data trove phoible phonetics database

InventoryID is a numeric foreign key referencing an inventory dimension table, with exactly 3,020 distinct values spanning 1–3,020 across 105,484 rows, implying heavy repeated use of each ID (average ~35 rows per ID). The distribution is remarkably flat and symmetric (skew ≈ −0.002, kurtosis ≈ −1.15, zero outliers), consistent with a well-populated lookup identifier rather than a measured quantity. Treatment: Left-join on this ID to the inventory dimension table; do not use raw numeric value as a feature. high · anthropic:default

n

105,484

nulls

0 (0.0%)

unique

3,020

min

1

max

3,020

mean

1479

median

1,464

std

843.1

q1

769

q3

2,237

iqr

1,468

skew

-0.002397

kurtosis

-1.146

n_outliers

0

outlier_rate

0

zero_rate

0

This column contains Glottocodes — the standardized 8-character language identifiers used by the Glottolog database (e.g., 'kham1282', 'dutc1256'), confirmed by the near-uniform length of 8 characters (mean 7.999, median 8.0) and the structured alphanumeric format. With only 2,177 unique codes across 105,484 rows, the duplicate rate is extremely high at 97.9%, meaning each language code recurs on average ~48 times — consistent with a dataset where many observations (e.g., words, features, speakers) are annotated per language. The top code 'kham1282' (Kham) appears 622 times, suggesting uneven language coverage in the dataset. Treatment: Left-join on this code against the Glottolog reference table to enrich with language family, geographic coordinates, and macro-area metadata. high · anthropic:default

n

105,484

nulls

0 (0.0%)

unique

2,177

len_min

2

len_max

8

len_mean

7.999

len_median

8

len_p95

8

word_mean

1

word_median

1

n_empty

0

n_duplicates

103,307

duplicate_rate

0.9794

vocab_size

2,168

readability_flesch_mean

94.15

emoji_rate

0

url_rate

0

one_word_rate

1

allcaps_rate

0

boilerplate_rate

0

This column contains ISO 639-3 three-letter language codes, a standardised identifier for natural languages. Every value is exactly 3 characters long (min, mean, max all equal 3) with zero nulls, confirming strict conformity to the standard. The duplicate rate is extremely high at 98.0%, meaning 2,095 distinct codes repeat across 105,484 rows — expected behaviour for a language tag applied to many records. The most frequent code 'mis' (miscellaneous/unattested language) appearing 828 times may warrant attention, as it signals a non-trivial share of records with unidentified languages. Treatment: Use as a categorical grouping key; consider flagging or separating records where ISO6393 equals 'mis' (unattested) before language-based analysis. high · anthropic:default

n

105,484

nulls

0 (0.0%)

unique

2,095

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

103,389

duplicate_rate

0.9801

vocab_size

2,086

readability_flesch_mean

119.5

emoji_rate

0

url_rate

0

one_word_rate

1

allcaps_rate

0

boilerplate_rate

0

This column contains human language names (e.g., 'Dutch', 'Chechen', 'Bengali', 'Iron Ossetic'), functioning as a categorical label drawn from a linguistically diverse vocabulary of 2,716 unique values across 105,484 rows. The duplicate rate of 97.4% (102,768 duplicates) confirms it is a low-cardinality repeating label, not a free-text field. Notably, 13.1% of values are all-caps, suggesting some entries use ISO-style abbreviations or codes alongside full names. The distribution is uneven — the top value 'Iron Ossetic' appears 444 times while many languages appear rarely — indicating a long-tail spread across minority and regional languages. Treatment: Encode as a categorical (label or target-encode) after normalising casing inconsistencies flagged by the 13.1% all-caps rate. high · anthropic:default

n

105,484

nulls

0 (0.0%)

unique

2,716

len_min

2

len_max

79

len_mean

7.822

len_median

7

len_p95

16

word_mean

1.201

word_median

1

n_empty

0

n_duplicates

102,768

duplicate_rate

0.9743

vocab_size

2,670

readability_flesch_mean

53.18

emoji_rate

0

url_rate

0

one_word_rate

0.8433

allcaps_rate

0.1314

boilerplate_rate

0

This column captures a specific dialect designation for each record in what appears to be a linguistic or language survey dataset. The dominant signal is extreme missingness-by-label: 71.9% of rows carry the value 'NA' and a further 7,692 rows (≈7.3%) are empty strings, meaning roughly 79% of records lack a meaningful dialect value. Despite 546 unique values, the effective entropy ratio is only 0.33, confirming that real dialect labels are thinly and unevenly spread across the remaining ~22,000 rows. Treatment: Treat 'NA' and empty-string as missing; consider collapsing rare dialects (below a frequency threshold) into an 'Other' bucket before encoding, and flag high missingness rate (~79%) before any modelling use. high · anthropic:default

n

105,484

nulls

0 (0.0%)

unique

546

top_value

NA

top_rate

0.7187

cardinality

546

entropy

2.969

entropy_ratio

0.3265

GlyphID is a categorical identifier column containing Unicode code point values (e.g., '006D' = 'm', '0069' = 'i', '0061' = 'a') stored as uppercase hexadecimal strings, almost certainly representing character-level glyph references in a typography, OCR, or text-rendering dataset. With only 3,142 unique values across 105,484 rows, the duplicate rate is extremely high at 97.0%, which is expected for a glyph/character frequency table but means this column functions as a low-cardinality label rather than a unique identifier despite its name. All values are fully uppercase (allcaps_rate 1.0), single-token (one_word_rate 1.0), and short (median length 4 characters), consistent with 4–6 character hex codes. The top values map to common Latin lowercase letters, suggesting the underlying corpus is predominantly Latin-script text. Treatment: Map hex strings to Unicode characters for interpretability, then encode as categorical (low-cardinality, 3142 levels) or group by Unicode block/script before modelling. high · anthropic:default

n

105,484

nulls

0 (0.0%)

unique

3,142

len_min

4

len_max

54

len_mean

6.503

len_median

4

len_p95

14

word_mean

1

word_median

1

n_empty

0

n_duplicates

102,342

duplicate_rate

0.9702

vocab_size

1,343

readability_flesch_mean

121.2

emoji_rate

0

url_rate

0

one_word_rate

1

allcaps_rate

1

boilerplate_rate

0

This column contains phoneme symbols from a linguistic or speech dataset, with 3,142 unique phoneme strings across 105,484 rows. Values are overwhelmingly single characters (len_median 1.0, len_mean 1.5, len_max 11), consistent with IPA or ARPABET-style phoneme notation. The duplicate rate is 97.0% (102,342 duplicates), which is expected given a finite phoneme inventory repeated across many words or utterances. The vocab_size of 1,339 distinct tokens against only 3,142 unique values suggests multi-character phoneme strings (e.g., digraphs or diacritics) are also present alongside single-character ones. Treatment: Encode as categorical (label or one-hot) for modelling; 3,142 unique values is manageable but consider grouping by manner/place of articulation if dimensionality is a concern. high · anthropic:default

n

105,484

nulls

0 (0.0%)

unique

3,142

len_min

1

len_max

11

len_mean

1.501

len_median

1

len_p95

3

word_mean

1

word_median

1

n_empty

0

n_duplicates

102,342

duplicate_rate

0.9702

vocab_size

1,339

readability_flesch_mean

114.4

emoji_rate

0

url_rate

0

one_word_rate

1

allcaps_rate

0.001754

boilerplate_rate

0

This column contains allophone representations from a phonology or linguistics dataset, storing the phonetic variants of phonemes (e.g., 'm', 'j', 'w', 's') as very short strings with a mean length of ~2 characters. Strikingly, 53,580 of 105,484 rows (roughly 50.8%) carry the sentinel value 'NA', indicating no allophone recorded, which dominates the duplicate rate of 93.5%. The 6,892 unique values across a vocabulary of only 1,263 words suggest a modest set of phonetic symbols combined in small clusters, consistent with IPA or similar notation. Treatment: Treat 'NA' as missing; encode remaining values as categorical or tokenize individual phoneme symbols before modelling. high · anthropic:default

n

105,484

nulls

0 (0.0%)

unique

6,892

len_min

1

len_max

37

len_mean

2.083

len_median

2

len_p95

4

word_mean

1.129

word_median

1

n_empty

0

n_duplicates

98,592

duplicate_rate

0.9347

vocab_size

1,263

readability_flesch_mean

116.2

emoji_rate

0

url_rate

0

one_word_rate

0.9131

allcaps_rate

0.00291

boilerplate_rate

0

This column is a boolean flag indicating whether a record is classified as 'marginal', with three distinct string values: FALSE, NA, and TRUE. The dominant value is FALSE (78.9% of 105,484 rows), while TRUE is strikingly rare at only 1,347 records (≈1.3%). The presence of 'NA' as a literal string value in 20,874 rows (≈19.8%) is noteworthy — these are not system nulls (null_rate is 0.0) but encoded string missings, which must be handled explicitly rather than via standard null imputation. Treatment: Encode as ternary (FALSE=0, TRUE=1, NA=missing) after converting string 'NA' to actual nulls, then decide on imputation strategy given 19.8% string-missing rate. high · anthropic:default

n

105,484

nulls

0 (0.0%)

unique

3

top_value

FALSE

top_rate

0.7893

cardinality

3

entropy

0.8122

entropy_ratio

0.5125

SegmentClass is a phonological category label classifying 105,484 linguistic segments into exactly three classes: consonant, vowel, and tone. Consonants dominate at 68.5% (72,282 occurrences), vowels account for 29.4% (31,052), and tones are a small minority at just 2.0% (2,150) — a distribution consistent with natural language phoneme inventories but with tones notably underrepresented, suggesting the dataset skews toward non-tonal languages or tonal markings are partially absent. Zero nulls and perfect coverage make this a clean, reliable label. Treatment: One-hot encode or use as a stratification variable; monitor class imbalance for the 'tone' minority class (2,150 samples) in any classification task. high · anthropic:default

n

105,484

nulls

0 (0.0%)

unique

3

top_value

consonant

top_rate

0.6852

cardinality

3

entropy

1.008

entropy_ratio

0.6357

This column identifies the source database or linguistic inventory from which each phonological record was drawn, with 8 distinct source codes across 105,484 rows and no nulls. The top source 'ph' dominates at 34.4% (36,274 rows), likely referring to PHOIBLE or a similar phoneme database, followed by 'ea', 'upsid', 'er', 'saphon', 'aa', 'spa', and 'ra'. The high entropy ratio of 0.899 indicates a relatively even spread across sources despite 'ph' leading — no single source overwhelmingly controls the data. Analysts should be aware that cross-source comparisons may introduce systematic coding differences, as each source may apply distinct phonological conventions. Treatment: One-hot encode or use as a stratification/grouping variable; check for source-specific biases before pooling. high · anthropic:default

n

105,484

nulls

0 (0.0%)

unique

8

top_value

ph

top_rate

0.3439

cardinality

8

entropy

2.697

entropy_ratio

0.8991

This column is a binary tone indicator with only two values: '0' (neutral/absent) and '+' (positive), across 105,484 rows with no nulls. The distribution is severely imbalanced — '0' accounts for 97.96% of records (103,334) while '+' appears in just 2,150 rows (~2%). The entropy of 0.144 (out of a maximum of 1.0 for a binary variable) confirms the near-total dominance of a single class, which would make any model trained on this label prone to predicting '0' exclusively. Treatment: Apply class-balancing techniques (e.g., oversampling '+' or class-weight adjustment) before using as a modelling target. high · anthropic:default

n

105,484

nulls

0 (0.0%)

unique

2

top_value

0

top_rate

0.9796

cardinality

2

entropy

0.1436

entropy_ratio

0.1436

This column is a binary categorical flag likely indicating the presence or absence of stress (e.g., a linguistic or physiological stress marker), encoded as '-' for the negative/absent case and '0' for the positive/present case. The distribution is severely imbalanced: '-' accounts for 97.96% of all 105,484 rows (103,334 occurrences) versus only 2,150 rows for '0'. The entropy ratio of 0.144 confirms near-minimum information content, meaning the positive class is rare and models trained on this column will need class-balancing strategies. Treatment: Apply class-balancing (oversampling or weighted loss) before modelling; consider encoding '-' as 0 and '0' as 1 for numeric compatibility. medium · anthropic:default

n

105,484

nulls

0 (0.0%)

unique

2

top_value

-

top_rate

0.9796

cardinality

2

entropy

0.1436

entropy_ratio

0.1436

n

105,484

nulls

0 (0.0%)

unique

8

top_value

-

top_rate

0.6849

cardinality

8

entropy

1.042

entropy_ratio

0.3472

This column appears to encode a directional or sign indicator with only 4 distinct values: '-', '0', '+', and the compound '-,+'. It is severely imbalanced: the dominant value '-' accounts for 97,764% of rows (103,125 of 105,484), while '+' appears just 204 times and the mixed label '-,+' only 5 times. The near-zero entropy ratio (0.082) confirms the column carries very little information variance, and any model trained on it will be overwhelmed by the '-' class. Treatment: Treat as ordinal or one-hot encode, but flag severe class imbalance (97.8% '-'); consider oversampling minority classes or collapsing '+' and '-,+' before modelling. high · anthropic:default

n

105,484

nulls

0 (0.0%)

unique

4

top_value

-

top_rate

0.9776

cardinality

4

entropy

0.1645

entropy_ratio

0.08225

This column encodes the sign or direction of longitude (or a signed numeric field), with only 6 distinct values across 105,484 rows. The dominant value '-' accounts for 89.9% of records, suggesting the dataset is heavily skewed toward negative longitudes (e.g., Western Hemisphere coordinates). The compound values '-,+', '+,-', and '-,-,+' appear in just 104 rows combined, hinting at rare multi-value or malformed entries that warrant inspection before modelling. Treatment: Investigate compound values ('-,+', '+,-', '-,-,+') for parsing errors; encode '-' as -1, '+' as +1, '0' as 0, and flag or impute the 104 compound rows. medium · anthropic:default

n

105,484

nulls

0 (0.0%)

unique

6

top_value

-

top_rate

0.8991

cardinality

6

entropy

0.5537

entropy_ratio

0.2142

This column encodes a binary phonological feature — consonantal — marking whether a segment is consonantal (+) or not (-), a standard distinctive feature in linguistics datasets. The dominant value is '+' at 60.9% (64,257 rows), with '-' covering 37.0% (39,041 rows). The near-zero third category '0' (2,151 rows) suggests underspecified segments, while the composite values '+,-' (34) and '-,+' (1) are anomalous multi-value entries that likely reflect data quality issues or ambiguous annotations. Treatment: Encode as ordinal or one-hot after splitting composite entries ('+,-', '-,+') into separate flags or flagging them for review. high · anthropic:default

n

105,484

nulls

0 (0.0%)

unique

5

top_value

+

top_rate

0.6092

cardinality

5

entropy

1.085

entropy_ratio

0.4672

n

105,484

nulls

0 (0.0%)

unique

8

top_value

+

top_rate

0.5301

cardinality

8

entropy

1.245

entropy_ratio

0.4149

This column encodes a phonological feature — whether a speech sound is a continuant (airflow continues through the vocal tract) — using '+', '-', and '0' (unspecified/N-A) notation standard in distinctive feature theory. The dominant values are '+' (54.9%, 57,952 rows) and '-' (44,585 rows), which together account for ~97% of records. Surprisingly, 7 of the 9 unique values are composite strings like '-,+' or '-,-,+', suggesting some rows encode sequences or multi-segment entries rather than single-segment features, which is atypical and may indicate data quality or schema inconsistency. Entropy ratio of 0.37 reflects moderate concentration driven almost entirely by the binary +/- split. Treatment: Treat '+'/'-'/'0' as a 3-class categorical; investigate and potentially split or flag the 796 composite multi-value rows before encoding. high · anthropic:default

n

105,484

nulls

0 (0.0%)

unique

9

top_value

+

top_rate

0.5494

cardinality

9

entropy

1.172

entropy_ratio

0.3696

This column encodes a delayed-release flag or classification for 105,484 records using a small set of symbolic tokens: '0' (no delay, 55% of rows), '-' (negative/early shift, 26%), '+' (positive/late shift, 19%), and compound combinations thereof. The compound values ('-,+', '0,-,+', '+,-', '0,0,-,+') suggest the column is sometimes multi-valued — packed as comma-separated strings — which is structurally inconsistent with a simple categorical and implies set-like semantics. No nulls are present, and the entropy ratio of 0.52 reflects a moderately skewed but non-trivial distribution dominated by the '0' class. Treatment: Split compound values on ',' into multi-hot binary columns ('has_0', 'has_minus', 'has_plus') before modelling. high · anthropic:default

n

105,484

nulls

0 (0.0%)

unique

7

top_value

0

top_rate

0.5502

cardinality

7

entropy

1.471

entropy_ratio

0.5238

This column captures whether a phoneme or linguistic segment is classified as an approximant, using a compact symbolic encoding where '-' means absent and '+' means present. The dominant value is '-' at 55.9% of rows (58,966), with '+' accounting for 41.9% (44,266), giving a near-binary distribution with very low entropy (1.12). Surprising are the small number of compound values ('-,+', '-,-,+', '+,-') totalling just 102 rows, suggesting a minority of segments carry ambiguous or multi-valued approximant classifications — possibly transcription artifacts or multi-segment bundles. Treatment: One-hot encode the two dominant values ('-', '+'); bin the three compound values into an 'ambiguous' category or flag and investigate as potential data quality issues before modelling. high · anthropic:default

n

105,484

nulls

0 (0.0%)

unique

6

top_value

-

top_rate

0.559

cardinality

6

entropy

1.12

entropy_ratio

0.4333

This column appears to encode a directional or signed-change indicator, with values like '-', '+', '0', and compound sequences such as '-,+' and '-,-,+' that suggest a history of sign changes or transitions. The dominant value '-' accounts for 96.7% of all 105,484 rows, producing severe class imbalance (entropy ratio of only 0.10), meaning positive or mixed-direction events are rare signals. The compound multi-value entries ('-,+', '-,-,+') are notable — they imply the field can store ordered sequences of transitions, not just a single state. No nulls are present. Treatment: One-hot encode single-value categories; treat compound sequence values ('-,+', '-,-,+') separately via sequence parsing or a dedicated binary flag for multi-transition events; oversample or weight minority classes before modelling. medium · anthropic:default

n

105,484

nulls

0 (0.0%)

unique

5

top_value

-

top_rate

0.9672

cardinality

5

entropy

0.2421

entropy_ratio

0.1043

This column encodes a phonological feature — specifically the presence or absence of a trill articulation — using a small symbol vocabulary of 6 distinct values. The dominant value is "-" (absent/negative), which accounts for 96.15% of 105,484 rows, producing an extremely low entropy of 0.276 and triggering an imbalance alert. The minority values ("0", "+", and compound sequences like "-,+") together cover fewer than 4,000 rows, suggesting trill is a rare feature in this phonological dataset. The compound values ("-,+", "-,-,+", "+,-") with counts of 26, 8, and 2 respectively hint at multi-segment or allophonic annotation, but are statistically negligible. Treatment: One-hot or ordinal encode with caution; severe class imbalance (96.15% negative class) means most models will need oversampling, class weighting, or collapsing rare compound categories before use. high · anthropic:default

n

105,484

nulls

0 (0.0%)

unique

6

top_value

-

top_rate

0.9615

cardinality

6

entropy

0.2762

entropy_ratio

0.1069

n

105,484

nulls

0 (0.0%)

unique

8

top_value

-

top_rate

0.8084

cardinality

8

entropy

0.897

entropy_ratio

0.299

This column encodes lateral direction or laterality coding, likely indicating the side(s) of a clinical finding, anatomical measurement, or test result, using '-' (e.g., left or negative), '+' (right or positive), and '0' (midline or neutral). The dominant value '-' accounts for 93.8% of all 105,484 rows, producing a very low entropy ratio of 0.134, meaning the column is heavily skewed toward a single class. Surprisingly, some values represent sequences of laterality codes (e.g., '-,+', '-,-,+'), suggesting multi-segment or bilateral recordings encoded as comma-delimited strings rather than separate fields. No nulls are present. Treatment: Split comma-delimited compound values into multi-hot binary flags for '-', '+', and '0' presence before modelling; expect severe class imbalance. high · anthropic:default

n

105,484

nulls

0 (0.0%)

unique

8

top_value

-

top_rate

0.9382

cardinality

8

entropy

0.4012

entropy_ratio

0.1337

This column captures labial articulation features in a phonological or linguistic dataset, encoding presence/absence/neutrality of a labial feature per segment (or per segment sequence). The dominant value is '-' (absent) at 68.2% of 105,484 rows, with '+' (present) at 26.8%, suggesting most segments are non-labial. Surprisingly, ~2.9% of values are compound strings like '-,+', '+,-', '-,-,+', indicating multi-segment bundles packed into a single cell rather than a flat atomic feature, which creates a parsing challenge and implies the column is not fully normalized. Treatment: Split compound values on ',' into separate per-segment records or encode as ordered multi-label; then one-hot or ordinal encode the atomic {'-', '+', '0'} values for modelling. high · anthropic:default

n

105,484

nulls

0 (0.0%)

unique

15

top_value

-

top_rate

0.6822

cardinality

15

entropy

1.182

entropy_ratio

0.3025

n

105,484

nulls

0 (0.0%)

unique

8

top_value

0

top_rate

0.703

cardinality

8

entropy

1.194

entropy_ratio

0.398

This column encodes labiodental phonetic feature annotations, likely from a linguistic or phonological dataset where each row represents a speech sound or segment. The dominant value '0' (74,124 rows, 70.3%) indicates the feature is absent or neutral, while '+' and '-' mark positive and negative feature values respectively — a standard binary distinctive-feature notation. Notably, multi-valued strings like '+,-', '-,+', and '+,+,-' appear (60 rows total), suggesting a small number of segments carry conflicting or composite annotations, which may indicate data entry inconsistency or deliberate underspecification. Entropy ratio of 0.39 confirms moderate imbalance with '0' dominating. Treatment: One-hot encode '+', '-', '0'; flag or inspect the 60 multi-valued rows ('+,-', '-,+', '+,+,-') for normalization before modelling. high · anthropic:default

n

105,484

nulls

0 (0.0%)

unique

6

top_value

0

top_rate

0.7027

cardinality

6

entropy

1.006

entropy_ratio

0.3891

This column encodes coronal articulation features in what appears to be a phonological or linguistic dataset, using binary '+'/'-' notation common in distinctive feature theory. The dominant value is '-' (62.8% of 105,484 rows), with '+' covering another 35.0%, making the two primary values account for ~98% of observations. The remaining values ('+,-', '-,+', '-,-,+', '+,-,+') suggest multi-segment or compound entries, which are rare (≤87 occurrences) but worth flagging as potential encoding inconsistencies or multi-value cells that may need splitting. Treatment: Encode primary values '+'/'-'/'0' as ordinal or one-hot features; isolate and inspect the 135 multi-value rows for parsing or splitting before modelling. high · anthropic:default

n

105,484

nulls

0 (0.0%)

unique

7

top_value

-

top_rate

0.6279

cardinality

7

entropy

1.08

entropy_ratio

0.3848

This column captures an anterior anatomical or directional finding coded as a signed categorical variable, with 6 distinct values across 105,484 rows and zero nulls. The dominant value '0' (64.8% of rows) likely indicates absence or neutral status, while '+' (24.4%) and '-' (10.8%) denote positive/negative findings. Surprisingly, a small number of rows (9, 5, and 3) contain compound multi-value strings like '-,+', '+,-', and '-,-,+', suggesting occasional data-entry concatenation errors or multi-event encoding that deviates from the expected single-symbol schema. Treatment: Map '0'/'+'/'-' to ordinal or one-hot encoded features; isolate and investigate the 17 compound-value rows before modelling. medium · anthropic:default

n

105,484

nulls

0 (0.0%)

unique

6

top_value

0

top_rate

0.6482

cardinality

6

entropy

1.251

entropy_ratio

0.4839

This column appears to encode a distribution or change-direction indicator, using a compact symbolic notation: '0' (no change), '-' (decrease), '+' (increase), and comma-separated sequences for multi-step or compound movements. The dominant value '0' covers 66% of 105,484 rows, with '-' (21.1%) and '+' (12.5%) accounting for most of the remainder. Surprisingly, 11 distinct values arise from combinations of these three symbols, suggesting some records capture sequences of directional changes rather than a single state. Entropy ratio of 0.37 confirms moderate but uneven information content, heavily concentrated in the single '0' class. Treatment: Encode as an ordinal or multi-hot feature by splitting on commas and mapping {'-': -1, '0': 0, '+': 1}; treat compound values as sequences. medium · anthropic:default

n

105,484

nulls

0 (0.0%)

unique

11

top_value

0

top_rate

0.6602

cardinality

11

entropy

1.273

entropy_ratio

0.3681

n

105,484

nulls

0 (0.0%)

unique

9

top_value

0

top_rate

0.6485

cardinality

9

entropy

1.287

entropy_ratio

0.406

This column captures a dorsal-surface marking or pattern indicator for biological specimens (likely fish or reptiles), encoding the presence/absence of a feature using '+', '-', and '0' symbols — sometimes as comma-separated sequences indicating multiple zones or segments. The dominant values are '+' (51.7%, n=54,535) and '-' (n=47,052), together accounting for ~96.3% of rows, with 'neutral/absent' coded as '0' (n=2,160). Surprisingly, 11 of the 13 categories are multi-value strings like '-,+' or '-,-,+', suggesting some records encode ordered sequences of dorsal sub-regions rather than a single binary state, creating an implicit structural inconsistency that warrants normalization. Treatment: Split multi-value entries on ',' into ordered sub-features or one-hot encode each position before modelling; treat '+', '-', '0' as a ternary categorical for single-value rows. high · anthropic:default

n

105,484

nulls

0 (0.0%)

unique

13

top_value

+

top_rate

0.517

cardinality

13

entropy

1.235

entropy_ratio

0.3338

This column encodes the direction of price/value movement at a 'high' point — likely a signal or pattern indicator from a time-series or financial dataset, using tokens '0' (no movement), '+' (up), and '-' (down), including multi-step sequences like '-,+' or '+,-,+'. The dominant value is '0' at 46.7% (49,247 rows), followed by '+' at 35,559 and '-' at 19,156, suggesting a strong asymmetry between upward and downward signals. The presence of compound sequence values (e.g., '+,-,+', '-,+,+') with very low frequency — some appearing only once or twice — indicates these multi-step patterns are rare edge cases that may need consolidation or separate treatment. Treatment: Encode top 3 values ('0', '+', '-') as ordinal or one-hot features; collapse rare multi-step sequences (≤845 occurrences) into an 'other' or structured sub-category. medium · anthropic:default

n

105,484

nulls

0 (0.0%)

unique

11

top_value

0

top_rate

0.4669

cardinality

11

entropy

1.594

entropy_ratio

0.4609

n

105,484

nulls

0 (0.0%)

unique

8

top_value

-

top_rate

0.4733

cardinality

8

entropy

1.305

entropy_ratio

0.4351

This column appears to encode a directional or signed-change indicator for a 'front' measurement, using values '0', '-', and '+' as atomic tokens that can be combined into sequences (e.g., '-,+', '+,-,-'). The dominant value '0' accounts for 46.75% of rows, with '-' (34,225) and '+' (20,683) making up most of the remainder — notably, negative changes outnumber positive ones by ~1.65:1. The compound sequence values ('-,+', '+,-', etc.) suggest multi-step event chains are encoded as a single string, which is an unusual encoding pattern that may require parsing before modelling. Treatment: Parse composite sequences (e.g., '-,+') into structured event arrays or ordinal counts; then one-hot or embed atomic states before modelling. medium · anthropic:default

n

105,484

nulls

0 (0.0%)

unique

13

top_value

0

top_rate

0.4675

cardinality

13

entropy

1.592

entropy_ratio

0.4302

This column encodes directional movement or change signals for a 'back' dimension, using a compact notation of '+', '-', and '0' tokens — likely representing price/value movement sequences (e.g., up, down, flat) over a lookback window. The dominant value is '0' at 46.7% (49,270 rows), followed by '-' at 39,749 and '+' at 15,547, indicating a strong bearish/negative skew relative to positive signals. Compound multi-step sequences like '+,-' (511) and '-,+' (367) exist but are rare, and a handful of three-step sequences appear at the tail, suggesting variable-length encoding that could cause parsing issues if treated as a simple label. Treatment: Parse composite multi-token values (e.g., '+,-') into structured sequences or ordinal scores before modelling; consider one-hot or frequency encoding for the simple single-token majority. medium · anthropic:default

n

105,484

nulls

0 (0.0%)

unique

12

top_value

0

top_rate

0.4671

cardinality

12

entropy

1.521

entropy_ratio

0.4244

n

105,484

nulls

0 (0.0%)

unique

8

top_value

0

top_rate

0.7132

cardinality

8

entropy

1.114

entropy_ratio

0.3712

This column encodes the phonetic feature 'retracted tongue root' (RTR), a binary or multi-valued linguistic annotation used in phonological databases to mark vowel or consonant articulation. The dominant value is '-' (absence of RTR) at 97.44% of 105,484 rows, making the feature extremely rare in this dataset — only ~2,696 tokens show any positive marking. The compound values ('-,+', '-,-,+', etc.) suggest per-segment annotation strings rather than single-token labels, indicating a sequence or multi-segment scope. Treatment: Flag severe class imbalance (97.44% negative); use oversampling or class-weighted models if predicting RTR; consider splitting compound strings into per-segment binary indicators before modelling. high · anthropic:default

n

105,484

nulls

0 (0.0%)

unique

7

top_value

-

top_rate

0.9744

cardinality

7

entropy

0.1935

entropy_ratio

0.06892

This column encodes the Advanced Tongue Root (ATR) phonological feature, a binary articulatory distinction marked as '+' (present), '-' (absent), or '0' (neutral/not applicable), typical of linguistic phoneme inventories. The distribution is severely imbalanced: '-' dominates at 97.87% (103,238 of 105,484 rows), '0' appears in only 2,235 rows, and '+' is nearly absent with just 11 occurrences. The near-zero entropy ratio (0.094) confirms that '+ATR' is a vanishingly rare feature in this dataset, which would make any model predicting '+' extremely difficult to train without resampling. Treatment: Treat as ordinal or one-hot encoded categorical; oversample or reweight the '+' class (n=11) before modelling, or collapse '+' and '0' if class separation is infeasible. high · anthropic:default

n

105,484

nulls

0 (0.0%)

unique

3

top_value

-

top_rate

0.9787

cardinality

3

entropy

0.1496

entropy_ratio

0.09438

n

105,484

nulls

0 (0.0%)

unique

7

top_value

+

top_rate

0.6797

cardinality

7

entropy

1.051

entropy_ratio

0.3745

This column encodes whether an epilaryngeal phonation source is present, using a ternary scheme: absent ('-'), present ('+')), or a neutral/ambiguous state ('0'). The distribution is severely imbalanced: the '-' (absent) class dominates at 97.9% of 105,484 rows, while '+' (present) appears in only 31 records (~0.03%), making positive-class detection extremely challenging. The near-zero entropy (0.147) confirms almost no informational variance in this column as-is. Treatment: Flag severe class imbalance ('+' = 31 of 105,484); apply oversampling or class-weighted modelling, and consider binary encoding after collapsing '-' vs. non-'-'. high · anthropic:default

n

105,484

nulls

0 (0.0%)

unique

3

top_value

-

top_rate

0.9793

cardinality

3

entropy

0.1474

entropy_ratio

0.09303

n

105,484

nulls

0 (0.0%)

unique

10

top_value

-

top_rate

0.9182

cardinality

10

entropy

0.4965

entropy_ratio

0.1495

This column captures a clinical or phonetic annotation for constricted glottis, encoded as presence/absence symbols across 105,484 records with no nulls and only 7 unique values. The dominant value is '-' (absent/negative), appearing in 94.5% of rows (99,727), while '+' (present) accounts for just 3,383 rows — indicating a rare positive condition. The compound values ('+,-', '-,+', '+,-,-', '-,-,+') suggest multi-observation or multi-segment sequences for a tiny fraction of records, but with counts of 141, 93, 1, and 1 respectively, these are near-negligible. The extremely low entropy (0.372, entropy ratio 0.132) confirms the column is heavily imbalanced toward the negative class. Treatment: Binarize into presence/absence flag; treat compound multi-segment values as positive; account for severe class imbalance (94.5% negative) during modelling. high · anthropic:default

n

105,484

nulls

0 (0.0%)

unique

7

top_value

-

top_rate

0.9454

cardinality

7

entropy

0.3717

entropy_ratio

0.1324

This column is a three-valued categorical flag, likely representing a directional or strength indicator with values '-', '0', and '+'. The dominant value is '-' at 68.1% (71,867 rows), '0' accounts for 31.5% (33,202 rows), and '+' is strikingly rare at only 415 occurrences (~0.4%), creating a heavily imbalanced distribution. The near-absence of '+' values is a notable surprise and may indicate a rare positive condition, signal, or classification outcome worth investigating for class imbalance before modelling. Treatment: Ordinal-encode as -1/0/1 or one-hot encode, and apply class-imbalance handling (e.g. oversampling '+') before modelling. high · anthropic:default

n

105,484

nulls

0 (0.0%)

unique

3

top_value

-

top_rate

0.6813

cardinality

3

entropy

0.9335

entropy_ratio

0.589

This column represents a ternary linguistic or phonological feature, almost certainly a 'lenis' (weak/voiced) marker with values '-' (absent/irrelevant), '0' (neutral), and '+' (present/lenis). The dominant value is '-' at 68.1% (71,866 rows), while the positive lenis marker '+' is strikingly rare at only 416 occurrences (~0.4%), creating a heavily imbalanced distribution. No nulls exist across all 105,484 rows, and entropy is moderate at 0.93 bits, well below the theoretical maximum, confirming the skew toward the negative class. Treatment: Encode as ordinal or one-hot; be aware that the '+' class (416 samples) is severely underrepresented and will require oversampling or class-weight adjustment before modelling. high · anthropic:default

n

105,484

nulls

0 (0.0%)

unique

3

top_value

-

top_rate

0.6813

cardinality

3

entropy

0.9336

entropy_ratio

0.589

This column encodes the presence or absence of a raised-larynx ejective phonological feature, using a diacritic notation system common in linguistic databases (e.g., IPA or feature matrices). The dominant value is '-' (absent/not applicable), appearing in 96.4% of 105,484 rows, creating severe class imbalance with an entropy ratio of only 0.10. Minority values include '0' (2,150 rows), '+' (1,573 rows), and compound sequences like '-,+' and '+,-', suggesting some segments receive multi-valued or composite feature annotations. The near-absence of nulls (0.0%) indicates complete annotation coverage, but the extreme skew means this feature will contribute negligible signal in most modelling contexts without deliberate resampling or grouping. Treatment: Collapse compound values ('-,+', '+,-', '-,-,+') into a unified category and apply oversampling or class-weight adjustment before modelling given 96.4% imbalance. high · anthropic:default

n

105,484

nulls

0 (0.0%)

unique

6

top_value

-

top_rate

0.9637

cardinality

6

entropy

0.2675

entropy_ratio

0.1035

This column encodes a phonological feature — specifically whether a sound has a lowered larynx implosive articulation — using a symbolic notation system ('+', '-', and combinations). The distribution is severely imbalanced: 97.3% of the 105,484 rows carry the default/absent value '-', with only 2,150 instances of '0', 716 of '+', and fewer than 10 combined entries. The near-zero entropy ratio (0.088) confirms this column carries almost no information for most records, which would make it a very weak standalone predictor. Treatment: Flag the severe imbalance; consider binarising ('+' vs. all others) or dropping if the rare positive class is insufficient for modelling purposes. high · anthropic:default

n

105,484

nulls

0 (0.0%)

unique

5

top_value

-

top_rate

0.9727

cardinality

5

entropy

0.2034

entropy_ratio

0.08759

This column captures click direction or interaction type, encoded as symbolic tokens ('-', '0', '+') with combination values ('+,-', '-,+'). The dominant value is '-' at 68.2% of 105,484 rows, while positive-click signals ('+', '+,-', '-,+') account for only ~311 rows combined (~0.3%), suggesting a heavily imbalanced outcome or event flag. The presence of multi-value strings like '+,-' and '-,+' implies ordered sequences of click events were sometimes collapsed into a single cell rather than normalized — this warrants investigation before modelling. Treatment: Ordinal-encode or one-hot after splitting multi-value entries ('+,-', '-,+'); treat class imbalance (~0.3% positive) before using as a classification target. high · anthropic:default

n

105,484

nulls

0 (0.0%)

unique

5

top_value

-

top_rate

0.6823

cardinality

5

entropy

0.9283

entropy_ratio

0.3998