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Get the Report →Analyze Airtable Data in R
Create data visualizations and use high-performance statistical functions to analyze Airtable data in Microsoft R Open.
Access Airtable data with pure R script and standard SQL. You can use the CData ODBC Driver for Airtable and the RODBC package to work with remote Airtable 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 Airtable data and visualize Airtable 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 Airtable as an ODBC Data Source
Information for connecting to Airtable follows, along with different instructions for configuring a DSN in Windows and Linux environments.
APIKey, BaseId and TableNames parameters are required to connect to Airtable. ViewNames is an optional parameter where views of the tables may be specified.
- APIKey : API Key of your account. To obtain this value, after logging in go to Account. In API section click Generate API key.
- BaseId : Id of your base. To obtain this value, it is in the same section as the APIKey. Click on Airtable API, or navigate to https://airtable.com/api and select a base. In the introduction section you can find "The ID of this base is appxxN2ftedc0nEG7."
- TableNames : A comma separated list of table names for the selected base. These are the same names of tables as found in the UI.
- ViewNames : A comma separated list of views in the format of (table.view) names. These are the same names of the views as found in the UI.
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 Airtable 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 Airtable Source]
Driver = CData ODBC Driver for Airtable
Description = My Description
APIKey = keymz3adb53RqsU
BaseId = appxxN2fe34r3rjdG7
TableNames = Table1,...
ViewNames = Table1.View1,...
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 Airtable Data as an ODBC Data Source
You can connect to a DSN in R with the following line:
conn <- odbcConnect("CData Airtable Source")
Schema Discovery
The driver models Airtable 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 Airtable API.
sampletable_1 <- sqlQuery(conn, "SELECT Id, Column1 FROM SampleTable_1 WHERE Column2 = 'SomeValue'", believeNRows=FALSE, rows_at_time=1)
You can view the results in a data viewer window with the following command:
View(sampletable_1)
Plot Airtable Data
You can now analyze Airtable 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(sampletable_1$Column1, main="Airtable SampleTable_1", names.arg = sampletable_1$Id, horiz=TRUE)