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  • List tuple 类型转成数组

    SKlearning大部分的输入数据都是M * N数组.

    然而我们从数据库或文件读取得来的通常是Python内定的类型tuple或list

    它们的优势就不说了,但是直接把list或tuple构成的二维数组传入scikit是会出问题的. 

    如:

    DeprecationWarning: Passing 1d arrays as data is deprecated in 0.17 and will raise ValueError in 0.19. Reshape your data either using X.reshape(-1, 1) if your data has a single feature or X.reshape(1, -1) if it contains a single sample.
      DeprecationWarning)
    

    下面贴上如何把list/tuple转为scikit使用的array

    首先, 准备数据如下:

    读取一行数据变为一维数组

        conn = sql.connect('result_sale.db')
        conn.text_factory = str
        dataSet = conn.execute('select * from sampleData')
        tpRows = dataSet.fetchone()
        conn.close()
        print type(tpRows)
        print tpRows
    
        lstRows = list(tpRows)
        aryRows1 = np.array(lstRows)  # 转成数组
        #aryRows2 = np.array(lstRows).reshape(1, -1)  # 转成1行N列 (二维数组)
        #aryRows3 = np.array(lstRows).reshape(-1, 1)  # 转成N行1列 (二维数组)
        print lstRows
        print aryRows1

    输入如下: 请留意输入的不同点 :)

    ('00', '01', '02', '03', '04', '05', '06', '07', '08')  (tuple) 
    ['00', '01', '02', '03', '04', '05', '06', '07', '08']  (list)
    ['00' '01' '02' '03' '04' '05' '06' '07' '08']          (array)
    
    Process finished with exit code 0
    

    一次性转换整个数据集

        conn = sql.connect('result_sale.db')
        conn.text_factory = str
        dataSet = conn.execute('select * from sampleData')
        tpRows = dataSet.fetchall()
        conn.close()
    
        aryRows1 = np.array(tpRows)  # 转成数组
        #aryRows2 = np.array(tpRows).reshape(1, -1)  # 转成1行N列 (二维数组)
        #aryRows3 = np.array(tpRows).reshape(-1, 1)  # 转成N行1列 (二维数组)
        print aryRows1
        #print aryRows2
        #print aryRows3

    输入如下:

    [['00' '01' '02' '03' '04' '05' '06' '07' '08']
     ['10' '11' '12' '13' '14' '15' '16' '17' '18']
     ['20' '21' '22' '23' '24' '25' '26' '27' '28']
     ['30' '31' '32' '33' '34' '35' '36' '37' '38']
     ['40' '41' '42' '43' '44' '45' '46' '47' '48']
     ['50' '51' '52' '53' '54' '55' '56' '57' '58']
     ['60' '61' '62' '63' '64' '65' '66' '67' '68']
     ['70' '71' '72' '73' '74' '75' '76' '77' '78']
     ['80' '81' '82' '83' '84' '85' '86' '87' '88']]
    
    Process finished with exit code 0
    

     逐条纪录转换, 可以用下标来引用数组

        conn = sql.connect('result_sale.db')
        conn.text_factory = str
        dataSet = conn.execute('select * from sampleData')
        tpRows = dataSet.fetchall()
        conn.close()
    
        #aryRows = np.zeros([len(tpRows), len(tpRows[0])])
        aryRows = np.ones_like(tpRows) #亦可使用 empty, empty_like, zeros, zeros_like 等方法
    
        j=0
        for row in tpRows:
            aryRows[j][:] = row
            j += 1
        print aryRows

    输入如下:

    [['00' '01' '02' '03' '04' '05' '06' '07' '08']
     ['10' '11' '12' '13' '14' '15' '16' '17' '18']
     ['20' '21' '22' '23' '24' '25' '26' '27' '28']
     ['30' '31' '32' '33' '34' '35' '36' '37' '38']
     ['40' '41' '42' '43' '44' '45' '46' '47' '48']
     ['50' '51' '52' '53' '54' '55' '56' '57' '58']
     ['60' '61' '62' '63' '64' '65' '66' '67' '68']
     ['70' '71' '72' '73' '74' '75' '76' '77' '78']
     ['80' '81' '82' '83' '84' '85' '86' '87' '88']]
    
    Process finished with exit code 0
    
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  • 原文地址:https://www.cnblogs.com/okokok/p/6008753.html
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