csv lessons

Author: rhelmstedter

days/13-15-text-games/rps_classes.py

@@ -51,20 +51,24 @@ def print_header():
     print("  15-way Rock Paper Scissors")
     print("=" * 30)
 
+
 def best_of(player1):
     print(f"Welcome {player1.name}!\n")
     while True:
         try:
             best_of_num = int(input("Enter an odd number of rounds to play:"))
             if best_of_num % 2 == 0:
                 raise EvenNumberException
-            print(f"OK {player1.name}, let's play best of {best_of_num} rounds. Good Luck!\n")
+            print(
+                f"OK {player1.name}, let's play best of {best_of_num} rounds. Good Luck!\n"
+            )
             break
         except ValueError:
             print("You did not enter an number.\n")
         except EvenNumberException:
-            print("You entered an even number which means the match could end in a tie.\n")
-            
+            print(
+                "You entered an even number which means the match could end in a tie.\n"
+            )
     return best_of_num
 
 
@@ -88,6 +92,7 @@ def game_loop(player1, player2, BEST_OF_NUM):
         time.sleep(0.25)
         p2_turn = get_computers_selection()
         print(f"The Computer chose {p2_turn.action}")
+
         determine_winner(p1_turn, p2_turn, player1, player2, victories)
         get_score(player1, player2)
         input("Press ENTER to move to the next round.")

days/37-39-csv-data-analysis/weather_csv_demo/myprogram.py

@@ -0,0 +1,30 @@
+import myresearch
+
+
+def main():
+    myresearch.init()
+    print("Weather research for Seattle, 2014-2015")
+    print()
+
+    print("The hottest 5 days:")
+    days = myresearch.hot_days()
+    for i, day in enumerate(days[:5]):
+        print(f"{i+1}. {day.actual_max_temp} F on {day.date}")
+    print()
+
+    print("The coldest 5 days:")
+    days = myresearch.cold_days()
+    for i, day in enumerate(days[:5]):
+        print(f"{i+1}. {day.actual_min_temp} F on {day.date}")
+    print()
+
+    print("The wettest 5 days:")
+    days = myresearch.wet_days()
+    for i, day in enumerate(days[:5]):
+        print(f"{i+1}. {day.actual_precipitation}\" on {day.date}")
+    print()
+
+
+
+if __name__ == "__main__":
+    main()

days/37-39-csv-data-analysis/weather_csv_demo/myresearch.py

@@ -0,0 +1,56 @@
+import csv
+import os
+from collections import namedtuple
+from typing import List
+
+data = []
+
+Record = namedtuple(
+    "Record",
+    "date,actual_mean_temp,actual_min_temp,actual_max_temp,average_min_temp,"
+    "average_max_temp,record_min_temp,record_max_temp,record_min_temp_year,"
+    "record_max_temp_year,actual_precipitation,average_precipitation,record_precipitation"
+)
+
+
+def init():
+    base_folder = os.path.dirname(__file__)
+    filename = os.path.join(base_folder, "data", "seattle.csv")
+
+    with open(filename, "r", encoding="utf-8") as f:
+        reader = csv.DictReader(f)
+
+        data.clear()
+        for row in reader:
+            record = parse_row(row)
+            data.append(record)
+
+
+def parse_row(row):
+    row["actual_mean_temp"] = int(row["actual_mean_temp"])
+    row["actual_min_temp"] = int(row["actual_min_temp"])
+    row["actual_max_temp"] = int(row["actual_max_temp"])
+    row["average_min_temp"] = int(row["average_min_temp"])
+    row["average_max_temp"] = int(row["average_max_temp"])
+    row["record_min_temp"] = int(row["record_min_temp"])
+    row["record_max_temp"] = int(row["record_max_temp"])
+    row["record_min_temp_year"] = int(row["record_min_temp_year"])
+    row["record_max_temp_year"] = int(row["record_max_temp_year"])
+    row["actual_precipitation"] = float(row["actual_precipitation"])
+    row["average_precipitation"] = float(row["average_precipitation"])
+    row["record_precipitation"] = float(row["record_precipitation"])
+
+    record = Record(**row)
+
+    return record
+
+def hot_days() -> List[Record]:
+    return sorted(data, key=lambda r: -r.actual_max_temp)
+
+def cold_days() -> List[Record]:
+    return sorted(data, key=lambda r: r.actual_max_temp)
+
+def wet_days() -> List[Record]:
+    return sorted(data, key=lambda r: -r.actual_precipitation)
+
+