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Leer Arrays Operations | Introduction to NumPy
Introduction to Data Analysis in Python
course content

Cursusinhoud

Introduction to Data Analysis in Python

Introduction to Data Analysis in Python

1. Basics
2. Data Types
3. Control Flow
4. Functions and Modules
5. Introduction to NumPy

book
Arrays Operations

NumPy arrays not only perform faster, but also support different operations, that are not available for built-in lists.

For example, you can add/subtract/multiply/divide by a certain number all the array elements. Or you can multiply two arrays element-by-element.

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# Import the library import numpy as np # Creating two arrays arr1 = np.array([1, 2, 3]) arr2 = np.array([10, 20, 30]) # Perform some arrays operations print(arr1 + 3) print(arr1 * arr2)
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Sectie 5. Hoofdstuk 3

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course content

Cursusinhoud

Introduction to Data Analysis in Python

Introduction to Data Analysis in Python

1. Basics
2. Data Types
3. Control Flow
4. Functions and Modules
5. Introduction to NumPy

book
Arrays Operations

NumPy arrays not only perform faster, but also support different operations, that are not available for built-in lists.

For example, you can add/subtract/multiply/divide by a certain number all the array elements. Or you can multiply two arrays element-by-element.

123456789
# Import the library import numpy as np # Creating two arrays arr1 = np.array([1, 2, 3]) arr2 = np.array([10, 20, 30]) # Perform some arrays operations print(arr1 + 3) print(arr1 * arr2)
copy

Was alles duidelijk?

Hoe kunnen we het verbeteren?

Bedankt voor je feedback!

Sectie 5. Hoofdstuk 3
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