salesanalyzer_mds.sales_summary_statistics
==========================================

.. py:module:: salesanalyzer_mds.sales_summary_statistics


Functions
---------

.. autoapisummary::

   salesanalyzer_mds.sales_summary_statistics.sales_summary_statistics


Module Contents
---------------

.. py:function:: sales_summary_statistics(sales_data: pandas.DataFrame, quantity_col: str = 'Quantity', price_col: str = 'UnitPrice', customer_col: str = 'CustomerID', invoice_col: str = 'InvoiceNo', description_col: str = 'Description') -> pandas.DataFrame

   Generate summary statistics for sales data, including total revenue, unique customers,
   average order value, top-selling products by quantity and revenue, and average revenue
   per customer.

   Args:
   -----
       sales_data (pandas.DataFrame): A DataFrame containing sales data with at least
                                      the following columns: quantity_col, price_col,
                                      customer_col, invoice_col, and description_col.
       quantity_col (str): The name of the column containing the quantity sold.
       price_col (str): The name of the column containing the unit price of the product.
       customer_col (str): The name of the column containing the customer ID.
       invoice_col (str): The name of the column containing the invoice number.
       description_col (str): The name of the column containing the product description.

   Returns:
   --------
       pandas.DataFrame: A DataFrame containing the calculated summary statistics. If
                         no sales data is provided, returns an empty DataFrame.

   The function computes the following statistics:
   - 'total_revenue': The total revenue generated by all sales.
   - 'unique_customers': The number of unique customers.
   - 'average_order_value': The average value of an order (sum of revenue per invoice).
   - 'top_selling_product_quantity': The product with the highest quantity sold.
   - 'top_selling_product_revenue': The product with the highest total revenue.
   - 'average_revenue_per_customer': The average revenue generated by each customer.

   Example:
   --------
   >>> df = pd.DataFrame({
   >>>     'Quantity': [10, 5, 3, 15],
   >>>     'UnitPrice': [100, 200, 150, 100],
   >>>     'CustomerID': [1, 2, 1, 3],
   >>>     'InvoiceNo': ['INV001', 'INV002', 'INV003', 'INV004'],
   >>>     'Description': ['Product A', 'Product B', 'Product A', 'Product C']
   >>> })
   >>> summary_df = sales_summary_statistics(df)
   >>> print(summary_df)
   total_revenue  unique_customers  average_order_value      0          3950.0                 3               987.5

      top_selling_product_quantity top_selling_product_revenue      0                Product C                Product C

      average_revenue_per_customer
   0                     1316.666667