Transposerows¶
Bases: FlowComponent
TransposeRows
Overview
The TransposeRows class is a component for transposing specified rows in a DataFrame by converting row values
into new columns based on pivot settings. This component supports options for preserving the original data,
handling empty results, and custom column configurations for the transposition.
.. table:: Properties :widths: auto
+------------------+----------+-----------+---------------------------------------------------------------+
| Name | Required | Summary |
+------------------+----------+-----------+---------------------------------------------------------------+
| pivot | Yes | List of columns to use as the pivot index for transposition. |
+------------------+----------+-----------+---------------------------------------------------------------+
| columns | Yes | Dictionary mapping row values to their target column names. |
+------------------+----------+-----------+---------------------------------------------------------------+
| preserve_original| No | Boolean indicating if the original rows should be preserved. |
+------------------+----------+-----------+---------------------------------------------------------------+
| allow_empty | No | Boolean indicating if empty columns should be allowed in the output. |
+------------------+----------+-----------+---------------------------------------------------------------+
Returns
This component returns a DataFrame with specified rows transposed into columns according to the provided pivot
and column configurations. If `preserve_original` is set to False, the original rows used in transposition
are removed. Any errors in column mapping or pivoting are raised with descriptive error messages.
Example:
```yaml
TransposeRows:
column: column_name
value: data
pivot:
- formid
- form_id
- orgid
preserve_original: true
allow_empty: true
columns:
'000_001': ad_hoc
'000_003': creation_timestamp
'000_004': user_device
000_008: geoloc
000_009: visit_length
'000_012': store_name
'000_013': store_id
'000_023': account_name
'000_024': store_designation
'000_026': region_name
000_029: store_timezone
'000_037': visitor_username
000_038: visitor_name
000_039: visitor_email
'000_045': visitor_role
'000_055': updated_timestamp
'000_065': activity_item_id
'000_063': time_in
'000_064': time_out
'000_066': position_id
'000_067': position_manager
'000_070': visit_status
'194834': retailer
VisitDateLocal: visit_timestamp
```
Add a pivoted column to the dataframe based on the given column name.
Parameters: - df: The input dataframe. - row_to_pivot: The column name to be pivoted. - new_name: The name of the column to be transposed.
Returns: - Dataframe with the new pivoted column.