Specify your increment value: Enter a value from 1-10,000.When using value ranges from two fields, you must create a new field.įield Name: Enter a name for the new field. Where do you want to add the new rows? When using a single field you can add the new rows to your existing field or create a new field to preserve your original data.This option is only available for Date and Date and Time data types, uses all values in the field, and requires that both fields have the same data type. Value ranges from two fields: Generate new rows using a value range between two date fields.Note: The Start value and End value fields can't be used to generate rows outside of your current data set. If you only want to use a range of values to generate the missing rows, set a Start value and End value. This option uses all values in the field. Use this option for Number (whole) or Date data types.īy default, use the minimum and maximum value to generate missing rows. Values from one field: Generate missing rows from values in a single field. How do you want to add new rows? Use one of the following options to select the field or fields where rows are missing.A New Rows step displays in the Flow pane.Ĭomplete the following steps to configure your options to generate the new rows. In the Flow pane, click the plus icon, and select New Rows. With New Rows you can generate the missing rows between the two dates, and create a new field called "All Days" to preserve your original data. Since you don't know how many orders were filled each day, you want the values for the new rows to be Null. Since no sales are recorded for those days, you want the quantity sold value to be zero.Įxample 2: You have a table of sales data where orders filled is recorded using a range of dates. With New Rows you can generate rows for your missing days and add them to you existing field "Days of the week". You need a row for every day, not just the days where you had sales. Set the values for the new rows to be zero, Null, or copy the value from the previous row.Įxample 1: You have a table of sales data, but there are some days where no sales are recorded. ![]()
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