From 9f46f2e4f833ebcd72d101e9ff71c9e84ddcc3e2 Mon Sep 17 00:00:00 2001 From: Ricarda <42298717+Hoch3007@users.noreply.github.com> Date: Sun, 23 Jun 2019 05:31:46 +0200 Subject: [PATCH] added more info to distinguish bokeh (#28103) added more info to distinguish bokeh from matplotlib and seaborn added a link to a cheat sheet --- guide/english/data-science-tools/visualization-bokeh/index.md | 3 +++ 1 file changed, 3 insertions(+) diff --git a/guide/english/data-science-tools/visualization-bokeh/index.md b/guide/english/data-science-tools/visualization-bokeh/index.md index bfda6d9f4b..0a07e18371 100644 --- a/guide/english/data-science-tools/visualization-bokeh/index.md +++ b/guide/english/data-science-tools/visualization-bokeh/index.md @@ -3,7 +3,10 @@ title: Bokeh --- Bokeh is a Python interactive visualization library, providing the elegant and concise interface to create plot, dashborads, and data applications. +This distinguishes bokeh from other visualization libraries such as matplotlib or seaborn. With the help of bokeh even very large data sets can be visualized. Because they can be adapted dynamically, e.g. by zooming into certain sections or selecting axes to be displayed, it is possible to provide a visual overview even over large amounts of data and to make the display interpretable. + ### More Information: [Bokeh Official Website](https://bokeh.pydata.org/en/latest/) [Bryan Van de Ven, PyBay2016, 55:47](https://www.youtube.com/watch?v=xqwCxuEBpxk) [Bryan Van de Ven, PyData SF 2016, 2:14:00](https://www.youtube.com/watch?v=M1-MVYLONZc) +[DataCamp.com bokeh Cheat Sheet] (https://s3.amazonaws.com/assets.datacamp.com/blog_assets/Python_Bokeh_Cheat_Sheet.pdf)