Replicate the app from the image.
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import streamlit as st
import pandas as pd
# Page config
st.set_page_config(page_title="Loan Dashboard", layout="wide")
# Sidebar
with st.sidebar:
st.image("https://via.placeholder.com/50", width=50) # Logo placeholder
st.markdown("---")
sections = ["Dashboard", "Products", "Wallet", "Loans", "Verify", "Portfolio",
"Partner tools", "Search", "More Apps", "Toolbar", "Cards", "People",
"Pricing", "Settings", "Media/Real-time"]
for section in sections:
st.sidebar.button(section)
# Main content
st.title("Wallet")
# Quick loan amounts
col1, col2, col3, col4 = st.columns(4)
with col1:
st.button("50 €", type="secondary")
with col2:
st.button("100 €", type="secondary")
with col3:
st.button("250 €", type="secondary")
with col4:
st.button("500 €", type="secondary")
# Loan details section
st.subheader("I Need A Loan In")
col1, col2 = st.columns([2, 3])
with col1:
st.selectbox("Currency", ["EUR"])
# Collateral input
st.text_input("Collateral", value="0.000000")
# Action buttons
col1a, col1b = st.columns(2)
with col1a:
st.button("NEW RISK LOAN", type="primary")
with col1b:
st.button("LOAN NOW", type="primary")
with col2:
# Loan parameters
params = {
"Term/Loan Repayment": "2m",
"Interest Rate": "60%",
"Loan Term": "Short-term",
"Best Method to repay": "USDT/USDC",
"Loan Funding type": "0.0000 BTC",
"Loan Funding Value": "500.00 €",
"Loan Organization Fee": "25%",
"Early Repayment Option": "Free",
"Loan Amount": "10000 €",
"Total cost of loan (from original)": "6000 €",
"Monthly Payment": "3334 €"
}
for key, value in params.items():
cols = st.columns([2, 1])
cols[0].text(key)
cols[1].text(value)
# Your loans section
st.subheader("Your Loans")
# Create sample loan data
loan_data = {
'Loan #': ['123-FDS-180185', 'Last Note'],
'Status': ['Active', 'Active'],
'Created': ['€ 1375728', '€ 20365412'],
'Date Range': ['LTC / € 35383514', 'LTC / € 50383514'],
'Duration': ['6 months', '6 months'],
'Term': ['12 months', '12 months'],
'Amount': ['€500.00', '€750.00']
}
df = pd.DataFrame(loan_data)
st.dataframe(df, hide_index=True)
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