Create app.py

app.py

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+import streamlit as st
+import pandas as pd
+import matplotlib.pyplot as plt
+import seaborn as sns
+
+# Create an empty DataFrame for expenses
+columns = ['Date', 'Category', 'Description', 'Amount']
+expenses_df = pd.DataFrame(columns=columns)
+
+# Streamlit app layout
+st.title('Expense Tracker')
+
+# Add new expense entry
+st.subheader("Add New Expense")
+
+date = st.date_input("Date")
+category = st.selectbox("Category", ['Food', 'Transport', 'Entertainment', 'Other'])
+description = st.text_input("Description")
+amount = st.number_input("Amount", min_value=0.0, format="%.2f")
+
+if st.button("Add Expense"):
+    new_expense = pd.DataFrame([[date, category, description, amount]], columns=expenses_df.columns)
+    expenses_df = pd.concat([expenses_df, new_expense], ignore_index=True)
+    st.success(f"Added expense: {description} - ${amount:.2f}")
+
+# Display all expenses
+st.subheader("Expenses List")
+st.write(expenses_df)
+
+# Generate summary by category
+category_summary = expenses_df.groupby('Category')['Amount'].sum().reset_index()
+
+# Show category summary
+st.subheader("Category Summary")
+st.write(category_summary)
+
+# Plot bar chart of expenses by category
+st.subheader("Expenses by Category (Bar Chart)")
+plt.figure(figsize=(10, 6))
+sns.barplot(x='Category', y='Amount', data=category_summary)
+plt.title('Total Expenses by Category')
+plt.xlabel('Category')
+plt.ylabel('Amount Spent ($)')
+plt.xticks(rotation=45)
+st.pyplot()
+
+# Pie chart for category-wise expenses
+st.subheader("Expense Distribution (Pie Chart)")
+plt.figure(figsize=(8, 8))
+category_summary.set_index('Category')['Amount'].plot(kind='pie', autopct='%1.1f%%', legend=False)
+plt.title('Expense Distribution by Category')
+plt.ylabel('')
+st.pyplot()
+
+# Save the expenses to a CSV file
+st.download_button(
+    label="Download Expenses as CSV",
+    data=expenses_df.to_csv(index=False),
+    file_name="expenses.csv",
+    mime="text/csv"
+)