Update app.py

app.py

@@ -1,69 +1,57 @@
 import streamlit as st
-import numpy as np 
+import numpy as np
 import pandas as pd
+import matplotlib.pyplot as plt
 
-st.title('App de prueba 👻')
-
-# Obtener la tasa de interés inicial y la cantidad inicial
-tasa_inicial = st.number_input("Escribe la tasa de interés nominal inicial (%):")
-A = st.number_input("Escribe la cantidad que ahorrarás ($):")
-T = st.number_input("Escribe cuantos meses quieres ver:")
-
-tasas_variables = []
-
-# Permitir al usuario ingresar tasas variables
-for i in range(int(T)):
-    tasa = st.number_input(f"Tasa de interés nominal para el mes {i+1} (%):", key=f"tasa_{i}")
-    tasas_variables.append(tasa)
-
-z = np.arange(T)
+st.title("Investment app ")
 
-# Calcular los retornos para tasas variables
-r_d = []
-r_c = []
+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
+)
 
-for i in range(int(T)):
-    retorno_discreto = A * (1 + tasas_variables[i]/(12*100))**i
-    retorno_continuo = A * np.exp(tasas_variables[i]/(12*100) * i)
-    
-    print(f"Mes {i+1}: retorno_continuo = {retorno_continuo}")
-    
-    r_d.append(retorno_discreto)
-    r_c.append(retorno_continuo)
+# Numpy array with the months
+t = np.arange(T + 1)
 
-    print("Longitud de r_c:", len(r_c))
+# Numpy array for the interest rate
+r_list = np.array([r] * len(t))
 
-print("r_d:", r_d)
-print("r_c:", r_c)
+# Numpy array with the returns for each month in t
+y = A * (1 + (r_list / (12*100)))**t
 
-new_dict = {"Mes": z, "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)
+# Create the investment dictionary
+inv_dict = {"Month": t, 
+            "Rate": r_list, 
+            "Returns": y, 
+            "Continuous returns": y_c}
 
-st.dataframe(df)
+# Create the investment dataframe
+inv_df = pd.DataFrame(inv_dict)
+inv_df.columns = inv_dict.keys()
 
-if len(r_c) > 0:
-    st.write(f"En {T} meses tendrás $ {r_c[-1]}")
-else:
-    st.write("Aún no se han calculado los retornos.")
+st.write(f"Table with returns at an interest rate of {r}")
+new_df = st.data_editor(inv_df)
 
-import matplotlib.pyplot as plt
+new_y = [A]
+new_y_c = [A]
 
-# Crear la figura y los ejes
-fig, ax = plt.subplots()
+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)
 
-# Trazar la evolución del crecimiento de la inversión
-ax.plot(df["Mes"], df["Retorno discreto"], label="Retorno discreto", marker='o')
-ax.plot(df["Mes"], df["Retorno continuo"], label="Retorno continuo", marker='x')
 
-# Agregar etiquetas y leyenda
-ax.set_xlabel('Mes')
-ax.set_ylabel('Retorno')
-ax.set_title('Evolución del crecimiento de la inversión')
-ax.legend()
 
-# Mostrar la gráfica
-st.pyplot(fig)