1. Array to Numpy
import numpy
a = numpy.array([1,2,3,4,5])
print(a[1])
output:
2
2.Using shape to change array dimensions
import numpy
change_array = numpy.array([1,2,3,4,5,6])
change_array.shape = (3, 2)
print change_array
#Output
[[1 2]
[3 4]
[5 6]]
3.reshape
import numpy
my_array = numpy.array([1,2,3,4,5,6])
print numpy.reshape(my_array,(3,2))
#Output
[[1 2]
[3 4]
[5 6]]
4. Transpose
import numpy
my_array = numpy.array([[1,2,3],
[4,5,6]])
print numpy.transpose(my_array)
#Output
[[1 4]
[2 5]
[3 6]]
5. Flatten
import numpy
my_array = numpy.array([[1,2,3],
[4,5,6]])
print my_array.flatten()
#Output
[1 2 3 4 5 6]
6. Concatenation
import numpy
array_1 = numpy.array([1,2,3])
array_2 = numpy.array([4,5,6])
array_3 = numpy.array([7,8,9])
print numpy.concatenate((array_1, array_2, array_3))
#Output
[1 2 3 4 5 6 7 8 9]
import numpy
array_1 = numpy.array([[1,2,3],[0,0,0]])
array_2 = numpy.array([[0,0,0],[7,8,9]])
print numpy.concatenate((array_1, array_2), axis = 1)
#Output
[[1 2 3 0 0 0]
[0 0 0 7 8 9]]
7. Zeros and Ones
Zeros
import numpy
print numpy.zeros((1,2)) #Default type is float
#Output : [[ 0. 0.]]
print numpy.zeros((1,2), dtype = numpy.int) #Type changes to int
#Output : [[0 0]]
Ones
import numpy
print numpy.ones((1,2)) #Default type is float
#Output : [[ 1. 1.]]
print numpy.ones((1,2), dtype = numpy.int) #Type changes to int
#Output : [[1 1]]
8. Addition, Subtraction, Multiply, Integer Division, Mod, Power
import numpy
a = numpy.array([1,2,3,4], float)
b = numpy.array([5,6,7,8], float)
#addition
print a + b #[ 6. 8. 10. 12.]
print numpy.add(a, b) #[ 6. 8. 10. 12.]
#subtraction
print a - b #[-4. -4. -4. -4.]
print numpy.subtract(a, b) #[-4. -4. -4. -4.]
#multiply
print a * b #[ 5. 12. 21. 32.]
print numpy.multiply(a, b) #[ 5. 12. 21. 32.]
#integer division
print a / b #[ 0.2 0.33333333 0.42857143 0.5 ]
print numpy.divide(a, b) #[ 0.2 0.33333333 0.42857143 0.5 ]
#mod
print a % b #[ 1. 2. 3. 4.]
print numpy.mod(a, b) #[ 1. 2. 3. 4.]
#power
print a**b #[ 1.00000000e+00 6.40000000e+01 2.18700000e+03 6.55360000e+04]
print numpy.power(a, b) #[ 1.00000000e+00 6.40000000e+01 2.18700000e+03 6.55360000e+04]
9. floor
import numpy
my_array = numpy.array([1.1, 2.2, 3.3, 4.4, 5.5, 6.6, 7.7, 8.8, 9.9])
print numpy.floor(my_array) #[ 1. 2. 3. 4. 5. 6. 7. 8. 9.]
10. ceil
import numpy
my_array = numpy.array([1.1, 2.2, 3.3, 4.4, 5.5, 6.6, 7.7, 8.8, 9.9])
print numpy.ceil(my_array) #[ 2. 3. 4. 5. 6. 7. 8. 9. 10.]
11. rint
the rint tool rounds to the nearest integer.
import numpy
my_array = numpy.array([1.1, 2.2, 3.3, 4.4, 5.5, 6.6, 7.7, 8.8, 9.9])
print numpy.rint(my_array) #[ 1. 2. 3. 4. 6. 7. 8. 9. 10.]
11. sum
import numpy
my_array = numpy.array([ [1, 2], [3, 4] ])
print numpy.sum(my_array, axis = 0) #Output : [4 6]
print numpy.sum(my_array, axis = 1) #Output : [3 7]
print numpy.sum(my_array, axis = None) #Output : 10
print numpy.sum(my_array) #Output : 10
12. prod
>>>import numpy
>>>my_array = numpy.array([ [1, 2], [3, 4] ])
>>>print numpy.prod(my_array, axis = 0) #Output : [3 8]
>>>print numpy.prod(my_array, axis = 1) #Output : [ 2 12]
>>>print numpy.prod(my_array, axis = None) #Output : 24
>>>print numpy.prod(my_array) #Output : 24
13. min
>>>import numpy
>>>my_array = numpy.array([[2, 5],
[3, 7],
[1, 3],
[4, 0]])
>>>print numpy.min(my_array, axis = 0) #Output : [1 0]
>>>print numpy.min(my_array, axis = 1) #Output : [2 3 1 0]
>>>print numpy.min(my_array, axis = None) #Output : 0
>>>print numpy.min(my_array) #Output : 0
14. max
>>>import numpy
>>>my_array = numpy.array([[2, 5],
[3, 7],
[1, 3],
[4, 0]])
>>>print numpy.max(my_array, axis = 0) #Output : [4 7]
>>>print numpy.max(my_array, axis = 1) #Output : [5 7 3 4]
>>>print numpy.max(my_array, axis = None) #Output : 7
>>>print numpy.max(my_array) #Output : 7
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