Update app.py

app.py

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+import streamlit as st 
+import pandas as pd
+import plotly.express as px
+import plotly.graph_objects as go
+
+st.title("Customer Lifetime Value App")
+
+# Read the dataset
+data = pd.read_excel('Online Retail.xlsx')
+
+# Get the user id
+user_id = st.selectbox('Select the user id :', data.CustomerID.unique())
+
+# Get the data for the selected user id
+user_data = data[data['CustomerID'] == user_id]
+
+# Calculate the CLV
+clv = (user_data.UnitPrice * user_data.Quantity).sum()
+
+st.write('Customer lifetime value : ', clv)
+
+# Calculate the next purchase date
+purchase_date = user_data.InvoiceDate.max()
+
+st.write('Next purchase date : ', purchase_date)
+
+# Get the purchase trend
+user_data['InvoiceDate'] = pd.to_datetime(user_data['InvoiceDate'])
+user_data['Day'] = user_data['InvoiceDate'].dt.day
+user_data['Month'] = user_data['InvoiceDate'].dt.month
+user_data['Week'] = user_data['InvoiceDate'].dt.week
+user_data['Year'] = user_data['InvoiceDate'].dt.year
+
+# Plot the graphs
+st.subheader('Purchase Trend')
+
+# Day Wise
+fig = go.Figure()
+fig.add_trace(go.Scatter(x=user_data.Day, y=user_data.Quantity, mode='lines+markers', name='Day Wise'))
+st.plotly_chart(fig)
+
+# Date Wise
+fig1 = px.line(user_data, x="InvoiceDate", y="Quantity", title='Date Wise')
+st.plotly_chart(fig1)
+
+# Week Wise
+fig2 = go.Figure()
+fig2.add_trace(go.Scatter(x=user_data.Week, y=user_data.Quantity, mode='lines+markers', name='Week Wise'))
+st.plotly_chart(fig2)
+
+# Month Wise
+fig3 = go.Figure()
+fig3.add_trace(go.Scatter(x=user_data.Month, y=user_data.Quantity, mode='lines+markers', name='Month Wise'))
+st.plotly_chart(fig3)
+
+# Risk of Churn
+if clv <= 0:
+    st.write('Risk of Churn : Yes')
+else:
+    st.write('Risk of Churn : No')