Notice: This page requires JavaScript to function properly.
Please enable JavaScript in your browser settings or update your browser.NumPy Arrays | Introduction to NumPy
Introduction to Data Analysis in Python
course content

Course Content

Introduction to Data Analysis in Python

Introduction to Data Analysis in Python

1. Basics
What is Python?Hello, Python!CommentsChallengeMath SkillsVariablesNaming Rules and Conventions
2. Data Types
Data Types in PythonNumeric TypesWhat is a String?Multiline StringsConcatenationAccessing String ElementsWhat is a List?Updating Lists
3. Control Flow
Boolean TypeIf/else StatementsIndentationIf/elif/elseChallenge 1Challenge 2For LoopIncrementing and DecrementingWhile Loop
4. Functions and Modules
Built-in FunctionsImporting ModulesUsing ModulesChallengeDefining FunctionsChallengeLambda Functions
5. Introduction to NumPy
What is the NumPy?NumPy ArraysArrays OperationsAggregate Functions2-D ArraysAggregating in 2-D Arrays

bookNumPy Arrays

Arrays that are provided by NumPy perform much faster than built-in Python lists. These are crucial objects for performing calculations.

To create an array from list, use the .array() method of NumPy, passing list of values as the parameter. For example,


              
12345678910

            
# Importing the library
import numpy as np

# List of values
val = [1, 2, 3, 4, 5]

# Creating a NumPy array
arr1 = np.array(val)
arr2 = np.array([1, 2, 3, 4, 5])
print(arr1, arr2)
copy
Choose the correct options of creating a NumPy array.

Choose the correct options of creating a NumPy array.

Select the correct answer

Everything was clear?

How can we improve it?

Thanks for your feedback!

Section 5. Chapter 2
some-alt