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:
| Column1   |   Column2 |    2012 |    2013 | 2014               |
|:----------|----------:|--------:|--------:|:-------------------|
| Company 1 |         0 | 0       | 2.52    | 2.64               |
|           |         1 | 0       | 2.20667 | 2.0585714285714287 |
|           |         2 | 0       | 2.09413 | 2.3811069090909087 |
|           |         3 | 0       | 1.9075  | 2.0625             |
| Company 2 |         0 | 2.46667 | 2.54667 | 0.0                |
|           |         1 | 2.35    | 2.44    | 0.0                |
|           |         2 | 2.073   | 2.272   | 0.0                |
|           |         3 | 0       | 0       | 0.0                |
| Company 3 |         0 | 0       | 2.60833 | 3.155              |
|           |         1 | 0       | 2.308   | 2.4778333333333333 |
|           |         2 | 0       | 2.30389 | 2.54425            |
|           |         3 | 0       | 0       | 0.0                |
| Company 4 |         0 | 0       | 0       | 0.0                |
|           |         1 | 2.15    | 2.21    | 0.0                |
|           |         2 | 2.05    | 2.21    | 0.0                |
|           |         3 | 0       | 0       | 0.0                |
| Company 5 |         0 | 2.2     | 2.47    | 0.0                |
|           |         1 | 0       | 0       | 0.0                |
|           |         2 | 1.67    | 1.87    | 0.0                |
|           |         3 | 0       | 0       | 0.0                |
| Company 6 |         0 | 0       | 0       | 0.0                |
|           |         1 | 0       | 0       |                    |
|           |         2 | 0       | 1.84786 | 1.55               |
|           |         3 | 0       | 0       |                    |

## Output:


source: excel_file
label: operator: ffill
ffill_end_idx: 0
operator: stack
stack_start_idx: 2
stack_end_idx: 4
alternative_label: operator: stack
stack_start_idx: 2
stack_end_idx: 4
operator: ffill
ffill_end_idx: 0