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Function array()

In fact, there are various functions in NumPy for creating arrays. Now, we'll explore one of the most commonly used ones, namely np.array(). Below, you'll find an example of how to use this function:

# Importing NumPy
import numpy as np

# Creating array
arr = np.array([1, 3, 5, 7, 9, 11, 13])

# Displaying array
print(arr)

              
12345678

            
# Importing NumPy
import numpy as np

# Creating array
arr = np.array([1, 3, 5, 7, 9, 11, 13])

# Displaying array
print(arr)
copy

Let's now determine the type of object that this function creates. We can do this using the well-known function type().

Note

The type() function takes an object of any type and returns its type. The argument can indeed be of any type: number, string, list, dictionary, tuple, function, class, module, etc.

import numpy as np
arr = np.array([1, 3, 5, 7, 9, 11, 13])

# Displaying array
print(arr)

# Displaying the type of created array
print(type(arr))

              
12345678

            
import numpy as np
arr = np.array([1, 3, 5, 7, 9, 11, 13])

# Displaying array
print(arr)

# Displaying the type of created array
print(type(arr))
copy

We can see the type of the created array is ndarray. But what does that mean? ndarray - This object is a multidimensional homogeneous array with a predetermined number of elements.

Now it's time to practice!

Uppgift

Swipe to start coding

  1. You have to create two NumPy arrays. The first one should look like this: [65, 2, 89, 5, 0, 1] and the second one should look like this: [1, 2, 3].
  2. Display these arrays on the screen.
  3. Display the type of these arrays on the screen.

Lösning

# Importing NumPy
import numpy as np

# 1. Creating arrays [65, 2, 89, 5, 0, 1] and [1, 2, 3]
arr_1 = np.array([65, 2, 89, 5, 0, 1])
arr_2 = np.array([1, 2, 3])

# 2. Displaying values of both arrays
print(arr_1, arr_2)

# 3. Displaying types of both arrays
print(type(arr_1), type(arr_2))

Var allt tydligt?

Hur kan vi förbättra det?

Tack för dina kommentarer!

Avsnitt 1. Kapitel 2
# Importing NumPy
import numpy as np

# 1. Creating arrays [65, 2, 89, 5, 0, 1] and [1, 2, 3]
arr_1 = np.___(___)
arr_2 = np.___(___)

# 2. Displaying values of both arrays
___(arr_1, ___)

# 3. Displaying types of both arrays
print(___(arr_1), ___(arr_2))

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