# DABench Task 220 - Perform comprehensive data preprocessing for the given dataset. This should include data cleaning, handling missing values, and feature engineering. Provide the cleaned dataset, and if any missing values were found, explain the strategy used to handle them. Additionally, generate a new feature called "diff_range" that represents the range of difference in selection (max_diffsel - min_diffsel) for each site.

## Task Description

Perform comprehensive data preprocessing for the given dataset. This should include data cleaning, handling missing values, and feature engineering. Provide the cleaned dataset, and if any missing values were found, explain the strategy used to handle them. Additionally, generate a new feature called "diff_range" that represents the range of difference in selection (max_diffsel - min_diffsel) for each site.

## Concepts

Comprehensive Data Preprocessing, Feature Engineering

## Data Description

Dataset file: `ferret-Pitt-2-preinf-lib2-100_sitediffsel.csv`

The data is available in the `train.csv` file in the public directory.

## Constraints

For data cleaning, ensure that there are no duplicated records or inconsistencies in the dataset. If missing values are found in any of the columns, use mean imputation to fill these missing values. For feature engineering, create a new column "diff_range" calculated as the difference between max_diffsel column and min_diffsel column.

## Files

- `train.csv` - The training data
- `sample_submission.csv` - A sample submission file in the correct format

## Submission Format

Submit a single-row CSV with columns `id,answer`.

- `id`: always `220`
- `answer`: `@missing_values_handling[<handling_description>]` where the description explains how missing values were handled (use "No missing values were found." if none).

## Evaluation

Submissions are evaluated on **exact match** with the ground truth answer (with tolerance of 0.01 for floating-point values).

## Goal

Provide the correct answer in the specified format.

## Difficulty Level

Hard
