Good morning,
I am facing a problem very easy to solve with a program, but not too
easy (at least IMHO) with a "declarative" approach.
I have a dataframe df with some information about bank branches with a
validity time associated (start date/end date, format YYYY-MM-DD) to
some attributes (for example number of employees assigned).
The following example will clarify this description:
BANK_ID BRANCH_ID EMPLOYEE # STARTDATE ENDDATE
B1 A15 30 2001-01-01 2001-10-15
B1 A15 28 2001-10-16 2001-12-31
B1 A15 32 2002-01-01 2003-04-18
B1 A15 33 2003-04-19 2004-12-31
B1 A15 29 2005-03-01 2010-12-31
B1 A15 30 2011-02-12 9999-12-31
........................................................................
........................................................................
.....................
I would like to find the "missing time intervals" ("holes" - in the
example 2005-01-01 to 2005-02-28 and from 2011-01-01 to 2011-02-11).
The "programmer's way" would be:
* Sort the data by "key" + start date
* For each occurrence add 1 day to end date and compare the
result with the start date of the following occurrence
Can someone help me in finding a "declarative" way to do it ?
Thank you in advance
Angelo Linardi
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