Update app.py

app.py

@@ -3,9 +3,10 @@ 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)
+# Initialize the DataFrame in the session state if it doesn't exist
+if 'expenses_df' not in st.session_state:
+    columns = ['Date', 'Category', 'Description', 'Amount']
+    st.session_state.expenses_df = pd.DataFrame(columns=columns)
 
 # Streamlit app layout
 st.title('Expense Tracker')
@@ -19,42 +20,73 @@ 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)
+    new_expense = pd.DataFrame([[date, category, description, amount]], columns=st.session_state.expenses_df.columns)
+    st.session_state.expenses_df = pd.concat([st.session_state.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)
+st.write(st.session_state.expenses_df)
 
 # Ensure 'Amount' is numeric (convert if necessary)
-expenses_df['Amount'] = pd.to_numeric(expenses_df['Amount'], errors='coerce')
+st.session_state.expenses_df['Amount'] = pd.to_numeric(st.session_state.expenses_df['Amount'], errors='coerce')
 
-# Generate summary by category
+# Show category summary
 st.subheader("Category Summary")
-category_summary = expenses_df.groupby('Category')['Amount'].sum().reset_index()
+category_summary = st.session_state.expenses_df.groupby('Category')['Amount'].sum().reset_index()
 st.write(category_summary)
 
+# Generate individual bar and pie charts per Category (grouped by Description)
+st.subheader("Bar Charts and Pie Charts per Category")
+
+# Get all unique categories
+unique_categories = st.session_state.expenses_df['Category'].unique()
+
+# Loop through each unique category to plot bar and pie charts by description
+for category in unique_categories:
+    category_df = st.session_state.expenses_df[st.session_state.expenses_df['Category'] == category]
+
+    # Bar chart: Expense distribution by description for this category
+    fig, ax = plt.subplots(figsize=(10, 6))
+    sns.barplot(x='Description', y='Amount', data=category_df, ax=ax)
+    ax.set_title(f'Total Expenses for Category: {category}')
+    ax.set_xlabel('Description')
+    ax.set_ylabel('Amount Spent ($)')
+    ax.set_xticklabels(ax.get_xticklabels(), rotation=45)
+    st.pyplot(fig)
+
+    # Pie chart: Expense distribution by description for this category
+    fig, ax = plt.subplots(figsize=(8, 8))
+    description_summary = category_df.groupby('Description')['Amount'].sum().reset_index()
+    description_summary.set_index('Description')['Amount'].plot(kind='pie', autopct='%1.1f%%', legend=False, ax=ax)
+    ax.set_title(f'Expense Distribution for Category: {category}')
+    ax.set_ylabel('')  # Hide ylabel
+    st.pyplot(fig)
+
+# Create overall bar and pie chart for all categories
+
 # Bar chart for total expenses by category
+st.subheader("Overall Expenses by Category")
 fig, ax = plt.subplots(figsize=(10, 6))
 sns.barplot(x='Category', y='Amount', data=category_summary, ax=ax)
-ax.set_title('Total Expenses by Category')
+ax.set_title('Total Expenses by Category (Overall)')
 ax.set_xlabel('Category')
 ax.set_ylabel('Amount Spent ($)')
 ax.set_xticklabels(ax.get_xticklabels(), rotation=45)
 st.pyplot(fig)
 
 # Pie chart for expense distribution by category
+st.subheader("Overall Expense Distribution")
 fig, ax = plt.subplots(figsize=(8, 8))
 category_summary.set_index('Category')['Amount'].plot(kind='pie', autopct='%1.1f%%', legend=False, ax=ax)
-ax.set_title('Expense Distribution by Category')
+ax.set_title('Expense Distribution by Category (Overall)')
 ax.set_ylabel('')  # Hide ylabel
 st.pyplot(fig)
 
 # Save the expenses to a CSV file
 st.download_button(
     label="Download Expenses as CSV",
-    data=expenses_df.to_csv(index=False),
+    data=st.session_state.expenses_df.to_csv(index=False),
     file_name="expenses.csv",
     mime="text/csv"
 )