Sign up to take part
Registered users can ask their own questions, contribute to discussions, and be part of the Community!
Added on June 1, 2021 9:05PM
Likes: 0
Replies: 3
I have uploaded an excel file , in which a column is just numbers (for example: 1,2,3,4,4a,4b) . However, once I have uploaded the file, in the explore tab, where I can preview the whole dataset, I notice that some cells are highlighted in red.
What does that mean?
@GSung
,
I hope you are doing well. From your description. I'm not exactly sure what you are seeing. I can't remember a time where I get a red highlighting. If the data is not too sensitive can you share a snapshot of what you are seeing?
I see you noted that you were working with numbers. However, when you listed some example values your called out "4a,4b". Unless you are working with Hex numbers rather than Decimal numbers these character sequences don't represent numbers and Dataiku DSS is going to have a hard time representing these as numbers. Initially you will have to treat these as strings and then convert from Hex back to integers or decimal values.
Finally given your description you may be running into a very useful feature to show leading, trailing, and multiple spaces in a field. The thing is that you have to ask for this feature to be turned on. So I don't think this is what you are looking at: You turn this feature on in the Display Menu of a dataset.
When you use this feature you get magenta (purple/pink) highlights in your data fields.
If that does not help. Please share more details, so that someone can help.
Hi,
Red highlighted values mean invalid values based on the inferred meaning (text, integer, decimal, gender, ...)
In your example, DSS would expect a valid value is an integer number so cells with values like 4a are going to be red.
Note you can modify manually the meaning to text if you want to correct it.
Hey @GSung
the red highlighted rows are showing invalid values, ie values not matching a selected meaning.
You can use the Analyze window to explore those more. For more information you can utilize the following resources:
You can also use a Prepare Recipe to Flag invalid rows
I hope this helps!