NumPy Creating Arrays

NumPy provides several ways to create arrays, allowing for flexibility and convenience when working with data. Here are some common methods for creating arrays:

Creating Arrays from Lists

NumPy arrays can be created from Python lists using the numpy.array() function.

import numpy as np

# Creating a 1-D array from a list
arr = np.array([1, 2, 3, 4, 5])
print(arr)

[1 2 3 4 5]

import numpy as np

# Creating a 2-D array from a list of lists
arr = np.array([[1, 2, 3], [4, 5, 6]])
print(arr)

[[1 2 3]
 [4 5 6]]

Creating Arrays with Specific Functions

NumPy provides several functions to create arrays with specific values or patterns:

• numpy.zeros() – Create an array filled with zeros
• numpy.ones() – Create an array filled with ones
• numpy.full() – Create an array filled with a specified value
• numpy.arange() – Create an array with a range of values
• numpy.linspace() – Create an array with evenly spaced values within a specified range

import numpy as np

# Creating a 2x3 array filled with zeros
arr = np.zeros((2, 3))
print(arr)

[[0. 0. 0.]
 [0. 0. 0.]]

import numpy as np

# Creating a 2x3 array filled with ones
arr = np.ones((2, 3))
print(arr)

[[1. 1. 1.]
 [1. 1. 1.]]

import numpy as np

# Creating a 2x3 array filled with the value 7
arr = np.full((2, 3), 7)
print(arr)

[[7 7 7]
 [7 7 7]]

import numpy as np

# Creating an array with values from 0 to 9
arr = np.arange(10)
print(arr)

[0 1 2 3 4 5 6 7 8 9]

import numpy as np

# Creating an array with 5 values evenly spaced between 0 and 1
arr = np.linspace(0, 1, 5)
print(arr)

[0.   0.25 0.5  0.75 1.  ]

Creating Arrays from Existing Data

NumPy can create arrays from existing data, such as lists, tuples, or other arrays.

import numpy as np

# Creating an array from a tuple
arr = np.array((1, 2, 3, 4, 5))
print(arr)

[1 2 3 4 5]

Conclusion

In this chapter, we’ve covered various methods for creating NumPy arrays, including creating arrays from lists and tuples, as well as using specific NumPy functions to generate arrays with particular values or patterns.