Data Editor
A datagrid editor based on Glide Data Grid
This component is introduced as an alternative to the datatable to support editing the displayed data.
Columns
The columns definition should be a list of dict, each dict describing the associated columns.
Property of a column dict:
title: The text to display in the header of the column.id: An id for the column, if not defined, will default to a lower case oftitlewidth: The width of the column.type: The type of the columns, default to"str".
Data
The data props of rx.data_editor accept a list of list, where each list represent a row of data to display in the table.
Simple Example
Here is a basic example of using the data_editor representing data with no interaction and no styling. Below we define the columns and the data which are taken in by the rx.data_editor component. When we define the columns we must define a title and a type for each column we create. The columns in the data must then match the defined type or errors will be thrown.
Interactive Example
Here we define a State, as shown below, that allows us to print the location of the cell as a heading when we click on it, using the on_cell_clicked event trigger. Check out all the other event triggers that you can use with datatable at the bottom of this page. We also define a group with a label Data. This groups all the columns with this group label under a larger group Data as seen in the table below.
Cell clicked:
Styling Example
Now let's style our datatable to make it look more aesthetic and easier to use. We must first import DataEditorTheme and then we can start setting our style props as seen below in dark_theme.
We then set these themes using theme=DataEditorTheme(**dark_theme). On top of the styling we can also set some props to make some other aesthetic changes to our datatable. We have set the row_height to equal 50 so that the content is easier to read. We have also made the smooth_scroll_x and smooth_scroll_y equal True so that we can smoothly scroll along the columns and rows. Finally, we added column_select=single, where column select can take any of the following values none, single or multiple.