Cleanse

The Cleanse action can help eliminate some of the impurities within the dataset to allow better post-processing. For instance, due to human error, there are leading spaces in some cells within a column, "Female" vs. " Female", causing the data to arbitrarily inflate in unique categories. Or in another example, some values are "nulls" within a numeric field, forcing the field to become a string field and lose all the numeric features.

Acho currently supports cleaning action at the column level, and the available cleaning actions are:

• cut string

  • from left

  • from right

• remove a specific character

• padding with a rule

  • from left

  • from right

• uppercase/lowercase standardization

  • capitalize all characters

  • capitalize the first character

  • decapitalize all character

• trim leading zeros

• trim spaces

  • from both left and right

  • from left

  • from right

• replacing string nulls with blanks

• replacing numeric nulls with zero