quirky tornadoes

This is a date column stored as ISO-formatted text (YYYY-MM-DD), with every value exactly 10 characters long and one token. Across 70,022 rows there are only 12,639 unique dates and an 81.9% duplicate rate, so many records share dates — top value 2011-04-27 appears 207 times. The range spans at least 1974-04-03 to 2023-03-31, suggesting it was misclassified as text rather than a date type. Treatment: Cast to a proper date type and use for temporal joins or time-based features. high · anthropic:claude-opus-4-7

n

70,022

nulls

0 (0.0%)

unique

12,639

len_min

10

len_max

10

len_mean

10

len_median

10

len_p95

10

word_mean

1

word_median

1

n_empty

0

n_duplicates

57,383

duplicate_rate

0.8195

vocab_size

7,831

readability_flesch_mean

121.2

emoji_rate

0

url_rate

0

one_word_rate

1

allcaps_rate

1

boilerplate_rate

0

This column holds clock times stored as 8-character HH:MM:SS strings, with all 70,022 rows non-null and uniform length (len_min=len_max=8). Only 1,438 distinct values appear and 97.95% are duplicates, with afternoon/evening slots like 16:00:00 (978), 17:00:00 (971) and 15:00:00 (959) dominating — consistent with event start times rather than free text. It's mistyped as text: parse to a proper time type before use. Treatment: Cast to a time type and bucket by hour for modelling. high · anthropic:claude-opus-4-7

n

70,022

nulls

0 (0.0%)

unique

1,438

len_min

8

len_max

8

len_mean

8

len_median

8

len_p95

8

word_mean

1

word_median

1

n_empty

0

n_duplicates

68,584

duplicate_rate

0.9795

vocab_size

1,352

readability_flesch_mean

121.2

emoji_rate

0

url_rate

0

one_word_rate

1

allcaps_rate

1

boilerplate_rate

0

This is a US state code column with 53 distinct values, slightly more than the 50 states (likely including DC and territories like PR). TX dominates at 13.3% of 70,022 rows, followed by KS (4,474) and OK (4,221), giving a clear southern/plains skew rather than a uniform national distribution. Entropy ratio of 0.847 confirms the distribution is fairly spread but not flat, and there are no nulls. Treatment: One-hot or target-encode; consider grouping low-frequency states into an 'Other' bucket. high · anthropic:claude-opus-4-7

n

70,022

nulls

0 (0.0%)

unique

53

top_value

TX

top_rate

0.1335

cardinality

53

entropy

4.851

entropy_ratio

0.8468

`mag` is a low-cardinality categorical with 7 distinct values dominated by '0' (46% of 70022 rows) and decreasing counts through '1','2','3','4','5'. The ordered integer levels suggest a magnitude or severity code rather than a free category, and the presence of '-9' (1024 rows) is the standout signal — almost certainly a sentinel for missing/unknown that is not being counted as null. Treatment: Recode '-9' as missing, then treat as an ordinal feature. high · anthropic:claude-opus-4-7

n

70,022

nulls

0 (0.0%)

unique

7

top_value

0

top_rate

0.4601

cardinality

7

entropy

1.772

entropy_ratio

0.6312

Counts of injuries stored as strings, with 209 distinct values across 70,022 rows and no nulls. The distribution is severely zero-inflated: '0' accounts for 88.8% of records, and entropy ratio is just 0.123. Tail values like '1' through '10' decay quickly but 209 unique tokens suggests very long tails or non-integer entries worth inspecting. Treatment: Cast to integer and model as a zero-inflated count (e.g., hurdle or ZIP regression). high · anthropic:claude-opus-4-7

n

70,022

nulls

0 (0.0%)

unique

209

top_value

0

top_rate

0.888

cardinality

209

entropy

0.9454

entropy_ratio

0.1227

This is a fatality count per event, stored as a categorical/string field with 50 distinct integer values and no nulls across 70,022 rows. The distribution is extremely imbalanced: '0' accounts for 97.72% of records, giving an entropy ratio of just 0.039, with '1' at 830 rows and a long thin tail (2 → 277, 3 → 134, down to single-digit counts at higher values). Despite being typed as categorical, the values are numeric and ordered, so the current encoding is likely a load artifact. Treatment: Cast to integer and model as a zero-inflated count rather than a categorical. high · anthropic:claude-opus-4-7

n

70,022

nulls

0 (0.0%)

unique

50

top_value

0

top_rate

0.9772

cardinality

50

entropy

0.2174

entropy_ratio

0.03852

Numeric loss values stored as text strings, with all 70,022 entries being single tokens (one_word_rate 1.0) and lengths of 1-10 characters. The distribution is heavily concentrated: '0.0' alone accounts for 22,764 rows and the duplicate_rate is 0.985 across only 1,019 unique values. Mixed formatting is a hazard — '0' and '0.0' appear as separate tokens, so a naive cast will collapse them but string-based grouping won't. Treatment: Cast to float (normalising '0' vs '0.0') before any modelling or aggregation. high · anthropic:claude-opus-4-7

n

70,022

nulls

0 (0.0%)

unique

1,019

len_min

1

len_max

10

len_mean

3.181

len_median

3

len_p95

5

word_mean

1

word_median

1

n_empty

0

n_duplicates

69,003

duplicate_rate

0.9854

vocab_size

503

readability_flesch_mean

121.2

emoji_rate

0

url_rate

0

one_word_rate

1

allcaps_rate

0.9251

boilerplate_rate

0

Values range from 17.72 to 61.02 with a mean of 37.14 and median of 37.03, consistent with a starting latitude (slat) field in decimal degrees, likely covering the contiguous US. The distribution is essentially symmetric (skew 0.04, kurtosis -0.58) with a tight IQR of 7.74 and only 70 outliers (0.10%). No nulls and no zeros, and 16,016 unique values across 70,022 rows suggest repeated coordinates rather than free-form noise. Treatment: Use as-is for geospatial features; optionally pair with a longitude column for distance or region encoding. high · anthropic:claude-opus-4-7

n

70,022

nulls

0 (0.0%)

unique

16,016

min

17.72

max

61.02

mean

37.14

median

37.03

std

5.09

q1

33.19

q3

40.93

iqr

7.74

skew

0.03792

kurtosis

-0.5825

n_outliers

70

outlier_rate

0.0009997

zero_rate

0

Values are negative decimal degrees ranging from -163.53 to -64.7151 with a median of -93.5, consistent with western-hemisphere longitudes (the 'slon' name suggests starting longitude). The distribution is mildly left-skewed (-0.32) and concentrated within an IQR of ~11.7 degrees around the central US longitude band. Only 951 outliers (1.36%) fall outside that range, and there are no nulls or zeros. Treatment: Use as a geographic coordinate; pair with the matching latitude column for spatial features rather than treating as a standalone scalar. high · anthropic:claude-opus-4-7

n

70,022

nulls

0 (0.0%)

unique

17,912

min

-163.5

max

-64.72

mean

-92.74

median

-93.5

std

8.677

q1

-98.4

q3

-86.69

iqr

11.71

skew

-0.3229

kurtosis

2.156

n_outliers

951

outlier_rate

0.01358

zero_rate

0

Almost certainly an event latitude in decimal degrees, with values spanning 17.72 to 61.02 — consistent with locations across North America. The distribution is roughly symmetric (skew 0.03, kurtosis -0.41) and centered near 37.26, with only 78 mild outliers. The standout concern is that 37.65% of rows are null, so coverage is partial. Treatment: Pair with the matching longitude and impute or filter the 37.65% nulls before any spatial modelling. high · anthropic:claude-opus-4-7

n

70,022

nulls

26,363 (37.6%)

unique

16,965

min

17.72

max

61.02

mean

37.26

median

37.13

std

4.942

q1

33.49

q3

40.91

iqr

7.42

skew

0.03404

kurtosis

-0.4085

n_outliers

78

outlier_rate

0.001787

zero_rate

0

This is almost certainly longitude (east coordinate), with values bounded between -163.53 and -64.7151 and a median of -92.47, consistent with points across North America. The distribution is moderately left-skewed (-0.60) with kurtosis 3.77 and a tight IQR of 11.26 around the median. Notably, 37.65% of rows are null, which will materially shrink any geo-based analysis. Treatment: Pair with the matching latitude column and filter out the ~38% null rows before spatial analysis. high · anthropic:claude-opus-4-7

n

70,022

nulls

26,363 (37.6%)

unique

18,586

min

-163.5

max

-64.72

mean

-92.19

median

-92.47

std

8.545

q1

-97.73

q3

-86.47

iqr

11.26

skew

-0.5954

kurtosis

3.766

n_outliers

647

outlier_rate

0.01482

zero_rate

0

Despite being typed as text, `len` holds short numeric tokens (length 3-8, one word each) like '0.1', '0.5', '1.0' — almost certainly a length or size measurement stored as strings. Values are highly concentrated: '0.1' alone covers 15,456 of 70,022 rows and the duplicate rate is 94.8% across only 3,663 unique tokens. The allcaps and one_word alerts are artefacts of numeric strings rather than real text signal. Treatment: Cast to float and treat as a numeric feature rather than text. high · anthropic:claude-opus-4-7

n

70,022

nulls

0 (0.0%)

unique

3,663

len_min

3

len_max

8

len_mean

3.626

len_median

3

len_p95

6

word_mean

1

word_median

1

n_empty

0

n_duplicates

66,359

duplicate_rate

0.9477

vocab_size

2,204

readability_flesch_mean

121.2

emoji_rate

0

url_rate

0

one_word_rate

1

allcaps_rate

1

boilerplate_rate

0

wid is a categorical column with 419 distinct values, all numeric-looking strings like '10', '50', '100', '30' — almost certainly a width or weight parameter stored as text rather than a true category. The distribution is heavily concentrated on round numbers: '10' alone covers 20.6% of 70022 rows and the top ten values are all multiples of 5 or 25, giving an entropy ratio of 0.51. No nulls, but the string encoding of clearly numeric quanta is the surprise. Treatment: cast to numeric and consider binning or log-transform given the round-number concentration. high · anthropic:claude-opus-4-7

n

70,022

nulls

0 (0.0%)

unique

419

top_value

10

top_rate

0.2059

cardinality

419

entropy

4.463

entropy_ratio

0.5124