ftable() function combines Cross-Tabulation with the ability to format , or “flatten”, contingency tables of 3 or more dimensions.
The resulting tables contain the combined counts of the categorical variables, (also factor variables in R), that are then arranged as a matrix, whose rows and columns correspond to the original data’s rows and columns. The
col.vars, control the format of the table.
Displaying a contingency table in this flat matrix form is often preferable to showing it as a higher-dimensional array. The
read.ftable, functions allow for the saving, and accessing of Contigency Tables of 3 or more dimensions.
Answers to the exercises are available here.
In order to demonstrate the
ftable() function’s capabilities, input the
Titanic data from R:
For the first exercise, create a basic flat contingency table from the Titanic data, using the
row.vars argument specifies the table variables that will format as table rows.
row.vars= is definable with variable numbers, or the variable names.
row.vars= to specify the variable,
Class, as the row variables.
col.vars arguments to specify
Sex as the row variables, and
Survived as the column variable.
col.vars are definable with variable numbers, or the variable names.
With the parameters from the ftable used in Exercise 3, reverse the order of the
Next, using the
ftable() code from Exercise 4, specify
Age as the column variable.
As you can see from this exercise,
ftable() allows for the formatting of data for different areas of inquiry.
data.frame() function will coerce ftable columns into rows. To demonstrate this, place the
ftable() from Exercise 5, within the
ftable.formula provides a formula interface, (a data = . argument), for creating flat contingency tables.
ftable(Survived ~ ., data = Titanic)
Use the formula interface for
ftable() to display the quantities in the
Titanic data for Male/Female passengers, by
ftable() function creates an object of class
ftable. In order to demonstrate this, save the results of the ftable formula from Exercise 7 as an ftable variable called
write.ftable() function, write the ftable,
titanicStats, to a file. Make sure your working directory is set to a folder where you can find the resulting file. Name the file, “table1”.
read.ftable() reads in a flat-like contingency table from a file.
read.ftable(), read the file, “table1”, into an R language environment variable called
Carl Witthoft says
These tables may be complicated, but they are not “complex” : they’re real. That may seem like a nit, but when doing math, one should use mathematical terms.
John Akwei says
Thanks, Carl. The HTML world now refers a lot to “Complex” data tables. There are even courses on Complex Data Tables. Hopefully, Complex vs. Real numbers isn’t suggested.
Complex Data Analysis (here “Complex” is not a math term)
hi,i can not understand that why Exercise 6 is ‘Using the data.frame() function will coerce ftable columns into rows.’.when i saw ,the outcome of exercise 6,i think it is
coerce ftable rows into columns. ==…i feel so sorry for my poor english.
oh ,i see,thank you