I need to be able to easily create hyperlinks for a table from dataframe, the easiest way being based on another column in the same dataframe. This will wrap column in the link from column_HREF by default. You can specify a different suffix.

This is still a work in progress. The new method doesn't quite have the same functionality or keywords as the original yet, such as header. I'm still settling on a subclass or patching a new class method onto dbc.Table (which you can see in the other branch).

I'm using the new walrus operator so you will need Python 3.8 or higher.

setup.py installs an egg which was causing dash to crash when debugging for reasons I can't explain. So clone and do the pip install . Maybe because I'm subclassing a component directly and that's not how components are generally created?

git clone https://github.com/astrowonk/dash_dataframe_table.git cd dash_dataframe_table pip install . 

You can run example.py app without install via pip or setup if you like.

git clone https://github.com/astrowonk/dash_dataframe_table.git cd dash_dataframe_table python example.py 

The example.py dash app shows it in action, both adding links automatically to the company column name, and styling the columns conditionally.

The module now monkeypatches a new dbc.Table.from_enhanced_dataframe onto the existing dbc.Table.

The company column is given hyperlinks from a midden Company_HREF column. See the example.py dash app code for more.

The method on this class also supports conditional style formatting. This can either be a list of matching values, or a callable that returns a boolean.

def color_positive(val): if val > 0: return {'className': 'table-success'} elif val < 0: return {'className': "table-warning"} cell_style_dict = { 'Company': [ (['Yahoo', 'Apple'], { 'font-weight': 'bold' }), (['Oracle'], { 'className': 'table-danger' }), ], 'Value2': lambda x: { 'background-color': '#7FFFD4' } if x > 10 else {}, 'Date': lambda x: { 'className': 'table-info' } if x.weekday() in [4, 6] else {}, 'Value': color_positive } html.Div( dbc.Table.from_enhanced_dataframe(df, striped=True, cell_style_dict=my_style_dict) )