Update app.py

app.py

@@ -3,10 +3,9 @@ import pandas as pd
 import matplotlib.pyplot as plt
 import seaborn as sns
 
-# 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)
+# Create an empty DataFrame for expenses
+columns = ['Date', 'Category', 'Description', 'Amount']
+expenses_df = pd.DataFrame(columns=columns)
 
 # Streamlit app layout
 st.title('Expense Tracker')
@@ -20,53 +19,42 @@ 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=st.session_state.expenses_df.columns)
-    st.session_state.expenses_df = pd.concat([st.session_state.expenses_df, new_expense], ignore_index=True)
+    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(st.session_state.expenses_df)
+st.write(expenses_df)
 
 # Ensure 'Amount' is numeric (convert if necessary)
-st.session_state.expenses_df['Amount'] = pd.to_numeric(st.session_state.expenses_df['Amount'], errors='coerce')
+expenses_df['Amount'] = pd.to_numeric(expenses_df['Amount'], errors='coerce')
 
-# Show category summary
+# Generate summary by category
 st.subheader("Category Summary")
-category_summary = st.session_state.expenses_df.groupby('Category')['Amount'].sum().reset_index()
+category_summary = 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 ($)')
-    ax.set_xticklabels(ax.get_xticklabels(), rotation=45)
-    st.pyplot(fig)
-
-    # Pie chart: Expense distribution by description for this category
-    fig, ax = plt.subplots(figsize=(8, 8))
-    description_summary = category_df.groupby('Description')['Amount'].sum().reset_index()
-    description_summary.set_index('Description')['Amount'].plot(kind='pie', autopct='%1.1f%%', legend=False, ax=ax)
-    ax.set_title(f'Expense Distribution for Category: {category}')
-    ax.set_ylabel('')  # Hide ylabel
-    st.pyplot(fig)
+# Bar chart for total expenses by category
+fig, ax = plt.subplots(figsize=(10, 6))
+sns.barplot(x='Category', y='Amount', data=category_summary, ax=ax)
+ax.set_title('Total Expenses by Category')
+ax.set_xlabel('Category')
+ax.set_ylabel('Amount Spent ($)')
+ax.set_xticklabels(ax.get_xticklabels(), rotation=45)
+st.pyplot(fig)
+
+# Pie chart for expense distribution by category
+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_ylabel('')  # Hide ylabel
+st.pyplot(fig)
 
 # Save the expenses to a CSV file
 st.download_button(
     label="Download Expenses as CSV",
-    data=st.session_state.expenses_df.to_csv(index=False),
+    data=expenses_df.to_csv(index=False),
     file_name="expenses.csv",
     mime="text/csv"
 )