Inforiver
EDITable
EDITable
  • Introduction to EDITable
    • Why EDITable?
    • Supported Database Connections
  • Get Started
    • EDITable Pre-requisites
      • Admin consent for EDITable's Entra ID
        • Basic consent
        • Full admin consent
    • Install EDITable
    • Add EDITable visual
  • Getting Data into EDITable
    • Connect to Data
      • Get data
      • Assign fields
      • Configuration Steps
        • Configure source
        • Configure Columns
        • Configure Type 2 SCDs (Optional)
    • Create a Table
      • Create From Scratch
      • Use Existing Table
      • Import Data
  • Working with EDITable
    • EDITable interface
    • Manage Columns
      • General
      • Constraints
      • Lookup and Relation
      • Display
      • Import/Export Configuration
      • Add Database Column
      • Insert Column
    • Column Access Control
    • Row Identification
    • Table Operations (Insert/Update/Delete)
      • Edit data
      • Bulk Edit
      • Find and Replace
      • Insert rows
      • Insert Column
      • Import rows
      • Delete rows
      • Duplicate rows
      • Copy rows
      • Preview Changes
      • Reset Changes
    • Explore data
      • Search and filter
      • Sort and reorder
      • Show/Hide columns
      • Pin columns
      • Group Rows By
      • Summarize Column
    • Basic formatting
    • Conditional Formatting
  • Row Access Control
  • Approval Workflow
    • Review Changes - Workflow process
  • Type 2 SCDs
    • Configuring Type 2 SCDs in EDITable
  • Audit logs
  • Webhook
  • Display Settings
  • Commenting and Collaboration
    • Assign users & task status
    • View all comments & track changes
    • Comment Settings
  • Admin Portal & EDITable Console
    • Tables
    • Transaction Logs
    • Insights (Metrics)
    • Utility
      • Download Report
      • Pipeline
        • Power BI & EDITable deployment pipelines
        • Deployment in different destinations
        • Trigger deployment pipeline from external applications
        • Logs & other pipeline options
    • Manage Profile
    • Admin Portal
      • User Management
      • Settings
        • General Settings
        • Writeback Settings
          • Settings
          • EDITable managed DB
        • API token
    • Onboarding Actions
  • Formula and Functions
    • Conditional statements
      • IF
      • IFNA
      • SWITCH
    • Logical functions
      • AND
      • IN
      • ISBLANK
      • ISEMPTY
      • ISNUMBER
      • NOT
      • OR
      • XOR
    • Math functions
      • ABS
      • AVERAGE
      • AVERAGEIF
      • AVERAGEEXNEG
      • AVERAGEEXZERO
      • AVERAGEEXZERONEG
      • CEILING
      • COUNT
      • COUNTIF
      • DIVIDE
      • EVEN
      • EXP
      • FLOOR
      • LOG
      • MAX
      • MIN
      • PCT
      • POWER
    • Text formatting functions
    • Date functions
      • DATE
      • DATE.FORMAT
    • Other operators
  • Keyboard Shortcuts
  • Release Notes
    • EDITable - v1.7.5
    • EDITable - v1.7
    • EDITable - v1.6.5
    • EDITable - v1.6
Powered by GitBook
On this page
  • 1. Minimum and Maximum
  • 2. Field Validation
  • 3. Default Value
  • 3.1. Static value
  • 3.2. Derived value
  1. Working with EDITable
  2. Manage Columns

Constraints

PreviousGeneralNextLookup and Relation

Last updated 3 months ago

This section provides options for limiting input values, setting default values, and configuring field validation.

1. Minimum and Maximum

Here you can specify the minimum and maximum values that can be entered into the columns. Any values outside of this range are not permitted. These limits can be applied to the input types: Number, Decimal, Date Time, and Date.

Consider the example below, where the minimum and maximum values are set for the 'Salary' column.

The existing values remain unchanged. However if a user enters a salary that falls outside the specified range, they will be notified of the minimum and maximum limits.

Note: You can also set any one of these limits (either minimum or maximum).

For Date and DateTime input types, users may choose a date range or both date and time range. Any date and time outside of this range will not be accepted.

2. Field Validation

This option is available for the Text input type, where you can specify whether to allow only numeric, alphanumeric, non-numeric, Email ID, or URL inputs. You can also specify a regex pattern to allow inputs that match a specific pattern. Inputs that do not match the pattern are flagged and rejected.

This ensures data correctness and accuracy.

The field value is validated against your specified input type configuration. If another type is entered, it is not accepted.

When you choose the 'Regex' option, a new field appears with the link 'Click to configure'.

After clicking the link, a pop-up appears where you can enter the regex pattern to be validated against. Click Apply and Save. In the example below, we have entered the regex text to validate the email ID or URL entered by the users.

When a user enters an incorrect email address or URL, the below prompt appears, and the input is rejected.

3. Default Value

EDITable lets you configure default values for the columns. When a new row is added, the specified column is automatically filled with the default value if you have set one.

To set a default value, click the highlighted option below, beside the required column.

3.1. Static value

To set a static value, select Manual and enter the value. In the example below, a static value is set as the default date for the 'Start Date' column.

Whenever a new row is added, this column value is automatically populated by default.

Reset to default on update

Checking the 'Reset to default on update' option sets the default value for newly inserted rows and disables the column from editing. The existing values are retained, and automatically changed to default only when users edit other values in the specific record. Find below an example where the value changes to the default.

For the 'Decimal' input type, you can also specify the default number of decimal digits to be allowed.

For the 'Person' input type, you can either use their name or email address as default.

For the 'Single-select' type, you can choose the default value from the list of options you have configured.

For the 'Check Box' type, the default values are automatically configured with the Boolean values: true and false. You can change these to 1/0 or yes/no, etc., if necessary.

3.2. Derived value

You can set derived values as defaults instead of using static values. These derived values are calculated using configurable formulas.

EDITable provides many Excel-like formulas and functions to help you perform these calculations. These values change dynamically as the underlying reference data changes.

Derived values can be set for the field types - Number, Decimal, Text, Date, DateTime, Person, and Email.

Recalculate data on update

Checking the 'Recalculate data on update' option sets the calculated value as default for newly inserted rows and disables the column from editing. The existing values are retained and automatically changed to the derived value only when users edit other values in the specific record.

We have discussed setting constraints and defaults for table data. In the next section, we will explore how to select and look up values from a table or visual for a single-select field type.

Minimum and Maximum
user notified about the min and max values
Minimum and maximum date range
Field Validation
Example
Regex option
Regex validation for Email ID column
Wrong text input
Click to configure default date
Setting static default value
Default value is filled automatically
Reset to default on update
Decimal input type
Person input type
Single-select input type
Checkbox type
Configure derived value
Recalculate data on update