Problem trying to highlight cells in dataTable

Dash Python
1

Good morning.

I’m trying to use conditional styles depending on the value of each cell in my DataTable.

An example of my data is the following:

data = pd.DataFrame(data = {‘fc’: [‘row_1’, ‘row_2’, ‘row_3’], ‘param_1’: [1,0,2], ‘param_2’: [3,0,1]})

and my code to show the DataTable:

tabla = DataTable(data = data.to_dict(‘rows’),
columns = [{‘id’: c, ‘name’: c} for c in data.columns],
style_as_list_view = True,
style_cell = {‘fontSize’: 15},
style_cell_conditional = {‘if’: {‘column_id’: ‘param_2’,
‘filter_query’: ‘{param_2} eq 3’},
‘backgroundColor’: ‘rgb(255,0,0)’
},
)

So I want that cells in column ‘param_2’ that have a value equal to 3 have red background, but instead, I’m getting my whole DataTable red.

Thanks you very much in advance!

2

So I think you are almost there. Here is an example of what I do. The for loop repeats the query for the column_id’s listed.

conditional += [
	{
	    'if': {
	        'column_id': x, 
                'filter': '{' + x + '}' + ' <= ' + str(threshold_max)
             },
	'backgroundColor': highlight
	} for x in ['b', 'd', 'f', 'h', 'j', 'l', 'n']
]

So, your filter_query line should become filter: '{' + param_2 + '}' == str(3)

There could be better ways of how I implemented my query, but it works and should get you going. Also, eq could be valid but since I’m running a version behind 1.0.0, I’m not 100% sure.

3

You’re super close! Just two things:

  • filter_query only applies to style_data_conditional, not style_cell_conditional (which also covers the headers)
  • It’s an array of objects, not just one object
    DataTable(
        data=data.to_dict('rows'),
        columns=[{'id': c, 'name': c} for c in data.columns],
        style_as_list_view=True,
        style_cell={'fontSize': 15},
        style_data_conditional=[{
            'if': {
                'column_id': 'param_2',
                'filter_query': '{param_2} eq 3'
            },
            'backgroundColor': 'rgb(255,0,0)'
        }],
    )

18%20PM

1 Like
4

Thanks to you guys!

I think that Alex has right, however, I still have the problem due to unicode issues :(, python 2 facts.