# Lession - #294 NumPy Creating Arrays

#### Creating arrays in NumPy

To create an array, you can use array method of numpy.
``````# Creating 1D array
a = np.array([1, 2, 3]>
# Creating 2D array
b = np.array([[1,2,3],[4,5,6]]>``````

##### Functions to create NumPy arrays:
``````a = np.zeros((2,2>>     # Create an array of all zeros
b = np.ones((1,2>>      # Create an array of all ones
pi = 3.14
c = np.full((2,2>, pi>  # Create a constant array of pi
d = np.eye(3>           # Creates a 3x3 identity matrix
e = np.random.random((2,2>>  # Create an array of random values``````

To make groupings of numbers, NumPy gives a function practically equivalent to go that returns arrays rather than lists.
1. arange: returns equitably divided values inside a given stretch. step size is indicated.
2. linspace: returns uniformly separated values inside a given stretch. num no. of components are returned.

``````A = np.arange(0, 30, 5>   # Creates [ 0, 5, 10, 15, 20, 25]
B = np.linspace(1, 15, 3> # Creates [ 1.0,  8.0, 15.0]``````

The Python List insert(>
method is an inbuilt function in Python that inserts a given element at a given index in a list.
The simplest way to convert a Python list to NumPy array is to use the np.array(>
function that takes an iterable and returns a NumPy array.
numpy average ... Compute the weighted average along the specified axis. ... Axis or axes along which to average.
A tutorial on using NumPy GitHub Gist: instantly share code, notes, and snippets.