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 arithmetic conditionally.
Arithmetic Conditionally: means that we can define conditions where the arithmetic operation should happen.
All of the discussed arithmetic functions take a where parameter in which we can specify that condition.
Addition
The add() 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:
import numpy as np
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)
Try it Yourself »
The example above will return [30 32 34 36 38 40] which is the sums of 10+20, 11+21, 12+22 etc.
Subtraction
The subtract() 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:
import numpy as np
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)
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The example above will return [-10 -1 8 17 26 35] which is the result of 10-20, 20-21, 30-22 etc.
Multiplication
The multiply() 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:
import numpy as np
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)
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The example above will return [200 420 660 920 1200 1500] which is the result of 10*20, 20*21, 30*22 etc.
Division
The divide() 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:
import numpy as np
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)
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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
The power() 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:
import numpy as np
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)
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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 the mod() and the remainder() functions
return 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:
import numpy as np
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)
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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 the remainder() function:
Example
Return the remainders:
import numpy as np
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)
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Quotient and Mod
The divmod() function
return 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:
import numpy as np
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)
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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 the absolute() and the abs() functions
do the same absolute operation element-wise but we should use absolute()
to avoid confusion with python's inbuilt math.abs()
Example
Return the quotient and mod:
import numpy as np
arr = np.array([-1, -2, 1, 2, 3, -4])
newarr = np.absolute(arr)
print(newarr)
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The example above will return [1 2 1 2 3 4].
