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Get the Report →Analyze Kintone Data in R
Create data visualizations and use high-performance statistical functions to analyze Kintone data in Microsoft R Open.
Access Kintone data with pure R script and standard SQL. You can use the CData ODBC Driver for Kintone and the RODBC package to work with remote Kintone 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 Kintone data and visualize Kintone data in R.
Install R
You can complement the driver's performance gains from multi-threading and managed code by running the multithreaded Microsoft R Open or by running R linked with the BLAS/LAPACK libraries. This article uses Microsoft R Open (MRO).
Connect to Kintone as an ODBC Data Source
Information for connecting to Kintone follows, along with different instructions for configuring a DSN in Windows and Linux environments.
In addition to the authentication values, set the following parameters to connect to and retrieve data from Kintone:
- Url: The URL of your account.
- GuestSpaceId: Optional. Set this when using a guest space.
Authenticating with Kintone
Kintone supports the following authentication methods.
Using Password Authentication
You must set the following to authenticate:
- User: The username of your account.
- Password: The password of your account.
Using Basic Authentication
If the basic authentication security feature is set on the domain, supply the additional login credentials with BasicAuthUser and BasicAuthPassword. Basic authentication requires these credentials in addition to User and Password.
Using Client SSL
Instead of basic authentication, you can specify a client certificate to authenticate. Set SSLClientCert, SSLClientCertType, SSLClientCertSubject, and SSLClientCertPassword. Additionally, set User and Password to your login credentials.
When you configure the DSN, you may also want to set the Max Rows connection property. This will limit the number of rows returned, which is especially helpful for improving performance when designing reports and visualizations.
Windows
If you have not already, first specify connection properties in an ODBC DSN (data source name). This is the last step of the driver installation. You can use the Microsoft ODBC Data Source Administrator to create and configure ODBC DSNs.
Linux
If you are installing the CData ODBC Driver for Kintone in a Linux environment, the driver installation predefines a system DSN. You can modify the DSN by editing the system data sources file (/etc/odbc.ini) and defining the required connection properties.
/etc/odbc.ini
[CData Kintone Source]
Driver = CData ODBC Driver for Kintone
Description = My Description
User = myuseraccount
Password = mypassword
Url = http://subdomain.domain.com
GuestSpaceId = myspaceid
For specific information on using these configuration files, please refer to the help documentation (installed and found online).
Load the RODBC Package
To use the driver, download the RODBC package. In RStudio, click Tools -> Install Packages and enter RODBC in the Packages box.
After installing the RODBC package, the following line loads the package:
library(RODBC)
Note: This article uses RODBC version 1.3-12. Using Microsoft R Open, you can test with the same version, using the checkpoint capabilities of Microsoft's MRAN repository. The checkpoint command enables you to install packages from a snapshot of the CRAN repository, hosted on the MRAN repository. The snapshot taken Jan. 1, 2016 contains version 1.3-12.
library(checkpoint)
checkpoint("2016-01-01")
Connect to Kintone Data as an ODBC Data Source
You can connect to a DSN in R with the following line:
conn <- odbcConnect("CData Kintone Source")
Schema Discovery
The driver models Kintone APIs as relational tables, views, and stored procedures. Use the following line to retrieve the list of tables:
sqlTables(conn)
Execute SQL Queries
Use the sqlQuery function to execute any SQL query supported by the Kintone API.
comments <- sqlQuery(conn, "SELECT CreatorName, Text FROM Comments WHERE AppId = '1354841'", believeNRows=FALSE, rows_at_time=1)
You can view the results in a data viewer window with the following command:
View(comments)
Plot Kintone Data
You can now analyze Kintone 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(comments$Text, main="Kintone Comments", names.arg = comments$CreatorName, horiz=TRUE)