Expense-Tracker / app.py
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Create app.py
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import streamlit as st
import pandas as pd
import os
import plotly.express as px
from datetime import datetime
# -------------------------------
# CONFIG & STYLES
# -------------------------------
st.set_page_config(page_title="πŸ’Έ Expense Tracker", layout="wide")
st.markdown(
"""
<style>
body {
background-color: #f8f9fa;
}
.title {
font-size: 40px;
font-weight: bold;
color: #2c3e50;
text-align: center;
margin-bottom: 10px;
}
.subtitle {
font-size: 18px;
color: #7f8c8d;
text-align: center;
margin-bottom: 30px;
}
.metric-card {
background: black;
padding: 20px;
border-radius: 15px;
text-align: center;
box-shadow: 0px 2px 6px rgba(0,0,0,0.1);
}
</style>
""",
unsafe_allow_html=True,
)
# -------------------------------
# FILE SETUP
# -------------------------------
CSV_FILE = "expenses.csv"
if not os.path.exists(CSV_FILE):
df = pd.DataFrame(columns=["date", "category", "amount", "description"])
df.to_csv(CSV_FILE, index=False)
# -------------------------------
# LOAD DATA
# -------------------------------
df = pd.read_csv(CSV_FILE)
# -------------------------------
# SIDEBAR NAVIGATION
# -------------------------------
st.sidebar.title("πŸ“Œ Navigation")
page = st.sidebar.radio("Go to", ["βž• Add Expense", "πŸ“Š Dashboard", "πŸ“‚ Expense Table"])
st.sidebar.markdown("---")
st.sidebar.write("πŸ’‘ Tip: Use filters to explore your expenses easily!")
# -------------------------------
# PAGE: ADD EXPENSE
# -------------------------------
if page == "βž• Add Expense":
st.markdown("<div class='title'>Add New Expense</div>", unsafe_allow_html=True)
with st.form("expense_form", clear_on_submit=True):
col1, col2 = st.columns(2)
with col1:
date = st.date_input("Date", datetime.today())
category = st.selectbox("Category", ["Food", "Transport", "Bills", "Entertainment", "Other"])
with col2:
amount = st.number_input("Amount", min_value=0.0, step=0.01)
description = st.text_input("Description")
submitted = st.form_submit_button("πŸ’Ύ Save Expense")
if submitted:
new_expense = pd.DataFrame(
[[date, category, amount, description]],
columns=["date", "category", "amount", "description"],
)
new_expense.to_csv(CSV_FILE, mode="a", header=False, index=False)
st.success("βœ… Expense saved successfully!")
# -------------------------------
# PAGE: DASHBOARD
# -------------------------------
elif page == "πŸ“Š Dashboard":
st.markdown("<div class='title'>Expense Dashboard</div>", unsafe_allow_html=True)
st.markdown("<div class='subtitle'>Visualize your spending habits</div>", unsafe_allow_html=True)
if df.empty:
st.warning("⚠️ No data available yet. Add some expenses first.")
else:
# Metrics Row
col1, col2, col3 = st.columns(3)
with col1:
st.markdown(f"<div class='metric-card'><h3>Total Spent</h3><p>Rs {df['amount'].sum():,.2f}</p></div>", unsafe_allow_html=True)
with col2:
top_cat = df.groupby("category")["amount"].sum().idxmax()
st.markdown(f"<div class='metric-card'><h3>Top Category</h3><p>{top_cat}</p></div>", unsafe_allow_html=True)
with col3:
avg = df["amount"].mean()
st.markdown(f"<div class='metric-card'><h3>Avg. Expense</h3><p>Rs {avg:,.2f}</p></div>", unsafe_allow_html=True)
st.markdown("---")
# Charts
col1, col2 = st.columns(2)
with col1:
fig1 = px.pie(df, names="category", values="amount", title="Expenses by Category", hole=0.4)
st.plotly_chart(fig1, use_container_width=True)
with col2:
df["date"] = pd.to_datetime(df["date"])
fig2 = px.line(df, x="date", y="amount", title="Expenses Over Time", markers=True)
st.plotly_chart(fig2, use_container_width=True)
# -------------------------------
# PAGE: EXPENSE TABLE
# -------------------------------
elif page == "πŸ“‚ Expense Table":
st.markdown("<div class='title'>Expense Records</div>", unsafe_allow_html=True)
if df.empty:
st.warning("⚠️ No expenses found. Add some first.")
else:
with st.expander("πŸ” Filters", expanded=True):
col1, col2 = st.columns(2)
with col1:
categories = st.multiselect("Filter by Category", df["category"].unique())
with col2:
date_range = st.date_input("Filter by Date Range", [])
filtered = df.copy()
if categories:
filtered = filtered[filtered["category"].isin(categories)]
if date_range:
if len(date_range) == 2:
start, end = date_range
filtered = filtered[(pd.to_datetime(filtered["date"]) >= pd.to_datetime(start)) &
(pd.to_datetime(filtered["date"]) <= pd.to_datetime(end))]
st.dataframe(filtered, use_container_width=True)