Challenge Overview
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The purpose of this challenge is to make our community members to get hands on with R and R Studio (IDE for R)
Introduction
R is an open source environment mainly used for statistical analysis and visualizations. R can also be used to create command line processors, REST APIs, even interactive web dashboards using packages developed by community members.
We are launching this fun challenge to introduce you to R, so that you can make yourself comfortable for the upcoming challenges on R.
R is a very simple programming language and learning R is extremely easy. Are you guys ready to rock and learn? Let’s jump in to the requirements!
Important Note
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This is a fun challenge. No prize money will be awarded for completing this challenge successfully.
- 25 T-shirts will be given randomly to the submitters who make a successful submission.
Challenge Requirements
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In this challenge, we will be creating a simple analyzer which will analyse data from the given set of files and generate statistical summary with supporting graphs
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You will be provided with a starter pack in which you will fill the missing pieces of code to make it a complete analyzer
Dataset
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We will be using the public dataset about fuel economy for this fun challenge. Subset of the above dataset is provided as part of the starter pack.
What will you learn?
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How to setup R and R Studio
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How to read files in R
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What is dataset and how to create a dataset from the input files
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How to do basic data analysis on the given dataset
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How to generate meaningful charts from the given dataset
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How to use packages dplyr and ggplot2
Learning Steps
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Download and Install R and R Studio. Installation instructions will vary according to your operating system. If you face any issues while installing R or R studio, please let us know in the forums, we are here to help. R studio serves as an IDE for R.
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Download the starter pack from forum
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Learn the basic concepts of R
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The starter pack code can be run from command line using the command `Rscript analyzer.R` from the root of the project.
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Fill the missing pieces of code in analyzer.R and read.R, so that the analyzer is complete and expected output files are generated in `output` directory
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After running `Rscript analyzer.R`, It should print the todo statement and print it’s corresponding output. The generated charts should be saved to the output directory as PNG or JPEG files.
E.g. TODO - Print first 20 rows of the dataset. You will be writing code like
print(“Print 20 rows of the dataset”)
head(dataset, 20)
Final Submission Guidelines
- After filling the missing pieces of code in the starter pack, zip your code and submit the zip file using the submit link in the challenge.