With the Coalesce columns function, you can easily
retrieve the first non null value across different columns to consolidate their data
into a new column.
In this example, you are working on a dataset that contains information about your
customers, including the different phone numbers at which you can reach them: office,
mobile or home number. You can notice that some values are empty. Because you do not
necessarily need to have 3 columns with similar information in your dataset, you can
choose to create a new one containing only one phone number for each row, and make sure
that the empty values are replaced with usable information at the same time. Here, you
want to prioritize the mobile phone numbers, and retrieve the office or home number as
backup.
Procedure
-
To prioritize the mobile phone number over the other numbers,
drag the phone_mobile column header and
drop it left of the phone_office
column.
The columns are now ordered as following:
-
Use
Ctrl +
click
or
Shift + click
to select the
headers of the three columns containing phone numbers.
-
In the Functions panel,
type Coalesce columns and click the
result to display the options of the associated function.
-
In the Direction
drop-down list, select Left to
right.
With the column order that you have set up, the function will
start by reading the phone_mobile column,
and will replace any empty value by the next non empty on its right.
-
Leave the default setting for the Values containing only non-printing characters drop-down list,
namely Consider empty.
-
Click Submit.
Results
A new consolidated column is created, where the missing mobile
phone numbers are replaced by the values of the next columns. You can now delete the
three source columns to only keep the new one, and rename it with a meaningful name if
you want.