numpy-1

作者: CaesarsTesla | 来源:发表于2017-06-15 13:19 被阅读59次
    • 1
    import numpy
    world_alcohol = numpy.genfromtxt("world_alcohol.txt", delimiter=",",dtype=str)
    print(type(world_alcohol))
    print (world_alcohol)
    # print (help(numpy.genfromtxt))
    
    <class 'numpy.ndarray'>
    [['Year' 'WHO region' 'Country' 'Beverage Types' 'Display Value']
     ['1986' 'Western Pacific' 'Viet Nam' 'Wine' '0']
     ['1986' 'Americas' 'Uruguay' 'Other' '0.5']
     ..., 
     ['1987' 'Africa' 'Malawi' 'Other' '0.75']
     ['1989' 'Americas' 'Bahamas' 'Wine' '1.5']
     ['1985' 'Africa' 'Malawi' 'Spirits' '0.31']]
    
    • 2
    #The numpy.array() function can take a list or list of lists as input. When we input a list, we get a one-dimensional array as a result:
    vector = numpy.array([5, 10, 15, 20])
    #When we input a list of lists, we get a matrix as a result:
    matrix = numpy.array([[5, 10, 15], [20, 25, 30], [35, 40, 45]])
    print (vector)
    print (matrix)
    
    [ 5 10 15 20]
    [[ 5 10 15]
     [20 25 30]
     [35 40 45]]
    
    • 3
    #We can use the ndarray.shape property to figure out how many elements are in the array
    vector = numpy.array([1, 2, 3, 4])
    print(vector.shape)
    #For matrices, the shape property contains a tuple with 2 elements.
    matrix = numpy.array([[5, 10, 15], [20, 25, 30]])
    print(matrix.shape)
    
    (4,)
    (2, 3)
    
    • 4
    import numpy
    #Each value in a NumPy array has to have the same data type
    #NumPy will automatically figure out an appropriate data type when reading in data or converting lists to arrays. 
    #You can check the data type of a NumPy array using the dtype property.
    numbers = numpy.array([1, 2, 3, 4])
    print (numbers)
    numbers.dtype
    
    [1 2 3 4]
    dtype('int64')
    
    • 5
    #When NumPy can't convert a value to a numeric data type like float or integer, it uses a special nan value that stands for Not a Number
    #nan is the missing data
    #1.98600000e+03 is actually 1.986 * 10 ^ 3
    world_alcohol
    
    array([['Year', 'WHO region', 'Country', 'Beverage Types', 'Display Value'],
           ['1986', 'Western Pacific', 'Viet Nam', 'Wine', '0'],
           ['1986', 'Americas', 'Uruguay', 'Other', '0.5'],
           ..., 
           ['1987', 'Africa', 'Malawi', 'Other', '0.75'],
           ['1989', 'Americas', 'Bahamas', 'Wine', '1.5'],
           ['1985', 'Africa', 'Malawi', 'Spirits', '0.31']], 
          dtype='<U52')
    
    • 6
    world_alcohol = numpy.genfromtxt("world_alcohol.txt", delimiter=",", dtype=str, skip_header=1)
    print(world_alcohol)
    
    [['1986' 'Western Pacific' 'Viet Nam' 'Wine' '0']
     ['1986' 'Americas' 'Uruguay' 'Other' '0.5']
     ['1985' 'Africa' "Cte d'Ivoire" 'Wine' '1.62']
     ..., 
     ['1987' 'Africa' 'Malawi' 'Other' '0.75']
     ['1989' 'Americas' 'Bahamas' 'Wine' '1.5']
     ['1985' 'Africa' 'Malawi' 'Spirits' '0.31']]
    
    • 7
    uruguay_other_1986 = world_alcohol[1,4]
    third_country = world_alcohol[2,2]
    print (uruguay_other_1986)
    print (third_country)
    
    0.5
    Cte d'Ivoire
    
    • 8
    vector = numpy.array([5, 10, 15, 20])
    print(vector[0:3])
    
    [ 5 10 15]
    
    • 9
    matrix = numpy.array([
                        [5, 10, 15], 
                        [20, 25, 30],
                        [35, 40, 45]
                     ])
    print(matrix[:,1])
    
    [10 25 40]
    
    • 10
    matrix = numpy.array([
                        [5, 10, 15], 
                        [20, 25, 30],
                        [35, 40, 45]
                     ])
    print(matrix[:,0:2])
    
    [[ 5 10]
     [20 25]
     [35 40]]
    
    • 11
    matrix = numpy.array([
                        [5, 10, 15], 
                        [20, 25, 30],
                        [35, 40, 45]
                     ])
    print(matrix[1:3,0:2])
    
    
    [[20 25]
     [35 40]]
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