Update app.py

app.py

@@ -1,6 +1,8 @@
 import numpy as np
 import streamlit as st
 import matplotlib.pyplot as plt
+from mpl_toolkits.mplot3d import Axes3D
+import inflect
 
 def prediction_pop_model(year, population, pred_year):
     n = len(year)
@@ -15,6 +17,10 @@ def prediction_pop_model(year, population, pred_year):
     pred_population = slope * (pred_year) + intercept
     return pred_population
 
+def number_to_words(number):
+    p = inflect.engine()
+    return p.number_to_words(number)
+
 # Data
 year = np.array([1952, 1957, 1962, 1967, 1972, 1977, 1982, 1987, 1992, 1997, 2002, 2007, 2009, 2011, 2013, 2015, 2017, 2019, 2021, 2023, 2024], dtype=np.float64)
 population = np.array([22223309, 25009741, 28173309, 31681188, 34807417, 38783863, 45681811, 52799062, 59402198, 66134291, 73312559, 75100000, 78300000, 81500000, 85800000, 89000000, 94800000, 98900000, 102800000, 106100000, 107300000], dtype=np.float64)
@@ -28,9 +34,25 @@ input_year = st.number_input("Enter the year you want to predict the population
 # Predict button
 if st.button("Predict"):
     predicted_population = prediction_pop_model(year, population, input_year)
-    st.write(f"Predicted Population for {input_year}: {predicted_population}")
+    population_words = number_to_words(predicted_population)
+    st.write(f"Predicted Population for {input_year}: {population_words}")
 
     # Plotting
+    fig = plt.figure(figsize=(10, 5))
+    ax = fig.add_subplot(111, projection='3d')
+    ax.scatter(year, population, zs=0, zdir='z', color='blue', label='Actual Population')
+    ax.plot(year, population, zs=0, zdir='z', color='blue')
+    ax.scatter([input_year], [predicted_population], zs=0, zdir='z', color='red', label='Predicted Population')
+    
+    ax.set_xlabel('Year')
+    ax.set_ylabel('Population')
+    ax.set_zlabel('Values')
+    ax.set_title('Population Prediction')
+    ax.legend()
+
+    st.pyplot(fig)
+
+    # 2D Plot for comparison
     plt.figure(figsize=(10, 5))
     plt.scatter(year, population, color='blue', label='Actual Population')
     plt.plot(year, population, color='blue')