iskm/wordfreq
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update README examples

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Robyn Speer 2020-10-01 16:05:43 -04:00
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28
README.md
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@ -45,16 +45,16 @@ frequency as a decimal between 0 and 1.
>>> from wordfreq import word_frequency
>>> word_frequency('cafe', 'en')
1.07e-05
1.05e-05
>>> word_frequency('café', 'en')
5.75e-06
5.62e-06
>>> word_frequency('cafe', 'fr')
1.51e-06
1.55e-06
>>> word_frequency('café', 'fr')
5.13e-05
6.61e-05
`zipf_frequency` is a variation on `word_frequency` that aims to return the
@ -72,16 +72,16 @@ one occurrence per billion words.
>>> from wordfreq import zipf_frequency
>>> zipf_frequency('the', 'en')
7.77
7.76
>>> zipf_frequency('word', 'en')
5.29
5.26
>>> zipf_frequency('frequency', 'en')
4.43
4.48
>>> zipf_frequency('zipf', 'en')
1.57
1.62
>>> zipf_frequency('zipf', 'en', wordlist='small')
0.0
@ -232,10 +232,10 @@ the list, in descending frequency order.
>>> from wordfreq import top_n_list
>>> top_n_list('en', 10)
['the', 'of', 'to', 'and', 'a', 'in', 'i', 'is', 'that', 'for']
['the', 'of', 'to', 'and', 'a', 'in', 'i', 'is', 'for', 'that']
>>> top_n_list('es', 10)
['de', 'la', 'que', 'el', 'en', 'y', 'a', 'los', 'no', 'se']
['de', 'la', 'que', 'el', 'en', 'y', 'a', 'los', 'no', 'un']
`iter_wordlist(lang, wordlist='best')` iterates through all the words in a
wordlist, in descending frequency order.
@ -302,16 +302,16 @@ tokenized according to this function.
>>> tokenize('l@s niñ@s', 'es')
['l@s', 'niñ@s']
>>> zipf_frequency('l@s', 'es')
2.8
2.82
Because tokenization in the real world is far from consistent, wordfreq will
also try to deal gracefully when you query it with texts that actually break
into multiple tokens:
>>> zipf_frequency('New York', 'en')
5.28
5.3
>>> zipf_frequency('北京地铁', 'zh') # "Beijing Subway"
3.61
3.23
The word frequencies are combined with the half-harmonic-mean function in order
to provide an estimate of what their combined frequency would be. In Chinese,
@ -326,7 +326,7 @@ you give it an uncommon combination of tokens, it will hugely over-estimate
their frequency:
>>> zipf_frequency('owl-flavored', 'en')
3.2
3.29
## Multi-script languages

6
scripts/top_n.py
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@ -1,14 +1,14 @@
"""
A quick script to output the top N words (1000 for now) in each language.
A quick script to output the top N words (500 for now) in each language.
You can send the output to a file and diff it to see changes between wordfreq
versions.
"""
import wordfreq
N = 1000
N = 500
if __name__ == '__main__':
for lang in sorted(wordfreq.available_languages()):
for word in wordfreq.top_n_list(lang, 1000):
for word in wordfreq.top_n_list(lang, N):
print('{}\t{}'.format(lang, word))