Create app.py

app.py

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+import streamlit as st
+import numpy as np
+import pandas as pd
+import matplotlib.pyplot as plt
+
+# Streamlit application
+def app():
+    st.title("Linear Equation Visualizer")
+
+    # Input fields for the equation y = mx + c
+    m = st.number_input("Enter the slope (m):", value=1.0)
+    c = st.number_input("Enter the y-intercept (c):", value=0.0)
+    x_value = st.number_input("Enter the x value to predict y:", value=0.0)
+
+    # Calculating y based on the input
+    y = m * x_value + c
+
+    # Displaying the calculated y
+    st.write(f"The calculated y value is: {y}")
+
+    # Generating data for the line
+    x = np.linspace(-10, 10, 100)
+    y_line = m * x + c
+
+    # Plotting the line
+    plt.figure(figsize=(10, 6))
+    plt.plot(x, y_line, '-r', label=f'y = {m}x + {c}')
+    plt.scatter(x_value, y, color='blue', label='Predicted Point')
+    plt.title("Graph of y = mx + c")
+    plt.xlabel("x")
+    plt.ylabel("y")
+    plt.legend()
+    plt.grid(True)
+    
+    # Displaying the plot
+    st.pyplot(plt)
+
+if __name__ == "__main__":
+    app()