To extract all valid email addresses from the text, we can use regular expressions. Here's the Python code to accomplish this: ```python import re text = "Contact information:\n1. John Doe - john.doe@example.com\n2. Jane Smith - jane@smith-family.net\n3. support@company.co.uk\n4. info@subdomain.example.org\n5. Invalid email: not.an.email.com\n6. Another invalid: @missing-username.com" # Regular expression pattern for email addresses pattern = r'\b[A-Za-z0-9._%+-]+@[A-Za-z0-9.-]+\.[A-Z|a-z]{2,}\b' # Find all matches of the pattern in the text matches = re.findall(pattern, text) # Join the matches into a comma-separated list result = ','.join(matches) result ``` I will now execute this code to extract the valid email addresses from the text. ```python import re text = "Contact information:\n1. John Doe - john.doe@example.com\n2. Jane Smith - jane@smith-family.net\n3. support@company.co.uk\n4. info@subdomain.example.org\n5. Invalid email: not.an.email.com\n6. Another invalid: @missing-username.com" # Regular expression pattern for email addresses pattern = r'\b[A-Za-z0-9._%+-]+@[A-Za-z0-9.-]+\.[A-Z|a-z]{2,}\b' # Find all matches of the pattern in the text matches = re.findall(pattern, text) # Join the matches into a comma-separated list result = ','.join(matches) result ```