import numpy
world_alcohol = numpy.genfromtxt("world_alcohol.txt",delimiter=",")
print(type(world_alcohol))
<class 'numpy.ndarray'>
# The numpy.array() function can take a list or list of lists as input. When we input a list, we get a one-dimensional arrat 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([[5,10,12],[20,25,30],[35,40,45]])
print(vector)
print(matrix)
[ 5 10 15 20]
[[ 5 10 12]
[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([1,2,3,4,5])
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)
(5,)
(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 date type of a NumPy array using the dtype property
numbers = numpy.array([1,2,'3',4.0])
print(numbers)
numbers.dtype
['1' '2' '3' '4.0']
dtype('<U21')
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]]
