begin work on viz

parse.py

@@ -0,0 +1,77 @@
+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)

viz.py

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+from dash import Dash, html
+import dash_cytoscape as cyto
+
+app = Dash(__name__)
+
+app.layout = html.Div([
+    html.P("Dash Cytoscape:"),
+    cyto.Cytoscape(
+        id='cytoscape',
+        elements=[
+            {'data': {'id': 'ca', 'label': 'Canada'}}, 
+            {'data': {'id': 'on', 'label': 'Ontario'}}, 
+            {'data': {'id': 'qc', 'label': 'Quebec'}},
+            {'data': {'source': 'ca', 'target': 'on'}}, 
+            {'data': {'source': 'ca', 'target': 'qc'}}
+        ],
+        layout={'name': 'breadthfirst'},
+        style={'width': '400px', 'height': '500px'}
+    )
+])
+
+
+app.run_server(debug=True)