| Image |  |
| EAN-13 | 9780448402154  |
| Product Name | How to Hide a Crocodile & Other Reptiles (All Aboard Books (Paperback)) |
| Language | English |
| Category | Book / Magazine / Publication |
| Short Description | Height:8.03 inches / Length:0.12 inches / Weight:0.19 pounds / Width:7.76 inches |
| Amazon.com |  Buy on Amazon ~ 0448402157 |
| SKU | ACAMP_BOOK_USEDVERYGOOD_0448402157 |
| Price New | 1.89 US Dollars (curriencies) |
| Price Used | 0.25 US Dollars (curriencies) |
| Width | 0.19 inches (convert) |
| Height | 8.06 inches (convert) |
| Length | 8.06 inches (convert) |
| Weight | 3.04 ounces (convert) |
| Author | Ruth Heller |
| Page Count | 32 |
| Binding | Paperback |
| Published | 10/27/1994 |
| Long Description | Go on a fascinating nature hunt to find the camouflaged turtle, snakes, iguana, and other intriguing reptiles hiding in the brilliantly-painted pages of this book. |
| Similar Items | 9780698117785: Chickens Aren't The Only Ones (World Of Nature Series) 9780698115590: The Reason For A Flower: A Book About Flowers, Pollen, And Seeds (Explore!) 9780448410913: The Reason For A Flower: A Book About Flowers, Pollen, And Seeds (Explore!) 9780448409658: How To Hide A Meadow Frog And Other Amphibians (Reading Railroad) 9780448404783: How To Hide An Octopus And Other Sea Creatures (Reading Railroad) 9780448404776: Ruth Heller's How to Hide a Butterfly & Other Insects (Reading Railroad Books) 9780448190273: How Hide A Whippoorwi 9780448104768: How Hide An Octopus 9780804565738: How To Hide A Butterfly And Other Insects 9780448409641: How To Hide A Parakeet & Other Birds View 13 more similar items |
| Created | 02-26-2012 6:38:13pm |
| Modified | 08-22-2017 5:33:26am |
| MD5 | 4840054bee4ecbe39ea8446b0c5a272b |
| SHA256 | ea578398b1b3e4354786f126d833ca4142979aac3f1c40e267c58ad94b164526 |
| Search Google | by EAN or by Title |
| Query Time | 0.0182629 |
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.