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Analyze YouTube Analytics Data in R

Create data visualizations and use high-performance statistical functions to analyze YouTube Analytics data in Microsoft R Open.

Access YouTube Analytics data with pure R script and standard SQL. You can use the CData ODBC Driver for YouTube Analytics and the RODBC package to work with remote YouTube Analytics 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 YouTube Analytics data and visualize YouTube Analytics 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 YouTube Analytics as an ODBC Data Source

Information for connecting to YouTube Analytics follows, along with different instructions for configuring a DSN in Windows and Linux environments.

YouTube Analytics uses the OAuth authentication standard. You can use the embedded CData OAuth credentials or you can register an application with Google to obtain your own.

In addition to the OAuth values, to access YouTube Analytics data set ChannelId to the Id of a YouTube channel. You can obtain the channel Id in the advanced account settings for your channel. If not specified, the channel of the currently authenticated user will be used.

If you want to generate content owner reports, specify the ContentOwnerId property. This is the Id of the copyright holder for content in YouTube's rights management system. The content owner is the person or organization that claims videos and sets their monetization policy.

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 YouTube Analytics 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 YouTubeAnalytics Source] Driver = CData ODBC Driver for YouTube Analytics Description = My Description ContentOwnerId = MyContentOwnerId ChannelId = MyChannelId

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 YouTube Analytics Data as an ODBC Data Source

You can connect to a DSN in R with the following line:

conn <- odbcConnect("CData YouTubeAnalytics Source")

Schema Discovery

The driver models YouTube Analytics 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 YouTube Analytics API.

groups <- sqlQuery(conn, "SELECT Snippet_Title, ContentDetails_ItemCount FROM Groups", believeNRows=FALSE, rows_at_time=1)

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

View(groups)

Plot YouTube Analytics Data

You can now analyze YouTube Analytics 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(groups$ContentDetails_ItemCount, main="YouTube Analytics Groups", names.arg = groups$Snippet_Title, horiz=TRUE)