What are Blocks?
Reports are comprised of multiple Blocks, which wrap up Python objects, such as Pandas DataFrames, Visualisations, and Markdown. Datapane also includes layout blocks to add tabs, pages, and interactive selects to your reports.
We are always adding new components, and if you have some ideas on what you would like to use in your reports, please start a discussion on the Datapane forum.
In this section we've grouped Blocks into Block types. Learn how to use them from our tutorials, and more detailed API usage can be found in our API docs.
Block types
-
dp.BigNumber
dp.DataTable
dp.Table
-
dp.Plot
-
dp.Code
dp.Formula
dp.HTML
dp.Text
-
dp.Divider
dp.Group
dp.Page
dp.Select
dp.SelectType
dp.Toggle
-
dp.Attachment
dp.Embed
dp.Media
Except for Page blocks, every block can be nested inside a layout block, meaning you can build arbitrarily complex reports. In addition, most blocks take optional name
and caption
parameters and display those to your viewers.
Default Block Handling
As well as explicitly specifying your block type (for instance, by using dp.Plot
), Datapane will try and choose the best block for your object if you pass it in directly, for instance as follows:
The defaults are as follows:
Object Type | Datapane Block |
---|---|
pandas DataFrame | dp.Table |
string | dp.Text |
Altair | dp.Plot |
Bokeh | dp.Plot |
Folium | dp.Plot |
Matplotlib / Seaborn | dp.Plot |
Plotly | dp.Plot |
Plotapi | dp.Plot |