This section and category includes mainly intermediate and more advanced techniques for R data analysis. It specially involve R mathematical functions, R Statistical functions, Probability functions in R, and R Character functions. Apply function as well as in this family, descriptive statistics, and table function family are talked about in this section too. We will also focus on how to write your own functions in R, and how to use control flow. In addition, some frequently used techniques such as reshaping, aggregating dataset are introduced.
We provide effective and economically affordable online training courses for R and Python, click here for more details and course registration ! When we have a data set on hand, the first step of data analysis is usually drawing descriptive statistics. The most common descriptive statistics for numerical variables are Read more…
We provide effective and economically affordable online training courses for R and Python, click here for more details and course registration ! In this post, we list some of the most common mathematical functions in R. abs() – compute absolute value of a numerical input. sqrt() – compute square root Read more…
We provide effective and economically affordable training courses for R and Python, click here for more details and course registration ! apply() function in R programming is used to perform a specified function, either a R base installation function or an user-written function, to the rows or columns of a Read more…
We provide effective and economically affordable training courses for R and Python, click here for more details and course registration ! R provides rich availability of using probability functions. Probability functions in R takes the form [dpqr][prob], Where [dpqr] represent which kind of variates the function works on d – Read more…
We provide effective and economically affordable training courses for R and Python, click here for more details and course registration ! When a data frame is created in R, usually parts of it will be used later. Subset of the dataset, either by row or by column, or both can Read more…
We provide effective and economically affordable training courses for R and Python, click here for more details and course registration ! sample() function in R selects random samples from a given population. The population can be all elements of a vector, observations of a data frame, etc. For example, in Read more…
We provide effective and economically affordable training courses for R and Python, click here for more details and course registration ! S3 class system is the most used R object oriented programming mechanism. The calling of ‘S3’ comes from the third version of S, which is the ancestor of R Read more…
We provide effective and economically affordable training courses for R and Python, click here for more details and course registration ! R’s environment system behaves as a hierarchical folder system where objects in an R session are located. So when a R session is started, and with several objects created, Read more…
In R programming, function aggregate() provides an easy way to calculate summary statistics of variables by specific groups in a data frame.
dplyr is a package that belongs to tidyverse framework. dplyr allows usage of pipeline structure (%>%), which can chain multiple functions together into one statement to make data management more effective. spread() of dplyr is a function that spreads the values of columns from the current data frame, and make them as column labels in the resulting data frame.