Task: Data-transform-reshape (source dataset: Auto-Tables)

Given a table, predict what python pandas transformation may be needed on the given input table. Valid choices for transformation include: {"stack", "wide_to_long", "transpose", "pivot", "explode", "ffill", "subtitles"}. Note that each of these is a common Python Pandas operator. Some transformations can have parameters. Each transformation and its parameters are describe as follows.
 
- stack: collapse homogeneous cols into rows.
@param (int): stack_start_idx: zero-based starting column index of the homogeneous column-group.
@param (int): stack_end_idx: zero-based ending column index of the homogeneous column-group.
 
- wide_to_long: collapse repeating col-groups into rows.
@param (int): wide_to_long_start_idx: zero-based starting column index of the repeating col-groups.
@param (int): wide_to_long_end_idx: zero-based ending column index of the repeating col-groups.
 
- transpose: convert rows to columns and vice versa.
 
- pivot: pivot repeating row-groups into cols.
@param (int): pivot_row_frequency: frequency of repeating row-groups.
 
- ffill: fill structurally empty cells in tables.
@param (int): ffill_end_idx: zero-based ending column index of the columns to be filled.
 
- explode: convert composite cells into atomic values
@param (int): explode_column_idx: zero-based column index of the column to be exploded.
 
- subtitle: convert table subtitles into a column.
 
OUTPUT the predicted transformation name along with its parameters for the given INPUT table in a JSON, e.g., {"transformation": "stack", "stack_start_idx": 1, "stack_end_idx": 5}. If the input table needs multi-step transformations (e.g, ffill followed by stack), list JSON of each transformation sequentially in a list, e.g., [{"transformation": "ffill", "ffill_end_idx": 1}, {"transformation": "stack", "stack_start_idx": 1, "stack_end_idx": 5}]. No explanation is needed.

## Input:
| Name          |   ID | Task 1 Description   | Task 1 Completed?   | Task 2 Description   | Task 2 Completed?   | Task 3 Description   | Task 3 Completed?   |
|:--------------|-----:|:---------------------|:--------------------|:---------------------|:--------------------|:---------------------|:--------------------|
| John Smith    |    1 | Buy a house          | Yes                 | Build a car          | No                  | Run a marathon       | Yes                 |
| Ryan Miller   |    2 | Buy a car            | No                  | Plant a tree         | Yes                 | Walk your dog        | No                  |
| Jude Rojas    |    3 | Buy a bike           | Yes                 | Build a house        | No                  | Play basketball      | No                  |
| Willow Howard |    4 | Buy a phone          | Yes                 | Build a car          | No                  | Play Tennis          | Yes                 |
| Cailyn Lee    |    5 | Buy a bike           | No                  | Plant a tree         | Yes                 | Walk your cat        | No                  |
| Erin Barry    |    6 | Buy a phone          | No                  | Build a house        | Yes                 | Run a marathon       | No                  |
| Makhi Pratt   |    7 | Buy a house          | Yes                 | Build a car          | No                  | Walk your dog        | No                  |
| Matilda Mills |    8 | Buy a bike           | No                  | Build a car          | No                  | Run a marathon       | Yes                 |
| Rashad Wood   |    9 | Buy a phone          | Yes                 | Build a house        | Yes                 | Walk your dog        | No                  |

## Output:


source: notebook
label: operator: wide_to_long
wide_to_long_start_idx: 2
wide_to_long_end_idx: 7