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import matplotlib.pyplot as plt
import pandas as pd
import os
def generate_report(df, spending_analysis, recommendations):
# Create a directory for images if it doesn't exist
images_dir = "images"
if not os.path.exists(images_dir):
os.makedirs(images_dir)
report = f"""
## Invoice Reader & Budget Categorizer Report
### Categorized Transactions
{df.groupby('category').apply(lambda x: x.to_markdown(index=False)).to_string()}
### Spending Insights
{spending_analysis}
### Budget Recommendations
{recommendations}
### Visualizations
#### Category-wise Spending
})
#### Monthly Spending Trend
})
"""
if not df.empty:
# Category-wise spending pie chart
category_spending = df.groupby("category")["amount"].sum()
plt.figure(figsize=(6, 6))
plt.pie(category_spending, labels=category_spending.index, autopct="%1.1f%%")
plt.title("Category-wise Spending")
plt.savefig(os.path.join(images_dir, "category_spending.png"))
plt.close()
# Monthly spending trend with validation
monthly_spending = df.groupby("month")["amount"].sum()
if len(monthly_spending) > 1: # Ensure multiple months
plt.figure(figsize=(8, 4))
monthly_spending.plot(kind="line", marker="o")
plt.title("Monthly Spending Trend")
plt.xlabel("Month")
plt.ylabel("Amount")
plt.savefig(os.path.join(images_dir, "monthly_spending.png"))
plt.close()
else:
report += "\n#### Monthly Spending Trend\n(No trend available: insufficient data across multiple months)"
return report |