Column Definitions

Setting the column_definitions parameter to preconfigure the formatting of your data requires a Mito Enterprise License.

Why use the column_definitions parameter?

The column_definitions parameter allows you to preconfigure the format of columns displayed in the Mito Spreadsheet. They're particularly useful when you need to apply conditional formatting to columns so your app users can instantly see informative data immedietly after loading your app.

Column Definitions Usage

The column_conditions parameter allows users to define conditional formatting rules for specific columns in specific dataframes displayed spreadsheet.

The column_conditions is a list of formatting configurations applied to each sheet.

• columns: Specifies the columns names to apply the conditional formatting rule to.

• conditional_formats: Specifies the conditional formatting rules for the specified columns.

• filters: Each filter is a pair of condition and value. For example, if the condition is 'greater' and the value is 5, the applied font_color and background_color will be applied to all cells in the specific column with a value greater than 5. See a full list available conditions here.

• font_color: The Hex string representation the font should be displayed in if the cell meets the required condition. A valid conditional format must have at least a font_color and/or background_color.

• backgrond_color: The Hex string representation the cell background should be colored in if the cell meets the required condition. A valid conditional format must have at least a font_color and/or background_color.

Example Usage

The below column_definitions displays applies conditional formatting to columns "A" and "B" in the first dataframe inside the spreadsheet.

spreadsheet(
    df1, 
    column_definitions=[
        [
            {
                'columns': ['A', 'B'],
                'conditional_formats': [{
                    'filters': [{'condition': 'greater', 'value': 5}], 
                    'font_color': '#c30010', 
                    'background_color': '#ffcbd1' 
                }] 
            }
        ]
    ]
)

Filter Conditions Reference List

Below is the complete list of conditions available to be used in a conditional format filter. Take note that most filter conditions are only valid if applied to a column with the correct data type, except for the filter conditions labelled with Any Data Type at the bottom of the table.

Column Data Type	Filter Conditions
Number	number_exactly
	number_not_exactly
	greater
	greater_than_or_equal
	less
	less_than_or_equal
	number_lowest
	number_highest
String	contains
	string_does_not_contain
	string_exactly
	string_not_exactly
	string_starts_with
	string_ends_with
	string_contains_case_insensitive
Dates	datetime_exactly
	datetime_not_exactly
	datetime_greater
	datetime_greater_than_or_equal
	datetime_less
	datetime_less_than_or_equal
Boolean	boolean_is_true
	boolean_is_false
Any Data Type	empty
	not_empty
	most_frequent
	least_frequent

More Examples

Applying conditional formatting to a single dataframe

spreadsheet(
    df1, 
    column_definitions=[
        [
            {
                'columns': ['A', 'B'],
                'conditional_formats': [{
                    'filters': [{'condition': 'greater', 'value': 5}], 
                    'font_color': '#c30010', 
                    'background_color': '#ffcbd1' 
                }] 
            }
        ]
    ]
)

Applying multiple conditional formatting rules to a single dataframe

spreadsheet(    
    df1, 
    column_definitions=[
        [
            {
                'columns': ['A'],
                'conditional_formats': [{
                    'filters': [{'condition': 'greater', 'value': 5}], 
                    'font_color': '#c30010', 
                    'background_color': '#ffcbd1' 
                }] 
            },
            {
                'columns': ['B'],
                'conditional_formats': [{
                    'filters': [{'condition': 'contains', 'value': 'invalid'}], 
                    'font_color': '#c30010', 
                    'background_color': '#ffcbd1' 
                }] 
            }
        ]
    ]
) 

Applying conditional formatting to multiple dataframes

spreadsheet(
    df1, 
    df2
    column_definitions=[
        [
            {
                'columns': ['A', 'B'],
                'conditional_formats': [{
                    'filters': [{'condition': 'greater', 'value': 5}], 
                    'font_color': '#c30010', 
                    'background_color': '#ffcbd1' 
                }] 
            },
        ],
        [
            {
                'columns': ['C', 'D'],
                'conditional_formats': [{
                    'filters': [{'condition': 'less', 'value': 0}], 
                    'font_color': '#c30010', 
                    'background_color': '#ffcbd1' 
                }] 
            },
        ],
    ]
)