something.py

import csv
import os
import xml.etree.ElementTree as ET

# Set the directory containing the dataset files
data_dir = '/path/to/dataset/files/'

# Set the threshold for outlier detection (in standard deviations from the mean)
threshold = 3

# Initialize the output XML report
report = ET.Element('report')

# Loop through all files in the data directory
for filename in os.listdir(data_dir):
    if filename.endswith('.csv'):
        # Open the file and read in the data
        with open(os.path.join(data_dir, filename)) as f:
            reader = csv.reader(f)
            data = list(reader)
        
        # Identify outliers in the data
        for i, row in enumerate(data):
            for j, value in enumerate(row):
                try:
                    value = float(value)
                    mean = sum(float(row[k]) for k in range(len(row)) if k != j) / (len(row) - 1)
                    std_dev = (sum((float(row[k]) - mean)**2 for k in range(len(row)) if k != j) / (len(row) - 1))**0.5
                    if abs(value - mean) > threshold * std_dev:
                        # Replace the outlier value with 'DATAERROR'
                        data[i][j] = 'DATAERROR'
                        
                        # Add a record of the change to the output report
                        record = ET.SubElement(report, 'record')
                        record.set('filename', filename)
                        record.set('line', str(i+1))
                        record.set('column', str(j+1))
                        record.set('value', str(value))
                        record.set('new_value', 'DATAERROR')
                        
                except ValueError:
                    # Skip non-numeric values
                    pass
        
        # Write the updated data back to the file
        with open(os.path.join(data_dir, filename), 'w', newline='') as f:
            writer = csv.writer(f)
            writer.writerows(data)

# Write the output report to a file
with open('report.xml', 'w') as f:
    f.write(ET.tostring(report, encoding='unicode'))