Columnize CSVs

Convert comma-separated values into a dataset format of rows and columns that can be easily analyzed and manipulated.

Parameters

  • Source Column: The column name containing the comma-separated values you want to convert. Defaults to content.
  • Delimiter: The delimiter used to separate cells in the comma-separated value. Defaults to ,.

Usage

To use the Columnize CSVs transformation, you will need to follow these steps:

  1. Specify the Source Column parameter with the name of the column that contains the text data you want to columnize.
  2. Specify the Delimiter parameter used to separate cells, default is ,.
  3. Run the transformation by clicking the Save and Run Transforms button.

Example 1: Tab-separated Values

Suppose we have a dataset with the following tab-separated values (TSV) data in the 'content' column:

product_id  product_name  price
1           Laptop        899.99
2           Tablet        499.99
3           Smartphone    699.99

To columnize the TSV data, configure the transformation as follows:

  • Source Column: content
  • Delimiter: \t (tab character)

The resulting structured dataset would look like this:

product_id | product_name | price
1          | Laptop       | 899.99
2          | Tablet       | 499.99
3          | Smartphone   | 699.99

Example 2: Custom Delimiter

Suppose we have a dataset with the following data using a custom delimiter (pipe | character) in the 'content' column:

order_id|customer_id|product_id|quantity
1001|1|1|2
1002|2|3|1
1003|3|2|4

To columnize the data with a custom delimiter, configure the transformation as follows:

  • Source Column: content
  • Delimiter: |

The resulting structured dataset would look like this:

order_id | customer_id | product_id | quantity
1001     | 1           | 1          | 2
1002     | 2           | 3          | 1
1003     | 3           | 2          | 4

Example 3: Data with Quotes

Suppose we have a dataset with the following data using quotes for values containing commas, stored in the 'content' column:

ID,Name,Address
1,John Doe,"123 Main St, Suite 400"
2,Jane Smith,"456 Elm St, Apartment 20A"

To columnize the data containing quotes, configure the transformation as follows:

  • Source Column: content
  • Delimiter: ,

The resulting structured dataset would look like this:

ID | Name     | Address
1  | John Doe | 123 Main St, Suite 400
2  | Jane Smith | 456 Elm St, Apartment 20A

The Columnize CSV transformation correctly handles values enclosed in quotes, ensuring accurate parsing of the dataset.