DataCleansing
Use the DataCleansing gem to standardize data formats and address missing or null values in the data.
Parameters
| Parameter | Description |
|---|---|
| Remove nulls from entire dataset | Removes any rows that contain null values. This operates on all columns—not just those you selected to clean. |
| Select columns to clean | Specifies the columns to apply data cleansing transformations to. |
| Replace null values in column | Replaces null values in selected columns with a specified default. Example: 0 for numeric columns, empty string for text |
| Remove unwanted characters | Removes specified characters from all values in the selected columns. Example: remove whitespaces or punctuation |
| Modify case | Converts text in selected columns to a specified case format. Example: lowercase, UPPERCASE, Title Case |
Example
Assume you have a dataset that includes all entries from a feedback survey.
| Name | Date | Rating | Feedback |
|---|---|---|---|
| Ada | 2025-04-18 | 5 | I really enjoy the product |
| scott | 2025-04-18 | 5 | NULL |
| emma | 2025-04-17 | 2 | The product is confusing |
| NULL | 2025-04-17 | 3 | NULL |
The following is one way to configure a DataCleansing gem for this table:
- Select columns to clean:
Name - Replace null values in column:
Not provided - Modify case:
Title Case
Result
After the transformation, the table will look like:
| Name | Date | Rating | Feedback |
|---|---|---|---|
| Ada | 2025-04-18 | 5 | I really enjoy the product |
| Scott | 2025-04-18 | 5 | NULL |
| Emma | 2025-04-17 | 2 | The product is confusing |
| Not provided | 2025-04-17 | 3 | NULL |