对numpy中的数组条件筛选功能详解

In [63]: data = np.array(['int','float','int','boolean','double','boolean'])
In [64]: data
Out[64]:
array(['int', 'float', 'int', 'boolean', 'double', 'boolean'],
  dtype='|S7')
In [65]: np.unique(data)
Out[65]:
array(['boolean', 'double', 'float', 'int'],
  dtype='|S7')
In [66]: data = np.array([1,5,3,6,2,4,1,3,5,7,9])
In [67]: data
Out[67]: array([1, 5, 3, 6, 2, 4, 1, 3, 5, 7, 9])
In [68]: np.unique(data)
Out[68]: array([1, 2, 3, 4, 5, 6, 7, 9])

In [69]: data1 = np.arange(10)
In [70]: data1
Out[70]: array([0, 1, 2, 3, 4, 5, 6, 7, 8, 9])
In [71]: data2 = np.array([2,8,6,4])
In [72]: np.intersect1d(data1,data2)
Out[72]: array([2, 4, 6, 8])

In [73]: np.union1d(data1,data2)
Out[73]: array([0, 1, 2, 3, 4, 5, 6, 7, 8, 9])

In [74]: np.in1d(data1,data2)
Out[74]: array([False, False, True, False, True, False, True, False, True, False], dtype=bool)
In [75]: np.in1d(data2,data1)
Out[75]: array([ True, True, True, True], dtype=bool)

In [76]: np.setdiff1d(data1,data2)
Out[76]: array([0, 1, 3, 5, 7, 9])
In [77]: np.setdiff1d(data2,data1)
Out[77]: array([], dtype=int32)

In [78]: np.setxor1d(data1,data2)
Out[78]: array([0, 1, 3, 5, 7, 9])
In [79]: np.setxor1d(data2,data1)
Out[79]: array([0, 1, 3, 5, 7, 9])