<jupyter_start><jupyter_text>1. Fill the missing piecesFill the `____` parts in the code below.<jupyter_code>words = ['PYTHON', 'JOHN', 'chEEse', 'hAm', 'DOE', '123']
upper_case_words = []

for word in words:
    if word.isupper():
        upper_case_words.append(word)
assert upper_case_words == ['PYTHON', 'JOHN', 'DOE']<jupyter_output><empty_output><jupyter_text>2. Calculate the sum of dict valuesCalculate the sum of the values in `magic_dict` by taking only into account numeric values (hint: see [isinstance](https://docs.python.org/3/library/functions.htmlisinstance)).<jupyter_code>magic_dict = dict(val1=44, val2='secret value', val3=55.0, val4=1)
# Your implementation
sum_of_values =  sum(x for x in magic_dict.values() if type(x)!= str )   
assert sum_of_values == 100<jupyter_output><empty_output><jupyter_text>3. Create a list of strings based on a list of numbersThe rules:* If the number is a multiple of five and odd, the string should be `'five odd'`* If the number is a multiple of five and even, the string should be `'five even'`* If the number is odd, the string is `'odd'`* If the number is even, the string is `'even'`<jupyter_code>numbers = [1, 3, 4, 6, 81, 80, 100, 95]
# Your implementation
my_list = []
for num in numbers:
    if num%5==0:
        if num%2!=0:
            my_list.append('five odd')
        else:
            my_list.append('five even')
    elif num%2!=0:
        my_list.append('odd')
    else:
        my_list.append('even')
assert my_list == ['odd', 'odd', 'even', 'even', 'odd', 'five even', 'five even', 'five odd']<jupyter_output><empty_output>
{'fraction_non_alphanumeric': 0.13847117794486216, 'fraction_numerical': 0.02443609022556391, 'mean_word_length': 4.377104377104377, 'pattern_counts': {'":': 0, '<': 13, '<?xml version=': 0, '>': 13, 'https://': 1, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 0, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
{'chain_length': '3', 'dir': 'jupyter-structured-clean-dedup', 'id': '112604', 'license': 'MIT', 'n_tokens_mistral': 574, 'n_tokens_neox': 546, 'n_words': 176, 'path': 'notebooks/beginner/exercises/for_loops_exercise.ipynb', 'repo_name': 'dramnay/learn-python3', 'size': '1596'}