Working with R

PASS Summit–Lightning Talk on R

/ Mitchell Pearson / Leave a comment

I’m excited to have the opportunity to speak at PASS Summit 2018. I am doing a quick 10 minute lightning talk on R integration with Power BI. Somehow I was able to sneak in with this incredible group of speakers! SHHHHH, don’t tell anyone lest they find out!

Speakers

I have loaded my slide deck here, this includes what you need to get started with R! Slide Deck

In this talk I am focusing on how R can be used to extend the capabilities and functionality of Power BI. More specifically, I will be using R to show the following four demos:

  • How to extract data from Power BI using R
  • How to unzip and process files with R
  • How to Download, unzip and process files
  • How to check if file exist before processing the file

Also, I have created blog posts with corresponding YouTube videos already on 3 of the 4 demos listed above!

YouTube

My YouTube channel is simply MitchellSQL

Blog: MitchellPearson.com

Below are the three blog posts that I have previously posted:

Export Data from Power BI using R

Unzip and Process files into Power BI with R

Download, unzip, and process with R

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Download and unzip files using R in Power BI

/ Mitchell Pearson / Leave a comment

In a previous blog, I wrote about how you could use R to unzip files. Well, that raises the question, can I download a zip file and then unzip it using R?

You can view the previous blog post on how to unzip files here.

Update: YouTube video can be found at the bottom of this post!

Download files using R

In general, downloading and processing a file can be done in Power BI very easily using “web” as the data source and you never have to worry about using R. However, if you need to do something more complex then R can be very helpful. For example, you may want to download a zip file, unzip it, and then process it.

In this example, I am going to download a zip file that contains names by state, this zip file is stored in the following location:

https://www.ssa.gov/oact/babynames/state/namesbystate.zip

This zip file has data for each of the different states, for this example I only want to look at the data for Florida. So we are going to unzip the file and only extract the data from the single file that we need data from.

Let’s take a look at the code in R Studio and break it down:

image

  1. First, I want to store the destination location and filename in a variable, this is done in lines 1-2.
  2. Next, I want to download the zip file and store it locally, this is done in lines 4-6.
  3. Thirdly, now the file will be unzipped and the file FL.TXT will be stored in the variable FLnames, lines 8-9.
  4. Lastly, we will read the text file and store it in the variable babynames.

The only thing we added in this example that was not in the previous blog post was the ability of downloading the code. If you, missed the previous blog and want to know how to import the data into Power BI, you can check that our here.

 

Thanks, for checking out my blog!

Using R to unzip and process files into Power BI

/ Mitchell Pearson / 4 Comments

There are a lot of blogs and videos out there on how to use R to enhance the visualization layer of Power BI. In this small series, I want to focus on how R can be used to improve the data importing and data cleansing capabilities of Power BI. Previously, I wrote how you could use the R language in Power BI to export data out to a CSV file. You can view that blog by following this link.

Update: Video embedded at bottom of blog post.

Although, I personally am not an expert when it comes to R, I’m learning more each day, it’s one of the topics I enjoy teaching the most in our Advanced Power BI Boot Camp.

Now it’s time for the required Pirate Picture: ARRRRRRRR. By the way, this image is from a tabletop game I like playing called Merchants & Marauders!!

Image result for pirate arrrrr

Getting Started with R in Power BI

To work with R you will need to have R installed. I use Microsoft R open, link provided below. You can optionally download R studio as well. Both of these are free downloads.

Required: Download the Microsoft R Open

Optional: Download R Studio

Discloser: At the time of this blog post, there is no built-in intellisense in Power BI to help write and debug R. Therefore, I use R Studio to write and test my code! R Studio is not a requirement, it is, in my experience, just very helpful.

UNZ and READ.CSV in R

The problem I want to solve in this blog post is how to unzip a file with Power BI and then process that file. Because I come from an enterprise BI background my first thought is to approach this problem with a tool like SSIS or PowerShell. However, there is an easier way, why else would we be here! Smile

I want to show you how you can use R to unzip and then extract data from a file all in one step. By the way, it’s really, really easy!

Let’s start off by looking at the code, this is all of it!:

image

  1. On line one, we are declaring a variable called data, this variable will store the results of our expression.
  2. On line two we are using read.csv to extract the results from the csv file, Customer Sales, and these results are stored in the variable from step one, please note that this process can not occur until after the file has been unzipped.
  3. On lines three and four we are using UNZ to unzip the file Customer Sale.zip and then return the file Customer Sales.csv.

And that’s it!

Wait, wait, wait…. What is line seven? Well, line seven allows me to test the results in R Studio. This is not needed for the importing data into Power BI Desktop. Oh, that reminds me, we need to import the data into Power BI Desktop!

Importing data using R in Power BI Desktop

As you are already aware, there are a lot of data sources available in Power BI, it shouldn’t surprise you that one of those data sources is R. Now let’s walk through how we can quickly import data from an R script into Power BI Desktop.

From the home ribbon in Power BI, click Get Data –> Other –> R Script. See screenshot below:

image

This will launch the R Script editor. As I previously mentioned, this script editor is simply a text box. Now we simply paste in our code from R studio, or if you happen to be an R aficionado you can just type your code in this box, as seen below:

image

Once we click ok, the Navigator window will open. Since we only declared one variable in our script, only one option will be provided. From here, everything is exactly the same as any other data source.

4_Navigator Window

Ok, now we’re done! I hope you enjoyed this blog post and I look forward to writing more, until next time.