Tablize Data Editor
💡 The Tablize Data Editor is the core tool for data processing within Tablize. Once data is imported into Tablize, you can use the Data Editor to manipulate the data, create data views and data dashboards, and even perform advanced data automation and API configurations.
📖 This document will provide explanations and insights into the "Tablize Data Editor" to assist you in better understanding and using Tablize.
Editor
The data editor can be divided into three areas:
- Table and View Switching Bar
- Switch between the current data table and data views created based on the table.
- Data Formula Panel, Data Import/Export Functions, and Formula Input Area
- Use the quick formula panel to process the table or input formulas for selected table columns.
- Table Content Area
- Add columns and rows and set various column properties.
Column Properties
Column properties in Tablize include text/number/percentage/checkbox/date/single choice/attachment, and other data types. Users can set different data types according to their needs.
Text Property
Setting the column field property as text format allows you to input any form of text content.
Number Property
Setting the column field property as a number format allows you to input numerical characters and set decimal places.
Percentage Property
Setting the column field property as a percentage format allows you to set decimal places.
The percentage rule is: 1=100%, 0.5=50%, and so on.
Checkbox Property
Setting the column field property as a checkbox format allows you to confirm and select data.
Date Property
Setting the column field property as a date format allows you to set either "Year-Month-Day" or "Year-Month-Day, Hour-Minute-Second" formats.
Single Choice Property
Setting the column field property as a single choice format allows you to add data options and make dropdown selections. You can also set data color highlighting.
Attachment Property
Setting the column field property as an attachment format allows you to upload local files (in various formats) to the table, storing them in the cloud.
