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Hands-On Data Science with R

You're reading from   Hands-On Data Science with R Techniques to perform data manipulation and mining to build smart analytical models using R

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Product type Paperback
Published in Nov 2018
Publisher Packt
ISBN-13 9781789139402
Length 420 pages
Edition 1st Edition
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Authors (4):
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Nataraj Dasgupta Nataraj Dasgupta
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Nataraj Dasgupta
Vitor Bianchi Lanzetta Vitor Bianchi Lanzetta
Author Profile Icon Vitor Bianchi Lanzetta
Vitor Bianchi Lanzetta
Doug Ortiz Doug Ortiz
Author Profile Icon Doug Ortiz
Doug Ortiz
Ricardo Anjoleto Farias Ricardo Anjoleto Farias
Author Profile Icon Ricardo Anjoleto Farias
Ricardo Anjoleto Farias
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Table of Contents (16) Chapters Close

Preface 1. Getting Started with Data Science and R FREE CHAPTER 2. Descriptive and Inferential Statistics 3. Data Wrangling with R 4. KDD, Data Mining, and Text Mining 5. Data Analysis with R 6. Machine Learning with R 7. Forecasting and ML App with R 8. Neural Networks and Deep Learning 9. Markovian in R 10. Visualizing Data 11. Going to Production with R 12. Large Scale Data Analytics with Hadoop 13. R on Cloud 14. The Road Ahead 15. Other Books You May Enjoy

Spark DataFrames within the RStudio IDE

Another simple way to start your Spark connections and browse your datasets is with the RStudio IDE. After you've installed the sparklyr package, it'll appear in the top-right part of your RStudio window, close to your R environment. If you aren't connected to Spark, it'll look like the following screenshot. If you are connected, call spark_disconnect_all() before continuing, so we'll be on the same page:

Figure 12.1: Spark shown in RStudio IDE

Click on the left arrow to see all connections, then click on the new connection button to establish a connection. A window will pop up where you can connect and manage Spark only with clicks:

Figure 12.2: Spark connection guide from RStudio IDE

Once you upload a DataFrame into your Spark connection, you can browse it by selecting the file shown here, just as you are used...

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