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Learn to work with tables and tabular data.
Tables (v2) refers to the latest version of table procedures in Kognitos, offering improved performance and expanded capabilities.
Table procedures in Kognitos provide a structured way to interact with tabular data, allowing users to read, modify, and analyze information efficiently. Tables are especially useful when working with lists, structured inputs, or datasets that require row-by-row operations.
Table Creation
Working with Table Rows
Working with Table Columns
Working with Table Cells
Here's a simple example of using our Table (v2) procedures to process some documents:
The procedures used in this example:
Lines 1-2:
Lines 4-7, 9-12, 14-17:
Lines 19-20:
list
The column names for the table. If not specified, an empty table will be created.
Empty
No
row count
number
Number of empty rows to create in the table.
0
No
table
The created table with specified column names or an empty table if no column names are provided.
create a tablecreate a table where
the column names are "USA", "Japan", "Egypt"
the row count is 3Manipulating Tables
create a table where
the column names are "Document ID", "Document Type", "Status"
insert a row in the table where
the Document ID is 721219
the Document Type is "Invoice"
the Status is "Pending"
insert a row in the table where
the Document ID is 324236
the Document Type is "Invoice"
the Status is "Completed"
insert a row in the table where
the Document ID is 384230
the Document Type is "Summary"
the Status is "Completed"
get the table's row where
the row selection formula is "Status == Pending"john
+ 1 (415) 691 9426
123 east street
San Francisco
joe
+ 1 (415) 691 1234
321 west street
San Jose
jack
+ 1 (415) 691 4595
213 north street
San Francisco
This procedure will consistently generate the same table. It can be easily expanded, modified, or used as a foundation for further data processing.
table
A table containing sample data with columns for Name, Number, Address, and City.
create a sample tablejohn
+ 1 (415) 691 9426
123 east street
San Francisco
joe
+ 1 (415) 691 1234
321 west street
San Jose
jack
create a sample table
get the table's rows where
the row selection formula is "City == San Francisco"
create a table from the rowsthe table
john
+ 1 (415) 691 9426
123 east street
San Francisco
jack
+ 1 (415) 691 4595
213 north street
+ 1 (415) 691 4595
213 north street
San Francisco
San Francisco
table
table
The original table from which the pivot table will be created.
No default
Yes
row fields
strings
The columns to use as the indexes of the pivot table.
No default
Yes
column field
pivot table
The generated pivot table.
For example, say we have a table defined in our automation as the sales data table.
North
Widget A
100
South
Widget B
250
East
Widget A
300
West
Widget B
450
East
300
0
300
North
100
0
100
the file
open the sales data table at the file
create a pivot table from the sales data table with
the row fields are "Region"
the column field is "Product"
the value field is "Sales"
the aggregation function is "sum"
the aggregate column name is "Sales"string
The column to use as the columns of the pivot table.
No default
Yes
value field
string
The column to use as the values of the pivot table.
No default
Yes
aggregation function
string
The function to aggregate the values in the pivot table. Valid options are sum, mean, and count.
No default
Yes
aggregate column name
string
The column name for the aggregated result in columns and row. Specified as: the aggregate column name is "column name"
No default
No
South
0
250
250
West
0
450
450
Sales
400
700
1100
Creates a combined table from two or more existing tables.
Moves a column in the table to a specified position.
This procedure can move a column in a table to a new position. This is useful when you want to bring important data to the front, match a preferred column order for readability, or prepare your table for export or integration with other systems. To use this procedure, specify which table you're working with and the new position for the column.
Deletes duplicate rows from the table, optionally based on specified columns.
This procedure removes duplicate rows from a table. If no columns are specified, all columns are considered when identifying duplicates. This automation procedure is useful for cleaning up data and removing redundancy.
By default, all columns are considered when removing duplicates.
Groups the rows of a table by specified criteria.
This procedure groups the rows of a table by a specified column, such as "City" or "Department", and returns a list of JSON objects, where each object contains the group name and the rows that belong to it. It's useful when you need to split a dataset into meaningful categories to process each group separately, like handling orders by region or users by role.
Below is a line-by-line overview of the automation syntax. Expand each line to learn more.
Combines multiple tables into a single table based on specified criteria.
This procedure combines multiple tables and merges them into a single table based on specified criteria. This is useful when you have related data spread across multiple sources and want to bring it all together for easier analysis or reporting.
Gets the column number of a specified column in a table.
Retrieves the column number (index) of the specified column in a table.
In this example, the column refers to the Address column in the table below.
Note: This sample table can be generated using the create a sample table procedure.
2
Since the columns are numbered starting at 0, the Address column has a column number (index) of 2.
Retrieves the number of columns in the table.
This procedure gets the number of columns in a table and is useful for understanding the table’s structure. You can use it to check if a table has the expected number of fields, validate schema changes, or make sure a table meets certain requirements before running other steps in a process. It’s also helpful when working with dynamic tables where the column count might change over time.
In this example, the table refers to the following table, which can be generated using the create a sample table procedure:
4
Converts a table column to a specified data type.
Rounds numeric values in a table column to a specified number of decimal places.
This procedure rounds the values in a specified column of a table to a given number of decimal digits. It automatically handles comma-separated values and converts non-numeric columns to numeric format before rounding. You can specify the number of decimal places and provide custom handling for missing values.
create a sample table
convert the table to a stringthe string
[{"Name":"john","Number":"+ 1 (415) 691 9426","Address":"123 east street","City":"San Francisco"},{"Name":"joe","Number":"+ 1 (415) 691 1234","Address":"321 west street","City":"San Jose"},{"Name":"jack","Number":"+ 1 (415) 691 4595","Address":"213 north street","City":"San Francisco"}]
+ 1 (415) 691 4595
213 north street
table
table
The table containing the column.
No default
Yes
new column number
int
The new position for the column.
No default
Yes
table
The table with the column moved.
john
San Francisco
+ 1 (415) 691 9426
123 east street
joe
San Jose
+ 1 (415) 691 1234
321 west street
jack
create a sample table
move the table's "City" column where
the new column number is 1San Francisco
column
column
The column whose index is to be retrieved.
No default
Yes
column number
The number of the column (index).
john
+ 1 (415) 691 9426
123 east street
San Francisco
joe
+ 1 (415) 691 1234
321 west street
San Jose
jack
+ 1 (415) 691 4595
213 north street
get the column's column numberSan Francisco
table
table
The table whose column count is to be retrieved.
No default
Yes
column count
The number of columns in the table.
john
+ 1 (415) 691 9426
123 east street
San Francisco
joe
+ 1 (415) 691 1234
321 west street
San Jose
jack
+ 1 (415) 691 4595
213 north street
get the table's column countSan Francisco
A list of tables to be combined.
No default
Either tables or first table and second table are required.
excluded columns
list of strings
A list of column names to be excluded from the combined table.
No default
No
included columns
dictionary
A dictionary specifying which columns to include from each table. The keys are table names, and the values are lists of column names to include.
No default
No
same columns
list of strings
A list of column names that are the same across all tables and should be combined into a single column in the combined table.
No default
No
first table
table
The first table to be combined.
No default
Either tables or first table and second table are required.
second table
table
The second table to be combined.
No default
Either tables or first table and second table are required.
tables
table
A combined table created from the specified tables, with considerations for excluded and included columns, as well as columns that are the same across tables.
list of tables
table
table
The table from which duplicate rows should be deleted.
No default
Yes
uniqueness columns
list of strings
Column names to consider for identifying duplicates.
All columns are used by default.
No
table
The updated table with duplicate rows removed.
This phrase should be written on a new line.
✅ Yes — This phrase is required.
✅ Yes — A reference to the table must be defined. Replace criteria with the grouping criteria.
group the table's rows by Citydictionary
Specifies which columns to include from each table. The dictionary keys are table identifiers, and the values are lists of column names to include.
No default
No
same columns
list of strings
Columns that are considered the same across tables and can be merged.
No default
No
tables
list of tables
The tables to be combined.
No default
Yes
excluded columns
list of strings
Columns to be excluded from the final table.
No default
No
table
A single table that combines the input tables according to the specified criteria.
included columns
The new names for the columns.
No default
Yes
table
table
The table containing the column to be renamed.
No default
Yes
old columns names
strings
The current name of the columns to be renamed.
No default
Yes
new column names
strings
create a combined table with
the tablescreate a combined table with
the first table
the second table
the excluded columns are "ID", "Timestamp"
the same columns are "Name", "Email"create a sample table
remove the duplicates from the tablecreate a sample table
remove the duplicates from the sample table where
the uniqueness columns are "name", "age"group the table's rows by City
use the above as the groups
process each group as follows
...combine the tablescombine the tables
the excluded columns are "ID", "Timestamp"
the same columns are "Name", "Email"rename the table's columns where
the old column names are "foo", "bar"
the new column names are "baz", "qux"In this example, the "Price" column contains some missing or empty values. When converting to integer, these blank entries are replaced with 0.
When converting a column with missing values to decimal format, a custom replacement value of 0.0 is used for empty cells.
table
table
The table containing the column.
No default
Yes
old column name
text
The new name for the column.
No default
Yes
new column name
table
The table with the column renamed.
create a sample table
rename the table's "City" column to "Location"john
+ 1 (415) 691 9426
123 east street
San Francisco
joe
+ 1 (415) 691 1234
321 west street
San Jose
jack
row number
number
The row number to insert to. (1-indexed)
No default
Yes
column name
string
The name of the column.
No default
Yes
value
any
The value to set.
No default
Yes
table
The updated table.
For this example, consider the following table, which can be generated using the create a sample table procedure:
john
+ 1 (415) 691 9426
123 east street
San Francisco
joe
+ 1 (415) 691 1234
321 west street
San Jose
jack
+ 1 (415) 691 4595
213 north street
john
+ 1 (415) 691 9426
123 east street
San Francisco
joe
+ 1 (415) 691 1234
321 west street
Mountain View
jack
Below is a line-by-line overview of the automation syntax. Expand each line to learn more.
Here, the file will raise a question prompting you to upload a file directly.
In this example, the file is provided as an S3 URL.
table
table
The table whose row count is to be retrieved.
No default
Yes
row count
The number of rows in the table.
In this example, the table refers to the following table, which can be generated using the create a sample table procedure:
john
+ 1 (415) 691 9426
123 east street
San Francisco
joe
+ 1 (415) 691 1234
321 west street
San Jose
jack
+ 1 (415) 691 4595
213 north street
get the table's row count3
Below is a line-by-line overview of the automation syntax. Expand each line to learn more.
Rounds decimal values in the "Age" column to whole numbers (no decimal places).
Rounds values in the "Tenure" column to exactly 2 decimal places.
Rounds a column while replacing any missing values with 0 before processing.
row
table's row
The row whose row number is to be retrieved.
No default
Yes
row number
The number of the row.
In this example, the table refers to the following table, which can be generated using the create a sample table procedure:
john
+ 1 (415) 691 9426
123 east street
San Francisco
joe
+ 1 (415) 691 1234
321 west street
San Jose
jack
+ 1 (415) 691 4595
213 north street
Here the row refers to the first row:
john
+ 1 (415) 691 9426
123 east street
San Francisco
0
Converts a specified non-empty JSON array of objects (or single object) into a table.
Converts a specified non-empty JSON array of objects (or single object) into a table. This is a specialized conversion procedure for JSON data that explicitly creates tables from JSON arrays.
jsons (required): A JSON array of objects or a single JSON object to be converted into a table.
A table where:
Each object in the array becomes a row
Object keys become column names
Object values become cell values
Result: Table with columns "a" and "b"
Result: Table preserving nested structures
Result: Original JSON structure preserved
Result: Single-row table
Result: Table with all fields, None/null values preserved
Deletes one or more specified columns from a table.
This procedure deletes a table's columns. It can be used to delete a single column or delete multiple columns from a table.
In the examples below, the table refers to the following table, which can be generated using the create a sample table procedure:
Replaces occurrences of a value in a table.
This procedure finds and replaces all instances of a value within a specific table column. It helps keep your data clean and consistent by automatically replacing all matching values in the selected column.
Extracts a table from an existing table.
This procedure helps you create a new table from an existing one by choosing which columns and rows to keep or remove. You can include or exclude specific columns and filter rows using selection formulas.
For the example below, consider the following table:
Retrieves a specified column from a table.
This procedure gets a column from a table, given the column's name. The data is returned as a single-column table. To get a list of values from a column instead, see the procedure Get a Column's Values.
In the examples below, the table refers to the following table, which can be generated using the create a sample table procedure:
Retrieves the value of a specified column from the row.
This procedure retrieves the value of a specific column from a given row in the table. It’s useful when you need to access individual data points or extract specific information to pass into other steps in an automation.
In this example, the table refers to the following table, which is generated using the create a sample table procedure:
the "Address": 321 west street
the "Name": joe
Combines multiple subtables into a single table.
This procedure joins a list of subtables into a single table. This is typically used to reverse the operation Split a Table. If you've used a different procedure to split the original table into subtables, then it is not recommended to use this one to join them.
All the subtables must have the same number of columns and matching column names.
Below is a line-by-line overview of the automation syntax. Expand each line to learn more.
the combined table
Split a large table into smaller subtables.
This procedure divides a given table into smaller subtables, each containing at most a specified number of rows. It is useful for handling large datasets that exceed processing or display limits.
The maximum supported row count is 30,000. If no row count is specified, the procedure defaults to using the maximum allowed.
Transposes a given table.
This procedure transposes a given table. It flips the table's rows to columns and the columns to rows. This may be useful when you want to view or work with your data from a different angle. For example, turning a list of dates in a column into headers across the top, or switching the focus from categories to individual entries.
Calculates an aggregate value of a table column.
cast the table's "Amt" column to "float"cast the table's "Max" column to "string"cast the table's "Price" column to "int"
the blank value is 0cast the table's "Amount" column to "float"
the blank value is 0.0set the cell in the table where
the column name is "City"
the row number is 2
the value is "Mountain View"the file
open the table at the filethe file is "s3://my-bucket/data/table.xlsx"
open a table at the fileround the table's "Age" columnround the table's "Tenure" column
the decimal digits is 2round the table's "Price" column
the blank value is 0.00create a sample table
get the table's row where
the row selection formula is "Name == john"
get the row's row numberconvert the jsons to a table100
10
300
200
5
500
This procedure will consistently generate the same table. It can be easily expanded, modified, or used as a foundation for further data processing.
table
A table with columns Amt, Min, and Max, and two rows of sample integer values.
create an integer table100
10
300
200
5
500
text
The new name for the column.
No default
Yes
+ 1 (415) 691 4595
213 north street
San Francisco
San Francisco
+ 1 (415) 691 4595
213 north street
San Francisco
San Francisco
San Francisco
cast the table's "Age" column to "float"the blank value is 0the file is "s3://my-bucket/data/table.xlsx"round the table's "Age" columnthe decimal digits is 2the blank value is 0Columns to exclude from the new table.
None
No
included row selection formula
string
Formula to select rows to include.
-
No
excluded row selection formula
string
Formula to select rows to exclude.
-
No
table
table
The original table from which the new table will be extracted.
No default
Yes
included columns
list of strings
Columns to include in the new table.
All
No
excluded columns
table
The extracted table
Apple
Red
Sweet
Banana
Yellow
Sweet
Lemon
Yellow
Sour
Apple
Red
Banana
Yellow
Lemon
Yellow
extract a subtable from the table where
the included columns are "Name", "Color"list of strings
213 NORTH STREET
SFO Francisco
table
table
The table to be queried.
No default
Yes
sql query
string
The SQL query to execute on the table, enclosed in quotes. [SQLite syntax]
No default
Yes
table
The resulting table after executing the SQL query.
John
+1 (415) 691 9426
123 EAST STREET
SFO Francisco
Joe
+1 (415) 691 1234
321 WEST STREET
SFO JOS
Jack
create a sample table
query the table with
the sql query is "SELECT Name, Number, UPPER(Address) AS Address, REPLACE(REPLACE(City, 'San', 'SFO'), 'Jose', 'JOS') AS City FROM sample table"+1 (415) 691 4595
row
table's row
The row from which to retrieve the value.
No default
Yes
column name
text
The name of the column to retrieve.
No default
Yes
value
The value of the specified column in the row.
john
+ 1 (415) 691 9426
123 east street
San Francisco
joe
+ 1 (415) 691 1234
321 west street
San Jose
jack
+ 1 (415) 691 4595
213 north street
create a sample table
get the table's row where
the row selection formula is @{"type": "selection_formula", "value": "City is 'San Jose'"}
get the row's Address
get the row's "Name"San Francisco
This phrase should be written on a new line.
✅ Yes — This phrase is required.
✅ Yes — A reference to the subtables must be provided.
Jack
+1 (415) 691 4595
213 North Street
San Francisco
John
+1 (415) 691 9426
123 East Street
San Francisco
Joe
+1 (415) 691 1234
321 West Street
create a sample table
split the sample table into subtables where
the row count is 1
join the subtables into the combined tableSan Jose
column
table's column
The column to perform the aggregation on.
No default
Yes
aggregate function
string
The function to use for aggregation. Valid options are: sum, mean, average, count, min, max, median, std, var.
No default
Yes
aggregate value
The result of the aggregation.
In the following examples, the column refers to the Amt column in the table below.
100
10
30
200
5
500
Note: This sample table can be generated using the create an integer table procedure.
get the column's count2
150.0
200
1
2
10
20
Obj 0
{"bar": "baz"}
[0, 1, 2]
Obj 1
{"bar": "busy"}
[1, 2, 3]
Obj 2
{"bar": "booze"}
[2, 3, 4]
Alice
30
NYC
column names
list of strings
The names of the columns to be deleted.
No default
Yes
table
The updated table with the specified columns removed.
john
+ 1 (415) 691 9426
123 east street
San Francisco
joe
+ 1 (415) 691 1234
321 west street
San Jose
jack
+ 1 (415) 691 4595
213 north street
john
123 east street
San Francisco
joe
321 west street
San Jose
jack
213 north street
San Francisco
123 east street
San Francisco
321 west street
San Jose
213 north street
San Francisco
delete the table's columns where
the column names are "Number"San Francisco
The value to be replaced.
No default
Yes
replacement
text/number/date
The value to replace with.
No default
Yes
213 north street
San Francisco
table
table
The table to perform the replacement in.
No default
Yes
column
text
The name of the column to perform replacement in.
No default
Yes
value
table
The updated table.
john
+ 1 (415) 691 9426
123 east street
San Francisco
joe
+ 1 (415) 691 1234
321 west street
Charlotte
jack
100
10
150
200
5
500
create a sample table
replace "San Jose" in the table's "City" column where
the replacement is "Charlotte"text/number/date
+ 1 (415) 691 4595
column name
string
The name of the column to retrieve.
No default
Yes
column
The specified column from the table.
john
+ 1 (415) 691 9426
123 east street
San Francisco
joe
+ 1 (415) 691 1234
321 west street
San Jose
jack
+ 1 (415) 691 4595
213 north street
123 east street
321 west street
213 north street
123 east street
321 west street
213 north street
get the table's column where
the column name is "Address"San Francisco
table
table
The table to be converted.
No default
Yes
csv file
The CSV representation of the table.
get the column's averageget the column's maxthe foos is "[ { \"a\": 1, \"b\": 2 }, { \"a\": 10, \"b\": 20 } ]"
the foos is a json
convert the foos to a tablethe foos is [
{"name": "Obj 0", "val": {"bar": "baz"}, "arr": [0, 1, 2]},
{"name": "Obj 1", "val": {"bar": "busy"}, "arr": [1, 2, 3]},
{"name": "Obj 2", "val": {"bar": "booze"}, "arr": [2, 3, 4]}
]
the foos is a json
convert the foos to a tablethe foos is [
{"name": "Obj 0", "val": "val 0"},
{"name": "Obj 1", "val": "val 1"},
{"name": "Obj 2", "val": "val 2"}
]
convert the foos to a table
convert the table to a jsonthe person is {"name": "Alice", "age": 30, "city": "NYC"}
convert the person to a tablethe results are [
{
"Customer": "TTX Company Inc. Chicago - IL EDI-WHL",
"Shop Name": "Corporate",
"Invoice Date": "",
"InvoiceId": "",
"Sales ID #": "",
"Current Balance": -9671.33
},
{
"Customer": "TTX Company Inc. Chicago - IL EDI-WHL",
"Shop Name": "Corporate Total",
"Invoice Date": None,
"InvoiceId": None,
"Current Balance": -9671.33
}
]
get the results as a json
convert the results to a tabledelete the table's columns where
the column names are "Name", "Number"create an integer table
replace 300 in the table's "Max" column where
the replacement is 150get the table's "Address" columnconvert the table to csvtable
Table
The table that contains the column to be updated
No default
Yes
the column name
Text
The name of the column to be updated.
No default
Yes
the column values
List
The values to update the column with
No default
Either the column values or the column formula must be provided for this procedure. If the row numbers are specified, then the column values is also required.
the column formula
Text
table
The table with the column updated.
In the examples below, the table refers to the following table, which can be generated using the create a sample table procedure:
john
+ 1 (415) 691 9426
123 east street
San Francisco
joe
+ 1 (415) 691 1234
321 west street
San Jose
jack
+ 1 (415) 691 4595
213 north street
john
+ 1 (415) 691 9426
123 east street
Mountain View
joe
+ 1 (415) 691 1234
321 west street
Cupertino
jack
john
+ 1 (415) 691 9426
123 east street
Dallas
joe
+ 1 (415) 691 1234
321 west street
Dallas
jack
In this example, multiple rows (1 & 2) are updated with the same value (Dallas).
row number
int
The row number (1-based) at which the empty row should be inserted.
Defaults to the end of the table
No
table
The updated table with the new empty row inserted.
For the examples below, consider the following table:
Orion
Nebula
1,344
Vega
Star
25
Titan
Moon
0.0008
insert an empty row in the tableOrion
Nebula
1,344
Vega
Star
25
Titan
Moon
0.0008
Orion
Nebula
1,344
Vega
Star
25
Below is a line-by-line overview of the automation syntax. Expand each line to learn more.
create a sample table
split the sample table into subtablesJohn
+1 (415) 691 9426
123 East Street
San Francisco
Joe
+1 (415) 691 1234
321 West Street
San Jose
Jack
the subtables
John
+1 (415) 691 9426
123 East Street
San Francisco
Joe
+1 (415) 691 1234
321 West Street
table
table
The table to transpose
No default
Yes
index column
text
The name of the index column for the transposed table
No default
No
table
The updated table after transposing.
create an integer table
transpose the table100
200
Amt
10
5
Min
300
500
Max
create a sample table
transpose the table where
the index column is "Name"
the new column names are "A1", "A2", "A3"+ 1 (415) 691 9426
123 east street
San Francisco
+ 1 (415) 691 1234
321 west street
San Jose
+ 1 (415) 691 4595
213 north street
San Francisco
Sorts a table by one or more columns with optional ascending/descending order.
This procedure sorts a table by one or more columns. The sort order (ascending or descending) can be specified. Optionally, you can specify a list of sort orders for multiple columns.
This is useful in a variety of situations—for example, you can sorting a score or sales column, arrange items alphabetically by name or category, or sort by date to show the most recent entries first.
For these examples, say we create a table using the following command:
In this example, no order is specified, so the default sorting order is ascending.
In this example, the "age" column is sorted in descending order.
In this example, both the "city" and "age" columns are sorted in different orders.
Replaces occurrences of a value in a table.
This procedure finds and replaces all instances of a specific value within a table. It can be used to update outdated information, correct mistakes, or standardize values across rows—like changing all instances of "Pending" to "In Progress," or replacing a misspelled name.
Updates a row in the table using values from a JSON object.
This procedure updates a row in the table using values from a JSON object. It's a way to update a table with data in JSON format, such as that from an API response or another part of your automation.
In this example, the first row is set to the JSON.
update the column in the table where
the column name is "City"
the column values are "Mountain View", "Cupertino", "Fremont"update the column in the table where
the column name is "City"
the row numbers are 1,2
the column values are "Dallas"insert an empty row in the table
the row number is 1create a sample table
split the sample table into subtables where
the row count is 2A formula applied to the column
No default
Either the column values or the column formula must be provided for this procedure.
the row numbers
List
The row numbers that apply to the column update
No default
No
the other table
Table
Another table to reference
No default
No
San Francisco
+ 1 (415) 691 4595
213 north street
Fremont
+ 1 (415) 691 4595
213 north street
Fremont
Titan
Moon
0.0008
+1 (415) 691 4595
213 North Street
San Francisco
San Jose
Jack
+1 (415) 691 4595
213 North Street
San Francisco
new column names
text
New names for the transposed columns
No default
No
string/number/date
The replacement or new value.
No default
Yes
213 north street
Santa Clara
table
table
The table to perform the replacement in.
No default
Yes
value
string/number/date
The value to be replaced.
No default
Yes
table
The updated table.
john
+ 1 (415) 691 9426
123 east street
Santa Clara
joe
+ 1 (415) 691 1234
321 west street
San Jose
jack
150
10
300
200
5
500
create a sample table
replace "San Franciso" in the table where
the replacement is "Santa Clara"create an integer table
replace 100 in the table where
the replacement is 150replacement
+ 1 (415) 691 4595
321 west street
San Jose
jack
+ 1 (415) 691 4595
213 north street
San Francisco
row number
number
Row number of the row to update (1-based). It is specified with the where keyword.
No default
Yes
json
dict
The JSON object containing the new values.
No default
Yes
table
The updated table.
alexis
+ 1 (415) 998 7742
987 south street
Atlanta
john
+ 1 (415) 691 9426
123 east street
San Francisco
joe
create a sample table
the json is {"name": "alexis", "Number": + 1 (415) 998 7742, "Address": "987 south street", City: "Atlanta"}
set the row to the json where
the row number is 1
the table is the sample table+ 1 (415) 691 1234
text
Optional sort order for single column. Format: ascending / descending column_name
No default
No
orders
text
Optional list of sort orders for multiple columns. Format: ascending / descending column_name for each column.
No default
No
table
table
The table to be sorted.
No default
Yes
column
text
The column(s) by which the table should be sorted. Can be a single column name or comma-separated list.
No default
Yes
table
The sorted table.
order
create a table where
the column names are "name", "age" and "address"sort the table by "age"sort the table by "age" where
the order is "descending age"sort the table by "city, age" where
the orders are "descending city", "ascending age"table
Table
The table to insert the column into
No default
Yes
column name
Text
The name of the column to insert
No default
Yes
column number
Number
The position of the column to be inserted.
Defaults to the end of the table, if no column number is specified.
No
column values
List
table
The table with the column inserted.
For this example, the table refers to the following table, which can be generated using the create a sample table procedure:
john
+ 1 (415) 691 9426
123 east street
San Francisco
joe
+ 1 (415) 691 1234
321 west street
San Jose
jack
+ 1 (415) 691 4595
213 north street
john
+ 1 (415) 691 9426
123 east street
San Francisco
30
joe
+ 1 (415) 691 1234
321 west street
For this example, the table refers to the following table, which can be generated using the create an integer table procedure:
100
10
30
200
5
500
100
10
30
0.5
200
5
500
0.5
To insert a new row into the table without providing a row number or a reference to a row, we specify data for all the columns in the table.
For this example, the row refers to the following row:
Beet
Red
Root
Converts a table into JSON.
This procedure transforms a given table into its JSON representation. It accepts a table as input and outputs a JSON that represents the table's structure and content.
Below is a line-by-line overview of the automation syntax. Expand each line to learn more.
the json
Address: 123 east street City: San Francisco Name: john Number: + 1 (415) 691 9426
Address: 321 west street City: San Jose Name: joe Number: + 1 (415) 691 1234
Address: 213 north street City: San Francisco Name: jack Number: + 1 (415) 691 4595
Consider the following table that is stored in a .xlsx file:
the json
Harvest Date: 01-15-2025 Harvest Time: '14:30:00' Quantity (kg): 150 Vegetable: Carrot
Harvest Date: 03-20-2025 Harvest Time: '09:00:00' Quantity (kg): 85 Vegetable: Broccoli
The table below lists common datetime codes that can be combined to specify a format string.
Each directive represents a specific component of a date or time, such as year, month, day, etc.
Merge two or more tables based on specified matching and merging criteria.
This procedure generates a merged table by combining data from multiple tables based on user-specified merge criteria. You can designate a master table and a working table and define how rows should be matched (exact or fuzzy match). Additionally, you can configure which columns to include or exclude, how to treat similarly named columns, and whether to sort the columns in the final output.
Below is a line-by-line overview of the automation syntax. Expand each line to learn more.
Retrieves a single row or multiple rows from a table.
This procedure gets a single row or multiple rows from a table. Optionally, a row selection formula can be specified to narrow the retrieval.
Below is a line-by-line overview of the automation syntax. Expand each line to learn more.
A question is raised saying Multiple rows found, please select a row to continue.
the rows
the rows
Copies a table to a new table with a specified name.
This procedure enables users to duplicate an existing table into a new table with a specified name. The new table will contain an exact copy of the data from the original table. This procedure is useful for creating backups, reusing data, or working on temporary versions without altering the original dataset.
In this example, the table is copied and the new table is given the name the backup table.
In this example, the sales data table is copied and the new table is given the name the test table. If any operations are performed on the test table, the sales data table will still hold the original data at the time of the copy and will not be affected.
insert a column in the table where
the column name is "Age"
the column values are 30, 25, 35insert a column in the table where
the column name is "Test Col"
the column formula is @{"type": "column_formula", "value": "conditional_column_copy(.05, Min <= 10)"}insert a row in the table where
the Name is "Beet"
the Color is "Red"
the Type is "Root"insert the row in the table where
the row number is 2json
string or json
The JSON input from which the table will be created.
No default
Yes
table
The table created from the JSON input.
the json
create a table from the jsonAlice
30
Bob
25
In this example, the json will raise a question prompting you to provide the JSON input. You can either enter it directly in the text box or upload a .json file.
The values to populate the column
No default
Either column values or a column formula need to be specified.
column formula
Text
A formula applied to the column
No default
Either column values or a column formula need to be specified.
default value
Text
A default value for the column
No default
No
other table
Table
Another table to reference
No default
No
San Francisco
San Jose
25
jack
+ 1 (415) 691 4595
213 north street
San Francisco
35
the row number is 3the row number is 3This phrase should be written on a new line.
✅ Yes — This phrase is required.
✅ Yes — A reference to the table must be provided.
Indented under convert the table to a json.
❌ No — This phrase is optional.
✅ Yes — Replace your-format with your desired datetime format.
%b
Abbreviated month name
Jun
%d
Day (01-31)
18
%H
Hour (24-hour, 00-23)
14
%I
Hour (12-hour, 01-12)
02
%p
AM/PM
PM
%M
Minute (00-59)
30
%S
Second (00-59)
45
%f
Microsecond (000000-999999)
000123
%z
UTC offset (+HHMM)
+0000
%Z
Timezone name
UTC
%j
Day of year (001-366)
169
%U
Week number (Sun first day)
25
%W
Week number (Mon first day)
25
%c
Locale date & time
Tue Jun 18 14:30:00 2025
%x
Locale date
06/18/25
%X
Locale time
14:30:00
Carrot
2025-01-15
14:30:00
150
Broccoli
2025-03-20
09:00:00
85
%Y
4-digit year
2025
%y
2-digit year
25
%m
Month (01-12)
06
%B
Full month name
create a sample table
convert the table to a jsonJune
the datetime format is "%Y-%d-%m"This phrase should be written on a new line.
✅ Yes — This phrase is required.
✅ Yes — A reference to the table must be defined in the automation.
Indented under get the table's row(s) where.
❌ No — This phrase is optional.
❌ No — This phrase does not require data.
213 north street
San Francisco
jack
+ 1 (415) 691 4595
john
+ 1 (415) 691 9426
123 east street
San Francisco
123 east street
San Francisco
john
+ 1 (415) 691 9426
321 west street
San Jose
joe
john
+ 1 (415) 691 9426
123 east street
San Francisco
jack
+ 1 (415) 691 4595
213 north street
create an sample table
get the table's row+ 1 (415) 691 1234
San Francisco
table
table
The table to be copied.
No default
Yes
table
A new table with the specified name containing the same data as the original table.
This phrase should be written on a new line.
✅ Yes — This phrase is required.
❌ No — This phrase does not require data.
Indented under create a merged table with.
❌ No — This phrase is optional.
✅ Yes — Table References need to be provided.
Indented under create a merged table with.
❌ No — This phrase is optional.
✅ Yes — Replace x with a reference to a table.
Indented under create a merged table with.
❌ No — This phrase is optional.
✅ Yes — Replace y with a reference to a table.
Indented under create a merged table with.
❌ No — This phrase is optional.
✅ Yes — Replace column1, column2, column3, etc. with the names of the columns.
Indented under create a merged table with.
❌ No — This phrase is optional.
✅ Yes — Replace column1, column2, column3, etc. with the names of the columns.
Indented under create a merged table with.
❌ No — This phrase is optional.
✅ Yes — Replace column1, column2, column3, etc. with the names of the columns.
Indented under create a merged table with.
❌ No — This phrase is optional.
✅ Yes — Replace column1, column2, column3, etc. with the names of the columns.
Indented under create a merged table with.
❌ No — This phrase is optional.
✅ Yes — Replace column1, column2, column3, etc. with the names of the columns.
Indented under create a merged table with.
❌ No — This phrase is optional.
✅ Yes — Replace column1, column2, column3, etc. with the names of the columns.
Indented under create a merged table with.
❌ No — This phrase is optional.
✅ Yes — Replace b with a reference to a table.
Indented under create a merged table with.
❌ No — This phrase is optional.
✅ Yes — Use either "on" or "off". Default value is "on", if not specified.
the master table is the abovethe working table is the aboveopen the table at the file
convert the table to a json
the datetime format is "%m-%d-%Y"create an sample table
get the table's row where
the row selection formula is "Name == john"create an sample table
get the table's rowscreate an sample table
get the table's rows where
the row selection formula is "City == San Francisco"copy the table as the backup tablecopy the sales data table as the test tablecreate a merged table with
the tables are the above tablescreate a merged table with
the tables are the above tables
the excluded columns are "FRIEND", "FOE"
the similar columns are "ALIAS" and "NAME", "MONEY" and "WORTH"create a merged table with
the tables are the above tables
the sort columns is "off"open a master table at "s3://my-bucket/data/master_table.xlsx"
open a working table at "s3://my-bucket/data/working_table.xlsx"
open a blacklist table at "s3://my-bucket/data/blacklist_table.xlsx"
create a merged table with
the master table
the working table
the master fuzzy match columns are "name", "age"
the working fuzzy match columns are "nom de guerre", "life span"
the master exact match columns are "address"
the working exact match columns are "location"
the blacklist tablethe blacklist table is the abovethe sort columns is "off"table
table
The table to be cleared.
No default
Yes
table
The cleared table with all data removed but columns retained.
In the example below, the table refers to the following table, which can be generated using the create a sample table procedure:
john
+ 1 (415) 691 9426
123 east street
San Francisco
joe
+ 1 (415) 691 1234
321 west street
San Jose
jack
+ 1 (415) 691 4595
213 north street
clear the tableGets the values of a specified column in a table.
Groups a table by a specified column and optionally aggregates other columns.
This procedure groups a table by the values in a specific column, and optionally aggregates other columns. This helps you organize and summarize data into meaningful categories. It's useful when you want to analyze totals, averages, or counts within each group, such as total sales by region or number of employees per department.
column name
string
The name of the column to retrieve.
No default
Yes
list
The specified column from the table as a list of values.
create a sample table
get the sample table's column's values where
the column name is "City"the values
San Francisco
San Jose
San Francisco
San Francisco
Below is a line-by-line overview of the automation syntax. Expand each line to learn more.
Converts a table into an Excel file with customizable filename and worksheet name.
This procedure converts a table into an Excel (.xlsx) file format. You can optionally specify a custom filename for the Excel file and a custom name for the worksheet. If no custom names are provided, the system will use default values ("Workbook1.xlsx" for the file and "Sheet1" for the worksheet).
Below is a line-by-line overview of the automation syntax. Expand each line to learn more.
Converts a table to Excel using default filename and worksheet name.
Converts a table to Excel with a specific filename.
Converts a table to Excel and uses it as an email attachment.
Retrieves a table's header.
This procedure retrieves a table's header. It returns a list of column names, or labels.
For this example, the table refers to the following table, which can be generated using the create a sample table procedure:
Name Number Address City
create a sample table
group the table's rows by Citygroup the table by City where
the other columns are "Salary's Sum", "Age's Mean"group the table by Projectthe other columns are "Salary's Sum", "Age's Mean"table
table
The table whose column names are to be retrieved.
No default
Yes
column names
The list of column names.
john
+ 1 (415) 691 9426
123 east street
San Francisco
joe
+ 1 (415) 691 1234
321 west street
San Jose
jack
+ 1 (415) 691 4595
213 north street
get the table's column namesSan Francisco
This phrase should be written on a new line.
✅ Yes — This phrase is required.
✅ Yes — A reference to the table must be defined in the automation.
Indented under convert the table to an excel where.
❌ No — This phrase is optional.
✅ Yes — Replace filename.xlsx with your desired filename. The .xlsx extension will be automatically added if not provided. If not specified, a default name will be generated.
Indented under convert the table to an excel where.
❌ No — This phrase is optional.
✅ Yes — Replace worksheet-name with your desired worksheet name. If not specified, defaults to "Sheet1".
the excel filename is "sales-report.xlsx"the worksheet name is "Sales Data"convert the table to an excelconvert the table to an excel where
the excel filename is "my-data.xlsx"
the worksheet name is "Sales Data"convert the table to an excel where
the excel filename is "monthly-report.xlsx"
send "Monthly Report" to "[email protected]" with
the attachment is the excelWhere the thing is replaced by a reference to a CSV or JSON object.
thing (required): The object to be converted into a table. Must be a CSV file or JSON object.
A table created from the CSV or JSON data.
Result: Table created from CSV file contents
Expected table structure:
John Doe
30
50000.5
New York
Jane Smith
25
45000.75
Los Angeles
...
...
...
Result: Round-trip conversion - table → CSV → table preserves data
Result: Table with columns "name" and "val"
Obj 0
val 0
Obj 1
val 1
Result: Single-row table
Alice
30
NYC
convert the csv to a tableconvert <the thing> to a tablethe csv
convert the csv to a tablecreate a sample table
convert the table to a csv
convert the csv to a tablethe foos is [{"name": "Obj 0", "val": "val 0"}, {"name": "Obj 1", "val": "val 1"}]
the foos is a json
convert the foos to a tablethe person is {"name": "Alice", "age": 30, "city": "NYC"}
the person is a json
convert the person to a table...
Use column formulas to dynamically populate and transform column data in your tables.
A column formula is an expression that defines how to calculate values for a table column. Column formulas use data from other columns, tables, or predefined logic to dynamically populate column values in a table. They are useful for:
Data transformation — combining first and last names, extracting values from JSON.
Mathematical operations — calculating totals, differences, or conditional values.
Sequence generation — creating ordered lists of numbers, dates, or time intervals.
In your automation, write:
Then, type a forward slash (/) to open the widget menu.
Select Column Formula.
Provide a Description that explains what the formula does.
Enter the formula expression in the Value field.
combineConcatenates column values together using a specified delimiter.
Syntax
Parameters
Example
This example combines the First Name and Last Name columns with a space in between.
extract_property_from_columnExtracts a property value from a JSON string in a specified column.
Syntax
Parameters
Example
Suppose you have a table where each row contains structured data in the Row with GST column — a JSON string that includes the item name and its GST (Goods and Services Tax) amount. You want to extract the GST value from that JSON and insert it as a new, standalone column called GST.
This command adds a new column named GST by parsing each row’s JSON string and extracting the value associated with the "GST" key.
the table
corresponding_value_from_other_tableRetrieves values from another table using fuzzy matching. It returns the best match, even if that match is reused across multiple rows. Useful when you're okay with repeated matches and just want the closest available value.
Syntax
Parameters
Example
Suppose you are working with two tables from a spreadsheet:
Main Table (Sheet with headers: "Pokemon" to "Finishing Move")
Rating Table (Sheet with headers: "Name" to "Rating")
You want to add the Pokémon’s type from the Main Table to the Rating Table, even if there are small differences in names (e.g., extra spaces or capitalization). Here's how you can define the column:
the rating table
The fuzzy match finds both "Pikachu" rows in the main table and chooses the best match for each.
corresponding_value_from_other_table_uniqueTries to assign each row a unique fuzzy match from another table. It performs a row-by-row comparison, returning a value from a specified column in the second table when the values in a specified column match (depending on the match percentage).
Unlike corresponding_value_from_other_table, this function tries to assign each row in the main table a unique match from the other table. If no unused match is found, it falls back to the previously matched row. This is useful when you want to avoid duplicate matches where possible.
Syntax
Parameters
Example
Suppose you are working with two tables from a spreadsheet:
Main Table (Sheet with headers: "Pokemon" to "Finishing Move")
Rating Table (Sheet with headers: "Name" to "Rating")
You want to add a PType column to the Rating Table that looks up the corresponding Type for each Pokémon from the Main Table. Here, the formula will populate the PType column in the Rating Table with the matching type from the Main Table, based on Pokémon names.
the rating table
sequence_of_numbersGenerates a number sequence that increases by a specified interval.
Syntax
Parameters
Example
This example generates a column of numbers that starts at 10 and increases by 5 for each row.
the table
conditional_column_copyConditionally copies a column value based on a specified condition.
Syntax
Parameters
Example
This example copies values from the "Quantity" column into a new "First Type" column, but only if the value is greater than 12.
the table
Adds two or more columns together. Each column is separated by a space and a + symbol.
Syntax
In this example, a table is created with three integer columns: Amt, Min, and Max using the procedure.
A column formula is then applied to sum the values from these columns, and the result is stored in a new column named Total.
elapsed_time_between_two_date_columnsCalculates the elapsed time between two date columns in specified units.
Syntax
This example calculates the number of days between a Start Date and an End Date column:
construct_dateReturns the date from the row's day, month, and year in a specified format.
sequence_of_datesGenerates a sequence of dates that increment by a specified number of days.
This example creates a column of dates with weekly intervals that start from January 1, 2024.
the table
sequence_of_timesGenerates a sequence of times that increment by a specified number of minutes.
This example generates a column of times that starts at 12:30 AM and increases by 30-minute intervals.
the table
sequence_of_monthsGenerates a sequence of months that increments by a specified number of months.
This example generates a column of months that starts from January 2024 and increments by 2 months.
the table
sequence_of_mondaysGenerates a sequence of Mondays that increments by a specified number of weeks.
This example generates a column of Mondays that starts from January 1, 2024 and increments by 2 weeks.
the table
sequence_of_weekdaysGenerates a sequence of weekdays (Monday to Friday) that start from a given date (skipping weekends).
This example generates a column of weekdays that starts from January 1, 2024 (Monday) and increments by 2 weekdays.
the table
Click Save to insert the formula into your automation.
100.0
Laptop
Store B
{"Item": "Laptop", "GST": 100.0}
200.0
20.0
Gyarados
Water
Gigantic
Hydro Pump
Bulbasaur
Grass
Small
Solar Beam
Pikachu
Wildcard
Small
Thunderbolt
90
Psychic
Gyarados
10
Water
Bulbasaur
23
Grass
Pikachu
100
Wildcard
Gyarados
Water
Gigantic
Hydro Pump
Bulbasaur
Grass
Small
Solar Beam
Gyarados
10
Water
Bulbasaur
23
Grass
delimiter
string
The delimiter used to separate the values. Examples: " ", ",", ";"
*columns
Any
The names of the columns to concatenate.
property_name
string
The property name to extract from the JSON.
column_name
string
The column containing JSON strings.
Book
Store A
{"Item": "Book", "GST": 10.0}
100.0
10.0
Laptop
Store B
{"Item": "Laptop", "GST": 100.0}
200.0
20.0
10.0
Book
Store A
{"Item": "Book", "GST": 10.0}
100.0
10.0
query_column
column
Column in the current table containing the values to match.
other_table_match_column
string
Name of the column in the other table to use for matching.
other_table_return_column
string
Name of the column in the other table to retrieve values from once matched.
Pikachu
Electric
Small
Thunderbolt
Charizard
Fire
Large
Blast Burn
Mewtwo
Psychic
Medium
Pikachu
70
Charizard
80
Mewtwo
90
Gyarados
10
Bulbasaur
23
Pikachu
100
Pikachu
70
Electric
Charizard
80
Fire
query_column
column
Column in the current table containing the values you want to match.
other_table_match_column
string
Name of the column in the other table to compare against.
other_table_return_column
string
Name of the column in the other table whose values you want returned.
match_percentage
int
Minimum match accuracy (0–100) required for values to be considered a match. Exact match = 100.
Pikachu
Electric
Small
Thunderbolt
Charizard
Fire
Large
Blast Burn
Mewtwo
Psychic
Medium
Pikachu
70
Charizard
80
Mewtwo
90
Gyarados
10
Bulbasaur
23
Pikachu
70
Electric
Charizard
80
Fire
Mewtwo
90
start
int
The first number in the sequence.
interval
int
The interval (difference) between consecutive numbers.
A001
10
A002
15
A003
20
column_value
Any
The value to potentially copy.
condition
bool
The condition used to decide whether to copy the value.
A001
10
-
A002
13
13
A003
20
column1
string
The name of the first column to add.
column2
string
The name of the second column to add.
column3
string
The name of the third column to add.
100
10
300
200
5
500
100
10
300
410
200
5
500
705
date_column1
string
The name of the first date column.
date_column2
string
The name of the second date column.
time_unit
string
The unit of time to calculate (days, hours, minutes, seconds).
day
int
The day component.
month
int
The month component.
year
int
The year component.
date_format
string
The format for the output date string (default: "%Y/%m/%d").
start_date
string
Starting date in YYYY-MM-DD format.
interval_days
int
Number of days between consecutive dates.
format
string
The format in which to display the date (default: "%Y-%m-%d").
A001
2024-01-01
A002
2024-01-08
A003
2024-01-15
start_time
string
Starting time in HH:MM format.
interval_minutes
int
Number of minutes between consecutive times.
format
int
Format string for the output time (default: '%I:%M %p').
A001
12:30 AM
A002
01:00 AM
A003
01:30 AM
start_month
string
Starting month in YYYY-MM format.
interval_months
int
Number of months between consecutive dates.
format
string
Format string for the output month (default: '%Y-%m').
A001
2024-01
A002
2024-03
A003
2024-05
start_monday
string
Starting Monday date in YYYY-MM-DD format.
interval_weeks
int
Number of weeks between consecutive Mondays.
format
int
Format string for the output date (default: '%Y-%m-%d').
A001
2024-01-01
A002
2024-01-15
A003
2024-01-29
start_date
string
Starting date in YYYY-MM-DD format.
interval_weekdays
int
Number of weekdays between consecutive dates.
format
int
Format string for the output date (default: '%Y-%m-%d').
A001
2024-01-01
A002
2024-01-03
A003
2024-01-05
Psystrike
Mewtwo
Psystrike
Psychic
20
the column formula iscombine(delimiter, column1, column2, ...)insert a column in the table where
the column name is "Full Name"
the column formula is @{"type": "column_formula", "value": "combine(' ', 'First Name', 'Last Name')"}extract_property_from_column(property_name, column_name)insert a column in the table where
the column name is "GST"
the column formula is @{"type": "column_formula", "value": "extract_property_from_column('GST', 'Row with GST')", "description": "extract the GST from the value in 'Row with GST' column."}corresponding_value_from_other_table(query_column, other_table_match_column, other_table_return_column)get the sheet's table whose first header is "Pokemon" and whose last header is "Finishing Move"
use the above as the main table
get the sheet's table whose first header is "Name" and whose last header is "Rating"
use the above as the rating table
insert a column in the rating table where
the column name is "PType"
the other table is the main table
the column formula is @{"type": "column_formula", "value": "corresponding_value_from_other_table(Name, 'Pokemon', 'Type')"}corresponding_value_from_other_table_unique(query_column, other_table_match_column, other_table_return_column, match_percentage)get the sheet's table whose first header is "Pokemon" and whose last header is "Finishing Move"
use the above as the main table
get the sheet's table whose first header is "Name" and whose last header is "Rating"
use the above as the rating table
insert a column in the rating table where
the column name is "PType"
the other table is the main table
the column formula is @{"type": "column_formula", "value": "corresponding_value_from_other_table_unique(Name, 'Pokemon', 'Type', 80)"}sequence_of_numbers(start, interval)create a table where
the headers are "ID"
the row count is 3
update the column in the table where
the column name is "ID"
the column values are "A001", "A002", "A003"
insert a column in the table where
the column name is "seq"
the column formula is @{"type": "column_formula", "value": "sequence_of_numbers(10, 5)", "description": "Sequence of numbers, starting with 10, interval of 5."}conditional_column_copy(column_value, condition)create a table where
the headers are "ID"
the row count is 3
update the column in the table where
the column name is "ID"
the column values are "A001", "A002", "A003"
insert a column in the table where
the column name is "Quantity"
the column values are 10, 13, 20
insert a column in the table where
the column name is "First Type"
the column formula is @{"type": "column_formula", "value": "conditional_column_copy(Quantity, Quantity > 12)"}{column1} + {column2} + {column3} ...create an integer table
insert a column in the table where
the column name is "Total"
the column formula is @{"type": "column_formula", "value": "Amt +Min + Max", "description": "Sum of all columns"}elapsed_time_between_two_date_columns(date_column1, date_column2, time_unit)insert a column in the table where
the column name is "Days Elapsed"
the column formula is @{"type": "column_formula", "value": "elapsed_time_between_two_date_columns('Start Date', 'End Date', 'days')"}construct_date(day, month, year)insert a column in the table where
the column name is "Start Date"
the column formula is @{"type": "column_formula", "value": "construct_date(2025, July, 30)"}sequence_of_dates(start_date, interval_days, format)create a table where
the headers are "ID"
the row count is 3
update the column in the table where
the column name is "ID"
the column values are "A001", "A002", "A003"
insert a column in the table where
the column name is "dates"
the column formula is @{"type": "column_formula", "value": "sequence_of_dates("2024-01-01", 7, "%Y-%m-%d")", "description": "Sequence of dates starting from Jan 1 2024, incrementing by 7 days"}sequence_of_times(start_time, interval_minutes, format)create a table where
the headers are "ID"
the row count is 3
update the column in the table where
the column name is "ID"
the column values are "A001", "A002", "A003"
insert a column in the table where
the column name is "times"
the column formula is @{"type": "column_formula", "value": "sequence_of_times("12:30 AM", 30, "%I:%M %p")", "description": "Sequence of times starting from 12:30 AM, incrementing by 30 minutes"}sequence_of_months(start_month, interval_months, format)create a table where
the headers are "ID"
the row count is 3
update the column in the table where
the column name is "ID"
the column values are "A001", "A002", "A003"
insert a column in the table where
the column name is "months"
the column formula is @{"type": "column_formula", "value": "sequence_of_months("2024-01", 2, "%Y-%m")", "description": "Sequence of months starting from Jan 2024, incrementing by 2 months"}sequence_of_mondays(start_monday, interval_weeks, format)create a table where
the headers are "ID"
the row count is 3
update the column in the table where
the column name is "ID"
the column values are "A001", "A002", "A003"
insert a column in the table where
the column name is "mondays"
the column formula is @{"type": "column_formula", "value": "sequence_of_mondays("2024-01-01", 2, "%Y-%m-%d")", "description": "Sequence of Mondays starting from Jan 1 2024, incrementing by 2 weeks"}sequence_of_weekdays(start_date, interval_weekdays, format)create a table where
the headers are "ID"
the row count is 3
update the column in the table where
the column name is "ID"
the column values are "A001", "A002", "A003"
insert a column in the table where
the column name is "weekdays"
the column formula is @{"type": "column_formula", "value": "sequence_of_weekdays("2024-01-01", 2, "%Y-%m-%d")", "description": "Sequence of weekdays starting from Jan 1 2024, skipping weekends, interval of 2 weekdays"}