Data extraction from text in Prompt Engineering / GenAI - Interactive Code Practice

Practice - 5 Tasks

1fill in blank

easy

Complete the code to extract all email addresses from the text using a regular expression.

Prompt Engineering / GenAI

import re
text = "Contact us at [e-mail] or [e-mail]"
emails = re.findall([1], text)
print(emails)

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A"[a-z]+"

B"[0-9]+"

C"\d{3}-\d{2}-\d{4}"

D"[a-zA-Z0-9._%+-]+@[a-zA-Z0-9.-]+\\.[a-zA-Z]{2,}"

Attempts:

3 left

💡 Hint

Common Mistakes

Using a regex that matches only numbers or unrelated patterns.

The regular expression [a-zA-Z0-9._%+-]+@[a-zA-Z0-9.-]+\.[a-zA-Z]{2,} matches typical email addresses in the text.

2fill in blank

medium

Complete the code to extract all dates in the format YYYY-MM-DD from the text.

Prompt Engineering / GenAI

import re
text = "The event is on 2024-06-15 and registration ends 2024-05-30."
dates = re.findall([1], text)
print(dates)

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A"\d{2}/\d{2}/\d{4}"

B"\d{4}-\d{2}-\d{2}"

C"[a-zA-Z]+ \d{1,2}, \d{4}"

D"\d{4}/\d{2}/\d{2}"

Attempts:

3 left

💡 Hint

Common Mistakes

Using slashes instead of dashes or wrong digit counts.

The regex \d{4}-\d{2}-\d{2} matches dates in the format YYYY-MM-DD.

3fill in blank

hard

Fix the error in the code to extract phone numbers in the format (XXX) XXX-XXXX.

Prompt Engineering / GenAI

import re
text = "Call me at [phone] or [phone]."
phones = re.findall([1], text)
print(phones)

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A"\(\d{3}\) \d{3}-\d{4}"

B"\d{3}-\d{3}-\d{4}"

C"\(\d{3}\)\d{3}-\d{4}"

D"\d{10}"

Attempts:

3 left

💡 Hint

Common Mistakes

Not escaping parentheses or missing the space after them.

The regex \(\d{3}\) \d{3}-\d{4} correctly matches phone numbers with parentheses and space.

4fill in blank

hard

Fill both blanks to create a dictionary of words and their lengths from the text, including only words longer than 4 letters.

Prompt Engineering / GenAI

text = "Machine learning extracts useful data from text"
words = text.split()
lengths = { [1] : [2] for word in words if len(word) > 4 }
print(lengths)

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Aword

Blen(word)

Cword.upper()

Dlen(text)

Attempts:

3 left

💡 Hint

Common Mistakes

Using the whole text length or uppercase words as keys or values.

The dictionary comprehension uses each word as key and its length len(word) as value, filtering words longer than 4 letters.

5fill in blank

hard

Fill all three blanks to create a dictionary of uppercase words and their lengths, including only words with length greater than 3.

Prompt Engineering / GenAI

text = "Data extraction from text is useful"
words = text.split()
result = { [1] : [2] for word in words if [3] }
print(result)

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Aword.upper()

Blen(word)

Clen(word) > 3

Dword.lower()

Attempts:

3 left

💡 Hint

Common Mistakes

Using lowercase words as keys or wrong filter conditions.

The dictionary comprehension uses the uppercase version of each word as key, its length as value, and filters words longer than 3 letters.