Added new salary-related terms and improved image outputs in salary.ipynb

2025-04-28 19:44:40 +01:00
parent 8207d8f1ff
commit 591d4611b6
27 changed files with 1782 additions and 12 deletions
@@ -0,0 +1,47 @@
+"""
+Keyword-based salary transaction analysis module.
+"""
+
+import re
+import pandas as pd
+from .config import SALARY_KEYWORDS
+
+class KeywordAnalyzer:
+    def __init__(self, df):
+        self.df = df
+        self.desc_df = None
+
+    def identify_salary_transactions(self):
+        """
+        Identifies potential salary-related transactions based on keywords
+        and month-year patterns in the 'description' column.
+        """
+        month_year_patterns = [
+            r"\b(?:JAN|FEB|MAR|APR|MAY|JUN|JUL|AUG|SEP|OCT|NOV|DEC)\s?\d{2,4}\b",
+            r"\b(?:JANUARY|FEBRUARY|MARCH|APRIL|MAY|JUNE|JULY|AUGUST|SEPTEMBER|OCTOBER|NOVEMBER|DECEMBER)\s?\d{2,4}\b"
+        ]
+
+        escaped_keywords = [re.escape(keyword.lower()) for keyword in SALARY_KEYWORDS]
+        combined_pattern = (
+            r'\b(?:' + '|'.join(escaped_keywords) + r')\b|' +
+            '|'.join(month_year_patterns)
+        )
+
+        self.df['is_salary_related'] = self.df['description'].str.lower().str.contains(
+            combined_pattern,
+            na=False,
+            regex=True
+        )
+
+        self.desc_df = self.df.copy()
+        return self.df
+
+    def get_salary_related_data(self):
+        """Get transactions identified as salary-related."""
+        if self.desc_df is None:
+            self.identify_salary_transactions()
+        
+        return self.desc_df[
+            (self.desc_df['is_salary_related'] == True) & 
+            (self.desc_df['initiated_by'] == 'C')
+        ]