Ellis Hughes and I finish up part 2 about lists. In this episode we explain how to do a number of statistical processes across list elements (summary statistics by group, regression models by group, correlation coefficients by group) and then wrap up by showing how to use lists to build a multi-page PDF report where each page represents the contents of one list element.
To watch our screen cast, CLICK HERE.
To access our code, CLICK HERE.
This week, Ellis Hughes and I discuss a very important and useful object in R, lists. Lists are critical to know about because of their versatility for storing any type of data formats and their ability to handle lots of data tasks very quickly.
In this first part on lists we discuss how to create a list, access the contents within a list, show their versatility, and walk through examples of how to iterate over lists with for loops and base R functions such as lapply.
To watch out screen cast, CLICK HERE.
To access our code, CLICK HERE.
This week, Eliis Hughes and I discuss factor variables, which are basically a numeric storage form of categorical variables that can be either unordered or ordered, depending on how you specify them. These variables are common to R (and other coding languages) as they use minimal memory for storage. We discuss what factors are, how to specify them, how to change levels of factors, and how they behave in regression models and when plotting data.
To watch our screen cast, CLICK HERE.
To access our code, CLICK HERE.
This week, Ellis and I continue our work from the last episode, where we talked about date objects, and discuss the building blocks of data science in R: vectors, matrices, and data frames. These are objects that we have used in every single one of the previous 104 episodes and this week we break them down and discuss what they are and how they function.
To watch our screen cast, CLICK HERE.
To access the code, CLICK HERE.
This week, Ellis Hughes and I discuss date objects in R, which can be rather confusing. We talk about what is under the hood of a date object, how to specify them, how to parse them, and how to calculate the difference between them.
If you work with any timestamped data (e.g., GPS, Accelerometer, Force Plate, etc.) this is going to be an episode that you will want to check out as dealing with those pesky date/time columns can be tricky!
To watch the screen cast, CLICK HERE.
To access our code, CLICK HERE.