Creating a one-dimensional NumPy array

• Last Updated : 02 Sep, 2020

One dimensional array contains elements only in one dimension. In other words, the shape of the NumPy array should contain only one value in the tuple. Let us see how to create 1 dimensional NumPy arrays.

Method 1: First make a list then pass it in numpy.array()

Python3

 `# importing the module ` `import` `numpy as np ` ` `  `# creating the list ` `list` `=` `[``100``, ``200``, ``300``, ``400``] ` ` `  `# creating 1-d array ` `n ``=` `np.array(``list``) ` `print``(n)`

Output:

`[100 200 300 400]`

Method 2: fromiter() is useful for creating non-numeric sequence type array however it can create any type of array. Here we will convert a string into a NumPy array of characters.

Python3

 `# imporint gthe module ` `import` `numpy as np ` ` `  `# creating the string ` `str` `=` `"geeksforgeeks"` ` `  `# creating 1-d array ` `x ``=` `np.fromiter(``str``, dtype ``=` `'U2'``) ` `print``(x)`

Output:

`['g' 'e' 'e' 'k' 's' 'f' 'o' 'r' 'g' 'e' 'e' 'k' 's']`

Method 3: arange() returns evenly spaced values within a given interval.

Python3

 `# importing the module ` `import` `numpy as np ` ` `  `# creating 1-d array ` `x ``=` `np.arange(``3``, ``10``, ``2``) ` `print``(x)`

Output:

`[3 5 7 9]`

Method 4: linspace() creates evenly space numerical elements between two given limits.

Python3

 `# importing the module ` `import` `numpy as np ` ` `  `# creating 1-d array ` `x ``=` `np.linspace(``3``, ``10``, ``3``) ` `print``(x)`

Output:

`[ 3.   6.5 10. ]`

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