将此权重/比例转换为列名列表，并使用Python根据其权重/分数矩阵格式进行排序

Question

将此权重/分数读数从输入.csv文件转换为列名列表，并使用Python Apache Beam按其降序权重/分数矩阵格式排序并写入另一个.csv文件

    Input .csv file
    user_id, cat_1, cat_2, cat_3, cat_4, cat_5, cat_6
    1 , 0.10, 0.2, 0.20, 0.12, 0.7, 0.6 
    2 , 0.6, 0.20, 0.12, 0.15, 0.13, 0.11    
    3 , 0.11, 0.10, 0.8, 0.12, 0.3, 0.7   


    Desired output .csv file 
    user_id, top_3_categories
    1, [('cat_3', '0.20'), ('cat_2', '0.2'), ('cat_1', '0.10')]
    2, [('cat_1', '0.6'), ('cat_2', '0.20'), ('cat_3', '0.12')]
    3, [('cat_3', '0.8'), ('cat_1', '0.11'), ('cat_2', '0.10')]

Answer 1

以下步骤使用pandas生成所需的输出：

with beam.Pipeline() as p:

    lines = p | "ReadCsv" >> ReadFromText(file_pattern="input_csv",skip_header_lines=1)

    def process_csv(line):
        import pandas as pd
        line = line.split(',')
        df = pd.DataFrame(data=[line],columns=['user_id', 'cat_1', 'cat_2', 'cat_3', 'cat_4', 'cat_5', 'cat_6']).set_index('user_id')
        df['top_3_categories'] = df.apply(lambda x: x.sort_values(ascending=False).iloc[:3].to_dict(OrderedDict), axis=1)
        df = df['top_3_categories'].apply(lambda x: str([(k,v) for k,v in x.iteritems()])).reset_index()

        return ",".join(list(df.iloc[0].values))

    lines = lines | "Process Data" >> beam.Map(fn=process_csv)
    lines | "Write csv" >> WriteToText(file_path_prefix="output.csv")