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Get the Report →Analyze Monday.com Data in R
Use standard R functions and the development environment of your choice to analyze Monday.com data with the CData JDBC Driver for Monday.com.
Access Monday.com 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 Monday.com and the RJDBC package to work with remote Monday.com 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 Monday.com and visualize Monday.com 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 Monday.com as a JDBC Data Source
You will need the following information to connect to Monday.com as a JDBC data source:
- Driver Class: Set this to cdata.jdbc.monday.MondayDriver
- 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 Monday.com:
driver <- JDBC(driverClass = "cdata.jdbc.monday.MondayDriver", classPath = "MyInstallationDir\lib\cdata.jdbc.monday.jar", identifier.quote = "'")
You can now use DBI functions to connect to Monday.com and execute SQL queries. Initialize the JDBC connection with the dbConnect function.
You can connect to Monday.com using either API Token authentication or OAuth authentication.
Connecting with an API Token
Connect to Monday.com by specifying the APIToken. Set the AuthScheme to Token and obtain the APIToken as follows:
- API tokens for admin users
- Log in to your Monday.com account and click on your avatar in the bottom left corner.
- Select Admin.
- Select "API" on the left side of the Admin page.
- Click the "Copy" button to copy the user's API token.
- API tokens for non-admin users
- Click on your profile picture in the bottom left of your screen.
- Select "Developers"
- Click "Developer" and then "My Access Tokens" at the top.
- Select "Show" next to the API token, where you'll be able to copy it.
Connecting with OAuth Authentication
Alternatively, you can establish a connection using OAuth (refer to the OAuth section of the Help documentation).
Built-in Connection String Designer
For assistance in constructing the JDBC URL, use the connection string designer built into the Monday.com JDBC Driver. Either double-click the JAR file or execute the jar file from the command-line.
java -jar cdata.jdbc.monday.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:monday:APIToken=eyJhbGciOiJIUzI1NiJ9.yJ0aWQiOjE0MTc4NzIxMiwidWlkIjoyNzI3ODM3OSwiaWFkIjoiMjAyMi0wMS0yMFQxMDo0NjoxMy45NDFaIiwicGV;")
Schema Discovery
The driver models Monday.com 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 Monday.com API:
invoices <- dbGetQuery(conn,"SELECT Id, DueDate FROM Invoices WHERE Status = 'SENT'")
You can view the results in a data viewer window with the following command:
View(invoices)
Plot Monday.com Data
You can now analyze Monday.com 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(invoices$DueDate, main="Monday.com Invoices", names.arg = invoices$Id, horiz=TRUE)