Microsoft In these days has reIeased an interesting paper about using R to preparing Data.

In this paper, they’ll demonstrate some of the things that can go wrong with data, and explore ways to address those issues using the R statistical language (https://cran.r-project.org/) before going on to analysis.

For faster numerical libraries, allte the paper is based on the Microsoft R Open distribution (https://mran.microsoft.com/open/).

The idealized goal in mind is using machine learning to build a predictive model.

In the paper that can be found on this link you cand ofund information about:

• Loading Data
• Shaping Data
• Variable type
• Check for bad or missing value
• Dealing with missing values (NA)
• Categorical variables with too many levels or with rare levels

Read it is very interesting!