Last updated on July 5th, 2020 at 06:15 pm
R is a programming language and the environment which is used in the case of statistical computing, data analytics, and the research. It is termed as one of the most popular languages that are commonly used by the statisticians, researchers, data analysts, and the marketers to retrieve, clean, analyse, visualise and to present the data. Because of its communicative syntax and easy-to-use interface method, it has fully grown in popularity in the recent years. Codes in R are far more compact as compared to the SAS. However, it makes the language tougher to retain all the syntax. You may probably need plenty of practice to get the hang of it. This makes some of the interview questions on R tricky and thus handling them becomes overwhelming for a few candidates. And, I strongly feel a desire for a common thread which should have all the tricky R queries asked in interviews. So that is why this article has come up with some of the Tricky R interview questions that are inevitably going to guide you towards the success.
Also Read: Advantages Of R Programming Language
1) Explain the data import in R language.
R provides an option to import data in R language. To start with the R commander user interface, the user should type the commands within the command R commander into the console. Then, data is imported in R language in the three ways such as –
Select the data set within the window or enter the name of the data set as required.
Data can be easily entered directly by using the editor of R Commander via data -> New Data Set. This works well only if the data set is not significant.
Data can also be imported from a URL or the open document (ASCII), or from any statistical package or the clipboard.
2) In R how will you be able to import Data?
You can easily import data by using R commander to import data in R, and there are three ways through that you can use to enter data into it.
- New dataset. – You can enter data directly via data
- Import data from plain text (ASCII) or the alternative files (SPSS, Minitab, etc.)
- Read a dataset either by writing the name of the data set or by choosing the data set within the window.
3) What are the data structures in R that's used to perform statistical analyses and build graphs?
R has data structures like the –
- Vectors – A vector can easily be defined as a set of sequence of data elements of the same basic type. Here is an example of the vector containing three numeric values 2, 3 and 5. (2, 3, 5)
- Matrices – A matrix is an assortment of data elements organised in a two-dimensional rectangular layout.
- Arrays – Arrays are the type of R data objects or say elements of the same data types which can easily store the data in more than two dimensions. Arrays can store only data type. An array is created using the array () function.
- Data frames – A data frame can be defined in the form of a table or the two-dimensional array-like structure in which every column contains values of 1 variable {and every} row contains one set of values from each of the column.
4) Mention what doesn't ‘R’ language do?
- Though R programming can easily connect to DBMS isn't a database, we can not claim R as a graphical user interface as it doesn’t consist any
- Though it relates to Excel/Microsoft Office easily, R language does not offer any spreadsheet view of the data.
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