Duplicate from deepakkaura26/clv

Co-authored-by: Deepak Kaura <deepakkaura26@users.noreply.huggingface.co>

.gitattributes

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+*.arrow filter=lfs diff=lfs merge=lfs -text
+*.bin filter=lfs diff=lfs merge=lfs -text
+*.bz2 filter=lfs diff=lfs merge=lfs -text
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+*.safetensors filter=lfs diff=lfs merge=lfs -text
+saved_model/**/* filter=lfs diff=lfs merge=lfs -text
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+*tfevents* filter=lfs diff=lfs merge=lfs -text
+online_retail_II.xlsx filter=lfs diff=lfs merge=lfs -text
+Online[[:space:]]Retail.csv filter=lfs diff=lfs merge=lfs -text

Online Retail.csv

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+version https://git-lfs.github.com/spec/v1
+oid sha256:28885729fc0acf344fb71901ea02a42d5c39b46850e4bc874a4a1cd194e75ba3
+size 46133213

README.md

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+---
+title: Clv
+emoji: ⚡
+colorFrom: yellow
+colorTo: purple
+sdk: streamlit
+sdk_version: 1.17.0
+app_file: app.py
+pinned: false
+license: apache-2.0
+duplicated_from: deepakkaura26/clv
+---
+
+Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference

app.py

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+import streamlit as st 
+import pandas as pd
+
+st.title("Customer Lifetime Value App")
+
+# Read the dataset
+data = pd.read_csv('Online Retail.csv')
+
+# 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')
+
+
+
+
+
+
+
+
+
+# Risk of Churn
+if clv <= 0:
+    st.write('Risk of Churn : Yes')
+else:
+    st.write('Risk of Churn : No')

online_retail_II.xlsx

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+size 45622278