Working with CSV Files

CSV files have a specific structure that must match the database. Each column heading must
exactly match the Attribute Code of the attribute that is represented by the column. To ensure
that the column headings can be read by Magento, first export the data from your store as a
CSV file. You can then edit the data and re-import it into Magento.
Important! We recommend that you use a program that supports UTF-8 encoding to edit CSV files,
such as Notepad++ or OpenOffice Calc. Microsoft Excel inserts additional characters into the
column header of the CSV file, which can prevent the data from being imported back into Magento.

Product CSV Structure

The catalog products CSV file contains information about products and the relationships
between them. The table has the following structure:

The first row of the table contains the names of the columns, there are two types of the names,
as shown in the following table. Other rows contain attributes values, service data, and
complex data. If a row contains the value in the SKU column, then this row the rows below it
describe the product. Each new SKU value begins the description of the next product.
Each category is entered as a path, with a forward slash (/) between each level. For example:
Furniture/Living Room. Do not include the Root Category in the path.
During import, if a row that contains the SKU value is found to be invalid, then the row, and
all other rows with data for that product cannot be imported.
The minimal table that can be imported contains only the SKU column, which can be used to
delete records from the database. There is no limit to the number of the columns he table can
have. Columns without data are ignored during the import process.

Customer CSV Structure

The customers CSV file contains customer information from the database, and has the
following structure:

The first row of the table contains the names of the attribute columns (which are the same as
attribute codes). There are two types of column names, as shown in the following table. Other
rows contain attribute values, service data, and complex data. Each row with non-empty
values in the “email” and “_website” columns starts the description of the subsequent
customer. Each row can represent customer data with or without address data, or the address
data only. In case a row contains only the address data, values in the columns, related to the
customer profile, will be ignored and may be empty.
To add or replace more than one address for a customer, in the import file add a row for each
new address with empty customer data and the new or updated address data below the
customer data row.

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