Need to get count of customer visit in a particular date range

Hi Team,

I am new to KNIME, trying to drive a column based on certain condition and would require experts advice on how to do it in KNIME.

I have a table which includes a list of customer’s phone number (indication that those are unique customer who had placed order) and date of order placed. I am trying to create additional columns like how many times a customer has placed an order in a specified time interval i.e. on weekly, monthly, quarterly and annually (on the basis of current date).

Can someone please guide me whether this is possible to be calculated?

Dataset would look like :

Dataset

Output result required ;

image

Please let know for further clarification required on my query.

Regards,
PKR

See workflow below. It provides an interactive set of tables for each phone number. Its not exactly the format you want, but frankly I don’t know how you would format it since there are 52 weeks, 12 months and 4 quarters in each year. You can use the search bar to search for specific phone numbers, weeks and months. Note if you use more than one calendar year, the workflow will count weeks, months and quarters across years.

Hi rfeigel,

Thanks a lot for putting time and efforts in building a solution for my request!!

I did review your result, it was very helpful. However, I perhaps should have mentioned my output columns as slightly different as follows;

image

I was not actually looking for the output for every week from the calendar, but still your solution had given me some idea to think little different and I carried out a different solution.

I was able to get the result that I was looking for but using “Date&Time Based Row Filter” Node and arranged it in the following manner.

Customer Grouping By Date.knwf (40.4 KB)

Please review and let me know if there is any other better way in doing the same process.

Note: The values in the table maybe slightly incorrect as the I had to duplicate the date column in the beginning to perform the grouping.

Regards,
Prem Kumar R