rotten tomatoes rotten tomatoes movies

Slug-style identifier column: every value is a single token (one_word_rate 1.0, word_mean 1.0) with mean length ~18 chars and 142052 uniques out of 143258 rows. The 1206 duplicates (0.84%) are surprising for an id field — top repeats like 'catch_me_if_you_can' and 'hear_no_evil' suggest these are title-derived slugs rather than guaranteed-unique keys. Readability score is meaningless here (−75.5) because the tokens are underscore-joined phrases, not prose. Treatment: Use as a join key but deduplicate first — it is not strictly unique. high · anthropic:claude-opus-4-7

n

143,258

nulls

0 (0.0%)

unique

142,052

len_min

1

len_max

178

len_mean

18.15

len_median

16

len_p95

37

word_mean

1

word_median

1

n_empty

0

n_duplicates

1,206

duplicate_rate

0.008418

vocab_size

19,976

readability_flesch_mean

-75.47

emoji_rate

0

url_rate

0

one_word_rate

1

allcaps_rate

0.005787

boilerplate_rate

0

Short titles (mean 17 chars, median 3 words) of what look like films or works — top values include 'The Return', 'A Christmas Carol', 'Hero', 'Blue'. Predominantly English (3946) but 29 other languages are detected, with Spanish (123), German (80), and French (72) most common. Notable duplication: 16,488 repeats (11.5% duplicate rate) across 126,403 unique values out of 143,258 rows, and 17% are single-word titles. Treatment: Normalise case and tokenize for embedding; do not treat as a unique key given the 11.5% duplicate rate. high · anthropic:claude-opus-4-7

n

143,258

nulls

367 (0.3%)

unique

126,403

len_min

1

len_max

176

len_mean

17.23

len_median

15

len_p95

37

word_mean

3.074

word_median

3

n_empty

0

n_duplicates

16,488

duplicate_rate

0.1154

vocab_size

17,597

readability_flesch_mean

60.62

emoji_rate

0

url_rate

0

one_word_rate

0.1715

allcaps_rate

0.003989

boilerplate_rate

9.098e-05

This is an audience rating score on a 0-100 scale with 101 unique integer values, mean 55.67 and median 57. The distribution is wide (std 24.55, IQR 39) and slightly left-skewed (skew -0.23, kurtosis -0.83) with no outliers flagged. The dominant concern is missingness: 48.87% of rows are null, so nearly half the dataset lacks this score. Treatment: Impute or add a missing-indicator before modelling given the ~49% null rate. high · anthropic:claude-opus-4-7

n

143,258

nulls

70,010 (48.9%)

unique

101

min

0

max

100

mean

55.67

median

57

std

24.55

q1

37

q3

76

iqr

39

skew

-0.2257

kurtosis

-0.8322

n_outliers

0

outlier_rate

0

zero_rate

0.0156

This is the Rotten Tomatoes critic score (tomatoMeter), a 0-100 percentage with 101 unique integer values, mean 65.77 and median 73. The distribution is left-skewed (skew -0.65) with Q1 at 45 and Q3 at 89, indicating most rated titles lean favorable. The dominant concern is coverage: 76.35% of rows are null, so the field is only populated for a minority of records. Treatment: Impute or add a missingness indicator before modelling given the 76% null rate. high · anthropic:claude-opus-4-7

n

143,258

nulls

109,381 (76.4%)

unique

101

min

0

max

100

mean

65.77

median

73

std

28.02

q1

45

q3

89

iqr

44

skew

-0.6467

kurtosis

-0.6657

n_outliers

0

outlier_rate

0

zero_rate

0.02084

This is a content rating field mixing theatrical (R, PG-13, PG, NC-17, G) and television (TVPG, TV14, TVMA, TVY7, TVG) classifications across 10 distinct values. The column is 90.23% null, so only ~9.77% of the 143,258 rows carry a rating, and within those R alone accounts for 55.28% of values. The mixed rating systems and the long tail (TVG, TVY7, G each appearing once) suggest inconsistent sourcing rather than a clean controlled vocabulary. Treatment: Normalize TV vs MPAA codes into a unified scheme and add an explicit 'missing' category before encoding. high · anthropic:claude-opus-4-7

n

143,258

nulls

129,267 (90.2%)

unique

10

top_value

R

top_rate

0.5528

cardinality

10

entropy

1.71

entropy_ratio

0.5147

This column stores content-rating descriptors (e.g. 'Language', 'Violence', 'Some Sexual Content') serialised as Python-style list literals rather than clean arrays. It is 90.23% null and, among the 14k populated rows, 40.3% are duplicates with only 8,353 unique values across 143,258 records. A handful of non-English entries (12 it, 5 ro, 1 km) appear despite the vocabulary being tiny (1,188 words), and the bracket/quote artefacts in top_words confirm the values were never parsed out of their string representation. Treatment: Parse the list-literal strings into a multi-hot encoding of rating tags before modelling. high · anthropic:claude-opus-4-7

n

143,258

nulls

129,267 (90.2%)

unique

8,353

len_min

5

len_max

148

len_mean

46.16

len_median

44

len_p95

88

word_mean

5.169

word_median

5

n_empty

0

n_duplicates

5,638

duplicate_rate

0.403

vocab_size

1,188

readability_flesch_mean

15.02

emoji_rate

0

url_rate

0

one_word_rate

0.05925

allcaps_rate

0.06168

boilerplate_rate

0

This is a theatrical release date stored as an ISO-format string (every value is exactly 10 characters and a single token, e.g. '2018-09-14'). It is sparsely populated — 78.52% null — and the non-null values are heavily repeated, with a 60.8% duplicate rate across 12,062 distinct dates. The 'allcaps' alert is a false positive driven by digits-only strings; there's no actual text content to mine. Treatment: Parse to date and impute or flag the 78.52% missing before any time-based feature engineering. high · anthropic:claude-opus-4-7

n

143,258

nulls

112,485 (78.5%)

unique

12,062

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

18,711

duplicate_rate

0.608

vocab_size

9,088

readability_flesch_mean

121.2

emoji_rate

0

url_rate

0

one_word_rate

1

allcaps_rate

1

boilerplate_rate

0

This is a streaming-release date stored as ISO-8601 text (len_median 10, one_word_rate 1.0, all top values match YYYY-MM-DD). Roughly 44.56% of rows are null and the duplicate_rate is 0.94, with a single date 2017-05-22 appearing 1232 times — heavy clustering on a few release days. The text-style alerts (allcaps, one_word, short_text) are artifacts of the date format, not a quality issue. Treatment: Parse to date dtype and treat missingness explicitly before any temporal feature engineering. high · anthropic:claude-opus-4-7

n

143,258

nulls

63,838 (44.6%)

unique

4,726

len_min

7

len_max

10

len_mean

10

len_median

10

len_p95

10

word_mean

1

word_median

1

n_empty

0

n_duplicates

74,694

duplicate_rate

0.9405

vocab_size

3,514

readability_flesch_mean

121.2

emoji_rate

0

url_rate

0

one_word_rate

1

allcaps_rate

1

boilerplate_rate

0

Movie or episode runtime in minutes, with a typical feature-length distribution (median 92, IQR 84-103). The tail is extreme: max 2700, skew 7.62, kurtosis 598.65, and 11.37% of rows flagged as outliers, suggesting a mix of shorts, multi-part specials, or full series totals alongside standard films. Roughly 9.65% of rows are null. Treatment: Cap or log-transform before modelling and impute the ~10% nulls. high · anthropic:claude-opus-4-7

n

143,258

nulls

13,827 (9.7%)

unique

324

min

1

max

2,700

mean

93.71

median

92

std

28.13

q1

84

q3

103

iqr

19

skew

7.623

kurtosis

598.7

n_outliers

14,720

outlier_rate

0.1137

zero_rate

0

This is a categorical genre label for films, often a single word like 'Drama' (27,860 rows) or 'Documentary' (15,162) but sometimes a comma-separated combo such as 'Comedy, Drama'. With only 66 distinct vocabulary tokens but 2,912 unique strings and a 97.8% duplicate rate, the cardinality comes entirely from how genres are concatenated. Note the 7.74% null rate and that 55% of values are single-word — multi-genre rows are the minority. Treatment: Split on comma and one-hot encode into a small set of genre flags. high · anthropic:claude-opus-4-7

n

143,258

nulls

11,083 (7.7%)

unique

2,912

len_min

3

len_max

101

len_mean

12.91

len_median

11

len_p95

32

word_mean

1.874

word_median

1

n_empty

0

n_duplicates

129,263

duplicate_rate

0.978

vocab_size

66

readability_flesch_mean

-19.66

emoji_rate

0

url_rate

0

one_word_rate

0.5533

allcaps_rate

0

boilerplate_rate

0

Categorical language label with 112 distinct values, dominated by English at 65.7% of non-null rows (85,034 of 143,258). The long tail spans regional variants (e.g., 'French (Canada)' vs 'French (France)', 'English (United Kingdom)') alongside bare language names like 'English' and 'French', suggesting inconsistent locale tagging that will fragment counts. Null rate is 9.67%, and entropy ratio of 0.38 confirms heavy concentration in a few categories. Treatment: Normalize locale variants to base language codes, then one-hot encode the top categories and bucket the rest as 'Other'. high · anthropic:claude-opus-4-7

n

143,258

nulls

13,858 (9.7%)

unique

112

top_value

English

top_rate

0.6571

cardinality

112

entropy

2.605

entropy_ratio

0.3827

Holds a film director's name, averaging 2.2 words and 14.8 characters with 62,207 unique values across 143,258 rows. The duplicate rate is 55.3% (76,857 rows), inflated by a 'Unknown Director' sentinel that occurs 3,544 times and should not be treated as a real name. Null rate is 2.93%, and the long tail (David DeCoteau at 129, Sam Newfield at 124) reflects prolific B-movie directors rather than data quality issues. Treatment: Replace 'Unknown Director' with null and use as a high-cardinality categorical (target/frequency encode). high · anthropic:claude-opus-4-7

n

143,258

nulls

4,194 (2.9%)

unique

62,207

len_min

1

len_max

326

len_mean

14.81

len_median

14

len_p95

26

word_mean

2.213

word_median

2

n_empty

0

n_duplicates

76,857

duplicate_rate

0.5527

vocab_size

16,693

readability_flesch_mean

47.17

emoji_rate

0

url_rate

0

one_word_rate

0.007356

allcaps_rate

7.191e-05

boilerplate_rate

0

Holds writer credits, typically one or two personal names averaging 2.7 words and 21 characters, with familiar figures like Jing Wong, Woody Allen, and Ingmar Bergman topping the list. Coverage is weak: 37.1% of rows are null and 25.3% are duplicates across 67,274 unique values, so a single column likely concatenates multiple co-writers per title. Top tokens (michael, david, john) confirm Western personal names dominate, though 'de' hints at multi-name strings or non-English credits mixed in. Treatment: Split on delimiters into individual writers and explode for any per-person analysis; impute or flag the 37% missing before modelling. high · anthropic:claude-opus-4-7

n

143,258

nulls

53,142 (37.1%)

unique

67,274

len_min

1

len_max

262

len_mean

21.34

len_median

16

len_p95

47

word_mean

2.711

word_median

2

n_empty

0

n_duplicates

22,842

duplicate_rate

0.2535

vocab_size

26,458

readability_flesch_mean

37.79

emoji_rate

0

url_rate

0

one_word_rate

0.005349

allcaps_rate

6.658e-05

boilerplate_rate

0

Box office gross stored as a short currency string like "$1.1M" — every value is one token, 99.99% allcaps, and lengths cluster between 2 and 7 characters. The column is 89.71% null and only 4,863 distinct values cover the 14,762 populated rows, with a 67.01% duplicate rate concentrated on round million-dollar figures. Note this is a coarse, pre-formatted string (millions only), not a precise revenue number. Treatment: Parse the "$X.XM" string into a numeric dollar amount and decide whether to impute or drop given the 89.71% null rate. high · anthropic:claude-opus-4-7

n

143,258

nulls

128,515 (89.7%)

unique

4,863

len_min

2

len_max

7

len_mean

5.977

len_median

6

len_p95

7

word_mean

1

word_median

1

n_empty

0

n_duplicates

9,880

duplicate_rate

0.6701

vocab_size

4,863

readability_flesch_mean

121.2

emoji_rate

0

url_rate

0

one_word_rate

1

allcaps_rate

0.9999

boilerplate_rate

0

This column lists film distributor names, dominated by major studios like Paramount Pictures (994), 20th Century Fox (745), and Universal Pictures (737). It is overwhelmingly sparse with an 83.94% null rate and a 83.94% duplicate rate across 3,694 unique values, suggesting most rows lack distributor data while a small set of studios accounts for the populated entries. Names are short (mean length 19.9 chars, median 2 words) and vocabulary is concentrated around terms like 'pictures', 'films', and 'entertainment'. Treatment: Normalize studio name variants and treat as a high-cardinality categorical with an explicit 'missing' bucket given the 83.94% null rate. high · anthropic:claude-opus-4-7

n

143,258

nulls

120,253 (83.9%)

unique

3,694

len_min

3

len_max

385

len_mean

19.89

len_median

17

len_p95

43

word_mean

2.649

word_median

2

n_empty

0

n_duplicates

19,311

duplicate_rate

0.8394

vocab_size

2,650

readability_flesch_mean

16.85

emoji_rate

0

url_rate

4.347e-05

one_word_rate

0.09376

allcaps_rate

0.01474

boilerplate_rate

0

Catalogues the audio mix format of each title (Surround, Dolby Digital, Stereo, Mono, etc.), with 551 distinct labels across 143,258 rows. The dominant issue is sparsity: 88.89% of values are null, and even among populated rows 'Surround' covers only 25.6%. Free-form combinations like 'Stereo, Surround' vs 'Surround, Stereo' and overlapping Dolby variants suggest the field is unnormalised multi-label text rather than a clean taxonomy. Treatment: Split on commas, normalise Dolby/Surround variants, and treat as multi-hot; consider dropping if downstream task can't tolerate 89% missingness. high · anthropic:claude-opus-4-7

n

143,258

nulls

127,341 (88.9%)

unique

551

top_value

Surround

top_rate

0.256

cardinality

551

entropy

4.663

entropy_ratio

0.5121