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