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Forward-merge branch-23.02 to branch-23.04 #440

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Jan 31, 2023
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Binary file modified docs/_images/RAPIDS_cuxfilter.png
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24 changes: 21 additions & 3 deletions docs/source/10_minutes_to_cuxfilter.ipynb
Original file line number Diff line number Diff line change
Expand Up @@ -60,6 +60,24 @@
"6. cuxfilter.assets"
]
},
{
"attachments": {},
"cell_type": "markdown",
"metadata": {},
"source": [
"### Architecure\n",
"\n",
"The current version of cuxfilter leverages jupyter notebook and bokeh server to reduce architecture and installation complexity."
]
},
{
"attachments": {},
"cell_type": "markdown",
"metadata": {},
"source": [
"![layout architecture](https://github.com/rapidsai/cuxfilter/raw/HEAD/docs/_images/RAPIDS_cuxfilter.png)"
]
},
{
"cell_type": "markdown",
"metadata": {},
Expand Down Expand Up @@ -930,7 +948,7 @@
],
"metadata": {
"kernelspec": {
"display_name": "Python 3.9.15 ('rapids-22.12')",
"display_name": "Python 3",
"language": "python",
"name": "python3"
},
Expand All @@ -944,11 +962,11 @@
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.9.15"
"version": "3.8.10 (default, Nov 26 2021, 20:14:08) \n[GCC 9.3.0]"
},
"vscode": {
"interpreter": {
"hash": "f6aa187a6aaade5733ad3b5ff5c82df04fb0b3dfac03c5ad044e20fb4c7093be"
"hash": "31f2aee4e71d21fbe5cf8b01ff0e069b9275f58929596ceb00d14d90e3e16cd6"
}
}
},
Expand Down
11 changes: 9 additions & 2 deletions python/cuxfilter/dashboard.py
Original file line number Diff line number Diff line change
Expand Up @@ -106,6 +106,12 @@ class DashBoard:
[0] Bokeh(Figure)
[chart2] Column(sizing_mode='scale_both', width=1600)
[0] Bokeh(Figure)`
>>> # d.app() for serving within notebook cell,
>>> # d.show() for serving as a separate web-app
>>> d.app() #or d.show()
displays interactive dashboard

do some visual querying/ crossfiltering
"""

_charts: Dict[str, Union[CUXF_BASE_CHARTS]]
Expand Down Expand Up @@ -362,9 +368,10 @@ def export(self):
>>> [line_chart_1, line_chart_2],
>>> layout=cuxfilter.layouts.double_feature
>>> )
>>> # d.app() for serving within notebook cell,
>>> # d.show() for serving as a separate web-app
>>> d.app() #or d.show()
displays dashboard
do some visual querying/ crossfiltering
displays interactive dashboard

>>> queried_df = d.export()
final query 2<=key<=4
Expand Down