Go to TogaWare.com Home Page. Data Science Desktop Survival Guide
by Graham Williams
Duck Duck Go



20180723 On ingesting the dataset into R we observe the variables identified (automatically) as having character base::class(). The expected values for such variables are strings of characters. We often call such variables categoric variables. Within R these are usually represented as a data type called factor and handled specially by many of the modelling algorithms.

We can observe some meta data for each of the character variables. Let's first identify the character variables.

# Identify the character variables by index.

ds %>%
  sapply(is.character) %>%
  which() %T>%
  print() ->
## location 
##        2

# Identify the chracter variables by name.

ds %>%
  names() %>%
  '['(chari) %T>%
  print() ->
## [1] "location"

We will review each one of these in more detail so as to understand how we make use of them in our analyses. In particular we consider which of the variables might be handled as factors.

Where a character variable takes on a limited number of possible values we might convert the variable from character into factor (categoric) so as to take advantage of special handling of factors in R.

In fact, we think of a factor as a variable that can only take on a specific number of known distinct values which we call the levels of the factor.

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