Home > Software Courses
Learn R Programming for best career opportunities in business analytics
R is a well-developed, simple and effective programming language which includes conditionals, loops, user defined recursive functions and input and output facilities. R has an effective data handling and storage facility, R provides a suite of operators for calculations on arrays, lists, vectors and matrices.
R Programming Concepts
Data Manipulation in R
Data Import Techniques in R
Exploratory Data Analysis (EDA) using R
Data Visualization in R
ICIT Course Completion Certificate will be awarded upon the completion of the project work (after the expert review) and upon scoring at least 50% marks in the quiz. ICIT certification is well recognized in top MNCs .
R programming training is pursued by working IT professionals who want to enhance their skills in data analysis, statistical analysis, machine learning, data mining.
1) Explain about data import in R language (get solved code examples for hands-on experience)
R Commander is used to import data in R language. To start the R commander GUI, the user must type in the command Rcmdr into the console. There are 3 different ways in which data can be imported in R language-
• Users can select the data set in the dialog box or enter the name of the data set (if they know).
• Data can also be entered directly using the editor of R Commander via Data->New Data Set. However, this works well when the data set is not too large.
• Data can also be imported from a URL or from a plain text file (ASCII), from any other statistical package or from the clipboard.
2) Two vectors X and Y are defined as follows – X <- c(3, 2, 4) and Y <- c(1, 2). What will be output of vector Z that is defined as Z <- X*Y.
In R language when the vectors have different lengths, the multiplication begins with the smaller vector and continues till all the elements in the larger vector have been multiplied.
The output of the above code will be –
Z <- (3, 4, 4)
3) How missing values and impossible values are represented in R language?
NaN (Not a Number) is used to represent impossible values whereas NA (Not Available) is used to represent missing values. The best way to answer this question would be to mention that deleting missing values is not a good idea because the probable cause for missing value could be some problem with data collection or programming or the query. It is good to find the root cause of the missing values and then take necessary steps handle them.
Disclaimer | Privacy Policy | Terms & Conditions