Create analyze.py

data/analyze.py

@@ -0,0 +1,40 @@
+import pandas as pd
+import os
+
+# Function to read CSV file with error handling
+def read_csv_with_error_handling(file_path):
+    try:
+        return pd.read_csv(file_path)
+    except FileNotFoundError:
+        print(f"Error: File '{file_path}' not found.")
+        return None
+
+# File paths
+file_paths = [
+    'data/daily_sales_data_0.csv',
+    'data/daily_sales_data_1.csv',
+    'data/daily_sales_data_2.csv'
+]
+
+# Load the three CSV files
+sales_data = [read_csv_with_error_handling(file_path) for file_path in file_paths]
+
+# Check if any file failed to load
+if any(data is None for data in sales_data):
+    print("Error: One or more files failed to load. Exiting.")
+    exit()
+
+# Combine the data from the three files
+combined_sales_data = pd.concat(sales_data)
+
+# Filter rows where the product is Pink Morsels
+pink_morsels_data = combined_sales_data[combined_sales_data['product'] == 'Pink Morsels']
+
+# Calculate total sales by multiplying quantity and price
+pink_morsels_data['sales'] = pink_morsels_data['quantity'] * pink_morsels_data['price']
+
+# Select and rearrange 
+formatted_data = pink_morsels_data[['sales', 'date', 'region']]
+
+# Save the formatted data into a single output file
+formatted_data.to_csv('formatted_sales_data.csv', index=False)