You are given a code snippet that is part of a larger program that deals with parsing and analyzing MNIST datasets. The goal of this problem is to implement a function called `parse_mnist` that can read a CSV file containing MNIST data and store it in a suitable data structure.

The `parse_mnist` function takes two parameters: `input_file` (a string representing the path to the input CSV file) and `output_file` (a string representing the path to the output file). The function should read the data from the input file, excluding the first row (which contains column headers), and store it in an appropriate data structure. The function should then write the parsed data to the output file.

You can assume that the input CSV file follows the following format:
- Each row represents an image in the MNIST dataset.
- The first column of each row consists of the label of the image (an integer).
- The remaining columns of each row consist of the pixel values of the image (integers between 0 and 255).

Your task is to complete the implementation of the `parse_mnist` function so that it correctly parses the input CSV file and writes the parsed data to the output file.

Note:
- You are only required to implement the `parse_mnist` function. The code snippet also includes another function that calculates and prints the accuracy of a given test data. You do not need to modify or implement this function.
- You should use the `csv` module from the Python Standard Library to read and write CSV files.
user
Sure, I can help you with implementing the `parse_mnist` function in Python. Here's a basic structure that you can use:

```python
import csv

def parse_mnist(input_file, output_file):

    # Initialize an empty list to store parsed data
    parsed_data = []

    # Use the csv.reader to parse input file
    with open(input_file, 'r') as csvfile:
        reader = csv.reader(csvfile)
        next(reader, None)  # skip the first row (column headers)

        # Iterate over all rows in input file
        for row in reader:

            # Extract label and image data from row
            label = int(row[0])
            image_data = [int(value) for value in row[1:]]

            # Create a dictionary containing label and image data
            parsed_data.append({'label': label, 'image_data': image_data})

    # Write parsed data to output file using csv.writer
    with open(output_file, 'w', newline='') as csvfile:
        writer = csv.writer(csvfile)

        # Write header row
        writer.writerow(['label', 'image_data'])

        # Write parsed data as rows
        for data in parsed_data:
            writer.writerow(data.values())

    print('Parsed data written to', output_file)
```

In this code, we first initialize an empty list to store the parsed data. We use `csv.reader` to parse the input file, append each row's label and image data to `parsed_data`, and then write this data to the output file using `csv.writer`. The output file header row, as well as each row of the parsed data, is written using the `writerow` method of `csv.writer`.

Please enhance the above code with error handling as per your requirements.
assistant
You are given a code snippet that is part of a larger program that deals with parsing and analyzing MNIST datasets. The goal of this problem is to implement a function called `parse_mnist` that can read a CSV file containing MNIST data and store it in a suitable data structure.

The `parse_mnist` function takes two parameters: `input_file` (a string representing the path to the input CSV file) and `output_file` (a string representing the path to the output file). The function should read the data from the input file, excluding the first row (which contains column headers), and store it in an appropriate data structure. The function should then write the parsed data to the output file.

You can assume that the input CSV file follows the following format:
- Each row represents an image in the MNIST dataset.
- The first column of each row consists of the label of the image (an integer).
- The remaining columns of each row consist of the pixel values of the image (integers between 0 and 255).

Your task is to complete the implementation of the `parse_mnist` function so that it correctly parses the input CSV file and writes the parsed data to the output file.

Note:
- You are only required to implement the `parse_mnist` function. The code snippet also includes another function that calculates and prints the accuracy of a given test data. You do not need to modify or implement this function.
- You should use the `csv` module from the Python Standard Library to read and write CSV files.
user
Sure, here's a simple implementation of the `parse_mnist` function using Python's built-in `csv` module. This function reads the MNIST data from the input CSV file, excludes the first row, and writes the parsed data to the output file.

```python
import csv

def parse_mnist(input_file, output_file):
    # Initialize empty list to store parsed data
    data = []

    # Open input file
    with open(input_file, 'r') as infile:
        # Create a CSV reader
        reader = csv.reader(infile)

        # Skip the first row (column headers)
        next(reader)

        # Parse each row of the CSV file
        for row in reader:
            # Convert string values to integers
            row = list(map(int, row))
            # Add parsed row to data list
            data.append(row)

    # Open output file
    with open(output_file, 'w', newline='') as outfile:
        # Create a CSV writer
        writer = csv.writer(outfile)

        # Write parsed data to output file
        writer.writerows(data)
```

This function first opens the input file and creates a CSV reader to read its contents. It skips the first row using the `next` function, then parses each subsequent row. The `map` function is used to convert each string value in a row to an integer. The parsed row is then added to the `data` list.

After all rows have been parsed, the function opens the output file and creates a CSV writer to write the parsed data. The `writerows` function is used to write all rows in the `data` list to the output file.
assistant