Referring to the table snippet above, each record has five fields for the last five fiscal years. The data will be either the number of that year or zero.
I need to calculate the Burns_5Yrs field based on the count of the number of non-zero years (in fields FY11 - FY15) in that record. The first three rows have examples manually entered. For example, the first record has activity in FY11 and FY14 so the result for Burns_5Yrs should be 2. The second row is also 2 and the third row is 4.
I've been doing this manually but now I have a table with 198 records so I'd like a programming solution, preferably in Python. Any help would be appreciated as I really don't know where to start.
Dave
Pandas was too clunky, so numpy in the field calculator... with pictures
The only thing to remember
- always choose the python parser... and there is no way to set it to default
- write a function... doesn't need to be fancy.
- any imports are done once, so if numpy is already imported, it is only imported once
- the function just contains the variables which will be used. In this example, I used the field names without the ! marks. There is no requirement for the variables to have the same field names
- in the expression box, you put function name (ie 'r') plus the variables to pass. The field names are being passed so enclose them in ! marks.
- save your function for later use if you like
That's all
