openintro | 📦 R package for data and supplemental functions | Data Visualization library

I need to load the dataframe teacher from library "openintro".

Then, I need to provide descriptive statistics, i.e. an appropriate numerical description for the variables degree, fte, years, retirement with some graphs.

What I understand from the task is that I need to check the base salary with every variable. so. I started to find an average salary for BA degrees and then for MA.

I would like to apply different linetype models on timeseries plot. Here is a reproducible example using a structure similar to my data/code. Let's say I want solid line for woman and dotted line for men.

I am trying to visualize two parallel planes in a 3D plot with the plotly package (for those that have access to Datacamp, it is this exercise: https://campus.datacamp.com/courses/multiple-and-logistic-regression/multiple-regression?ex=9)

At some point in the construction of this graph, you need to create a matrix to fit the planes that match the categorical variable (plane_new = condition is new, plane_used = condition is used). The problem is, that the two datasets that I used as input (corresponding to the two levels of condition), have different number of observations. I can't seem to figure out how I can get these matrices to be comparable, so that the planes are correctly fit as geometrical objects in the figure.

I hope an R-wizard can help me out ;). Here's my code: