Principal component analysis (PCA) PCA is a dimension reduction techniques. So, if we have a large number of predictors, instead of using all the predictors for modelling or other analysis, we can compressed all the information from the variables and create a new set of variables.
In a couple of days, I am going to conduct a pre-conference workshop for Malaysian R conference 2021. So, some of the data that I am going to use for this workshop is available in a table in pdf form.
These are some of the packages that I find useful for data exploration. Basically, this post serves more as my note for future reference. I will list out packages (and some awesome functions from that particular package) rather than specific functions.