Hugging Face's logo

Datasets:
MB-IDK
/
EN-wordfreq-370k

Dataset card Files
xet
Community
Dataset Viewer
Duplicate
The dataset viewer is not available for this split.
Cannot load the dataset split (in streaming mode) to extract the first rows.
Error code:   StreamingRowsError
Exception:    CastError
Message:      Couldn't cast
text: string
word: null
frequency: null
to
{'word': Value('string'), 'frequency': Value('int64')}
because column names don't match
Traceback:    Traceback (most recent call last):
                File "/src/services/worker/src/worker/utils.py", line 99, in get_rows_or_raise
                  return get_rows(
                         ^^^^^^^^^
                File "/src/libs/libcommon/src/libcommon/utils.py", line 272, in decorator
                  return func(*args, **kwargs)
                         ^^^^^^^^^^^^^^^^^^^^^
                File "/src/services/worker/src/worker/utils.py", line 77, in get_rows
                  rows_plus_one = list(itertools.islice(ds, rows_max_number + 1))
                                  ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 2543, in __iter__
                  for key, example in ex_iterable:
                                      ^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 2060, in __iter__
                  for key, pa_table in self._iter_arrow():
                                       ^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 2092, in _iter_arrow
                  pa_table = cast_table_to_features(pa_table, self.features)
                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/table.py", line 2192, in cast_table_to_features
                  raise CastError(
              datasets.table.CastError: Couldn't cast
              text: string
              word: null
              frequency: null
              to
              {'word': Value('string'), 'frequency': Value('int64')}
              because column names don't match

Need help to make the dataset viewer work? Make sure to review how to configure the dataset viewer, and open a discussion for direct support.

📚 English Words Frequency Database

📖 Description

Dataset containing 370,105 English words with their usage frequencies. Designed for:

  • Word games (WordBomb, Scrabble, etc.)
  • NLP preprocessing
  • Frequency-based word ranking
  • Linguistic research

Words are sorted by descending frequency, meaning common words appear first.

🎯 Use Cases

  • Word games: Implement word difficulty levels or scoring systems
  • NLP preprocessing: Filter rare words, create frequency-based embeddings
  • Education: Generate vocabulary lists by frequency
  • Research: Study word frequency distributions in English

📁 Files

File Description Format
word_alpha.txt Original word list One word per line
word_freq.txt Word + frequency word frequency (tab-separated)

Format Example

the 53703179 of 30922370 and 25642069 to 23626165 in 18305045 a 14559895 is 10404655 that 9287175 for 7847443 it 7167584

📊 Statistics

Metric Value
Total words 370,105
Real frequencies ~192,000 words (≈52%)
Estimated frequencies ~178,000 words (≈48%)
Coverage 100% (every word has a frequency)
Total frequency sum ~1.2 billion
Most frequent word "the" (53.7M)
Least frequent word Various rare words (frequency: 1-500)

🔗 Sources & Credits

Original Word List

Frequency Source 1 (Wikipedia)

Frequency Source 2 (General Corpus)

⚙️ Generation Method

  1. Collection: Load both frequency datasets (~3.8M unique word-frequency pairs combined)

  2. Matching: Cross-reference frequencies with the 370k English word list

  3. Estimation for missing words:

    • Try base forms (suffix removal: -ing, -ed, -s, -ly, -er, -est, -tion)
    • Average frequency from derived forms when available
    • Fallback formula when no matches found:

    frequency = max(1, int(500 / len(word)))

  4. Sorting: Final list ordered by descending frequency

🛠️ Tools Used

· Environment: Termux (Android) · Python: 3.12 · Libraries: pandas, numpy, requests · Utilities: wget, grep, sort

📈 Sample Data

Rank Word Frequency 1 the 53,703,179 2 of 30,922,370 3 and 25,642,069 4 to 23,626,165 5 in 18,305,045 ... ... ... 370,101 zyzzyva 12 370,102 zythum 8 370,103 zymurgy 5 370,104 zymotic 3 370,105 zymolysis 2

🚀 Loading the Dataset

Using Hugging Face Datasets

from datasets import load_dataset

dataset = load_dataset("Zenith__/english-words-frequency") df = dataset["train"].to_pandas()

Manual Download

wget https://huggingface.co/datasets/Zenith__/english-words-frequency/resolve/main/word_freq.txt

📜 License

This dataset combines sources under MIT and Unlicense licenses. Free for commercial and non-commercial use. No attribution required but appreciated.

🤝 Contributing

Found an issue? Have suggestions? Feel free to:

· Open an issue on the GitHub repository · Submit a pull request · Contact the maintainer

👤 Creator

Zenith__ Generated: 2026-02-16 Contact: GitHub Profile

📚 Citation

If you use this dataset in your research, please cite:

@misc{english_words_frequency_2026, author = {Zenith__}, title = {English Words Frequency Database}, year = {2026}, publisher = {Hugging Face}, url = {https://huggingface.co/datasets/Zenith__/english-words-frequency} }

🔄 Version History

Version Date Changes 1.0.0 2026-02-16 Initial release

Made with ❤️ for the NLP community

Downloads last month
14