Analyze PayPal Data in R

Ready to get started?

Download for a free trial:

Download Now

Learn more:

PayPal JDBC Driver

Easy-to-use PayPal client enables Java-based applications to easily consume PayPal Transactions, Orders, Sales, Invoices, etc.



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

Access PayPal 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 PayPal and the RJDBC package to work with remote PayPal 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 PayPal and visualize PayPal 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 PayPal as a JDBC Data Source

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

  • Driver Class: Set this to cdata.jdbc.paypal.PayPalDriver
  • 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 PayPal:

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

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

The provider surfaces tables from two PayPal APIs. The APIs use different authentication methods.

  • The REST API uses the OAuth standard. To authenticate to the REST API, you will need to set the OAuthClientId, OAuthClientSecret, and CallbackURL properties.
  • The Classic API requires Signature API credentials. To authenticate to the Classic API, you will need to obtain an API username, password, and signature.

See the "Getting Started" chapter of the help documentation for a guide to obtaining the necessary API credentials.

To select the API you want to work with, you can set the Schema property to REST or SOAP. By default the SOAP schema will be used.

For testing purposes you can set UseSandbox to true and use sandbox credentials.

Built-in Connection String Designer

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

java -jar cdata.jdbc.paypal.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:paypal:Schema=SOAP;Username=sandbox-facilitator_api1.test.com;Password=xyz123;Signature=zx2127;InitiateOAuth=GETANDREFRESH")

Schema Discovery

The driver models PayPal 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 PayPal API:

transactions <- dbGetQuery(conn,"SELECT Date, GrossAmount FROM Transactions")

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

View(transactions)

Plot PayPal Data

You can now analyze PayPal 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(transactions$GrossAmount, main="PayPal Transactions", names.arg = transactions$Date, horiz=TRUE)