Update app.py

app.py

@@ -15,7 +15,10 @@ DEFAULT_ROLLS = 10
 # Define a function to roll dice
 def roll_dice(num_rolls, dice_type):
     rolls = np.random.randint(1, dice_type + 1, size=num_rolls)
-    return rolls
+    variables = np.random.randn(num_rolls)
+    df = pd.DataFrame({"Roll": rolls, "Variable": variables})
+    df.index.name = f"{dice_type}-sided dice"
+    return df
 
 # Define a function to plot tokens
 def plot_tokens(health_tokens, coin_tokens):
@@ -35,20 +38,21 @@ num_rolls = st.slider("Choose the number of rolls:", 1, 1000000, DEFAULT_ROLLS)
 # Roll dice for each type and accumulate high rolls and tokens
 history = {"health_tokens": [0], "coin_tokens": [0]}
 for dice_type in DICE_TYPES:
-    rolls = roll_dice(num_rolls, dice_type)
-    highest_rolls = sum(roll == dice_type for roll in rolls)
+    df = roll_dice(num_rolls, dice_type)
     st.write(f"Results for {dice_type}-sided dice:")
-    for roll in rolls:
-        st.write(f"{EMOJI_LIST[dice_type]} {roll}")
+    for roll, var in zip(df["Roll"], df["Variable"]):
+        st.write(f"{EMOJI_LIST[dice_type]} {roll} ({var:.2f})")
         if roll == dice_type:
             st.write("Congratulations! You rolled the highest value!")
             if dice_type == 100:
                 st.write("Adding 10 coins for rolling over 90 on 100-sided dice.")
                 history["coin_tokens"].append(history["coin_tokens"][-1] + 10)
-    history[f"{dice_type}-sided dice high rolls"] = highest_rolls
-    history["roll_history"] = {**history.get("roll_history", {}), dice_type: rolls}
-    history["health_tokens"].append(history.get("20-sided dice high rolls", 0))
-    history["coin_tokens"].append(history.get("100-sided dice high rolls", 0))
+    history[f"{dice_type}-sided dice high rolls"] = sum(df["Roll"] == dice_type)
+    history["roll_history"] = {**history.get("roll_history", {}), f"{dice_type}-sided dice": df}
+
+    # Update token accumulation
+    history["health_tokens"].append(sum(df.loc[20, "Roll"] == 20))
+    history["coin_tokens"].append(sum(df.loc[100, "Roll"] == 100) * 10)
 
 # Plot token accumulation
 st.write("Token Accumulation:")