Can any one explain how to import a Microsoft Excel file in to a MySQL database?
For example, my Excel table looks like this:
Country | Amount | Qty
----------------------------------
America | 93 | 0.60
Greece | 9377 | 0.80
Australia | 9375 | 0.80
Thanks in Advance.
Fero
Step 1 Create Your CSV file
Step 2 log in to your mysql server
Step 3 load your csv file
There's a simple online tool that can do this called sqlizer.io.
You upload an XLSX file to it, enter a sheet name and cell range, and it will generate a CREATE TABLE statement and a bunch of INSERT statements to import all your data into a MySQL database.
There are actually several ways to import an excel file in to a MySQL database with varying degrees of complexity and success.
Excel2MySQL or Navicat utilities. Full disclosure, I am the author of Excel2MySQL. These 2 utilities aren't free, but they are the easiest option and have the fewest limitations. They also include additional features to help with importing Excel data into MySQL. For example, Excel2MySQL automatically creates your table and automatically optimizes field data types like dates, times, floats, etc. If your in a hurry or can't get the other options to work with your data then these utilities may suit your needs.
LOAD DATA INFILE: This popular option is perhaps the most technical and requires some understanding of MySQL command execution. You must manually create your table before loading and use appropriately sized VARCHAR field types. Therefore, your field data types are not optimized. LOAD DATA INFILE has trouble importing large files that exceed 'max_allowed_packet' size. Special attention is required to avoid problems importing special characters and foreign unicode characters. Here is a recent example I used to import a csv file named test.csv.
phpMyAdmin: Select your database first, then select the Import tab. phpMyAdmin will automatically create your table and size your VARCHAR fields, but it won't optimize the field types. phpMyAdmin has trouble importing large files that exceed 'max_allowed_packet' size.
MySQL for Excel: This is a free Excel Add-in from Oracle. This option is a bit tedious because it uses a wizard and the import is slow and buggy with large files, but this may be a good option for small files with VARCHAR data. Fields are not optimized.
When using text files to import data, I had problems with quotes and how Excel was formatting numbers. For example, my Excel configuration used the comma as decimal separator instead of the dot.
Now I use Microsoft Access 2010 to open my MySql table as linked table. There I can simply copy and paste cells from Excel to Access.
To do this, first install the MySql ODBC driver and create an ODBC connection. Then in access, in the "External Data" tab, open "ODBC Database" dialog and link to any table using the ODBC connection.
Below is another method to import spreadsheet data into a MySQL database that doesn't rely on any extra software. Let's assume you want to import your Excel table into the
sales
table of a MySQL database namedmydatabase
.Select the relevant cells:
Paste into Mr. Data Converter and select the output as MySQL:
Change the table name and column definitions to fit your requirements in the generated output:
If you're using MySQL Workbench or already logged into
mysql
from the command line, then you can execute the generated SQL statements from step 3 directly. Otherwise, paste the code into a text file (e.g.,import.sql
) and execute this command from a Unix shell:mysql mydatabase < import.sql
Other ways to import from a SQL file can be found in this Stack Overflow answer.
Export it into some text format. The easiest will probably be a tab-delimited version, but CSV can work as well.
Use the load data capability. See http://dev.mysql.com/doc/refman/5.1/en/load-data.html
Look half way down the page, as it will gives a good example for tab separated data:
FIELDS TERMINATED BY '\t' ENCLOSED BY '' ESCAPED BY '\'
Check your data. Sometimes quoting or escaping has problems, and you need to adjust your source, import command-- or it may just be easier to post-process via SQL.