data trove glottolog languoids

This column is a structured language or dialect identifier, following the Glottolog-style 8-character code pattern (4 letters + 4 digits, e.g. 'tibe1272', 'east2553'). All 23,740 values are exactly 8 characters long (len_min/max/mean/median all equal 8) with zero nulls and zero duplicates, making it a perfect primary key. The top_words sample aligns precisely with Glottolog languoid codes, suggesting this is a linguistic database. No anomalies — the column is unusually clean. Treatment: Retain as primary key; left-join on this id to enrich with Glottolog metadata. high · anthropic:default

n

23,740

nulls

0 (0.0%)

unique

23,740

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

0

duplicate_rate

0

vocab_size

20,000

readability_flesch_mean

86.11

emoji_rate

0

url_rate

0

one_word_rate

1

allcaps_rate

0

boilerplate_rate

0

This column represents language family identifiers, using Glottolog-style codes (e.g., 'atla1278' = Atlantic-Congo, 'aust1307' = Austronesian, 'indo1319' = Indo-European). With only 287 unique values across 23,740 rows it acts as a low-to-medium cardinality grouping key for linguistic families. The top value 'atla1278' is notably dominant at 20.0% of rows (4,663 records), and the top two families together account for roughly 36% of the dataset, signalling a heavily skewed distribution toward large African and Pacific language families. Treatment: Left-join on this id to a language-family reference table; use as a categorical grouping variable or fixed effect in models, noting the severe class imbalance toward 'atla1278' and 'aust1307'. high · anthropic:default

n

23,740

nulls

429 (1.8%)

unique

287

top_value

atla1278

top_rate

0.2

cardinality

287

entropy

4.886

entropy_ratio

0.5984

This column contains Glottolog language family or clade identifiers — fixed 8-character alphanumeric codes (e.g. 'book1242', 'pidg1258') linking each row to a parent node in a linguistic taxonomy. Every value is exactly 8 characters long (len_min=8, len_max=8) and all are single tokens (one_word_rate=1.0), consistent with Glottolog's standardised glottocode format. The duplicate rate is notably high at 68.5%, with 'book1242' appearing 399 times, indicating many child languages share the same parent grouping — expected for a hierarchical classification. Null rate is low at 1.81%, suggesting most records have a resolvable parent. Treatment: Left-join on this id against a Glottolog taxonomy table to enrich with family-level linguistic metadata. high · anthropic:default

n

23,740

nulls

429 (1.8%)

unique

7,338

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

15,973

duplicate_rate

0.6852

vocab_size

7,189

readability_flesch_mean

91.19

emoji_rate

0

url_rate

0

one_word_rate

1

allcaps_rate

0

boilerplate_rate

0

This column contains names of linguistic or geographic entities — likely language varieties, dialects, or regional groupings, as evidenced by top words such as 'nuclear', 'central', 'western', 'eastern', 'northern', 'southern', 'language', and 'sign'. All 23,740 rows are unique with zero nulls and zero duplicates, making this a perfect natural-language identifier. Surprisingly, 69.5% of values are single words despite a mean length of ~9.95 characters, suggesting a mix of short atomic names and multi-word descriptors (up to 58 characters), with a vocabulary of 17,915 distinct tokens across the corpus. Treatment: Use as a human-readable label or index key; tokenize and embed if semantic similarity between names is needed downstream. high · anthropic:default

n

23,740

nulls

0 (0.0%)

unique

23,740

len_min

1

len_max

58

len_mean

9.95

len_median

8

len_p95

22

word_mean

1.398

word_median

1

n_empty

0

n_duplicates

0

duplicate_rate

0

vocab_size

17,915

readability_flesch_mean

42.62

emoji_rate

0

url_rate

0

one_word_rate

0.6953

allcaps_rate

0.0001685

boilerplate_rate

0

This column is a boolean flag (stored as strings 'True'/'False') indicating whether a record has some bookkeeping status applied — likely a soft-delete, correction, or administrative override marker. The distribution is severely imbalanced: 98.3% of rows are 'False' (23,341) versus only 1.7% 'True' (399), which triggered the imbalance alert. The entropy of 0.123 confirms near-zero information variance, meaning this flag is rarely set. Analysts should treat the 'True' minority with care as it may mark records to exclude or handle separately. Treatment: Use as a filter or stratification variable; if modelling, oversample or reweight the 399 'True' cases, or exclude them if they represent invalid/corrected records. high · anthropic:default

n

23,740

nulls

0 (0.0%)

unique

2

top_value

False

top_rate

0.9832

cardinality

2

entropy

0.1231

entropy_ratio

0.1231

This column classifies linguistic entities into one of three hierarchical levels: 'dialect', 'language', and 'family', suggesting the dataset concerns a linguistic taxonomy or inventory (e.g., Ethnologue-style data). With only 3 unique values across 23,740 rows and zero nulls, it is a clean, fully populated categorical field. Notably, 'dialect' is the modal class at ~46% (10,920), followed by 'language' at ~35.7% (8,481) and 'family' at ~18.3% (4,339) — the class imbalance is moderate but not severe. The entropy ratio of 0.943 is surprisingly high for a 3-class variable, indicating near-uniform distribution across categories. Treatment: One-hot encode or ordinal-encode (dialect < language < family) depending on whether hierarchy is meaningful to the model. high · anthropic:default

n

23,740

nulls

0 (0.0%)

unique

3

top_value

dialect

top_rate

0.46

cardinality

3

entropy

1.494

entropy_ratio

0.9426

This column represents a conservation or endangerment status classification, most likely for languages or species, with 6 distinct ordinal categories ranging from 'safe' to 'extinct'. The distribution is heavily skewed: 'safe' dominates at nearly 80% of records (18,965 of 23,740), while the threatened categories collectively account for only ~20%. The low entropy ratio (0.445) confirms this imbalance, and analysts building classification models should expect a significant class imbalance problem. Treatment: Encode as ordinal (safe < vulnerable < severely endangered < definitely endangered < critically endangered < extinct) and apply class-imbalance mitigation (e.g., oversampling or class weights) before modelling. high · anthropic:default

n

23,740

nulls

0 (0.0%)

unique

6

top_value

safe

top_rate

0.7989

cardinality

6

entropy

1.15

entropy_ratio

0.4447

This column contains geographic latitude values for records in the dataset, spanning from -55.27° (southern South America or similar) to 73.14° (Arctic latitudes), consistent with global coverage. The most striking issue is a 66.54% null rate — two-thirds of rows lack a latitude value, which severely limits spatial analysis. The distribution is mildly right-skewed (skew 0.54) with a mean of ~8.2° and median of ~6.3°, suggesting a concentration of records in tropical/equatorial regions. Only 129 outliers are flagged (1.6%), so the non-null values themselves appear geographically plausible. Treatment: Investigate and impute or filter nulls (66.54% missing) before use; pair with longitude for spatial modelling or clustering. high · anthropic:default

n

23,740

nulls

15,797 (66.5%)

unique

7,798

min

-55.27

max

73.14

mean

8.17

median

6.306

std

18.96

q1

-5.137

q3

19.34

iqr

24.47

skew

0.5403

kurtosis

0.3006

n_outliers

129

outlier_rate

0.01624

zero_rate

0

This column represents geographic longitude, covering nearly the full global range from –178.785° to 179.306°. The null rate of 66.54% is a critical alert — two-thirds of records lack a coordinate, which may indicate missing geolocation data for a large subset of entities. The IQR of ~117° and std of ~81° confirm values are broadly distributed across hemispheres, and the mean (51.27°) skewing toward positive (Eastern) longitudes with a median of 47.72° suggests a concentration in Europe/Asia. Only 13 outliers are flagged despite the extreme range, consistent with legitimate global coordinates rather than data entry errors. Treatment: Investigate and impute or filter the 66.54% null records before use; pair with latitude for geospatial modelling or clustering. high · anthropic:default

n

23,740

nulls

15,797 (66.5%)

unique

7,757

min

-178.8

max

179.3

mean

51.27

median

47.72

std

81.14

q1

7.235

q3

124.1

iqr

116.9

skew

-0.4832

kurtosis

-0.7745

n_outliers

13

outlier_rate

0.001637

zero_rate

0

This column contains ISO 639-3 language codes — standardised three-letter identifiers for individual languages (e.g., 'aiz', 'kbt', 'mij'). Every non-null value is exactly 3 characters long (min=3, max=3, mean=3.0) and appears only once, yielding 7,968 unique codes across 7,968 vocabulary entries with zero duplicates — consistent with a lookup or reference table of distinct languages. The striking concern is a 66.44% null rate, meaning two-thirds of the 23,740 rows carry no code at all, which likely reflects languages or entries not yet mapped to an ISO 639-3 identifier. Treatment: Left-join on this code to enrich with ISO 639-3 language metadata; investigate and impute or flag the 66.44% nulls before joining. high · anthropic:default

n

23,740

nulls

15,772 (66.4%)

unique

7,968

len_min

3

len_max

3

len_mean

3

len_median

3

len_p95

3

word_mean

1

word_median

1

n_empty

0

n_duplicates

0

duplicate_rate

0

vocab_size

7,968

readability_flesch_mean

119.5

emoji_rate

0

url_rate

0

one_word_rate

1

allcaps_rate

0

boilerplate_rate

0

This column contains textual descriptions with zero null values across 23,740 rows. The profile was skipped by saturn, so no uniqueness, length, or token statistics are available — the column's exact nature (short labels vs. long free text) cannot be determined from the evidence. The 'skipped' alert and absent stats dict suggest the profiler either timed out or excluded this column type from deep analysis. Treatment: Tokenize and embed before modelling, or apply NLP preprocessing (stopword removal, TF-IDF/sentence embeddings) depending on downstream task. low · anthropic:default

n

23,740

nulls

0 (0.0%)

unique

—

This column contains markup or formatted description text (likely HTML, Markdown, or similar) across 23,740 rows with zero nulls. The profiler skipped detailed analysis — indicated by the 'skipped' alert — so no uniqueness, length, or content statistics are available. Without further inspection, the content type and cardinality are unknown, but the name strongly implies free-form or templated descriptive text with embedded formatting syntax. Treatment: Strip markup tags, then tokenize and embed before modelling, or inspect raw values to confirm structure before deciding on parsing strategy. low · anthropic:default

n

23,740

nulls

0 (0.0%)

unique

—

This column counts the number of children or family members associated with a record, with 90.8% of values being exactly zero and a median of 0.0 — meaning the vast majority of subjects have no associated family/child count. The distribution is extraordinarily right-skewed (skew = 44.4, kurtosis = 2352.9) with a max of 859.0 and 2,179 outliers (9.2% of rows), suggesting a small subset of records have implausibly large counts that warrant investigation for data-entry errors or aggregation anomalies. Treatment: Investigate extreme values (max 859.0) for data errors; consider capping/winsorizing at a defensible threshold, then apply log1p transform before modelling. high · anthropic:default

n

23,740

nulls

0 (0.0%)

unique

88

min

0

max

859

mean

0.8792

median

0

std

13.2

q1

0

q3

0

iqr

0

skew

44.4

kurtosis

2353

n_outliers

2,179

outlier_rate

0.09179

zero_rate

0.9082

This column counts the number of child languages associated with a record, likely in a linguistic or taxonomy dataset. The distribution is extremely right-skewed (skew = 41.86, kurtosis = 2115.08): 81.7% of rows have a value of zero, the median is 0.0, and the IQR is 0.0, yet the mean is ~2.0 and the max reaches 1,435. This implies a small number of parent-language nodes dominate with very large child counts, while most entries are leaf nodes with no children. Over 18% of rows (4,339) are flagged as outliers, reinforcing the extreme concentration at zero with a long, sparse upper tail. Treatment: Log-transform (log1p) or apply a zero-inflated model; consider a binary 'has_children' flag as a complementary feature given the 81.7% zero rate. high · anthropic:default

n

23,740

nulls

0 (0.0%)

unique

126

min

0

max

1,435

mean

1.996

median

0

std

23.41

q1

0

q3

0

iqr

0

skew

41.86

kurtosis

2115

n_outliers

4,339

outlier_rate

0.1828

zero_rate

0.8172

This column counts the number of child dialects associated with each record in what appears to be a linguistic or language-taxonomy dataset. The distribution is extreme: 74.4% of rows have zero child dialects, the median is 0, and the IQR is just 0–1, yet the mean is 3.39 and the maximum reaches 2369—producing a skew of 42.2 and a kurtosis of 2159.3. Nearly 18% of rows (4,272) are flagged as outliers, indicating a small number of language/dialect nodes act as hubs with enormous fan-out while the vast majority are leaf nodes. Treatment: Log-transform (log1p) before regression or distance-based modelling; consider also a binary 'has_children' flag and a separate high-cardinality indicator given the extreme outliers. high · anthropic:default

n

23,740

nulls

0 (0.0%)

unique

164

min

0

max

2,369

mean

3.389

median

0

std

36.8

q1

0

q3

1

iqr

1

skew

42.22

kurtosis

2159

n_outliers

4,272

outlier_rate

0.1799

zero_rate

0.7442

This column contains ISO 3166-1 alpha-2 country codes, functioning as a categorical geographic identifier for each record. The most striking issue is its 64.24% null rate, meaning nearly two-thirds of the 23,740 rows carry no country information. Among populated rows, Papua New Guinea ('PG') dominates at 10.29% of non-null values, followed by Indonesia ('ID') and Nigeria ('NG') — a developing-world skew that may reflect data collection bias. The 680-unique-value count is anomalously high for standard two-letter ISO codes (only ~250 exist), suggesting some values may be multi-code concatenations, malformed entries, or non-standard codes. Treatment: Investigate the 680 distinct values for malformed or concatenated codes; impute or flag nulls (64.24% missing) before use; one-hot encode or embed after cleaning. medium · anthropic:default

n

23,740

nulls

15,250 (64.2%)

unique

680

top_value

PG

top_rate

0.1029

cardinality

680

entropy

6.493

entropy_ratio

0.6901