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Leer Challenge 1: Array Creation | NumPy
Data Science Interview Challenge

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Challenge 1: Array Creation

NumPy allows for an efficient and structured approach to create arrays. The benefits of this approach are:

  • Flexibility: NumPy provides numerous functions to create arrays, whether they are uniform, random, or based on existing data. This means you can generate data suitable for a wide range of scenarios.

  • Speed: Creating arrays using NumPy is generally faster than using standard Python lists, particularly for larger arrays.

  • Integration: You can use NumPy arrays seamlessly with many other libraries, enhancing compatibility.

In essence, when dealing with numerical data, using NumPy's array creation capabilities can enhance both the speed and the reliability of your data generation process.

Taak

Swipe to start coding

Numpy provides powerful tools to efficiently create arrays filled with data.

  1. Use numpy to create an array of 10 zeros.
  2. Now, create an array of 10 fives.
  3. Generate an array with numbers from 10 to 20.

Oplossing

import numpy as np

# 1. Use numpy to create an array of 10 zeros.
array_zeros = np.zeros(10)
print(array_zeros)

# 2. Now, create an array of 10 fives.
array_fives = np.zeros(10) + 5
print(array_fives)

# 3. Generate an array with numbers from 10 to 20, inclusive.
range_array = np.arange(10, 21)
print(range_array)

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Sectie 2. Hoofdstuk 1
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import numpy as np

# 1. Use numpy to create an array of 10 zeros.
array_zeros = ___
print(array_zeros)

# 2. Now, create an array of 10 fives.
array_fives = ___
print(array_fives)

# 3. Generate an array with numbers from 10 to 20.
range_array = ___
print(range_array)

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