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R With PowerBI: A Step-by-Step Guide

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R With PowerBI: A Step-by-Step Guide

An in-depth guide to integrating your R scripts with Microsoft's PowerBI software to create eye-popping visualizations for your data.

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There's been a lot of interest everywhere on how to integrate R scripts with Microsoft PowerBI dashboards. Here is a step by step guide to this.

Lets assume that you have some readymade R code available, for example, with the ggplot2 library. Lets use the following scripts to perform analytics using CHOL data.

  1. Open R studio or R Package (CRAN) & install ggplot2 library first.

  2. Paste the following R script and execute it:
  3. install.packages(‘ggplot2’)
    library(ggplot2)
    chol <- read.table(url(“http://assets.datacamp.com/blog_assets/chol.txt&#8221;"), header = TRUE)
    #Take the column “AGE” from the “chol” dataset and make a histogram it
    qplot(chol$AGE , geom = “histogram”)
    ggplot(data-chol, aes(chol$AGE)) + geom_histogram()

    You should be able to see the visual output like this.

    Histogram

  4. Next, execute the following pieces of R code to find out the binwidth argument using the ‘qplot()‘ function:
  5. qplot(chol$AGE,
    geom = “histogram”,
    binwidth = 0.5)

    qplot.JPG

  6. Lets get some help from the hist() function in R:
  7. #Lets take help from hist() function
    qplot(chol$AGE,
    geom=”histogram”,
    binwidth = 0.5,
    main = “Histogram for Age”,
    xlab = “Age”,
    fill=I(“blue”))

    hist.JPG

  8. Now, add an I() function for nested colors:
  9. #Add col argument, I() function where nested color.
    qplot(chol$AGE,
    geom=”histogram”,
    binwidth = 0.5,
    main = “Histogram for Age”,
    xlab = “Age”,
    fill=I(“blue”),
    col=I(“red”))

    I func.JPG

  10. Next, adjust ggplot2 a little by using the following code:
  11. #Adjusting ggplot
    ggplot(data=chol, aes(chol$AGE)) +
    geom_histogram(breaks=seq(20, 50, by = 2),
    col=”red”,
    fill=”green”,
    alpha = .2) +
    labs(title=”Histogram for Age”) +
    labs(x=”Age”, y=”Count”) +
    xlim(c(18,52)) +
    ylim(c(0,30))

    adjustggplot

  12. Plot a bar graph with the following code:
  13. #Plotting Bar Graph
    qplot(chol$AGE,
    geom=”bar”,
    binwidth = 0.5,
    main = “Bar Graph for Mort”,
    xlab = “Mort”,
    fill=I(“Red”))

    bargraph.JPG

  14. Next, open the PowerBI desktop tool. You can download it for free from this link. Now, click on the Get Data tab to start exploring and connect with an R dataset. Rscript.JPG
  15. If you already have R installed on the same system as PowerBI, you just need to paste the R scripts in the code pen. Otherwise you need to install R in the system where you are using the PowerBI desktop like this:

    Rexe

  16. Next, you can also choose the ‘custom R visual’ in PowerBI desktop visualizations and provide the required R scripts to build visuals and finally click ‘Run’.
  17. RPBI.JPG

  18. Build all the R function visuals by following the same steps and save the dashboard.
  19. Dashboard

  20. You can refresh an R script in Power BI Desktop. When you refresh an R script, Power BI Desktop runs the R script again in the Power BI Desktop environment.

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Topics:
r ,powerbi ,analytics ,big data ,data visualization

Published at DZone with permission of Anindita Basak, DZone MVB. See the original article here.

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