敏捷数据科学 - 数据丰富

数据丰富是指用于增强、细化和改进原始数据的一系列过程。 它指的是有用的数据转换(原始数据到有用信息)。 数据丰富的过程侧重于使数据成为现代商业或企业有价值的数据资产。

最常见的数据丰富过程包括通过使用特定的决策算法来纠正数据库中的拼写错误或印刷错误。 数据丰富工具向简单的数据表添加有用的信息。

考虑以下用于单词拼写更正的代码 −

import re
from collections import Counter
def words(text): return re.findall(r'\w+', text.lower())
WORDS = Counter(words(open('big.txt').read()))

def P(word, N=sum(WORDS.values())):
   "Probabilities of words"
   return WORDS[word] / N
	
def correction(word):
   "Spelling correction of word"
   return max(candidates(word), key=P)
	
def candidates(word):
   "Generate possible spelling corrections for word."
   return (known([word]) or known(edits1(word)) or known(edits2(word)) or [word])
	
def known(words):
   "The subset of `words` that appear in the dictionary of WORDS."
   return set(w for w in words if w in WORDS)
	
def edits1(word):
   "All edits that are one edit away from `word`."
   letters = 'abcdefghijklmnopqrstuvwxyz'
   splits = [(word[:i], word[i:]) for i in range(len(word) + 1)]
   deletes = [L + R[1:] for L, R in splits if R]
   transposes = [L + R[1] + R[0] + R[2:] for L, R in splits if len(R)>1]
   replaces = [L + c + R[1:] for L, R in splits if R for c in letters]
   inserts = [L + c + R for L, R in splits for c in letters]
   return set(deletes + transposes + replaces + inserts)
	
def edits2(word):
   "All edits that are two edits away from `word`."
   return (e2 for e1 in edits1(word) for e2 in edits1(e1))
   print(correction('speling'))
   print(correction('korrectud'))

在此程序中，我们将与包含更正单词的"big.txt"进行匹配。 单词与文本文件中包含的单词匹配并相应地打印相应的结果。

输出

上面的代码将生成以下输出 −