Variable options for empty levels within factor

[myjulo]

Hi there,

I recently started using your dataMeta package. I noticed that when variable options are generated with the build_dict function, that no variable options are generated for empty levels within factor variables. It would be very useful if it would do so, as when preparing datasets to share with collaborating groups. Often variables are designed to have levels that are only applicable to a specific collaborator.

I'm sorry if it is just my novelty to the package and I'm overseeing an option in the build_dict function, but if it is not yet incorporated I think many people would find it useful if variable options are also generated for unused factor levels.

Many thanks!

[dmrodz]

Hello, Try changing from factor to character since factors will naturally exclude empty levels. This will incorporate all of the options available. Once your dictionary is built, you can remove any levels or mask them for your specific data sharing purposes before appending to the source dataset (or alternatively consider generating a dictionary for each specific collaborator, given each dataset). Thanks, Dania M. Rodriguez https://github.com/dmrodz https://www.linkedin.com/in/dmrodz

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On Thu, Jul 23, 2020, 15:41 myjulo ***@***.***> wrote: Hi there, I recently started using your dataMeta package. I noticed that when variable options are generated with the build_dict function, that no variable options are generated for empty levels within factor variables. It would be very useful if it would do so, as when preparing datasets to share with collaborating groups. Often variables are designed to have levels that are only applicable to a specific collaborator. I'm sorry if it is just my novelty to the package and I'm overseeing an option in the build_dict function, but if it is not yet incorporated I think many people would find it useful if variable options are also generated for unused factor levels. Many thanks! — You are receiving this because you are subscribed to this thread. Reply to this email directly, view it on GitHub <#10>, or unsubscribe <https://github.com/notifications/unsubscribe-auth/AB2ZIBA4M2V6JQJFQE6NDGDR5CG6PANCNFSM4PGBSHNA> .

[myjulo]

Hi Diana,

Thank you for the quick response. I tried to change all the factor variables to characters, but that didn't do it unfortunately. Because certain values are not existing in the dataset yet, it is also excluding them when converting to character variables, right?

The way I worked around it is to add a couple of rows that contain the factor levels that I need incorporated. I build the dictionary and then remove those specific rows again.

[dmrodz]

Aah, I see what you mean. I'll look into this and get back to you. In the meantime, it will build the dictionary with the available data values from the source dataset. Then you would need to add any additional values not yet used in separate (like you already did). This can be fixed by adding an option to include 'not currently used' data values while making the linker. More soon and thanks for bringing this up!! Dania M. Rodriguez https://github.com/dmrodz https://www.linkedin.com/in/dmrodz

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On Thu, Jul 23, 2020, 20:54 myjulo ***@***.***> wrote: Hi Diana, Thank you for the quick response. I tried to change all the factor variables to characters, but that didn't do it unfortunately. Because certain values are not existing in the dataset yet, it is also excluding them when converting to character variables, right? The way I worked around it is to add a couple of rows that contain the factor levels that I need incorporated. I build the dictionary and then remove those specific rows again. — You are receiving this because you modified the open/close state. Reply to this email directly, view it on GitHub <#10 (comment)>, or unsubscribe <https://github.com/notifications/unsubscribe-auth/AB2ZIBBF72UJVU4XDEVOSSLR5DLTJANCNFSM4PGBSHNA> .

[myjulo]

Great! I look forward seeing the updates! Thank you!

[dmrodz]

Reopening to edit next in queue