Analysis of Sales Data: Top-Selling Products

Oct 28, 2024, 8:29 AM

Sales .xlsx

Missing file

What are the top-selling products?

The top-selling products based on the order quantity are as follows:
  1. Product with index 36: 2775 units sold
  2. Product with index 1: 2570 units sold
  3. Product with index 32: 2569 units sold
  4. Product with index 11: 2535 units sold
  5. Product with index 26: 2535 units sold
If you have any more questions or need further analysis, feel free to ask!

Can you show a visualization of the top-selling products?

Can you analyze the sales trends over time?

What is the average order quantity per month?

The average order quantity per month is as follows:
  • January 2020: 5.50 units
  • February 2020: 5.54 units
  • March 2020: 5.50 units
  • April 2020: 5.52 units
These values represent the average number of units ordered per month. If you have any more questions or need further analysis, feel free to ask!

What are the sales trends for a specific product?

Could you please specify the product index for which you would like to analyze the sales trends? You can refer to the product indices listed earlier, such as 36, 1, 32, etc.

each region is best ?

To determine which region is best in terms of sales, we need to analyze the sales data by region. However, the current dataset does not explicitly contain a 'region' column.
If you have additional data or context that specifies regions, please provide it. Otherwise, we can analyze the data based on available columns such as Storeindex or Sales Channel to infer regional performance.
Could you provide more information or specify how regions are defined in your dataset?

the storeindex can find on another sheet

It seems there was an error because the column 'Storeindex' does not exist in the store_info DataFrame. This might be due to a misunderstanding of the data structure.
Let's first examine the store_info DataFrame to understand its structure and identify the correct column to use for merging with the sales data. We will need to ensure that the column used for merging corresponds to the 'Storeindex' in the sales data.
The store_info DataFrame contains the following columns:
  • State Code
  • State
  • Region
It seems there is no direct column named Storeindex. We might need to use State Code or another identifier to match with the sales data.
Let's attempt to merge using State Code and Storeindex from the sales data to determine the best-performing region.

What are the top-performing products?

The top-performing products based on total order quantity are:
  1. Product Index 36 with a total order quantity of 2775.
  2. Product Index 1 with a total order quantity of 2570.
  3. Product Index 32 with a total order quantity of 2569.
  4. Product Index 11 with a total order quantity of 2535.
  5. Product Index 26 with a total order quantity of 2535.
These products have the highest sales quantities in the dataset. If you have any further questions or need additional analysis, feel free to ask!

How can I visualize the sales data by region?

It seems there was an error because the variable sales_data was not defined. This was a mistake in the code where I intended to use the df variable, which contains the sales data.
Let's correct this by using the correct variable name and ensure that the data types match for merging.
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