# How to create a vector in Python using NumPy

NumPy is a general-purpose array-processing package. It provides a high-performance multidimensional array object, and tools for working with these arrays. It is the fundamental package for scientific computing with Python. Numpy is basically used for creating array of n dimensions.

Vector are built from components, which are ordinary numbers. We can think of a vector as a list of numbers, and vector algebra as operations performed on the numbers in the list. In other words vector is the numpy 1-D array.

In order to create a vector we use `np.array` method.

Syntax : np.array(list)

Argument : It take 1-D list it can be 1 row and n columns or n rows and 1 column

Return : It returns vector which is numpy.ndarray

Note : We can create vector with other method as well which return 1-D numpy array for example `np.arange(10)`, `np.zeros((4, 1))` gives 1-D array, but most appropriate way is using `np.array` with the 1-D list.

Creating a Vector
In this example we will create a horizontal vector and a vertical vector

 `# importing numpy ` `import` `numpy as np ` ` `  `# creating a 1-D list (Horizontal) ` `list1 ``=` `[``1``, ``2``, ``3``] ` ` `  `# creating a 1-D list (Vertical) ` `list2 ``=` `[[``10``], ` `        ``[``20``], ` `        ``[``30``]] ` ` `  `# creating a vector1 ` `# vector as row ` `vector1 ``=` `np.array(list1) ` ` `  `# creating a vector 2 ` `# vector as column ` `vector2 ``=` `np.array(list2) ` ` `  ` `  `# showing horizontal vector ` `print``(``"Horizontal Vector"``) ` `print``(vector1) ` ` `  `print``(``"----------------"``) ` ` `  `# showing vertical vector ` `print``(``"Vertical Vector"``) ` `print``(vector2) `

Output :

```Horizontal Vector
[1 2 3]
----------------
Vertical Vector
[[10]
[20]
[30]]
```

Basic Arithmetic operation:
In this example we will see do arithmetic operations which are element-wise between two vectors of equal length to result in a new vector with the same length

 `# importing numpy ` `import` `numpy as np ` ` `  `# creating a 1-D list (Horizontal) ` `list1 ``=` `[``5``, ``6``, ``9``] ` ` `  `# creating a 1-D list (Horizontal) ` `list2 ``=` `[``1``, ``2``, ``3``] ` ` `  `# creating first vector  ` `vector1 ``=` `np.array(list1) ` ` `  `# printing vector1 ` `print``(``"First Vector          : "` `+` `str``(vector1)) ` ` `  `# creating secodn vector ` `vector2 ``=` `np.array(list2) ` ` `  `# printing vector2 ` `print``(``"Second Vector         : "` `+` `str``(vector2)) ` ` `  `# adding both the vector ` `# a + b = (a1 + b1, a2 + b2, a3 + b3) ` `addition ``=` `vector1 ``+` `vector2 ` ` `  `# printing addition vector ` `print``(``"Vector Addition       : "` `+` `str``(addition)) ` ` `  `# subtracting both the vector ` `# a - b = (a1 - b1, a2 - b2, a3 - b3) ` `subtraction ``=` `vector1 ``-` `vector2 ` ` `  `# printing addition vector ` `print``(``"Vector Substraction   : "` `+` `str``(subtraction)) ` ` `  `# multiplying  both the vector ` `# a * b = (a1 * b1, a2 * b2, a3 * b3) ` `multiplication ``=` `vector1 ``*` `vector2 ` ` `  `# printing multiplication vector ` `print``(``"Vector Multiplication : "` `+` `str``(multiplication)) ` ` `  `# dividing  both the vector ` `# a / b = (a1 / b1, a2 / b2, a3 / b3) ` `division ``=` `vector1 ``/` `vector2 ` ` `  `# printing multiplication vector ` `print``(``"Vector Division       : "` `+` `str``(multiplication)) ` `  `

Output :

```First Vector          : [5 6 9]
Second Vector         : [1 2 3]
Vector Addition       : [ 6  8 12]
Vector Substraction   : [4 4 6]
Vector Multiplication : [ 5 12 27]
Vector Division       : [ 5 12 27]
```

Vector Dot Product
In mathematics, the dot product or scalar product is an algebraic operation that takes two equal-length sequences of numbers and returns a single number.
For this we will use `dot` method.

 `# importing numpy ` `import` `numpy as np ` ` `  `# creating a 1-D list (Horizontal) ` `list1 ``=` `[``5``, ``6``, ``9``] ` ` `  `# creating a 1-D list (Horizontal) ` `list2 ``=` `[``1``, ``2``, ``3``] ` ` `  `# creating first vector  ` `vector1 ``=` `np.array(list1) ` ` `  `# printing vector1 ` `print``(``"First Vector  : "` `+` `str``(vector1)) ` ` `  `# creating secodn vector ` `vector2 ``=` `np.array(list2) ` ` `  `# printing vector2 ` `print``(``"Second Vector : "` `+` `str``(vector2)) ` ` `  `# getting dot product of both the vectors ` `# a . b = (a1 * b1 + a2 * b2 + a3 * b3) ` `# a . b = (a1b1 + a2b2 + a3b3) ` `dot_product ``=` `vector1.dot(vector2) ` ` `  `# printing dot product ` `print``(``"Dot Product   : "` `+` `str``(dot_product)) `

```First Vector  : [5 6 9]
Second Vector : [1 2 3]
Dot Product   : 44
```

Vector-Scalar Multiplication
Multiplying a vector by a scalar is called scalar multiplication. To perform scalar multiplication, we need to multiply the scalar by each component of the vector.

 `# importing numpy ` `import` `numpy as np ` ` `  `# creating a 1-D list (Horizontal) ` `list1 ``=` `[``1``, ``2``, ``3``] ` ` `  `# creating first vector  ` `vector ``=` `np.array(list1) ` ` `  `# printing vector1 ` `print``(``"Vector  : "` `+` `str``(vector)) ` ` `  `# scalar value  ` `scalar ``=` `2` ` `  `# printing scalar value ` `print``(``"Scalar  : "` `+` `str``(scalar)) ` `  `  `# getting scalar multiplication value ` `# s * v = (s * v1, s * v2, s * v3) ` `scalar_mul ``=` `vector ``*` `scalar ` ` `  `# printing dot product ` `print``(``"Scalar Multiplication : "` `+` `str``(scalar_mul)) ` ` `  ` `  `  `

Output

```Vector  : [1 2 3]
Scalar  : 2
Scalar Multiplication : [2 4 6]

```

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