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Analyze additions and subtractions to/from a data set

0

$begingroup$

I have a data set in the following form:

Product | Date
123 | 2019-01-01
456 | 2019-01-01
123 | 2019-01-02
123 | 2019-01-03
456 | 2019-01-03
123 | 2019-01-04
456 | 2019-01-04
789 | 2019-01-04

This is just a simplified version. The full set has ~300 products and four months of data. I want to understand how the product set changed over time. It's obviously easy to calculate the count per day and see that I lost one product on Jan 2nd and gained one on Jan4th, but then I don't know what product it was.

Is there a more systematic way of going about this? Ideally the output would show me a list of days and what products dropped out / were added that day. I thought about min(date), max(date) by product before, but products can drop and be added repeatedly and I wouldn't capture this back and forth this way.

Available environments are Python, SQL, and Excel.

Thanks

python sql excel

share|improve this question

asked Apr 5 at 19:12

BerbatovBerbatov

11

$endgroup$

add a comment | 

0

$begingroup$

I have a data set in the following form:

Product | Date
123 | 2019-01-01
456 | 2019-01-01
123 | 2019-01-02
123 | 2019-01-03
456 | 2019-01-03
123 | 2019-01-04
456 | 2019-01-04
789 | 2019-01-04

This is just a simplified version. The full set has ~300 products and four months of data. I want to understand how the product set changed over time. It's obviously easy to calculate the count per day and see that I lost one product on Jan 2nd and gained one on Jan4th, but then I don't know what product it was.

Is there a more systematic way of going about this? Ideally the output would show me a list of days and what products dropped out / were added that day. I thought about min(date), max(date) by product before, but products can drop and be added repeatedly and I wouldn't capture this back and forth this way.

Available environments are Python, SQL, and Excel.

Thanks

python sql excel

share|improve this question

asked Apr 5 at 19:12

BerbatovBerbatov

11

$endgroup$

add a comment | 

$begingroup$

I have a data set in the following form:

Product | Date
123 | 2019-01-01
456 | 2019-01-01
123 | 2019-01-02
123 | 2019-01-03
456 | 2019-01-03
123 | 2019-01-04
456 | 2019-01-04
789 | 2019-01-04

This is just a simplified version. The full set has ~300 products and four months of data. I want to understand how the product set changed over time. It's obviously easy to calculate the count per day and see that I lost one product on Jan 2nd and gained one on Jan4th, but then I don't know what product it was.

Is there a more systematic way of going about this? Ideally the output would show me a list of days and what products dropped out / were added that day. I thought about min(date), max(date) by product before, but products can drop and be added repeatedly and I wouldn't capture this back and forth this way.

Available environments are Python, SQL, and Excel.

Thanks

python sql excel

share|improve this question

asked Apr 5 at 19:12

BerbatovBerbatov

11

$endgroup$

Product | Date
123 | 2019-01-01
456 | 2019-01-01
123 | 2019-01-02
123 | 2019-01-03
456 | 2019-01-03
123 | 2019-01-04
456 | 2019-01-04
789 | 2019-01-04

share|improve this question

asked Apr 5 at 19:12

BerbatovBerbatov

11

share|improve this question

asked Apr 5 at 19:12

BerbatovBerbatov

11

asked Apr 5 at 19:12

BerbatovBerbatov

11

asked Apr 5 at 19:12

BerbatovBerbatov

11