我正在尝试在pandas类中实现Peter Norvig's spell checker,其中包含从SQL数据库中提取的单词。数据包含通常包含多个拼写错误的用户查询,我希望此类将返回最可能的查询(拼写正确)。
使用返回pandas数据帧的数据库查询初始化类。例如:
query count
0 foo bar 1864
1 super foo 73
2 bar of foos 1629
3 crazy foos 940
下面的大部分内容都是直接来自彼得的作品,但我对该课程所做的修改似乎并不正常。我的猜测是它与删除Counter功能(WORDS = Counter(words(open('big.txt').read()))
)有关,但我不确定从数据帧获得相同功能的最佳方法。
下面的当前课程:
class _SpellCheckClient(object):
"""Wraps functionality to check the spelling of a query."""
def __init__(self, team, table, dremel_connection):
self.df = database_connection.ExecuteQuery(
'SELECT query, COUNT(query) AS count FROM table GROUP BY 1;'
def expected_word(self, word):
"""Most probable spelling correction for word."""
return max(self._candidates(word), key=self._probability)
def _probability(self, query):
"""Probability of a given word within a query."""
query_count = self.df.loc[self.df['query'] == query]['count'].values
return query_count / self.df['count'].sum()
def _candidates(self, word):
"""Generate possible spelling corrections for word."""
return (self._known([word])
or self._known(self._one_edits_from_word(word))
or self._known(self._two_edits_from_word(word))
or [word])
def _known(self, query):
"""The subset of `words` that appear in the dictionary of WORDS."""
# return set(w for w in query if w in WORDS)
return set(w for w in query if w in self.df['query'].value_counts)
def _one_edits_from_word(self, word):
"""All edits that are one edit away from `word`."""
splits = [(word[:i], word[i:]) for i in xrange(len(word) + 1)]
deletes = [left + right[1:] for left, right in splits if right]
transposes = [left + right[1] + right[0] + right[2:]
for left, right in splits
if len(right) > 1]
replaces = [left + center + right[1:]
for left, right in splits
if right for center in LETTERS]
inserts = [left + center + right
for left, right in splits
for center in LETTERS]
return set(deletes + transposes + replaces + inserts)
def _two_edits_from_word(self, word):
"""All edits that are two edits away from `word`."""
return (e2 for e1 in self._one_edits_from_word(word)
for e2 in self._one_edits_from_word(e1))
提前致谢!
答案 0 :(得分:0)
对于寻找答案的人来说,下面是对我有用的:
def _words(df):
"""Returns the total count of each word within a dataframe."""
return df['query'].str.get_dummies(sep=' ').T.dot(df['count'])
class _SpellCheckClient(object):
"""Wraps functionality to check the spelling of a query."""
def __init__(self, team, table, database_connection):
self.df = database_connection
self.words = _words(self.df)
def expected_word(self, query):
"""Most probable spelling correction for word."""
return max(self._candidates(query), key=self._probability)
def _probability(self, query):
"""Probability of a given word within a query."""
return self.words.pipe(lambda x: x / x.sum()).get(query, 0.0)
def _candidates(self, query):
"""Generate possible spelling corrections for word."""
return (self._known(self._one_edits_from_query(query))
or self._known(self._two_edits_from_query(query))
or [query])
def _known(self, query):
"""The subset of `query` that appear in the search console database."""
return set(w for w in query if self.words.get(w))
def _one_edits_from_query(self, query):
"""All edits that are one edit away from `query`."""
splits = [(query[:i], query[i:]) for i in xrange(len(query) + 1)]
deletes = [left + right[1:] for left, right in splits if right]
transposes = [left + right[1] + right[0] + right[2:]
for left, right in splits
if len(right) > 1]
replaces = [left + center + right[1:]
for left, right in splits
if right for center in LETTERS]
inserts = [left + center + right
for left, right in splits
for center in LETTERS]
return set(deletes + transposes + replaces + inserts)
def _two_edits_from_query(self, query):
"""All edits that are two edits away from `query`."""
return (e2 for e1 in self._one_edits_from_query(query)
for e2 in self._one_edits_from_query(e1))
答案 1 :(得分:0)
import pandas as pd
from spellchecker import SpellChecker
df = pd.Series(['Customir','Tast','Hlp'])
spell = SpellChecker(distance=1)
def Correct(x):
return spell.correction(x)
df = df.apply(Correct)
df
0 customer
1 last
2 help
dtype: object