{"id":345,"date":"2018-09-01T10:42:21","date_gmt":"2018-09-01T05:12:21","guid":{"rendered":"https:\/\/www.techandtrain.com\/blog\/?p=345"},"modified":"2025-10-22T14:55:34","modified_gmt":"2025-10-22T09:25:34","slug":"learning-r-programming-part-1","status":"publish","type":"post","link":"https:\/\/www.techandtrain.com\/blog\/2018\/09\/learning-r-programming-part-1\/","title":{"rendered":"Learning R Programming – Part 1"},"content":{"rendered":"

As per Glassdoor Top 5 skills in Data Science for job openings are:<\/strong><\/p>\n

    \n
  1. Python<\/li>\n
  2. R<\/li>\n
  3. SQL<\/li>\n
  4. Hadoop<\/li>\n
  5. Java<\/li>\n<\/ol>\n

    Most Java developers know SQL, Hadoop & Java to a good extent in today’s environment, two important skills Python & R should be learned by the Java developer \/ architect \/ manager if s\/he wants to contribute \/ work in Data Science area. In this article you will find a structured step by step approach for learning programming in R.<\/p>\n

      \n
    1. To start with install R and familiarize yourself with R Console & R Script interface. You can run commands on both but it’s best to write multiple commands and try them out in script editor. Use short cut CTRL + R to run your commands in R Script editor.<\/li>\n
    2. Explore menu options like Package -> Install \/ Load \/ Choose CRAN Mirror. By default many commands for statistics, visualization, etc. are given in R by default. Big set of libraries are already loaded into R by default and 100s more are available. Select any mirror to download new packages and install \/ load them step by step. You will need working internet connection. Learn how to set working directory. You can see default libraries available in R using library()<\/li>\n
    3. From there move on to various R Objects \/ Data Types – Explore Data Frame, Vector, List, Matrices, Arrays and Factors. Try out examples for the same.<\/li>\n
    4. Next step learn to load \/ read and write datasets by commands like read.csv \/ write.csv. You can also read \/ write excel sheets but for it you will need other packages. See the basic commands like summary, structure & fix to analyze \/ edit your dataset<\/li>\n
    5. Next step – go through various categories of operators (logical, mathematical, relational) and concepts like pipe %>%, constants, rules for naming identifiers followed by various statistical functions directly available in R. You can get help on a command by using ?<COMMAND>. Also, learn to create functions and use conditions like if<\/li>\n
    6. By now you should revise basics of statistics & various visualization charts which are taught typically in Year 1 \/ Semester 1 of MBA. Explore various default commands for statistics built into R by default. Some examples – mean, variance, standard deviation, etc.<\/li>\n
    7. Learn to manipulate \/ read \/ write datasets using subset, sample_n & sample_frac and using dplyr package which has commands like select & filter among others<\/li>\n
    8. Check various types of default visualization commands in R for various charts like barplot & pie. Post this learn how to use ggplot2 package<\/li>\n
    9. You will get many datasets at kaggle.com and various websites like stock exchanges – NSE \/ BSE, RBI, Open Data websites of various Governments and others<\/li>\n
    10. Explore top 20 packages of R categorized by various areas as given below.<\/li>\n<\/ol>\n

      An advantage of learning R is that you will become better at statistics & data science. It’s much simpler than Java in terms of syntax and structure and is influenced by open source languages \/ scripting like Linux, etc.<\/p>\n

      Reach out to me at neil@techandtrain.com<\/a> if you want to discuss R, conduct a training for MBA \/ BE \/ MCA \/ MSc students in R or want to conduct a workshop for your managers \/ executives on Data Science \/ R \/ Java \/ etc.<\/p>\n

      \"\"<\/a><\/p>\n

      References:<\/strong><\/p>\n

      Top 10 skills for Data Science – Glassdoor Economic Research<\/a><\/p>\n

      Top 20 packages in R<\/a><\/p>\n","protected":false},"excerpt":{"rendered":"

      As per Glassdoor Top 5 skills in Data Science for job openings are: Python R SQL Hadoop Java Most Java 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