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Buckaroo is built to expedite the most basic task in data analysis, looking at the raw data. It speeds up common tasks with histograms, sorting, extensible stats, and post processing functions. This is all built around an interactive widget that allows users to quickly swap between different views and transformations of dataframes.
The new release uses shapely's _repr_svg() to provide a thumbnail visualization for each geometry object found in a GeoPandas Dataframe.
Future planned features for GeoPandas
JS based SVG rendering for increased performance
Summary stats for GeoPandas Dataframes. Summary stats, histograms and pinned rows of summary stats are a core feature of Buckaroo, There are a couple of quirks that prevent this from working with GeoPandas, but I expect them to easy to resolve.
I'm eager to hear from GeoPandas users about your workflows. What kind of summary stats would you want on a dataframe? What do you want in a table visualization?
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Hello all,
The 0.6.5 release of the Bucakroo Table for Jupyter now supports Geopandas.
![Screenshot 2024-03-08 at 2 11 05 PM](https://private-user-images.githubusercontent.com/40453/311340471-d91d7e35-dfa4-4441-820a-33fe859ab07c.png?jwt=eyJhbGciOiJIUzI1NiIsInR5cCI6IkpXVCJ9.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.fVobBUTuaOvV9pZewojkd4ykOgDlWZ6IkjtEJ1p652A)
Buckaroo is built to expedite the most basic task in data analysis, looking at the raw data. It speeds up common tasks with histograms, sorting, extensible stats, and post processing functions. This is all built around an interactive widget that allows users to quickly swap between different views and transformations of dataframes.
The new release uses shapely's
_repr_svg()
to provide a thumbnail visualization for each geometry object found in a GeoPandas Dataframe.Future planned features for GeoPandas
Geopandas support for Buckaroo on Youtube
I'm eager to hear from GeoPandas users about your workflows. What kind of summary stats would you want on a dataframe? What do you want in a table visualization?
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