# DABench Task 726 - 2. Perform comprehensive data preprocessing on the 'horsepower' column. Handle any missing values by imputing them with the mean horsepower value. Then, transform the 'horsepower' column by applying a log transformation. Calculate the mean and standard deviation of the transformed 'horsepower' column.

## Task Description

2. Perform comprehensive data preprocessing on the 'horsepower' column. Handle any missing values by imputing them with the mean horsepower value. Then, transform the 'horsepower' column by applying a log transformation. Calculate the mean and standard deviation of the transformed 'horsepower' column.

## Concepts

Comprehensive Data Preprocessing, Feature Engineering, Summary Statistics

## Data Description

Dataset file: `auto-mpg.csv`

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

## Constraints

{
- Handle missing values by imputing them with the mean 'horsepower'.
- Log-transformation should be a natural logarithm (base e).
- Mean and standard deviation should be calculated after the transformation and rounding to two decimal places.
}

## Files

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

## Submission Format

Submit a CSV with columns `id,answer`, containing one row. In the `answer` cell include both markers (space or newline separated) in this order (quote the cell as in the sample to preserve spaces/newlines):
@mean_transformed_horsepower[mean_transformed_horsepower] @stddev_transformed_horsepower[stddev_transformed_horsepower]

"mean_transformed_horsepower" is the mean of the transformed 'horsepower' and "stddev_transformed_horsepower" is the standard deviation of the transformed 'horsepower'. Each value should be a float, rounded to two decimal places.

## 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
