-
Book Overview & Buying
-
Table Of Contents
Mastering Data analysis with R
By :
Although some filtering algorithms were already discussed in the previous chapters, the dplyr package contains some magic features that have not yet been covered and are worth mentioning here. As we all know by this time, the
subset function in base, or the filter function from dplyr is used for filtering rows, and the
select function can be used to choose a subset of columns.
The function filtering rows usually takes an R expression, which returns the IDs of the rows to drop, similar to the which function. On the other hand, providing such R expressions to describe column names is often more problematic for the select function; it's harder if not impossible to evaluate R expressions on column names.
The dplyr package provides some useful functions to select some columns of the data, based on column name patterns. For example, we can keep only the variables ending with the string, delay:
> library(dplyr) > library(hflights) > str(select(hflights...
Change the font size
Change margin width
Change background colour