<jupyter_start><jupyter_text>Find Gender from First Name<jupyter_code>def find_gender_from_first_name(name):
    if name.upper() in new_male_list:
        print "Male"
    elif name.upper() in new_female_list:
        print "Female"
    else:
        print "Unknown"<jupyter_output><empty_output><jupyter_text>Let's do some Gender Testing<jupyter_code>find_gender_from_first_name('Harsh')
find_gender_from_first_name('Marry')
find_gender_from_first_name('Satya')<jupyter_output>Unknown
{'fraction_non_alphanumeric': 0.09690721649484536, 'fraction_numerical': 0.0, 'mean_word_length': 6.476923076923077, 'pattern_counts': {'":': 0, '<': 8, '<?xml version=': 0, '>': 8, 'https://': 0, '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': '2', 'dir': 'jupyter-structured-clean-dedup', 'id': '165607', 'license': 'MIT', 'n_tokens_mistral': 185, 'n_tokens_neox': 174, 'n_words': 27, 'path': 'src/Gender_Prediction.ipynb', 'repo_name': 'tapilab/is-hparik11', 'size': '485'}