v1

data_entry.py

@@ -0,0 +1,41 @@
+from datetime import datetime
+
+date_format = "%d-%m-%Y"
+allowed_categories = {"I": "Income", "E": "Expense"}
+
+def get_date(prompt, allow_default=False):
+    date_str = input(prompt)
+    if(allow_default and not date_str):
+        return datetime.today().strftime(date_format)
+
+    try:
+        valid_date = datetime.strptime(date_str, date_format)
+        return valid_date.strftime(date_format)
+    except ValueError:
+        print("Invalid date format. Please enter a valid date (dd-mm-yyyy).")
+        return get_date(prompt, allow_default)
+
+def get_amount():
+    try:
+        amount = float(input('Enter the amount: '))
+        if amount <= 0:
+            raise ValueError("Please enter a valid amount.")
+        return amount
+    except ValueError as e:
+        print(e)
+        return get_amount()
+
+def get_category():
+    category = input("Enter the category ('I' for Income, 'E' for Expense): ").upper()
+    if(category not in allowed_categories):
+        print("Please enter a valid input.")
+        return get_category()
+    else:
+        return allowed_categories[category]
+
+def get_description():
+    description = input("Enter a Description (optional): ")
+    if(description):
+        return description
+    else:
+        return "N/A"

expense_tracker.py

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+import pandas as pd
+import csv
+from datetime import datetime
+from data_entry import get_amount, get_category, get_date, get_description
+import matplotlib.pyplot as plt
+
+date_format = "%d-%m-%Y"
+
+class CSV:
+    CSV_FILE = "finance_data.csv"
+
+    @classmethod
+    def initialize_csv(cls):
+        try:
+            pd.read_csv(cls.CSV_FILE)
+        except FileNotFoundError:
+            df = pd.DataFrame(columns=["Date", "Amount", "Category", "Description"])
+            df.to_csv(cls.CSV_FILE, index=False)
+
+    @classmethod
+    def add_entry(cls, date, amount, category, description):
+        new_entry = {
+            "Date": date,
+            "Amount": amount,
+            "Category": category,
+            "Description": description
+        }
+        df = pd.DataFrame([new_entry])
+        df.to_csv(cls.CSV_FILE, mode='a', header=False, index=False)
+
+    @classmethod
+    def get_transactions(cls, startDate, endDate):
+        df = pd.read_csv(cls.CSV_FILE)
+        df["Date"] = df["Date"].map(lambda x: datetime.strptime(x, date_format))
+        startDate = datetime.strptime(startDate, date_format)
+        endDate = datetime.strptime(endDate, date_format)
+
+        mask = (df["Date"] >= startDate) & (df["Date"] <= endDate)
+        filtered_data = df.loc[mask]
+        if filtered_data.empty:
+            print("No Transactions")
+        else:
+            print(f"Transactions from {startDate.strftime(date_format)} to {endDate.strftime(date_format)}")
+            print(filtered_data.to_string(index=False, formatters={"Date": lambda x: x.strftime(date_format)}))
+
+            total_income = filtered_data[filtered_data["Category"] == "Income"]["Amount"].sum()
+            total_expense = filtered_data[filtered_data["Category"] == "Expense"]["Amount"].sum()
+
+            print("\nSummary:")
+            print(f"Total Income: ₹{total_income:.2f}")
+            print(f"Total Expense: ₹{total_expense:.2f}")
+            print(f"Net Savings: ₹{(total_income-total_expense):.2f}")
+
+            return filtered_data 
+
+def add():
+    CSV.initialize_csv()
+    date = get_date("Enter the Date of the transaction (dd-mm-yyyy). Press enter for using today's date: ", allow_default=True)
+    amount = get_amount()
+    category = get_category()
+    description = get_description()
+    CSV.add_entry(date, amount, category, description)
+
+def plotTransactions(dataframe):
+    dataframe.set_index('Date', inplace=True)
+
+    income = dataframe[dataframe["Category"]=="Income"].resample('D').sum().reindex(dataframe.index, fill_value=0)
+    expense = dataframe[dataframe["Category"]=="Expense"].resample('D').sum().reindex(dataframe.index, fill_value=0)
+
+    plt.figure(figsize=(10,5))
+    plt.plot(income.index, income["Amount"], label="Income", color="g")
+    plt.plot(expense.index, expense["Amount"], label="Expense", color="r")
+    plt.xlabel("Date")
+    plt.ylabel("Amount")
+    plt.title("Income and Expenses over time-range")
+    plt.legend()
+    plt.grid(True)
+    plt.show()
+
+def main():
+    while True:
+        print("\n1. Add new transaction")
+        print("2. View transactions and summary within a date range")
+        print("3. Exit")
+        choice = input("Enter your choice (1-3): ")
+
+        if choice == "1":
+            add()
+        elif choice == "2":
+            startDate = get_date("Enter start date (dd-mm-yyyy): ")
+            endDate = get_date("Enter end date (dd-mm-yyyy): ")
+            filteredData = CSV.get_transactions(startDate, endDate)
+
+            if input("Do you want to see a plot of the data? (y/n): ").lower() == 'y':
+                plotTransactions(filteredData)
+        elif choice == "3":
+            print("Exiting...")
+            exit()
+        else:
+            print("Invalid Choice")
+
+if __name__ == "__main__":
+    main()

finance_data.csv

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+Date,Amount,Category,Description
+01-07-2024,1000,Income,Salary
+02-07-2024,150,Expense,Groceries
+03-07-2024,100,Expense,Transport
+04-07-2024,50,Expense,Coffee
+05-07-2024,500,Income,Freelance
+06-07-2024,200,Expense,Utilities
+07-07-2024,400,Income,Investment
+08-07-2024,180,Expense,Shopping
+09-07-2024,250,Income,Bonus
+10-07-2024,80,Expense,Entertainment
+11-07-2024,150,Expense,Groceries
+12-07-2024,220,Expense,Medical
+13-07-2024,1000,Income,Salary
+14-07-2024,90,Expense,Transport
+15-07-2024,100,Expense,Coffee