Arrays - operations
NumPy - The Basics
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Published Sep 22 2025, updated Aug 17 2026
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NumPyPython
Arithmetic Operations
+,-,*,/,**→ element-wise addition, subtraction, multiplication, division, power.- Works element-wise, so array shapes must be compatible.
Examples:
import numpy as np# Create arraysa = np.array([1, 2, 3])b = np.array([4, 5, 6])print(a + 5)# [6 7 8]print(a * 5)# [ 5 10 15]print("Addition:", a + b)# Addition: [5 7 9]print("Subtraction:", a - b)# Subtraction: [-3 -3 -3]print("Multiplication:", a * b)# Multiplication: [ 4 10 18]print("Division:", b / a)# Division: [4. 2.5 2. ]print("Power:", a ** 2)# Power: [1 4 9]Arithmetic operations also support broadcasting:
- Broadcasting allows NumPy to perform element-wise operations on arrays of different shapes.
- NumPy “stretches” the smaller array across the larger one without actually copying data.
- Rules for broadcasting:
- If arrays have different dimensions, prepend 1s to the smaller shape.
- Arrays are compatible if in every dimension they are equal or one of them is 1.
- NumPy stretches the dimension with size 1 to match the other array.
Examples:
import numpy as np# 1D arraya = np.array([1, 2, 3])# 2D array (3 rows, 3 columns)b = np.array([[10, 20, 30], [40, 50, 60], [70, 80, 90]])# Broadcasting in arithmetic operationsprint("Addition:\n", b + a)# → [[11 22 33]# [41 52 63]# [71 82 93]]print("Subtraction:\n", b - a)# → [[ 9 18 27]# [39 48 57]# [69 78 87]]print("Multiplication:\n", b * a)# → [[10 40 90]# [40 100 180]# [70 160 270]]print("Division:\n", b / a)# → [[10. 10. 10.]# [40. 25. 20.]# [70. 40. 30.]]Comparison Operations
- Comparison operations are element-wise checks between arrays, or between an array and a scalar.
- They return a boolean array (
True/False) with the same shape as the input arrays which can be used for masking, filtering, or conditional operations. - Works for arrays of same shape, or using broadcasting if shapes are compatible.
Comparison operators:
==- Equal to!=- Not equal to<- Less than>- Greater than<=- Less than or equal to>=- Greater than or equal to
Examples:
import numpy as np# Arraysa = np.array([1, 2, 3, 4])b = np.array([2, 2, 0, 5])# Element-wise comparisonprint("a == b:", a == b) # → [False True False False]print("a != b:", a != b) # → [ True False True True]print("a > b:", a > b) # → [False False True False]print("a < b:", a < b) # → [ True False False True]print("a >= b:", a >= b) # → [False True True False]print("a <= b:", a <= b) # → [ True True False True]# Comparison with scalarprint("a > 2:", a > 2) # → [False False True True]print("a <= 3:", a <= 3) # → [ True True True False]Combining Comparisons:
- You can combine comparisons using bitwise operators:
&- AND|- OR~- NOT- Use parentheses for each condition when combining.
Example:
mask = (a > 1) & (b < 5)print(mask) # → [False False True True]