EAN-13	0194550094586
UPC-A	194550094586
Category	Clothing: Footwear
Long Description	Make a statement when you step out in the Nina Tansy pointed-toe heel. Lightweight with durable construction. Slip-on sling-back pump with hidden stretch goring panels. Man-made upper, lining, insole and outsole. Cushioned footbed for comfortable wear. Grippy outsole for secure footing. Imported. Measurements: Heel Height: 3 in Weight: 6.7 oz Product measurements were taken using size 9, width M. Please note that measurements may vary by size. Weight of footwear is based on a single item, not a pair
Product Name	0194550094586
Created	03-19-2023 1:33:41pm
Modified	03-19-2023 1:44:29pm
MD5	a8dd34d14f9b6dbb0cfdbae0ff9133da
SHA256	9973ffc6f2de4a4cffb8dc608ae731152075121002e73dcb7c7802e591919d76
Search Google	by EAN or by Title
Query Time	0.0071280

This product was recently detected and it could take some time for us to locate more information. You can check back later or you can contribute to the site by entering the additional information to this page.

We do our best to track down as much information as possible about each product but in the end, it takes people like you to help us out by looking at the products and adding information. After all, we can't get our hands on every product in the database.

We have web bots that go out into the wild and try to find additional data but they can only do so much. That is why we rely on the public and manufacturers to provide quality data.

Hopefully, what you are finding here is of value and you will continue to use the site and to help us by adding more data. We really appreciate every bit of help we get.

Article of interest

Here we will demonstrate the most basic example of importing the CSV data files that we produce on this site into your MySQL database.

For information about various databases you can use and how to import CSV files into them, please view the overview article "Importing CSV data into your database".

For this example, we are going to import the product data CSV file out of the sample_ean_data.zip but this same process will work on the full data download file. We will also be executing the commands in the MySQL Workbench but you can also use the command line tool with the same commands if you like.

First, start by creating a blank table. Use the table layout described in the read_me file for the most up-to-date table layout. It is suggested that you not use any indexing at this point. You can add indexes later. It is most likely that you will have your own tables where you want to store your data so importing the CSV files can be done into temporary tables and then later copied over to your tables. Leaving off the indexes and constraints on these import tables reduces the risk of import errors. Here is an example:

create table ean_product
(
    EAN13             varchar(13),
    UPCA              varchar(12),
    UPCE              varchar(8),
    SKU               varchar(200),
    PriceNew          numeric(15,2),
    PriceUsed         numeric(15,2),
    PriceDate         date,
    company           varchar(13),
    product           varchar(100),
    description       varchar(100),
    category          int,
    url               varchar(500),
    created           datetime,
    modified          datetime
);


Next we perform the import using the LOAD DATA INFILE command. The path to the file depends on where you saved the data and which operating system you are on. For Windows users you might find your file on the C: drive and Linux users may find your date in your home (~) folder. This example shows a Linux import. Only the path would be different between the operating systems.

LOAD DATA LOCAL
    INFILE '~/sample_ean_data/sample_ean_product.csv' 
    INTO TABLE ean_product
    FIELDS TERMINATED BY ',' ENCLOSED BY '"' ESCAPED BY '\\'
    LINES TERMINATED BY '\r\n'
    IGNORE 1 LINES;


Finally, lets look at the data that we just imported.

SELECT * FROM EAN_PRODUCT;


You may have seen some warnings after the import command. If you are concerned about these warnings, examine the data. It could be that some data has grown beyond the size specified in the read_me file. If you are worried, make the fields larger and try the process again after deleting all of the data out of the table.