add examples of data preprocessing

enron_spam.py

@@ -0,0 +1,24 @@
+import pandas as pd
+
+
+df = pd.read_csv('enron_spam_data.csv')
+
+data = []
+for index, row in df.iterrows():
+    message = row['Message']
+    subject = row['Subject']
+    if not message or type(message) == float:
+        message = subject
+        subject = ''
+    elif not subject or type(subject) == float:
+        subject = message
+        message = ''
+    spam_ham = row['Spam/Ham']
+    is_spam = 1 if spam_ham.lower() == 'spam' else 0
+    text = (str(subject) + """
+
+""" + str(message)).strip()
+    data.append({'text': text, 'is_spam': is_spam})
+
+df = pd.DataFrame(data)
+df.to_csv('enron_spam_clean.csv', index=False)

spam_assassin.js

@@ -0,0 +1,30 @@
+const fs = require('fs');
+const corpus = require('@stdlib/datasets-spam-assassin');
+
+const data = corpus();
+let csvData = "text,is_spam\n";
+
+
+function cleanText(str) {
+    if (str.startsWith('""') && str.endsWith('""')) str = str.substring(2, str.length - 2)
+    else if (str.startsWith('"') && str.endsWith('"')) str = str.substring(1, str.length - 1)
+    str = str.replace(/["]/g, '""')
+    if (str.includes('\n') || str.includes(',') || str.includes(`""`)) str = '"' + str + '"'
+    return str
+}
+
+
+for (let i = 0; i < data.length; i++) {
+    const text = data[i].text;
+    const group = data[i].group;
+    let isSpam = 0;
+    if (group.includes('spam')) {
+        isSpam = 1;
+    }
+    csvData += cleanText(text) + ',' + isSpam + '\n';
+}
+
+fs.writeFile('spam_data.csv', csvData, (err) => {
+    if (err) throw err;
+    console.log('CSV file saved!');
+});

spam_assassin.py

@@ -0,0 +1,35 @@
+import pandas as pd
+
+special = []
+df = pd.read_csv('spam_data.csv')
+
+for index, row in df.iterrows():
+    text = row['text']
+
+    if text is not None and text != '' and 'Subject: ' in text:
+        subject = text.split("""
+Subject: """)[1]
+        
+        if '\n' in subject:
+            subject = subject.split("\n")[0].strip()
+        elif '\r' in subject:
+            subject = subject.split("\r")[0].strip()
+        else:
+            raise Exception('No newline found in subject: ' + str(text))
+        content = text.split("""
+
+""")[1:]
+        content = """
+
+""".join(content)
+        
+        text = subject + """
+
+""" + content
+        
+        df.at[index, 'text'] = text
+    else:
+        special.append({'text': text, 'is_spam': row['is_spam']})
+
+df.to_csv('spam_data_clean.csv', index=False)
+pd.DataFrame(special).to_csv('special.csv', index=False)