Creating a table from CSV in MySQL
In this article, we aim to understand how to create a table from CSV in MySQL database.
Businesses and organizations must quickly generate tables from large amounts of data. These organizations typically have large CSV files with large amounts of data evenly distributed across multiple fields in the file to accomplish this task.
Sometimes, it becomes necessary for an analyst to create a table directly from such CSV files. In this tutorial, let us understand this concept.
Let's collect some data in a CSV file to understand this better.
We can name this file as dummy_data. See our CSV file as shown below.
Now that we have our data set up in a CSV file, let's learn how to convert this data into a table in MySQL.
Creating a table from CSV in MySQL using MySQL Workbench
TablesWe can do this
in MySQL Workbench by right clicking on the tab for our database . It will show us 表数据导入向导the tabs.
As shown in the figure below.
After clicking on the tab, we can select the path of the CSV file and click 下一步as shown below.
We keep clicking Next until our task is executed. After successfully running all the tabs, you can see the created tables in the left tab of MySQL Workbench.
The name of the newly created table will be the same as the file name given previously.
Alternatively, we can look up data from the table to ensure that the table has been created. We can do this using the query below.
SELECT * from dummy_data;
The query loops through our entire table and fetches the values. The output of the query is shown below.
Client Job Name Fees Paid Taxes Paid Total Billed Your Earnings
b pay per project -7.6 -0.38 38 30.02
A How-To Style Article Writers Needed -26.1 -1.31 130.5 103.09
C Consultancy Technical writers for -19.8 -0.99 99 78.21
d Developing a Machine Learning model -5 -0.25 25 19.75
ASWe use aliases with keywords
in MySQL Jobsto increase the readability of programs in output blocks.
So, with the help of queries and methods, we can create a new table from CSV entries efficiently and quickly in MySQL.
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