Evaluate data quality of various attributes #30
Description
Consider expanding or dropping (more likely) certain characteristics for which data is unreliable or null.
For example "leaf" column contains majority null values. First check that this isn't a code issue, and if not, consider the usefulness of the data. Could prove to be valuable information even if just 10% of entries have it. In which case we could ask for user feedback to fill data.
Also consider possible categories for useful future data. The more (reliable) data the better!
As we continue to scrape from other sources like permapeople, pomiferous, etc..., we'll find many characteristics of one database are undefined in the other. Discuss and evaluate how to combine databases.