科学计算库numpy

import numpy

world_alcohol = numpy.genfromtxt("world_alcohol.txt", delimiter=",", dtype=str)
print(type(world_alcohol))
print (world_alcohol) 
#print (help(numpy.genfromtxt)) #帮助文档
‘‘‘
<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‘]]
‘‘‘

#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]]
‘‘‘

#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)
‘‘‘

#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])
numbers.dtype
‘‘‘
dtype(‘int32‘)
‘‘‘

#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‘)
‘‘‘

world_alcohol = numpy.genfromtxt("world_alcohol.txt", delimiter=",", dtype="U75", 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‘]]
‘‘‘

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
‘‘‘

vector = numpy.array([5, 10, 15, 20])
print(vector[0:3])  
‘‘‘
[ 5 10 15]
‘‘‘

matrix = numpy.array([
                    [5, 10, 15], 
                    [20, 25, 30],
                    [35, 40, 45]
                 ])
print(matrix[:,1])
‘‘‘
[10 25 40]
‘‘‘

matrix = numpy.array([
                    [5, 10, 15], 
                    [20, 25, 30],
                    [35, 40, 45]
                 ])
print(matrix[:,0:2])
‘‘‘
[[ 5 10]
 [20 25]
 [35 40]]
‘‘‘

matrix = numpy.array([
                    [5, 10, 15], 
                    [20, 25, 30],
                    [35, 40, 45]
                 ])
print(matrix[1:3,0:2])
‘‘‘
[[20 25]
 [35 40]]
‘‘‘