Week 2: Plots, tapply and data frames
examples of plots
R has powerful graphical capabilities, which can be easy to use:
R code or the
video of some example plots
introduction/definitions
We define factors, levels, and data frames, using the CO2 (Carbon Dioxide Uptake in Grass Plants) built-in R example:
R code or the
video about these definitions
introduction to tapply
We continue to use the CO2 data set, and we introduce the tapply function:
R code or the
video about tapply
more about tapply
We continue to explore tapply using the iris data; we group a vector of numerical values to create a factor:
R code or the
video with iris example
using tapply with dice
We give an example with dice, using the tapply function:
R code or the
video with dice example
using tapply with geyser data
We give an example with the geyser data, using the tapply function;
again we turn a vector of integers into a factor, using grouping:
R code or the
video with geyser data
using tapply with the length function, and with mtcars data
We use the mtcars data to showcase the use of the length function in the tapply (just like the table function):
R code or the
video with mtcars data
using tapply with the na.rm=T parameter
We use the airquality data set to deal with NA values in the tapply:
R code or the
video with airquality data
exploring data from the Columbia River Estuary
The Center for Coastal Margin Observation and Predication makes a great deal of data publicly available; we use it to explore importing and exporting data:
You will need to download the csv file and save it in your directory.
R code or the
video with CMOP data
further exploring the data from the Columbia River Estuary
We continue to explore CMOP's data, including a brief explore of finding and dealing with an outlier in a large data set:
R code or the
another video with CMOP data