v1.2.0
What's Changed
1.2.0
2022-08-21
Added
pd.Series
as a default renderable type (to go with the existingpd.DataFrame
andnp.ndarray
types)- Support for the following data types inside
pd.DataFrame
columns:type
andnp.dtype
shapely.geometry
objectspd.Timedelta
anddatetime.timedelta
pd.Period
pd.Interval
complex
numbersipaddress.IPv4Address
and.IPv6Address
- Extra dataset generation functions for development/testing under
dx.utils.datatypes
dx.quick_random_dataframe(n_rows, n_columns)
to get apd.DataFrame
of 0.0-1.0 floats (convenience wrapper forpd.DataFrame(np.random.rand(n_rows, n_columns))
)dx.random_dataframe()
with different boolean values to enable based on available datatypes (dx.DX_DATATYPES
)
settings_context
context manager to allow temporarily changing a setting (or multiple)- Logging via
structlog
(default level:logging.WARNING
)
Changed
- Default sampling method changed from
outer
torandom
Fixed
- Displaying a dataframe with an out-of-order index (like with
.sample()
) no longer resets the index before sending data to the frontend. - Index/column flattening and string-formatting is behind settings and is handled more explicitly
dx
should no longer interfere with other media type / mime bundles (e.g. matplotlib) formatted by the existing IPython display formatted
- 1.1.3 updates by @shouples in #19
- fix github workflow for publishing to pypi by @shouples in #15
- display ID registration prep, formatter registration fixes, index updates, dtype handlers, expanded data generators by @shouples in #16
Full Changelog: v1.1.2...v1.2.0