파이썬 메모리 줄이는 코드 (정형데이터)

파이썬에서 데이터 프레임의 메모리를 줄여주는 코드

def reduce_mem_usage(df):
    """ iterate through all the columns of a dataframe and modify the data type
        to reduce memory usage.        
    """
    start_mem = df.memory_usage().sum() / 1024**2
    # print('Memory usage of dataframe is {:.2f} MB'.format(start_mem))
    cols = [c for c in df.columns if c not in ['log_date', 'date', 'etc_str2']]
    for col in cols:
        # print("#" * 50)
        # print(col, "의 작업을 시작합니다.")
        col_type = df[col].dtype
        if col_type != object:
            c_min = df[col].min()
            c_max = df[col].max()
            if str(col_type)[:3] == 'int':
                if c_min > np.iinfo(np.int8).min and c_max < np.iinfo(np.int8).max:
                    df[col] = df[col].astype(np.int8)
                elif c_min > np.iinfo(np.int16).min and c_max < np.iinfo(np.int16).max:
                    df[col] = df[col].astype(np.int16)
                elif c_min > np.iinfo(np.int32).min and c_max < np.iinfo(np.int32).max:
                    df[col] = df[col].astype(np.int32)
                elif c_min > np.iinfo(np.int64).min and c_max < np.iinfo(np.int64).max:
                    df[col] = df[col].astype(np.int64)  
            else:
                if c_min > np.finfo(np.float16).min and c_max < np.finfo(np.float16).max:
                    df[col] = df[col].astype(np.float16)
                elif c_min > np.finfo(np.float32).min and c_max < np.finfo(np.float32).max:
                    df[col] = df[col].astype(np.float32)
                else:
                    df[col] = df[col].astype(np.float64)

    end_mem = df.memory_usage().sum() / 1024**2
    # print('Memory usage after optimization is: {:.2f} MB'.format(end_mem))
    # print('Decreased by {:.1f}%'.format(100 * (start_mem - end_mem) / start_mem))

    return df

data = reduce_mem_usage(data)

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