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