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初级

WHERE：大于等于条件

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初级参考 完整示例代码供参考，建议自己理解后重新输入 
def solve():
    import sqlite3
    import pandas as pd
    conn = sqlite3.connect(':memory:')
    df = pd.read_csv('https://liangdaima.com/static/data/german_credit_risk.csv')
    df.to_sql('german_credit_risk', conn, index=False)
    result = conn.execute('SELECT * FROM german_credit_risk WHERE "Credit amount" >= 10000').fetchall()
    conn.close()
    return result

示例

输入
print(solve())
期望输出
[(18, 44, 'female', 3, 'free', 'little', 'moderate', 12579, 24, 'car', 'bad'), (63, 25, 'male', 2, 'own', 'little', 'moderate', 14421, 48, 'business', 'bad'), (87, 47, 'male', 2, 'free', 'moderate', 'moderate', 12612, 36, 'education', 'bad'), (95, 58, 'male', 2, 'rent', 'little', 'moderate', 15945, 54, 'business', 'bad'), (105, 39, 'male', 3, 'own', 'little', 'moderate', 11938, 24, 'vacation/others', 'bad'), (134, 21, 'female', 2, 'own', 'moderate', None, 10144, 60, 'radio/TV', 'good'), (205, 38, 'male', 3, 'free', 'little', 'little', 10623, 30, 'car', 'good'), (226, 27, 'male', 2, 'own', 'rich', 'moderate', 10961, 48, 'radio/TV', 'bad'), (236, 23, 'male', 0, 'own', None, 'moderate', 14555, 6, 'car', 'bad'), (272, 36, 'male', 3, 'free', None, 'moderate', 12169, 48, 'car', 'good'), (274, 34, 'male', 1, 'own', 'little', 'little', 11998, 30, 'repairs', 'bad'), (285, 35, 'female', 1, 'own', 'little', 'little', 10722, 47, 'car', 'good'), (304, 44, 'male', 2, 'free', 'quite rich', None, 10127, 48, 'car', 'bad'), (333, 24, 'female', 1, 'rent', 'moderate', None, 11590, 48, 'car', 'bad'), (373, 63, 'male', 3, 'free', None, None, 13756, 60, 'car', 'good'), (374, 60, 'female', 3, 'free', 'moderate', 'moderate', 14782, 60, 'vacation/others', 'bad'), (378, 57, 'male', 3, 'free', 'little', 'moderate', 14318, 36, 'car', 'bad'), (381, 38, 'female', 3, 'free', 'little', 'moderate', 12976, 18, 'car', 'bad'), (395, 32, 'male', 2, 'rent', 'moderate', 'moderate', 11760, 39, 'education', 'good'), (431, 29, 'male', 3, 'own', 'little', 'moderate', 11328, 24, 'vacation/others', 'bad'), (450, 30, 'male', 3, 'own', None, None, 11054, 36, 'car', 'good'), (563, 37, 'male', 2, 'free', None, 'moderate', 12389, 36, 'car', 'bad'), (615, 48, 'male', 3, 'own', None, 'moderate', 12204, 48, 'business', 'good'), (637, 21, 'male', 2, 'own', 'little', None, 15653, 60, 'radio/TV', 'good'), (657, 37, 'male', 2, 'own', None, None, 10222, 48, 'radio/TV', 'good'), (672, 42, 'male', 3, 'own', 'little', None, 10366, 60, 'car', 'good'), (714, 27, 'male', 3, 'own', 'little', 'moderate', 14027, 60, 'car', 'bad'), (736, 23, 'female', 3, 'rent', 'little', 'moderate', 11560, 24, 'car', 'bad'), (744, 30, 'male', 3, 'own', None, 'little', 14179, 39, 'furniture/equipment', 'good'), (763, 30, 'male', 3, 'free', None, None, 12680, 21, 'car', 'bad'), (818, 43, 'male', 3, 'own', 'little', 'little', 15857, 36, 'vacation/others', 'good'), (832, 29, 'male', 2, 'rent', 'little', 'little', 11816, 45, 'business', 'bad'), (854, 45, 'male', 2, 'own', 'little', None, 10875, 36, 'car', 'good'), (887, 23, 'male', 2, 'own', 'little', 'moderate', 15672, 48, 'business', 'bad'), (902, 42, 'male', 2, 'free', None, None, 10477, 36, 'car', 'good'), (915, 32, 'female', 3, 'own', 'little', 'moderate', 18424, 48, 'vacation/others', 'bad'), (917, 68, 'male', 3, 'own', 'little', 'little', 14896, 6, 'car', 'bad'), (921, 37, 'male', 3, 'own', 'quite rich', None, 12749, 48, 'radio/TV', 'good'), (927, 39, 'male', 2, 'free', 'little', 'little', 10297, 48, 'car', 'bad'), (953, 26, 'female', 3, 'own', 'little', None, 10974, 36, 'furniture/equipment', 'bad')]
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