Simple Arithmetic
Simple Arithmetic
You could use arithmetic operators+-*/directly between NumPy arrays, but this section discusses an extension of the same where we have functions that can take any array-like objects e.g. lists, tuples etc. and perform arithmeticconditionally.
Arithmetic Conditionally: means that we can define conditions where the arithmetic operation should happen.
All of the discussed arithmetic functions take awhere parameter in which we can specify that condition.
Addition
Theadd() function sums the content of two arrays, and return the results in a new array.
Example
Add the values in arr1 to the values in arr2:
arr1 = np.array([10, 11, 12, 13, 14, 15])
arr2 = np.array([20, 21, 22, 23, 24, 25])
newarr = np.add(arr1, arr2)
print(newarr)
The example above will return [30 32 34 36 38 40] which is the sums of 10+20, 11+21, 12+22 etc.
Subtraction
Thesubtract() function subtracts the values from one array with the values from another array,and return the results in a new array.
Example
Subtract the values in arr2 from the values in arr1:
arr1 = np.array([10, 20, 30, 40, 50, 60])
arr2 = np.array([20, 21, 22, 23, 24, 25])
newarr = np.subtract(arr1, arr2)
print(newarr)
The example above will return [-10 -1 8 17 26 35] which is the result of 10-20, 20-21, 30-22 etc.
Multiplication
Themultiply() function multiplies the values from one array with the values from another array,and return the results in a new array.
Example
Multiply the values in arr1 with the values in arr2:
arr1 = np.array([10, 20, 30, 40, 50, 60])
arr2 = np.array([20, 21, 22, 23, 24, 25])
newarr = np.multiply(arr1, arr2)
print(newarr)
The example above will return [200 420 660 920 1200 1500] which is the result of 10*20, 20*21, 30*22 etc.
Division
Thedivide() function divides the values from one array with the values from another array,and return the results in a new array.
Example
Divide the values in arr1 with the values in arr2:
arr1 = np.array([10, 20, 30, 40, 50, 60])
arr2 = np.array([3, 5, 10, 8, 2, 33])
newarr = np.divide(arr1, arr2)
print(newarr)
The example above will return [3.33333333 4. 3. 5. 25. 1.81818182] which is the result of 10/3, 20/5, 30/10 etc.
Power
Thepower() function rises the values from the first array to the power of the values of the second array,and return the results in a new array.
Example
Raise the valules in arr1 to the power of values in arr2:
arr1 = np.array([10, 20, 30, 40, 50, 60])
arr2 = np.array([3, 5, 6, 8, 2, 33])
newarr = np.power(arr1, arr2)
print(newarr)
The example above will return [1000 3200000 729000000 6553600000000 2500 0] which is the result of 10*10*10, 20*20*20*20*20, 30*30*30*30*30*30 etc.
Remainder
Both themod() and theremainder() functionsreturn the remainder of the values in the first array corresponding to the values in the second array, and return the results in a new array.
Example
Return the remainders:
arr1 = np.array([10, 20, 30, 40, 50, 60])
arr2 = np.array([3, 7, 9, 8, 2, 33])
newarr = np.mod(arr1, arr2)
print(newarr)
The example above will return [1 6 3 0 0 27] which is the remainders when you divide 10 with 3 (10%3), 20 with 7 (20%7) 30 with 9 (30%9) etc.
You get the same result when using theremainder() function:
Example
Return the remainders:
arr1 = np.array([10, 20, 30, 40, 50, 60])
arr2 = np.array([3, 7, 9, 8, 2, 33])
newarr = np.remainder(arr1, arr2)
print(newarr)
Quotient and Mod
Thedivmod() functionreturn both the quotient and the mod. The return value is two arrays, the first array contains the quotient and second array contains the mod.
Example
Return the quotient and mod:
arr1 = np.array([10, 20, 30, 40, 50, 60])
arr2 = np.array([3, 7, 9, 8, 2, 33])
newarr = np.divmod(arr1, arr2)
print(newarr)
The example above will return:
(array([3, 2, 3, 5, 25, 1]), array([1, 6, 3, 0, 0, 27]))
The first array represents the quotients, (the integer value when you divide 10 with 3, 20 with 7, 30 with 9 etc.
The second array represents the remainders of the same divisions.
Absolute Values
Both theabsolute() and theabs() functions do the same absolute operation element-wise but we should useabsolute() to avoid confusion with python's inbuiltmath.abs()
Example
Return the quotient and mod:
arr = np.array([-1, -2, 1, 2, 3, -4])
newarr = np.absolute(arr)
print(newarr)
The example above will return [1 2 1 2 3 4].
