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:
| Coutry Name   | Indicator                                                         |   2000 |   2001 |   2002 |   2003 |   2004 |   2005 |   2006 |   2007 |   2008 |   2009 |   2010 |   2011 |   2012 |   2013 |   2014 |   2015 |
|:--------------|:------------------------------------------------------------------|-------:|-------:|-------:|-------:|-------:|-------:|-------:|-------:|-------:|-------:|-------:|-------:|-------:|-------:|-------:|-------:|
| Afghnistan    | Overall Global Gender Gap Index                                   |  0.433 |  0.699 |  0.691 |  0.466 |  0.165 |  0.28  |  0.059 |  0.788 |  0.19  |  0.986 |  0.051 |  0.916 |  0.705 |  0.424 |  0.666 |  0.101 |
| Afghnistan    | Global Gender Gap Political Empowerment subindex                  |  0.72  |  0.978 |  0.658 |  0.652 |  1     |  0.346 |  0.125 |  0.434 |  0.195 |  0.847 |  0.863 |  0.418 |  0.038 |  0.429 |  0.504 |  0.982 |
| Afghnistan    | Global Gender Gap Economic Participation and Opportunity Subindex |  0.136 |  0.231 |  0.216 |  0.766 |  0.705 |  0.513 |  0.746 |  0.29  |  0.968 |  0.177 |  0.825 |  0.796 |  0.137 |  0.055 |  0.955 |  0.908 |
| Afghnistan    | Global Gender Gap Educational Attainment Subindex                 |  0.928 |  0.205 |  0.154 |  0.924 |  0.497 |  0.611 |  0.287 |  0.909 |  0.47  |  0.72  |  0.062 |  0.286 |  0.018 |  0.874 |  0.161 |  0.952 |
| Afghnistan    | Global Gender Gap Health and Survival Subinex                     |  0.999 |  0.429 |  1     |  0.743 |  0.334 |  0.757 |  0.35  |  0.09  |  0.565 |  0.598 |  0.791 |  0.801 |  0.588 |  0.902 |  0.175 |  0.283 |
| Angola        | Overall Global Gender Gap Index                                   |  0.784 |  0.17  |  0.887 |  0.594 |  0.386 |  0.343 |  0.969 |  0.302 |  0.541 |  0.039 |  0.585 |  0.152 |  0.267 |  0.703 |  0.352 |  0.657 |
| Angola        | Global Gender Gap Political Empowerment subindex                  |  0.879 |  0.277 |  0.501 |  0.383 |  0.843 |  0.33  |  0.227 |  0.738 |  0.896 |  0.319 |  0.62  |  0.616 |  0.839 |  0.51  |  0.454 |  0.74  |
| Angola        | Global Gender Gap Economic Participation and Opportunity Subindex |  0.011 |  0.371 |  0.261 |  0.764 |  0.947 |  0.031 |  0.188 |  0.918 |  0.802 |  0.033 |  0.599 |  0.906 |  0.788 |  0.504 |  0.425 |  0.176 |
| Angola        | Global Gender Gap Educational Attainment Subindex                 |  0.588 |  0.592 |  0.263 |  0.897 |  0.975 |  0.17  |  0.3   |  0.742 |  0.949 |  0.202 |  0.422 |  0.387 |  0.631 |  0.095 |  0.081 |  0.208 |
| Angola        | Global Gender Gap Health and Survival Subinex                     |  0.647 |  0.752 |  0.004 |  0.067 |  0.181 |  0.269 |  0.381 |  0.365 |  0.736 |  0.958 |  0.09  |  0.56  |  0.982 |  0.631 |  0.857 |  0.417 |
| Albania       | Overall Global Gender Gap Index                                   |  0.406 |  0.969 |  0.475 |  0.873 |  0.32  |  0.885 |  0.692 |  0.485 |  0.184 |  0.468 |  0.791 |  0.79  |  0.147 |  0.579 |  0.605 |  0.174 |
| Albania       | Global Gender Gap Political Empowerment subindex                  |  0.361 |  0.629 |  0.96  |  0.991 |  0.333 |  0.477 |  0.425 |  0.896 |  0.948 |  0.542 |  0.324 |  0.539 |  0.626 |  0.904 |  0.068 |  0.222 |
| Albania       | Global Gender Gap Economic Participation and Opportunity Subindex |  0.964 |  0.604 |  0.033 |  0.779 |  0.353 |  0.645 |  0.66  |  0.294 |  0.96  |  0.533 |  0.53  |  0.131 |  0.392 |  0.503 |  0.039 |  0.9   |
| Albania       | Global Gender Gap Educational Attainment Subindex                 |  0.376 |  0.786 |  0.857 |  0.467 |  0.298 |  0.755 |  0.073 |  0.437 |  0.714 |  0.95  |  0.209 |  0.471 |  0.752 |  0.347 |  0.568 |  0.809 |
| Albania       | Global Gender Gap Health and Survival Subinex                     |  0.084 |  0.745 |  0.036 |  0.962 |  0.814 |  0.307 |  0.22  |  0.12  |  0.763 |  0.053 |  0.545 |  0.753 |  0.843 |  0.602 |  0.977 |  0.901 |

## Output:


source: stackoverflow
label: operator: stack
stack_start_idx: 2
stack_end_idx: 17