Update app.py

app.py

@@ -1,31 +1,55 @@
-import streamlit as st 
+import streamlit as st
 import numpy as np
 import pandas as pd
+import matplotlib.pyplot as plt
 
-st.title('Cashflow App')
 
-y = st.number_input("Escribe la tasa de interés nominal (%):")
+# Streamlit app layout
 
-A = st.number_input("Escribe la cantidad que ahorrarás ($):")
+st.title("Paying insurance with my savings account 💼")
 
-T = st.number_input("Escribe el número de años que quieres ver: ",
-                   step=1)
+# Create the inputs (A, r, n)
 
-z = np.arange(T+1)
+A = st.number_input("How much do you want monthly?")
 
-r_d = A * (1 + y/(12*100))**z
+r = st.number_input("What is the interest rate?")
 
-r_c = A * np.exp(y*z/(12*100))
+n = int(st.number_input("For how many months?", step = 1))
 
-future_value = A * ((1 + y) ** T)
 
-new_dict = {"Año": z,
-            "Retorno Discreto": r_d,
-           "Retorno Continuo": r_c}
+# Create the outputs
 
-df= pd.DataFrame(new_dict)
-df.columns = new_dict.keys()
+Pn_d = (A * 12 / r) * (1 - (1 / (1 + r/12)**n))
 
-st.dataframe(df)
+# Pn_c = (A / (np.exp(r/12) - 1)) * (1 - np.exp(- r * n / 12))
 
-st.write(f"En {T} tendrás un valor futuro de $ {future_value}") 
+
+# Print the outputs
+
+st.write(f"The value of P is {Pn_d:,.2f} with discrete model")
+
+# st.write(f"The value of P is {Pn_c:,.2f} with continuous model")
+
+
+# Draw the plot
+
+cf_list = [-Pn_d] + [A] * n
+cf_dict = pd.DataFrame({"cashflows": cf_list}).astype(float)
+cf_df = st.dataframe(cf_dict.T)
+
+# Prepare data for the plot
+colors = ["green" if cf > 0 else "red" for cf in cf_dict.cashflows]
+plt.scatter(range(n + 1), cf_dict.cashflows, c=colors)
+plt.title("Cashflow Diagram")
+plt.xlabel("Period")
+plt.ylabel("Cashflow")
+for i, cf in enumerate(cf_dict.cashflows):
+    plt.annotate(
+        f"{cf:,.2f}",
+        (i, cf),
+        textcoords="offset points",
+        xytext=(0, n),
+        ha="center",
+    )
+st.pyplot(plt)
+😘