.g., TF-IDF or sentence transformer) before modelling; consider deduplicating or grouping by alert template for frequency analysis. high · anthropic:default

n

571

nulls

0 (0.0%)

unique

527

top_value

Southeast Alaska Inside Waters from Dixon Entrance to Skagway Wind forecasts reflect the predominant speed and direction expected. Sea forecasts represent the average of the highest one-third of the combined windwave and swell height. .TONIGHT...N wind 25 kt. Seas 5 ft. Heavy freezing spray. .WED...N wind 15 kt diminishing to 10 kt in the morning. Seas 3 ft in the morning then 2 ft or less. Light freezing spray in the early morning. .WED NIGHT...N wind 10 kt. Seas 2 ft or less. .THU...N wind 10 kt. Seas 2 ft or less. Light freezing spray. .THU NIGHT...N wind 15 kt. Seas 2 ft or less. Snow. .FRI...N gale to 35 kt. Seas 5 ft. .SAT...N gale to 45 kt. Seas 2 ft or less. .SUN...N gale to 35 kt. Seas 2 ft or less.

top_rate

0.007005

cardinality

527

entropy

8.992

entropy_ratio

0.9945

This column is an ordinal severity classification with 5 levels — Moderate, Minor, Severe, Unknown, and Extreme — likely describing the intensity of incidents, events, or conditions. 'Moderate' dominates at 36.9% of records (208/571), and 'Extreme' is strikingly rare at only 5 occurrences, suggesting a heavily right-skewed real-world distribution where catastrophic events are uncommon. The 19 'Unknown' values represent a data-quality concern distinct from the 1.4% null rate, effectively adding a second form of missingness. Entropy ratio of 0.77 indicates a reasonably spread distribution, though the extreme imbalance at the tail warrants attention for any classification task. Treatment: Encode as ordinal (Minor < Moderate < Severe < Extreme); treat 'Unknown' as a separate missing indicator before modelling. high · anthropic:default

n

571

nulls

8 (1.4%)

unique

5

top_value

Moderate

top_rate

0.3694

cardinality

5

entropy

1.788

entropy_ratio

0.7698

This column encodes an analyst-assigned confidence level for some observation or classification, with four ordinal categories: Likely, Observed, Unknown, and Possible. The distribution is severely skewed: 'Likely' dominates at 89.3% of all records (503/571), while 'Observed', 'Unknown', and 'Possible' each account for only 18–24 records. The low entropy ratio of 0.328 confirms near-constant behaviour, and the 1.4% null rate is minor. The near-total dominance of a single category limits this column's discriminative power as a feature. Treatment: Ordinal-encode with awareness of severe class imbalance; consider collapsing minority categories or using as a stratification variable rather than a predictive feature. high · anthropic:default

n

571

nulls

8 (1.4%)

unique

4

top_value

Likely

top_rate

0.8934

cardinality

4

entropy

0.6569

entropy_ratio

0.3285

This column is a categorical urgency classification, likely from an incident or request management system, with 5 distinct levels. It is severely dominated by 'Expected' (510 out of 571 rows, 90.6%), leaving the remaining 4 categories — 'Unknown', 'Future', 'Past', and 'Immediate' — collectively accounting for fewer than 10% of records. The very low entropy ratio of 0.27 confirms extreme class imbalance, which will limit this column's discriminative power in most models. The 'Immediate' category, presumably the most critical, appears only 6 times, making it near-invisible to any classifier trained on this distribution. Treatment: One-hot encode but flag severe class imbalance; consider oversampling minority classes (especially 'Immediate' with n=6) or collapsing into binary 'Expected vs. Other' before modelling. high · anthropic:default

n

571

nulls

8 (1.4%)

unique

5

top_value

Expected

top_rate

0.9059

cardinality

5

entropy

0.6276

entropy_ratio

0.2703

This column contains geographic area descriptions used in weather or emergency alerts, predominantly covering coastal and inland waterways of Southeast Alaska (e.g., 'Glacier Bay', 'Stephens Passage', 'Northern Lynn Canal') with some continental US zones also present (e.g., 'Greater Lake Tahoe Area', 'Sacramento Mountains'). With 441 unique values across only 571 rows and an entropy ratio of 0.98, cardinality is extremely high — nearly every row is a distinct area. The long-tail alert confirms that most areas appear only once or twice, with even the top value ('Glacier Bay') appearing just 9 times (1.6% of rows). The multi-zone concatenated entries (e.g., 'Greater Lake Tahoe Area; Greater Lake Tahoe Area') suggest some records bundle multiple zones into a single string, which may cause deduplication or parsing issues. Treatment: Parse semicolon-delimited multi-zone entries into separate records, then use as a grouping/filter dimension rather than a model feature; too high-cardinality for direct encoding without aggregation. high · anthropic:default

n

571

nulls

8 (1.4%)

unique

441

top_value

Glacier Bay

top_rate

0.01599

cardinality

441

entropy

8.608

entropy_ratio

0.9799

The column 'sent' has 571 non-null rows but was skipped by the profiler, leaving its type and value distribution entirely unknown. No stats, uniqueness counts, or distribution metrics are available. The name suggests a boolean flag (e.g., message/email sent status) or a timestamp, but this cannot be confirmed from the evidence. An analyst should inspect raw values directly before any downstream use. Treatment: Inspect raw values to determine dtype, then re-profile before any modelling or filtering. low · anthropic:default

n

571

nulls

0 (0.0%)

unique

—

The column 'effective' contains 571 non-null values but was skipped by the profiler, leaving its type and distribution entirely unknown. No stats, uniqueness count, or value samples are available, so its semantic role cannot be determined from this evidence alone. The name suggests a boolean flag (e.g., is-effective) or a date (effective date/start), but this is speculation beyond the evidence. Treatment: Manually inspect raw values to determine type, then re-profile before any modelling use. low · anthropic:default

n

571

nulls

0 (0.0%)

unique

—

The column 'onset' likely records the timing or start of a clinical or epidemiological event (e.g., symptom onset date), but the profiler emitted a 'skipped' alert and returned no stats, leaving its true type and distribution entirely uncharacterised. With 571 non-null rows and zero null rate, data is present, but nothing about format, uniqueness, or value range can be confirmed from this evidence alone. An analyst should inspect raw values to determine whether it is a date string, numeric duration, or categorical stage before any downstream use. Treatment: Inspect raw values to confirm type (date vs. numeric vs. categorical), then parse or encode accordingly before modelling. low · anthropic:default

n

571

nulls

0 (0.0%)

unique

—

The column 'expires' likely represents an expiration date or timestamp field, but the profiler skipped analysis entirely, yielding no stats, no uniqueness count, and a kind of 'unknown'. With 571 non-null rows and zero null rate, data is present but its structure or encoding prevented saturn from classifying it. No further distributional signals are available from the evidence. Treatment: Inspect raw values to confirm encoding (ISO string, epoch int, or other format), parse to datetime, then use as a feature or filter boundary. low · anthropic:default

n

571

nulls

0 (0.0%)

unique

—

n

571

nulls

555 (97.2%)

unique

16

min

25.76

max

69.65

mean

40.46

median

35.45

std

11.58

q1

34.96

q3

41

iqr

6.043

skew

1.508

kurtosis

1.297

n_outliers

4

outlier_rate

0.25

zero_rate

0

n

571

nulls

555 (97.2%)

unique

16

min

-120.6

max

18.96

mean

-84.42

median

-95.31

std

45.23

q1

-120.2

q3

-78.65

iqr

41.52

skew

1.283

kurtosis

0.3248

n_outliers

2

outlier_rate

0.125

zero_rate

0

n

571

nulls

563 (98.6%)

unique

8

top_value

Ball Lightning

top_rate

0.125

cardinality

8

entropy

3

entropy_ratio

1

This column is named 'date' and contains 571 non-null values with a 0.0% null rate, suggesting it is a timestamp or date field. However, saturn skipped profiling it (kind: 'unknown', no stats, no uniqueness count), so no distribution, range, or format details are available. The absence of any computed statistics prevents assessment of cardinality, temporal range, or potential drift. Treat with caution until the parsing issue causing the skip is resolved. Treatment: Investigate why saturn skipped this column, parse to a proper datetime type, then extract temporal features or use as an index. low · anthropic:default

n

571

nulls

0 (0.0%)

unique

—

n

571

nulls

563 (98.6%)

unique

6

top_value

International

top_rate

0.375

cardinality

6

entropy

2.406

entropy_ratio

0.9306

n

571

nulls

563 (98.6%)

unique

4

top_value

USA

top_rate

0.625

cardinality

4

entropy

1.549

entropy_ratio

0.7744

n

571

nulls

563 (98.6%)

unique

5

top_value

N/A

top_rate

0.5

cardinality

5

entropy

2

entropy_ratio

0.8614

n

571

nulls

563 (98.6%)

unique

8

top_value

Journal of Geophysical Research

top_rate

0.125

cardinality

8

entropy

3

entropy_ratio

1