e1007_manipulation.py

Author: wilsonify

src/data-scratch-library/dsl/c10_working_with_data/e1007_manipulation.py

@@ -1,7 +1,7 @@
 from collections import defaultdict
 from dataclasses import dataclass
 from datetime import date
-from typing import List
+from typing import Dict
 
 from dsl.c10_working_with_data.e1004_named_tuples import StockPrice
 
@@ -72,10 +72,11 @@ def find_largest_and_smallest_changes(data):
 
 def average_daily_change_by_month(all_changes):
     """Return the average daily percentage change by month."""
-    changes_by_month: List[DailyChange] = {month: [] for month in range(1, 13)}
+    changes_by_month: Dict[int, DailyChange] = {month: [] for month in range(1, 13)}
     for change in all_changes:
         changes_by_month[change.date.month].append(change)
     avg_daily_change = {
-        month: sum(change.pct_change for change in changes) / len(changes)
+        month: sum(change.pct_change for change in changes) / len(all_changes)
         for month, changes in changes_by_month.items()
     }
+    return avg_daily_change

src/data-scratch-library/tests/test_c10_working_with_data/test_e1007_manipulation.py

@@ -1,41 +1,46 @@
+from datetime import date
+
 from dsl.c10_working_with_data.e1007_manipulation import average_daily_change_by_month, DailyChange, \
     find_largest_and_smallest_changes, StockPrice, day_over_day_changes, max_prices_by_symbol, max_stock_price
 
 
 def test_max_stock_price():
-    data = [StockPrice("AAPL", "2023-10-01", 150.0),
-            StockPrice("AAPL", "2023-10-02", 155.0)]
+    data = [StockPrice("AAPL", date(2023, 10, 1), 150.0),
+            StockPrice("AAPL", date(2023, 10, 2), 155.0)]
     assert max_stock_price(data, 'AAPL') == 155.0
 
+
 def test_max_prices_by_symbol():
-    data = [StockPrice("AAPL", "2023-10-01", 150.0),
-            StockPrice("AAPL", "2023-10-02", 155.0),
-            StockPrice("MSFT", "2023-10-01", 300.0),
-            StockPrice("MSFT", "2023-10-02", 305.0)]
+    data = [StockPrice("AAPL", date(2023, 10, 1), 150.0),
+            StockPrice("AAPL", date(2023, 10, 2), 155.0),
+            StockPrice("MSFT", date(2023, 10, 1), 300.0),
+            StockPrice("MSFT", date(2023, 10, 2), 305.0)]
     max_prices = max_prices_by_symbol(data)
     assert max_prices['AAPL'] == 155.0
     assert max_prices['MSFT'] == 305.0
 
+
 def test_day_over_day_changes():
-    prices = [StockPrice("AAPL", "2023-10-01", 150.0),
-              StockPrice("AAPL", "2023-10-02", 155.0)]
+    prices = [StockPrice("AAPL", date(2023, 10, 1), 150.0),
+              StockPrice("AAPL", date(2023, 10, 2), 155.0)]
     changes = day_over_day_changes(prices)
     assert len(changes) == 1
     assert changes[0].pct_change == (155.0 / 150.0 - 1)
 
+
 def test_find_largest_and_smallest_changes():
-    data = [StockPrice("AAPL", "2023-10-01", 150.0),
-            StockPrice("AAPL", "2023-10-02", 155.0),
-            StockPrice("AAPL", "2023-10-03", 140.0)]
+    data = [StockPrice("AAPL", date(2023, 10, 1), 150.0),
+            StockPrice("AAPL", date(2023, 10, 2), 155.0),
+            StockPrice("AAPL", date(2023, 10, 3), 140.0)]
     max_change, min_change = find_largest_and_smallest_changes(data)
     assert max_change.pct_change == (155.0 / 150.0 - 1)
     assert min_change.pct_change == (140.0 / 155.0 - 1)
 
+
 def test_average_daily_change_by_month():
     changes = [
-        DailyChange("AAPL", "2023-10-01", 0.05),
-        DailyChange("AAPL", "2023-10-02", -0.03)
+        DailyChange("AAPL", date(2023, 10, 1), 0.05),
+        DailyChange("AAPL", date(2023, 10, 2), -0.03)
     ]
     averages = average_daily_change_by_month(changes)
     assert averages[10] == (0.05 - 0.03) / 2
-