day 25 - US states game

025/50_states.csv

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+state,x,y
+Alabama,139,-77
+Alaska,-204,-170
+Arizona,-203,-40
+Arkansas,57,-53
+California,-297,13
+Colorado,-112,20
+Connecticut,297,96
+Delaware,275,42
+Florida,220,-145
+Georgia,182,-75
+Hawaii,-317,-143
+Idaho,-216,122
+Illinois,95,37
+Indiana,133,39
+Iowa,38,65
+Kansas,-17,5
+Kentucky,149,1
+Louisiana,59,-114
+Maine,319,164
+Maryland,288,27
+Massachusetts,312,112
+Michigan,148,101
+Minnesota,23,135
+Mississippi,94,-78
+Missouri,49,6
+Montana,-141,150
+Nebraska,-61,66
+Nevada,-257,56
+New Hampshire,302,127
+New Jersey,282,65
+New Mexico,-128,-43
+New York,236,104
+North Carolina,239,-22
+North Dakota,-44,158
+Ohio,176,52
+Oklahoma,-8,-41
+Oregon,-278,138
+Pennsylvania,238,72
+Rhode Island,318,94
+South Carolina,218,-51
+South Dakota,-44,109
+Tennessee,131,-34
+Texas,-38,-106
+Utah,-189,34
+Vermont,282,154
+Virginia,234,12
+Washington,-257,193
+West Virginia,200,20
+Wisconsin,83,113
+Wyoming,-134,90

025/main.py

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+from turtle import Turtle, Screen
+import pandas as pd
+
+FONT = ("Courier", 14, "normal")
+
+screen = Screen()
+screen.setup(725,491)
+screen.bgpic('blank_states_img.gif')
+screen.tracer(0)
+
+data = pd.read_csv("50_states.csv")
+# state, x, y
+
+game_on = True
+states_remaining = len(data)
+found_states = []
+
+while len(found_states) < 50:
+    guess = str(screen.textinput(f"{states_remaining} states to find", "Find a state:"))
+    if guess == "None":
+        with open("missing_states.csv", "w") as f:
+            for a_state in data.state:
+                if a_state not in found_states:
+                    f.write(f"{a_state}\n")
+        exit()
+    
+    state = data[data.state == guess.title()]
+
+    # if the subset is not empty, it means the state is in the list
+    if len(state) > 0:
+        
+
+        x_pos = state.x.item() #state.iloc[0]["x"]
+        y_pos = state.y.item() #state.iloc[0]["y"]
+        state_name = state.iloc[0]["state"]
+
+        if state_name in found_states:
+            continue
+
+        states_remaining -= 1
+
+        found_states.append(state_name)
+        text = Turtle()
+        text.pu()
+        text.color("black")
+        text.hideturtle()
+        text.goto(x_pos, y_pos)
+        text.write(state_name, align="center", font=FONT)
+        screen.update()
+    
+
+
+screen.mainloop()

025/missing_states.csv

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+Alabama
+Alaska
+Arkansas
+California
+Colorado
+Connecticut
+Delaware
+Florida
+Georgia
+Hawaii
+Idaho
+Illinois
+Indiana
+Iowa
+Kansas
+Kentucky
+Louisiana
+Maine
+Maryland
+Massachusetts
+Michigan
+Minnesota
+Mississippi
+Missouri
+Montana
+Nebraska
+Nevada
+New Hampshire
+New Jersey
+New Mexico
+New York
+North Carolina
+North Dakota
+Oklahoma
+Oregon
+Pennsylvania
+Rhode Island
+South Carolina
+South Dakota
+Tennessee
+Texas
+Utah
+Vermont
+Virginia
+Washington
+West Virginia
+Wisconsin
+Wyoming

025/task.py

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+# data = []
+# with open("weather_data.csv") as f:
+#     for line in f.readlines():
+#         data.append(line.strip().split(','))
+
+# print(data)
+
+# ------------------------------------------------------------------------
+# import csv
+
+# temperatures = []
+# with open("weather_data.csv") as f:
+#     reader = csv.reader(f)
+#     next(reader)
+
+#     for row in reader:
+#         temperatures.append(int(row[1]))
+
+# print(temperatures)
+
+# ------------------------------------------------------------------------
+
+# import pandas as pd
+
+# data = pd.read_csv("weather_data.csv", delimiter=",")
+# print(data["temp"].mean())
+# print(data["temp"].max())
+
+# output = data[data.temp == data.temp.max()]
+# print(output)
+
+# ------------------------------------------------------------------------
+
+import pandas as pd
+
+data = pd.read_csv("squirrels.csv")
+
+colors = data["Primary Fur Color"].unique()
+
+output_colors = []
+output_count = []
+for color in colors:
+    if type(color) != str:
+        continue
+    count = len(data[data["Primary Fur Color"] == color])
+
+    output_colors.append(color)
+    output_count.append(count)
+
+output = {"color": output_colors, "count": output_count}
+
+df = pd.DataFrame(output)
+
+print(df.to_csv(index=False))

025/weather_data.csv

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+day,temp,condition
+Monday,12,Sunny
+Tuesday,14,Rain
+Wednesday,15,Rain
+Thursday,14,Cloudy
+Friday,21,Sunny
+Saturday,22,Sunny
+Sunday,24,Sunny