Oftentimes we wish to select columns, not by explicitly spelling out their names or positions, but by criteria satisfied
by the desired columns. The three most common scenarios are:
Name Pattern where we cover how to select columns whose names satisfy a
given pattern e.g. select columns with a name that contains the string ‘_id’ .
Data Type where we cover how to select columns of one or more data types e.g.
select columns with a numeric data type.
Data Criteria where we cover how to select columns whose data satisfies a
certain condition e.g. the percentage of missing values is below 10%.
In Multiple Conditions, we cover how to combine multiple
conditions in different ways to realize more complex column selection logic
Implicit column selection works in two steps:
Identification
We write logic that checks which columns of a table satisfy certain conditions returns the names of the columns to be
selected.
Extraction
This output from step 1 is then passed to the selection operator SELECT to carry out the extraction of columns from
the original table.