78 lines
2.1 KiB
Python
78 lines
2.1 KiB
Python
import csv
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import re
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import matplotlib.pyplot as plt
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import numpy as np
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from collections import Counter
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from pprint import pprint
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stop_words = ['of', 'and', 'the', 'we', 'in', 'to', 'what', 'a', 'on', 'an',
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'do', 'for', 'with', 'is', 'it', 'that', 'this', 'as', 'by',
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'are', 'using', 'from', 'how', 'has', 'be', 'or', 'can', 'our',
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'at', 'why', 'when', 'introduction']
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file_path = 'data.csv'
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data = []
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def parse_csv(file_path):
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with open(file_path, 'r') as file:
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reader = csv.reader(file)
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for row in reader:
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data.append(row)
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def extract_journal_titles(data):
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journal_titles = []
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for row in data:
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if "(edited volume)" not in row[3]:
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journal_titles.append(row[3])
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count_journal_titles = Counter(journal_titles).most_common(20)
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pprint(count_journal_titles)
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def extract_title_keywords(data):
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title_keywords = []
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re_words = []
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for row in data:
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raw_words = row[2].split(' ')
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for word in raw_words:
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re_word = re.sub(r'[^a-zA-Z\-]', '', word)
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re_words.append((re_word, row[2]))
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title_keywords = [(word.lower(), title) for (word, title) in re_words if word.lower() not in stop_words]
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return title_keywords
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def print_title_keywords(data):
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title_keywords = extract_title_keywords(data)
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title_keywords = [word[0] for word in title_keywords]
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count_title_words = Counter(title_keywords).most_common(20)
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pprint(count_title_words)
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def histogram(data):
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dates = []
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for row in data:
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dates.append(int(row[4]))
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years = range(min(dates), max(dates)+2)
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plt.hist(dates, bins=years)
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plt.show()
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def dash_viz(data):
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title_keywords = extract_title_keywords(data)
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word_output = {}
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for line in title_keywords:
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if line[0] not in word_output:
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word_output[line[0]] = [line[1]]
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else:
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word_output[line[0]].append(line[1])
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pprint(word_output)
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if __name__ == '__main__':
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parse_csv(file_path)
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data = data[1:]
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extract_journal_titles(data)
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print_title_keywords(data)
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dash_viz(data)
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histogram(data)
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