* [WiP] [explore] proper filtering of NULLs and ''
TODO: handling of Druid equivalents
* Unit tests
* Some refactoring
* [druid] fix 'Unorderable types' when col has nuls
Error "unorderable types: str() < int()" occurs when grouping by a
numerical Druid colummn that contains null values.
* druid/pydruid returns strings in the datafram with NAs for nulls
* Superset has custom logic around get_fillna_for_col that fills in the
NULLs based on declared column type (FLOAT here), so now we have a mixed
bag of type in the series
* pandas chokes on pivot_table or groupby operations as it cannot sorts
mixed types
The approach here is to stringify and fillna('<NULL>') to get a
consistent series.
* typo
* Fix druid_func tests
* Addressing more comments
* last touches
* Allowing limit ordering by post-aggregation metrics
* don't overwrite og dictionaries
* update tests
* python3 compat
* code review comments, add tests, implement it in groupby as well
* python 3 compat for unittest
* more self
* Throw exception when get aggregations is called with postaggs
* Treat adhoc metrics as another aggregation
Before this PR the only way to query lat/long is in the shape of 2
columns that contains lat and long.
Now we're adding 2 more options:
* a single column that has lat and long with a delimiter in between
* support for geohashes - geohashes are cool