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1. Re: Vintage curve Analysis in Tableau
Norbert MaijoorNov 10, 2017 4:34 AM (in response to Lihos G)
Hi Lihos,
Could you share a workbook in .tbwx format?
Regards,
Norbert
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2. Re: Vintage curve Analysis in Tableau
Lihos G Nov 13, 2017 10:52 PM (in response to Norbert Maijoor)I have attached my workbook to the original post.
Thanks
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3. Re: Vintage curve Analysis in Tableau
Norbert MaijoorNov 14, 2017 2:11 AM (in response to Lihos G)
Hi Lihos,
Upfront it'' not final but an initial setup;) Find my approach as reference and stored in attached workbook version 10.3 located in the original thread.
1. Pivoted the datasource
1. D1. Monthnotation: mid([Month],1,3)
2. D2. Month convert:
if [D1. Monthnotation]="JAN" then 1
elseif [D1. Monthnotation]="FEB" then 2
elseif [D1. Monthnotation]="MAR" then 3
elseif [D1. Monthnotation]="APR" then 4
elseif [D1. Monthnotation]="MAY" then 5
elseif [D1. Monthnotation]="JUN" then 6
elseif [D1. Monthnotation]="JUL" then 7
elseif [D1. Monthnotation]="AUG" then 8
elseif [D1. Monthnotation]="SEP" then 9
elseif [D1. Monthnotation]="OCT" then 10
elseif [D1. Monthnotation]="NOV" then 11
elseif [D1. Monthnotation]="DEC" then 12
END //PS did could be done more efficiently;)
3. D3 Year: int("20"+str(mid([Month],5,2)))
4. D4. Date: MAKEDATE([D3. Year],[D2. Month convert],1)
5. D5. Dateadd: dateadd('year',1,[D4. Date])
6. Drag required objects to the indicated locations.
Please validate and look forward to receive your feedback.
Regards,
Norbert
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4. Re: Vintage curve Analysis in Tableau
Lihos G Nov 20, 2017 11:21 PM (in response to Norbert Maijoor)Hey Nobert,
It works like a charm. Thanks for helping me out.
Though the Calculated field 'M1. Divided by Disbursal Month' didn't gave the Correct Values.
so I created three different Calculated fields 'sumOfDisbursalAmt'
, 'sumPivotFields'
and 'VintagePercentage'
which did the trick.
Now only concern is, How can I limit each row to a particular month(logic of which I explained in the Original Post).
I am writing it here Again: We have to consider only those columns which has all the values (no blanks). Yellow colored values are to be considered.
For Example: for FY 2014 we will use column 1 to 42, since Data is up to Sept 2017(FY2018) so for FY2014 (March is the last month for each financial year) March of FY2014 to Sept FY2018 is 42 months. Similarly for FY2015 : March of FY2015 to Sept of FY2018 is 30 months, so for FY2015 consider columns from 1 to 30. So on and so forth..
In Other words, For Each Financial Year, we have to select that Month Column, where all the Loans that originated in a particular Financial Year has Values ignore Rest.