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