* Filtering out SQLLab views out of table list view by default
This adds a `is_sqllab_view` flag in the "tables" table, and makes the
filters those out in the Tables list view.
The filter showing on top may be a bit confusing, but certainly less
than seeing lots of user generated views.
* flake
* Addressing comments
The default setting which would look for either `count` first and then
any metric stopped working when we landed MetricsControl. This mimics
the previous behavior
* Fix how the annotation layer interpretes the timestamp string without timezone info; use it as UTC
* [Bug fix] Fixed/Refactored annotation layer code so that non-timeseries annotations are applied based on the updated chart object after adding all data
* [Bug fix] Fixed/Refactored annotation layer code so that non-timeseries annotations are applied based on the updated chart object after adding all data
* Fixed indentation
* Fix the key string value in case series.key is a string
* Fix the key string value in case series.key is a string
* Add ISO duration to time grains
* Use ISO duration
* Remove debugging code
* Add module to yarn.lock
* Remove autolint
* Druid granularity as ISO
* Remove dangling comma
* [sql lab] preserve schema through visualize flow
https://github.com/apache/incubator-superset/pull/4696 got tangled
into refactoring views out of views/core.py and onto views/sql_lab.py
This is the same PR without the refactoring.
* Fix lint
* Disabled run query button if sql query editor is empty
* Removing unnecessary white space
* Fix failing test for sql props
* Adding sql variable into propTypes and defaultProps
* [bugfix] convert metrics to numeric in dataframe
It appears sometimes the dbapi driver and pandas's read_sql fail at
returning the proper numeric types for metrics and they show up as
`object` in the dataframe. This results in "No numeric types to
aggregate" errors when trying to perform aggregations or pivoting in
pandas.
This PR looks for metrics in dataframes that are typed as "object"
and uses pandas' to_numeric to convert.
* Fix tests
* Remove all iteritems
superset appends DRUID_TZ info to intervals but not to granularity which causes one day's data return as 2 days. This fix is also pass DRUID_TZ to granularity.
* 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
* Fix deepequality logic
Zeroed-in on this while a Deck Scatter Plot chart was prompting for
refresh on-load.
I'm pretty sure using JSON.stringify as a proxy for deep equality is
wrong.
Not sure how to handle yarn.lock changes here. The changes on yarn.lock
are the result of "only" running `yarn add deep-equal`
* Adressing comments