Update app.py

app.py

@@ -3,41 +3,67 @@ import numpy as np
 import pandas as pd
 import matplotlib.pyplot as plt
 
-st.title('App de prueba')
+st.title("Investment app 💼")
 
-A = st.number_input("Escribe la cantidad que ahorrarás ($): ")
-T = st.number_input("Escribe cuantos meses quieres ver: ", step=1)
+A = st.number_input(
+    "Insert the initial investment (in $): "
+)
+r = st.number_input(
+    "Insert the interest rate (nominal in %): "
+)
+T = st.number_input(
+    "Insert the number of months of your investment: ",
+    step=1
+)
 
-tasas = []
-for i in range(int(T)):
-    tasa = st.number_input(f"Tasa de interés nominal para el mes {i+1} (%): ")
-    tasas.append(tasa)
+# Numpy array with the months
+t = np.arange(T + 1)
 
-if T > 0:
-    z = np.arange(T)
+# Numpy array for the interest rate
+r_list = np.array([r] * len(t))
 
-    r_d = A * (1 + np.array(tasas) / (12 * 100)) ** z
-    r_c = A * np.exp(np.array(tasas) * z / (12 * 100))
+# Numpy array with the returns for each month in t
+y = A * (1 + (r_list / (12*100)))**t
 
-    new_dict = {"Mes": np.arange(1, T+1),
-                "Retorno discreto": r_d,
-                "Retorno continuo": r_c}
+# Numpy array with the continuously compunded returns
+y_c = A * np.exp(r_list * t / (12*100))
 
-    df = pd.DataFrame(new_dict)
-    st.dataframe(df)
+# Create the investment dictionary
+inv_dict = {"Month": t, 
+            "Rate": r_list, 
+            "Returns": y, 
+            "Continuous returns": y_c}
 
-    st.write(f"En {int(T)} meses tendrás: $ {r_c[-1]}")
+# Create the investment dataframe
+inv_df = pd.DataFrame(inv_dict)
+inv_df.columns = inv_dict.keys()
 
-    # Creación de la gráfica
-    plt.figure(figsize=(10, 6))
-    plt.plot(np.arange(1, T+1), r_c, label='Retorno continuo', marker='o', linestyle='-', color='blue', alpha=0.8)
-    plt.xlabel('Mes')
-    plt.ylabel('Inversión ($)')
-    plt.title('Crecimiento de la inversión a lo largo de los meses', fontsize=16, fontweight='bold')
-    plt.grid(True, linestyle='--', alpha=0.5)
-    plt.legend()
-    plt.tight_layout()
-    st.pyplot(plt)
+st.write(f"Table with returns at an interest rate of {r}")
+new_df = st.data_editor(inv_df)
 
-else:
-    st.write("Por favor, ingresa un valor de T mayor que 0.")
+new_y = [A]
+new_y_c = [A]
+
+for i in range(1, len(t)):
+    r_temp = new_df["Rate"].values[i]
+    # New numpy array with the returns for each month in t
+    val =  new_y[i-1] * (1 + r_temp / (12*100))
+    new_y.append(val)
+
+    # New numpy array with the continuously compunded returns
+    val_c = new_y_c[i-1] * np.exp(r_temp / (12*100))
+    new_y_c.append(val_c)
+
+new_df["Returns"] = new_y
+new_df["Continuous returns"] = new_y_c
+new_df["Actual returns"] = 100 * (new_df["Continuous returns"] - new_df["Continuous returns"].shift(1)) / new_df["Continuous returns"].shift(1)
+
+st.dataframe(new_df)
+
+fig, ax = plt.subplots()
+ax.set_title("Investment returns plot")
+ax.set_xlabel("Months")
+ax.set_ylabel("Actual returns")
+ax.plot(new_df["Month"], new_df["Actual returns"])
+
+st.pyplot(fig)