How to extract Google Analytics data in R and Excel

You will need RGoogleAnalytics package to extract Google Analytics data in R. The package was developed by Michael Pearmain, and it provides functions for accessing and retrieving data from the Google Analytics API. This article is based on the package’s supporting documentation. To download the documentation use this link: RGoogleAnalytics documentation.

First, install the package RgoogleAnalytics. It requires the packages “lubridate” and “httr” to be installed as well.



If you have problems with downloading the packages, check your R version. RGoogleAnalytics requires R version 3.0.2 or newer.

Then, you will use the Auth function to authorize the RGoogleAnalytics package to your Google Analytics Account using Oauth2.0.
The function Auth expects a Client ID and Client Secret. To get these, you will have to register an application with the Google Analytics API:
1. Go to the Google Developers Console
2. Create a New Project and enable the Google Analytics API
3. On the Credentials screen, create a new Client ID for Application Type “Installed Application”
4. Copy the Client ID and Client Secret to your R Script


Enable Google Analytics API


Create a new Client ID






Now you can authorize the RGoogleAnalytics package to your Google Analytics Account. <- "your_client_ID_here"
client.secret <- "your_client_secret_here"
token <- Auth(, client.secret)

Save the token into the file


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Getting data from the Web with R and some basic functionality

We will load a dataset into R and do some manipulations in order to show some basic functionality.

The dataset can be downloaded here This dataset is a subset of the May 2014 State Occupational Employment and Wage Estimates Report in California by Computer and Mathematical Occupations. The original dataset can be found here


  1. The dataset has to be downloaded in your working directory. Getwd() funcion returns an absolute filepath representing the current working directory of the R process. To change your working directory in R you need to use setwd(dir) function or go to the File menu in the R Cosole and choose “Change dir”.
  2. Create a directory for the data
if(!file.exists("salaries")) {
  1. Download the file
fileUrl < - "your link here"
download.file(fileUrl,destfile = "./salaries/computer.xls")
  1. Next step is to install the xlsx R package if you have not done so previously. To install xlsx, use install.packages(“xlsx”), to ensure if you have it or no, enter find.package(“xlsx”) in the console. After xlsx is done installing, load it using library(xlsx).
  2. Read the file
salariesData <-read.xlsx("./salaries/computer.xls",

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How to subset data in R

How to subset a certain column



data.frame[ , # of the column]


data.frame[ , ""]

All three options above are the same, we are choosing a certain column. For example, if we have a data frame survey which consists of 1,000 observations, and each observation is described by 3 variables: gender, age, and marital status, by using survey$age we can subset the column named “age” for all 1,000 observations.

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