Adds plot with monthly income/spending

It separates the monthly transactions by categories and tracks income
and spending along the defined time range.
Now prints the total income/spending and the net result for the define
period of time.
Plot code is surrounded with an if False for future toggle on/off.

main.py

@@ -1,5 +1,7 @@
+from datetime import date
 from pathlib import Path
 import logging
+import matplotlib.pyplot as plt
 import pickle
 import sys
 
@@ -128,3 +130,90 @@ if __name__ == "__main__":
     #     Tr.write_transactions(Path("data") / f, file_transactions)
     #
     Tr.write_transactions("transactions.csv", transactions)
+
+    monthly_transactions = transactions.get_transactions_by_month(
+        start=date(2020, 1, 1), end=date(2020, 8, 31)
+    )
+    monthly_transactions_by_cat = []
+    for month_transactions in monthly_transactions.values():
+        cat = month_transactions.get_transactions_by_category()
+        monthly_transactions_by_cat.append(cat)
+
+    for month, month_transactions in zip(
+        monthly_transactions.keys(), monthly_transactions_by_cat
+    ):
+        nulls = sum(t.value for t in month_transactions["Null"])
+        if nulls != 0:
+            print(f"{month} {nulls}")
+
+    expense_categories = [
+        *Categories.get_fixed_expenses(),
+        *Categories.get_variable_expenses(),
+        *Categories.get_discretionary_expenses(),
+    ]
+
+    if False:
+        t = list(monthly_transactions.keys())
+        income = [
+            float(
+                sum(
+                    t.value
+                    for cat, transactions in months.items()
+                    for t in transactions
+                    if cat in Categories.get_income_categories()
+                )
+            )
+            for months in monthly_transactions_by_cat
+        ]
+        # income = []
+        # for months in monthly_transactions_by_cat:
+        #     for cat, transactions in months.items():
+        #         if cat in Categories.get_income_categories():
+        #             income.append(sum(transactions))
+
+        expenses = []
+        for category in expense_categories:
+            expense_value = [
+                -float(sum(t.value for t in month[category]))
+                for month in monthly_transactions_by_cat
+            ]
+            expenses.append(expense_value)
+        # expenses = [transactions for months in monthly_transactions_by_cat for cat, transactions in months.items()
+        #             if cat not in Categories.get_income_categories() and transactions]
+        for expense in expenses:
+            for i, month in reversed(list(enumerate(t))):
+                if expense[i] < 0:
+                    if i - 1 < 0:
+                        break
+                    else:
+                        expense[i - 1] += expense[i]
+                        expense[i] = 0
+
+        plt.plot(t, income, label="Income")
+        plt.stackplot(t, expenses, labels=expense_categories)
+        plt.legend(loc="upper left")
+        plt.show()
+
+    income = [
+        sum(
+            t.value
+            for cat, transactions in months.items()
+            for t in transactions
+            if cat in Categories.get_income_categories()
+        )
+        for months in monthly_transactions_by_cat
+    ]
+
+    expenses = []
+    for category in expense_categories:
+        expense_value = [
+            -sum(t.value for t in month[category])
+            for month in monthly_transactions_by_cat
+        ]
+        expenses.extend(expense_value)
+
+    print(
+        "Income: {}, Expenses: {}, Net = {}".format(
+            sum(income), sum(expenses), sum(income) - sum(expenses)
+        )
+    )