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56 lines
1.7 KiB
Python
56 lines
1.7 KiB
Python
import collections
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# this script was adapted from:
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# https://towardsdatascience.com/very-simple-python-script-for-extracting-most-common-words-from-a-story-1e3570d0b9d0
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# open and read file
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file = open(input("\nFile you want to categorize is: \n"), encoding="utf8")
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a = file.read()
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# my stopwords are common words I don't want to count, like "a", "an", "the".
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stopwords = set(line.strip() for line in open('stopwords.txt'))
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# dictionary
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wordcount = {}
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# spliting words from punctuation so "book" and "book!" counts as the same word
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for word in a.lower().split():
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word = word.replace(".","")
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word = word.replace(",","")
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word = word.replace(":","")
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word = word.replace("\"","")
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word = word.replace("!","")
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word = word.replace("“","")
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word = word.replace("‘","")
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word = word.replace("*","")
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# counting
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if word not in stopwords:
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if word not in wordcount:
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wordcount[word] = 1
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else:
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wordcount[word] += 1
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# print x most common words
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# n_print = int(input("How many most common words to print: "))
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n_print = int(3)
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print("\nMost common words are:")
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word_counter = collections.Counter(wordcount)
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for word, count in word_counter.most_common(n_print):
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print(word,"—", count)
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# categories
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# words that are inside the category Library Studies
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library_studies = set(line.strip() for line in open('library_studies.txt'))
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for word, count in word_counter.most_common(n_print):
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if word in library_studies:
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print("\nWe suggest the following categorization for this file:\nLibrary Studies\n")
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break
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else:
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print("\nWe don't have any suggestion of categorization for this file.\n")
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# Close the file
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file.close()
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