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Analyze WooCommerce Data in R

Use standard R functions and the development environment of your choice to analyze WooCommerce data with the CData JDBC Driver for WooCommerce.

Access WooCommerce data with pure R script and standard SQL on any machine where R and Java can be installed. You can use the CData JDBC Driver for WooCommerce and the RJDBC package to work with remote WooCommerce data in R. By using the CData Driver, you are leveraging a driver written for industry-proven standards to access your data in the popular, open-source R language. This article shows how to use the driver to execute SQL queries to WooCommerce and visualize WooCommerce data by calling standard R functions.

Install R

You can match the driver's performance gains from multi-threading and managed code by running the multithreaded Microsoft R Open or by running open R linked with the BLAS/LAPACK libraries. This article uses Microsoft R Open 3.2.3, which is preconfigured to install packages from the Jan. 1, 2016 snapshot of the CRAN repository. This snapshot ensures reproducibility.

Load the RJDBC Package

To use the driver, download the RJDBC package. After installing the RJDBC package, the following line loads the package:

library(RJDBC)

Connect to WooCommerce as a JDBC Data Source

You will need the following information to connect to WooCommerce as a JDBC data source:

  • Driver Class: Set this to cdata.jdbc.woocommerce.WooCommerceDriver
  • Classpath: Set this to the location of the driver JAR. By default this is the lib subfolder of the installation folder.

The DBI functions, such as dbConnect and dbSendQuery, provide a unified interface for writing data access code in R. Use the following line to initialize a DBI driver that can make JDBC requests to the CData JDBC Driver for WooCommerce:

driver <- JDBC(driverClass = "cdata.jdbc.woocommerce.WooCommerceDriver", classPath = "MyInstallationDir\lib\cdata.jdbc.woocommerce.jar", identifier.quote = "'")

You can now use DBI functions to connect to WooCommerce and execute SQL queries. Initialize the JDBC connection with the dbConnect function.

WooCommerce supports the following authentication methods: one-legged OAuth1.0 Authentication and standard OAuth2.0 Authentication.

Connecting using one-legged OAuth 1.0 Authentication

Specify the following properties (NOTE: the below credentials are generated from &service; settings page and should not be confused with the credentials generated by using WordPress OAuth2.0 plugin):

  • ConsumerKey
  • ConsumerSecret

Connecting using WordPress OAuth 2.0 Authentication

After having configured the plugin, you may connect to WooCommerce by providing the following connection properties:

  • OAuthClientId
  • OAuthClientSecret
  • CallbackURL
  • InitiateOAuth - Set this to either GETANDREFRESH or REFRESH

In either case, you will need to set the Url property to the URL of the WooCommerce instance.

Built-in Connection String Designer

For assistance in constructing the JDBC URL, use the connection string designer built into the WooCommerce JDBC Driver. Either double-click the JAR file or execute the jar file from the command-line.

java -jar cdata.jdbc.woocommerce.jar

Fill in the connection properties and copy the connection string to the clipboard.

Below is a sample dbConnect call, including a typical JDBC connection string:

conn <- dbConnect(driver,"jdbc:woocommerce:Url=https://example.com/; ConsumerKey=ck_ec52c76185c088ecaa3145287c8acba55a6f59ad; ConsumerSecret=cs_9fde14bf57126156701a7563fc87575713c355e5; InitiateOAuth=GETANDREFRESH")

Schema Discovery

The driver models WooCommerce APIs as relational tables, views, and stored procedures. Use the following line to retrieve the list of tables:

dbListTables(conn)

Execute SQL Queries

You can use the dbGetQuery function to execute any SQL query supported by the WooCommerce API:

orders <- dbGetQuery(conn,"SELECT ParentId, Total FROM Orders WHERE ParentId = '3'")

You can view the results in a data viewer window with the following command:

View(orders)

Plot WooCommerce Data

You can now analyze WooCommerce data with any of the data visualization packages available in the CRAN repository. You can create simple bar plots with the built-in bar plot function:

par(las=2,ps=10,mar=c(5,15,4,2)) barplot(orders$Total, main="WooCommerce Orders", names.arg = orders$ParentId, horiz=TRUE)