NYAMS SPEAKS

The functions and packages described below are not limited to the use cases discussed in this post. Some can be found in more than one package and can be applied in more than one way.  I use the iris dataset for the examples. It has 150 rows and 5 columns namely: Sepal.Length, Sepal.Width, Petal.Length, Petal.Width and Species  The pipe operator ( %>%) This function can be found in the dplyr package. It is one of those functions you learn earlier on when you start doing a lot of visualization and deep dive exploratory analyses. I envision it as a funnel to sift your bulk data through till you are left with what you want. While on the same package, there are some functions that are worth mentioning ends_with/starts_with : useful in selecting specific columns to keep based on pattern summarise : In most cases this should return a one row summary and is most useful after grouping data. Example (for the pipe function and the first two complimentary functions) iri...

A Short Back story I am an MSc mathematics graduate who took lots of applied statistics classes.  I have a BSc Actuarial Science undergraduate degree too. The two courses sort of set me up on this path and that is how I found myself as an intern in the Enterprise Data & Analytics department of a hospital immediately after graduation. Now onto the list: The healthcare lingo will throw you off! For someone who has never liked being sick and thankfully has a very limited number of interactions with hospital personnel, there were some words that caught me off-guard from the first day at orientation. I mean "my doctor" worked pretty fine but I have to refer to them as "PCP - primary care provider". All the other physicians I called "the doctor". (My doctor : the doctor).  The first project requirements were given to me in this lingo too and I did not want to ask a question after each sentence because that would have turned out to be a lengthy conversation. ...