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:
| Amortising Interest rate swap             | Class A                | Class B                | Class C                | Class D                | Class E                | Class F                | Class G                |
|:------------------------------------------|:-----------------------|:-----------------------|:-----------------------|:-----------------------|:-----------------------|:-----------------------|:-----------------------|
| Initial principal                         | 690000000              | 24400000               | 99000000               | 58000000               | 31000000               | 46000000               | 98000000               |
| Underlying principal for Reporting period | 59348349               | 3074112.08             | 8978405.63             | 9318573.30             | 1210634.08             | 8373086.98             | 9370171.44             |
| Paying leg                                | Fixed Interest rate    | Fixed Interest rate    | Fixed Interest rate    | Fixed Interest rate    | Fixed Interest rate    | Fixed Interest rate    | Fixed Interest rate    |
| Receiving leg                             | Floating Interest rate | Floating Interest rate | Floating Interest rate | Floating Interest rate | Floating Interest rate | Floating Interest rate | Floating Interest rate |
| Net swap payments / Net swap receipts     | 107234.23              | 5742.35                | 83930.07               | 55203.29               | 33786.59               | 39646.89               | 87938.24               |

## Output:


source: excel_file
label: transpose