R Tutorial: Understanding your qualitative variables

Key Takeaways

in this lesson we'll introduce our dataset look at converting and understanding our qualitative variables and learn some new deep higher functions in the previous exercise we were working with a data set called multiple-choice responses this is a sample of data from the kaggle 2017 data science survey Kaggle is an online platform for predictive modeling and analytics competitions this survey was given to current and aspiring data scientists analysts data engineers and others in the data science field they got about 16,000 responses on questions ranging from demographic information to the usefulness of different learning platforms to what languages they wanted to use in the coming year we'll be using this data set throughout the course just like with numerical variables our first step when looking at categorical variables should be to get a high level summary instead of numerical summaries like the mean and standard deviation we can look at the number of categories and the name of each but as we saw when examining our dataset currently some of the variables are characters not factors how can we change this first we need to identify which columns are characters we can use is dot character for this next we can use the function as dot factor to change columns from characters to factors if we want to do this for all character columns we can take advantage of D Pires mutate if function this function takes two arguments the first needs to be a function that returns true or false mutate if we'll check each column to see if that condition is true and if so we'll change the column based on the second argument once our columns are factors we want to find out more about each one we can use two functions and levels and levels and level we'll give us a number of levels of a factor and levels will give us their names what if we want to scale up and check the number of levels for all factor columns in a data set you've probably used deep liars summarized before to take summary information like the mean of a single column if we want to apply a summary function meaning one that returns a single number to all columns that meet a certain condition we can use deep liars summarize if this works just like mutate if we first check if the column is a factor and if it is get the number of levels time to put this into practice