@pramilamayuren ,
welcome to the Dataiku Community, we are glad to have you join us.
In general one does not manually delete a row in a dataset by highlighting the row and pressing delete. Interactions with data rows is way more like dealing with a database in Dataiku. This is partially because in Dataiku we are trying to create reproducible automated data flows, that gather and update data over time, and not so much one time analysis.
You have not said much in your note about the source of the extra row. So, Iโm going to point to some general ideas here. If you share some more details with the community we might be able to target our responses.
- One of the time I see extra rows is when importing files created by others. Stoping the inclusion of the extra row at the data source would be a good thing for data you repeatedly gather.
- If the situation is like an extra blank row at the top of a dataset imported from a file like MS Excel or CSV. There are options to skip rows in the file import dialog box.
- if this is a one time import of data simply going to the source data and deleting the offending row can be a quick answer. Then import the data without the extra line
- Then we get to filtering in say a visual recipe. (This can be done in many other recipe types as well. There are loads of ways to filter rows.) However in general we have to identify a unique pattern that defines the row we want to filter and none of the others. For example you might filter on a row by it Id number or if a column is blank, orโฆ the options are almost unlimited.
- For small datasets you can convert the dataset to manually editable in Dataiku. And simply select the row and delete it. This only works with relatively small data sets. Over time, this is likely error prone and not an automatically reproducible work flow which is what we are trying to create in Dataiku DSS.
Hope this helps a bit. The Dataiku Academy will show you how to do a bunch of these things Https://academy.Dataiku.com
--Tom
