ml 32m movies

source /home/coolhand/html/datavis/data_trove/entertainment/movies/ml-32m/movies.csv 87,585 rows 3 columns profiled 2026-05-01 raw JSON static .html .ipynb Report Notebook

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dataset summary · high confidence anthropic:claude-opus-4-7

This dataset is a movie catalogue of 87,585 rows with three columns: a unique movieId, a title, and a pipe-delimited genres string. The genres column is the most analytically interesting: only 1,798 unique combinations exist, and Drama, Documentary, and Comedy dominate, while 7,080 rows are tagged '(no genres listed)' — a sizeable gap worth flagging. Titles are nearly unique (87,382 distinct of 87,585), and the frequent '(2014)'–'(2019)' tokens in titles suggest the catalogue skews toward recent years. movieId spans 1 to 292,757 with no outliers, indicating a sparse identifier range rather than a clean sequence. Start with the genre distribution and the missing-genre share before any deeper modelling.

citing: row_count · columns.genres.n_unique · columns.genres.top_values · columns.genres.stats.one_word_rate · columns.title.n_unique · columns.title.top_words · columns.title.stats.len_mean · columns.movieId.stats.min · columns.movieId.stats.max · columns.movieId.stats.median

Charts the summary said to look at first

genres · See how Drama, Documentary, and Comedy dominate, and note the large '(no genres listed)' bucket.

Show data table

Character-length distribution for genres (mean: 13.240326539932637).
chars	count
3 – 5	125
5 – 7	24325
7 – 9	3474
9 – 10	2417
10 – 12	14431
12 – 14	11262
14 – 16	3313
16 – 18	2692
18 – 20	9626
20 – 22	5612
22 – 23	3690
23 – 25	1617
25 – 27	1066
27 – 29	758
29 – 31	1008
31 – 33	640
33 – 34	366
34 – 36	430
36 – 38	193
38 – 40	76
40 – 42	135
42 – 44	159
44 – 46	42
46 – 47	45
47 – 49	25
49 – 51	30
51 – 53	5
53 – 55	9
55 – 57	6
57 – 58	3
58 – 60	3
60 – 62	0
62 – 64	0
64 – 66	1
66 – 68	0
68 – 70	0
70 – 71	0
71 – 73	0
73 – 75	0
75 – 77	1

genres · Share of the top genre combinations versus the long tail of 1,798 unique strings.

Show data table

Character-length distribution for genres (mean: 13.240326539932637).
chars	count
3 – 5	125
5 – 7	24325
7 – 9	3474
9 – 10	2417
10 – 12	14431
12 – 14	11262
14 – 16	3313
16 – 18	2692
18 – 20	9626
20 – 22	5612
22 – 23	3690
23 – 25	1617
25 – 27	1066
27 – 29	758
29 – 31	1008
31 – 33	640
33 – 34	366
34 – 36	430
36 – 38	193
38 – 40	76
40 – 42	135
42 – 44	159
44 – 46	42
46 – 47	45
47 – 49	25
49 – 51	30
51 – 53	5
53 – 55	9
55 – 57	6
57 – 58	3
58 – 60	3
60 – 62	0
62 – 64	0
64 – 66	1
66 – 68	0
68 – 70	0
70 – 71	0
71 – 73	0
73 – 75	0
75 – 77	1

title · Title character-length distribution centres near 23 with a long tail out to 191.

Show data table

Character-length distribution for title (mean: 25.281349546155162).
chars	count
2 – 7	44
7 – 11	1905
11 – 16	14749
16 – 21	17609
21 – 26	20947
26 – 30	12610
30 – 35	7127
35 – 40	3670
40 – 45	3134
45 – 49	2086
49 – 54	1102
54 – 59	932
59 – 63	548
63 – 68	381
68 – 73	213
73 – 78	180
78 – 82	123
82 – 87	81
87 – 92	41
92 – 96	33
96 – 101	23
101 – 106	13
106 – 111	11
111 – 115	8
115 – 120	3
120 – 125	1
125 – 130	2
130 – 134	4
134 – 139	0
139 – 144	2
144 – 148	1
148 – 153	0
153 – 158	0
158 – 163	1
163 – 167	0
167 – 172	0
172 – 177	0
177 – 182	0
182 – 186	0
186 – 191	1

movieId · Check how movieIds spread from 1 to 292,757 to gauge sparsity in the identifier range.

Show data table

Histogram bins for movieId (median: 165741.0).
bin	count
1 – 7320	7196
7320 – 1.464e+04	1111
1.464e+04 – 2.196e+04	0
2.196e+04 – 2.928e+04	1114
2.928e+04 – 3.66e+04	796
3.66e+04 – 4.391e+04	435
4.391e+04 – 5.123e+04	754
5.123e+04 – 5.855e+04	816
5.855e+04 – 6.587e+04	789
6.587e+04 – 7.319e+04	1132
7.319e+04 – 8.051e+04	1107
8.051e+04 – 8.783e+04	1398
8.783e+04 – 9.515e+04	1556
9.515e+04 – 1.025e+05	1541
1.025e+05 – 1.098e+05	1535
1.098e+05 – 1.171e+05	1847
1.171e+05 – 1.244e+05	2673
1.244e+05 – 1.317e+05	2763
1.317e+05 – 1.391e+05	3280
1.391e+05 – 1.464e+05	3282
1.464e+05 – 1.537e+05	3146
1.537e+05 – 1.61e+05	3258
1.61e+05 – 1.683e+05	3464
1.683e+05 – 1.757e+05	3492
1.757e+05 – 1.83e+05	3484
1.83e+05 – 1.903e+05	3486
1.903e+05 – 1.976e+05	3401
1.976e+05 – 2.049e+05	3369
2.049e+05 – 2.122e+05	3050
2.122e+05 – 2.196e+05	2907
2.196e+05 – 2.269e+05	2325
2.269e+05 – 2.342e+05	1839
2.342e+05 – 2.415e+05	1672
2.415e+05 – 2.488e+05	1531
2.488e+05 – 2.562e+05	1566
2.562e+05 – 2.635e+05	1679
2.635e+05 – 2.708e+05	1911
2.708e+05 – 2.781e+05	2168
2.781e+05 – 2.854e+05	2580
2.854e+05 – 2.928e+05	2132

Schema

3 columns

Per-column summary. Click column name to jump to its detail.
				Alerts
movieId	numeric	0.0%	87,585
title	text	0.0%	87,382	near_unique
genres	text	0.0%	1,798	one_word duplicates

movieId

numeric identifier

movieId is fully unique across all 87585 rows with zero nulls, spanning 1 to 292757 — classic surrogate key behaviour rather than a measurable quantity. The wide range with a mean of 157651 and median of 165741 suggests non-contiguous IDs (gaps in the sequence), but there is no statistical signal to extract from it. Treatment: use as a join key; exclude from modelling features. high · anthropic:claude-opus-4-7

n: 87,585
nulls: 0 (0.0%)
unique: 87,585
min: 1
max: 292,757
mean: 1.577e+05
median: 165,741
std: 7.901e+04
q1: 112,657
q3: 213,203
iqr: 100,546
skew: -0.3914
kurtosis: -0.5775
n_outliers: 0
outlier_rate: 0
zero_rate: 0

title

text free_text near_unique

Short free-text titles, averaging 4.2 words and 25 characters, with 87,382 unique values across 87,585 rows. The frequent year tokens like (2018), (2016), (2017), (2019) suggest these are titled works (likely films or publications) with release years appended. Near-unique with only 203 duplicates and a high Flesch readability of 81.2; emoji and URL rates are effectively zero. Treatment: Tokenize and embed (or strip the trailing year into a separate feature) before modelling; do not use as a key. high · anthropic:claude-opus-4-7

n: 87,585
nulls: 0 (0.0%)
unique: 87,382
len_min: 2
len_max: 191
len_mean: 25.28
len_median: 23
len_p95: 48
word_mean: 4.226
word_median: 4
n_empty: 0
n_duplicates: 203
duplicate_rate: 0.002318
vocab_size: 19,981
readability_flesch_mean: 81.2
emoji_rate: 3.425e-05
url_rate: 0
one_word_rate: 0.001279
allcaps_rate: 0.005526
boilerplate_rate: 9.134e-05

genres

text feature one_word duplicates

Pipe-delimited movie genre tags, with 1,798 distinct combinations across 87,585 rows and a 97.9% duplicate rate. Drama (12,443), Documentary (8,132), and Comedy (7,761) dominate, while 7,080 rows carry the literal placeholder '(no genres listed)' that should be treated as missing. 91.9% of values are single tokens (word_mean 1.16), so multi-genre entries like 'Comedy|Drama' are the minority. Treatment: split on '|' and one-hot or multi-hot encode; recode '(no genres listed)' as null. high · anthropic:claude-opus-4-7

n: 87,585
nulls: 0 (0.0%)
unique: 1,798
len_min: 3
len_max: 77
len_mean: 13.24
len_median: 12
len_p95: 27
word_mean: 1.162
word_median: 1
n_empty: 0
n_duplicates: 85,787
duplicate_rate: 0.9795
vocab_size: 909
readability_flesch_mean: -117.7
emoji_rate: 0
url_rate: 0
one_word_rate: 0.9192
allcaps_rate: 1.142e-05
boilerplate_rate: 0