Dx

_2022-08-21_

Added
- `pd.Series` as a default renderable type (to go with the existing `pd.DataFrame` and `np.ndarray` types)
- Support for the following data types inside `pd.DataFrame` columns:
- `type` and `np.dtype`
- `shapely.geometry` objects
- `pd.Timedelta` and `datetime.timedelta`
- `pd.Period`
- `pd.Interval`
- `complex` numbers
- `ipaddress.IPv4Address` and `.IPv6Address`
- Extra dataset generation functions for development/testing under `dx.utils.datatypes`
- `dx.quick_random_dataframe(n_rows, n_columns)` to get a `pd.DataFrame` of 0.0-1.0 floats (convenience wrapper for `pd.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` to `random`

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 formatter

_2022-07-22_
Added
- Additional metadata sent to frontends to triage issues with output sizes and `dx` settings
Fixed
- `simple`/`enhanced` display modes no longer raise JSON errors trying to serialize `pd.NA` values
- `SAMPLE_METHOD` returning incorrect value (`True` instead of `DXSampleMethod`) when compared with `COLUMN_SAMPLE_METHOD` and `ROW_SAMPLE_METHOD`
- Truncating rows no longer alters dtypes by adding `...` values

_2022-08-05_
Added
- Helper text for adjusting settings after a dataset has been truncated
- `.reset_index()` when a custom/MultiIndex is used to preserve `0-n` row numbers at the `index` level
- Support for geopandas GeoDataFrames and GeoSeries objects
- `dx.random_dataframe(num_rows, num_columns)` convenience function
- More tests!

Changed
- `default` display mode (vanilla pandas) renamed to `plain`

Fixed
- Properly pass `metadata` through during the `IPython.display` calls to render dataresource/dx formatted data
- `plain` display format tests use a basic IPython `DisplayFormatter` instead of `None`

<img width="568" alt="image" src="https://user-images.githubusercontent.com/7707189/182971951-52b440ae-f894-4eb0-8941-3cadd78aef0a.png">

_2022-07-22_
**Added**
- Direct support for `application/vnd.dataresource+json` media type display formatting
- reverting all settings to `pandas` defaults with `dx.reset()` or switching to the `DISPAY_MODE` setting to `default`
- `pydantic` dependency for BaseSettings use
- `pandas`-inspired `dx.set_option(setting_name, setting_value)`
- `dx.set_display_mode()` convenience function for globally switching between `simple` (simpleTable/DEX), `enhanced` (GRID), and `default` (vanilla pandas)
- Auto-truncating rows and columns of `pd.DataFrame` objects based on `DISPLAY_MAX_ROWS`, `DISPLAY_MAX_COLUMNS`, and `MAX_RENDER_SIZE_BYTES` (1MB default) size limits before rendering (for `simple` & `enhanced` display modes), with blueprintjs flavored warnings
- `SAMPLING_MODE` setting to better control how truncating happens ("first", "last", "outer", "inner", and "random" options)
- `RANDOM_SEED` setting for random sampling

**Fixed**
- Support for non-string column and index values (possibly temporary) to allow `build_table_schema` to work with `pd.MultiIndex` values

_2022-05-06_
**Fixed**
* Lowered the minimum required `ipython` version from `8.2.0` to `7.31.1`

_2022-04-26_
**Fixed**
* `dx.register()` (`dx.enable()`, deprecated) and `dx.deregister()` (`dx.disable()`, deprecated) will now update the default display formatting for pandas `DataFrame` objects as intended