word stringlengths 2 17 ⌀ | rank int64 1 1.74k | band int64 1 3 | sfi float64 47.2 71.5 | freq_per_million float64 5.29 1.42k |
|---|---|---|---|---|
mister | 1 | 1 | 71.51 | 1,416.4 |
goods | 2 | 1 | 66.71 | 468.5 |
equity | 3 | 1 | 66.15 | 411.67 |
dividend | 4 | 1 | 65.15 | 327.16 |
portfolio | 5 | 1 | 64.97 | 314.17 |
sponsorship | 6 | 1 | 62.37 | 172.54 |
inventory | 7 | 1 | 63.62 | 230.19 |
transaction | 8 | 1 | 64.52 | 283.43 |
non | 9 | 1 | 64.38 | 273.88 |
lease | 10 | 1 | 63.06 | 202.09 |
hedge | 11 | 1 | 62.32 | 170.71 |
distribution | 12 | 1 | 63.3 | 213.91 |
premium | 13 | 1 | 62.93 | 196.21 |
client | 14 | 1 | 63.27 | 212.36 |
impact | 15 | 1 | 63.3 | 213.6 |
authority | 16 | 1 | 63.37 | 217.48 |
obtain | 17 | 1 | 62.67 | 184.93 |
maturity | 18 | 1 | 61.63 | 145.44 |
publish | 19 | 1 | 62.63 | 183.07 |
sometime | 20 | 1 | 62.08 | 161.3 |
economist | 21 | 1 | 61.59 | 144.2 |
media | 22 | 1 | 61.78 | 150.64 |
marginal | 23 | 1 | 60.97 | 124.98 |
seller | 24 | 1 | 61.28 | 134.26 |
merger | 25 | 1 | 61.37 | 137.16 |
audit | 26 | 1 | 61.09 | 128.4 |
e-book | 27 | 1 | 60.51 | 112.43 |
consumption | 28 | 1 | 60.96 | 124.67 |
variance | 29 | 1 | 59.49 | 88.89 |
depreciation | 30 | 1 | 59.88 | 97.18 |
strategic | 31 | 1 | 60.71 | 117.86 |
anti | 32 | 1 | 59.89 | 97.41 |
recession | 33 | 1 | 60.73 | 118.2 |
entity | 34 | 1 | 59.9 | 97.74 |
utility | 35 | 1 | 60.39 | 109.43 |
productivity | 36 | 1 | 60.63 | 115.54 |
euro | 37 | 1 | 59.75 | 94.31 |
overhead | 38 | 1 | 58.95 | 78.52 |
organizational | 39 | 1 | 59.84 | 96.33 |
commodity | 40 | 1 | 60.23 | 105.4 |
monetary | 41 | 1 | 60.42 | 110.17 |
aggregate | 42 | 1 | 59.8 | 95.61 |
valuation | 43 | 1 | 59.81 | 95.75 |
fiscal | 44 | 1 | 60.13 | 103 |
payable | 45 | 1 | 59.29 | 84.9 |
default | 46 | 1 | 59.8 | 95.61 |
aspect | 47 | 1 | 59.91 | 97.84 |
calculation | 48 | 1 | 59.62 | 91.62 |
subsidiary | 49 | 1 | 59.87 | 97.02 |
mid | 50 | 1 | 59.86 | 96.85 |
allocation | 51 | 1 | 59.23 | 83.75 |
coupon | 52 | 1 | 58.95 | 78.52 |
volatility | 53 | 1 | 58.81 | 76.01 |
retailer | 54 | 1 | 59.85 | 96.67 |
deviation | 55 | 1 | 58.64 | 73.1 |
receivable | 56 | 1 | 58.03 | 63.59 |
equilibrium | 57 | 1 | 59.13 | 81.8 |
pre | 58 | 1 | 59.7 | 93.43 |
creditor | 59 | 1 | 59.52 | 89.57 |
derivative | 60 | 1 | 59.09 | 81.08 |
sub | 61 | 1 | 58.37 | 68.7 |
incur | 62 | 1 | 59.04 | 80.19 |
surplus | 63 | 1 | 59.5 | 89.2 |
annuity | 64 | 1 | 57.44 | 55.41 |
disclosure | 65 | 1 | 58.9 | 77.68 |
regime | 66 | 1 | 58.53 | 71.26 |
risky | 67 | 1 | 58.86 | 76.89 |
leverage | 68 | 1 | 58.37 | 68.65 |
broker | 69 | 1 | 58.84 | 76.61 |
outstanding | 70 | 1 | 58.71 | 74.24 |
internet | 71 | 1 | 57.99 | 63 |
parliament | 72 | 1 | 56.92 | 49.22 |
coalition | 73 | 1 | 57.15 | 51.87 |
maximize | 74 | 1 | 58.36 | 68.48 |
beta | 75 | 1 | 57.72 | 59.21 |
lender | 76 | 1 | 58.7 | 74.08 |
gross | 77 | 1 | 58.51 | 70.91 |
liquidity | 78 | 1 | 58.68 | 73.77 |
stockholder | 79 | 1 | 56.64 | 46.17 |
vendor | 80 | 1 | 58.46 | 70.12 |
fraud | 81 | 1 | 58.67 | 73.59 |
allocate | 82 | 1 | 58.37 | 68.7 |
regulator | 83 | 1 | 58.01 | 63.3 |
par | 84 | 1 | 57.74 | 59.38 |
swap | 85 | 1 | 58.18 | 65.83 |
bankruptcy | 86 | 1 | 58.49 | 70.69 |
provider | 87 | 1 | 57.76 | 59.7 |
regression | 88 | 1 | 57.04 | 50.54 |
turnover | 89 | 1 | 58.29 | 67.41 |
accountant | 90 | 1 | 58.1 | 64.59 |
constitution | 91 | 1 | 56.67 | 46.43 |
trader | 92 | 1 | 58.21 | 66.24 |
monopoly | 93 | 1 | 58.34 | 68.23 |
correlation | 94 | 1 | 57.41 | 55.1 |
stockmarket | 95 | 1 | 56.21 | 41.79 |
ex | 96 | 1 | 58.42 | 69.43 |
profitable | 97 | 1 | 58.38 | 68.94 |
breach | 98 | 1 | 58.08 | 64.23 |
subsidy | 99 | 1 | 57.99 | 62.96 |
auditor | 100 | 1 | 58.09 | 64.42 |
End of preview. Expand in Data Studio
NLTK Word Lists
English word lists from NLTK, the New General Service List Project, and Bing Liu's Opinion Lexicon.
Configs
| Config | Words | Schema | License | Source |
|---|---|---|---|---|
en |
235,886 | word |
NLTK (other) | NLTK words corpus |
en-basic |
850 | word |
Public domain | Ogden Basic English (1930) |
ngsl |
2,809 | word, rank, sfi, freq_per_million |
CC-BY-SA 4.0 | New General Service List 1.2 |
toeic |
1,250 | word, rank, sfi, freq_per_million |
CC-BY-SA 4.0 | TOEIC Service List 1.2 |
nawl |
963 | word, rank, band, sfi, freq_per_million |
CC-BY-SA 4.0 | New Academic Word List 1.2 |
bsl |
1,744 | word, rank, band, sfi, freq_per_million |
CC-BY-SA 4.0 | Business Service List 1.2 |
opinion-positive |
2,006 | word |
CC-BY 4.0 | Hu & Liu Opinion Lexicon |
opinion-negative |
4,783 | word |
CC-BY 4.0 | Hu & Liu Opinion Lexicon |
See Also
These related word list datasets are also accessible via nltk.corpus.words.words():
| Dataset | Contents | NLTK access |
|---|---|---|
| nltk-data-hub/dolch | 315 Dolch sight words, 8 POS configs | words.words("dolch"), words.words("dolch-verbs"), … |
| nltk-data-hub/swadesh | 207 Swadesh concepts × 24 languages | words.words("swadesh-en"), words.words("swadesh-de"), … |
Schemas
en, en-basic, opinion-positive, opinion-negative — word only
| Column | Type | Description |
|---|---|---|
word |
string | The word |
ngsl and toeic — frequency metadata, no band
| Column | Type | Description |
|---|---|---|
word |
string | Headword / lemma |
rank |
int | Frequency rank (1 = most frequent) |
sfi |
float | Standard Frequency Index |
freq_per_million |
float | Adjusted frequency per million words |
nawl and bsl — frequency metadata + pedagogical band
| Column | Type | Description |
|---|---|---|
word |
string | Headword / lemma |
rank |
int | Frequency rank within this list |
band |
int | Pedagogical band grouping (lower = more frequent) |
sfi |
float | Standard Frequency Index |
freq_per_million |
float | Adjusted frequency per million words |
Usage
from datasets import load_dataset
ds = load_dataset("nltk-data-hub/words", "ngsl")
ds = load_dataset("nltk-data-hub/words", "nawl")
ds = load_dataset("nltk-data-hub/words", "opinion-positive")
ds = load_dataset("nltk-data-hub/words", "opinion-negative")
Via NLTK
import nltk
nltk.download("words", hf=True)
nltk.corpus.words.words("ngsl") # 2,809 words, frequency order
nltk.corpus.words.words("nawl") # 963 academic words
nltk.corpus.words.words("bsl") # 1,744 business words
nltk.corpus.words.words("toeic") # 1,250 TOEIC words
nltk.corpus.words.words("opinion-positive") # 2,006 positive opinion words
nltk.corpus.words.words("opinion-negative") # 4,783 negative opinion words
nltk.corpus.words.words("en") # 235,886 words
nltk.corpus.words.words("en-basic") # Ogden 850
# Routed to nltk-data-hub/dolch:
nltk.corpus.words.words("dolch") # 315 Dolch sight words
nltk.corpus.words.words("dolch-verbs") # 92 Dolch verbs
# Routed to nltk-data-hub/swadesh:
nltk.corpus.words.words("swadesh-en") # 207 English Swadesh words
nltk.corpus.words.words("swadesh-de") # 207 German Swadesh words
Licenses
en,en-basic: distributed as part of the NLTK corpus data package.ngsl,toeic,nawl,bsl: © Browne, Culligan & Phillips, licensed under CC-BY-SA 4.0.opinion-positive,opinion-negative: © Bing Liu, licensed under CC-BY 4.0.
Citations
@book{nltk,
author = {Bird, Steven and Klein, Ewan and Loper, Edward},
title = {Natural Language Processing with Python},
publisher = {O'Reilly Media},
year = {2009},
url = {https://www.nltk.org/}
}
@article{ngsl,
author = {Browne, Charles},
title = {A New General Service List: The Better Mousetrap We've Been Looking For?},
journal = {Vocabulary Learning and Instruction},
volume = {3},
number = {2},
pages = {1--10},
year = {2014},
doi = {10.7820/vli.v03.2.browne}
}
@misc{nawl,
author = {Browne, Charles and Culligan, Brent and Phillips, Joseph},
title = {New Academic Word List 1.2},
year = {2013},
url = {https://www.newgeneralservicelist.com/nawl-new-academic-word-list}
}
@misc{tsl,
author = {Browne, Charles and Culligan, Brent},
title = {TOEIC Service List 1.2},
year = {2016},
url = {https://www.newgeneralservicelist.com/toeic-service-list}
}
@misc{bsl,
author = {Browne, Charles and Culligan, Brent},
title = {Business Service List 1.2},
year = {2016},
url = {https://www.newgeneralservicelist.com/business-service-list}
}
@inproceedings{opinion_lexicon,
author = {Hu, Minqing and Liu, Bing},
title = {Mining and Summarizing Customer Reviews},
booktitle = {Proceedings of KDD-2004},
year = {2004},
url = {http://www.cs.uic.edu/~liub/FBS/sentiment-analysis.html}
}
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