Tmelt¶
Bases: FlowComponent
tMelt
Overview
The tMelt class is a component for transforming a DataFrame from a wide format to a long format using the
Pandas `melt` function. It reshapes data by unpivoting columns, making it easier to analyze or process data
with a simpler, long-form structure.
.. table:: Properties
:widths: auto
+----------------+----------+-----------+---------------------------------------------------------------+
| Name | Required | Summary |
+----------------+----------+-----------+---------------------------------------------------------------+
| index | Yes | Column(s) to use as identifier variables for melting. |
+----------------+----------+-----------+---------------------------------------------------------------+
| name | No | Name to use for the "variable" column in the result DataFrame. |
| | | Defaults to "name". |
+----------------+----------+-----------+---------------------------------------------------------------+
| value | No | Name to use for the "value" column in the result DataFrame. |
| | | Defaults to "value". |
+----------------+----------+-----------+---------------------------------------------------------------+
| values | No | List of columns to unpivot. If None, all remaining columns are used. |
+----------------+----------+-----------+---------------------------------------------------------------+
Returns
This component returns a DataFrame in long format where specified columns are unpivoted to create two
new columns: one for variable names (`name`) and one for values (`value`). Metrics on the row and column
counts of the transformed DataFrame are recorded. Any errors during transformation are logged and raised
with descriptive error messages.
Example:
```yaml
tMelt:
index:
- AL No.
- Store Format
name: product_name
value: displays_quantity
```