A Simple Introduction to Python
Series: Chapman & Hall/CRC The Python Series;
- Publisher's listprice GBP 24.99
-
12 647 Ft (12 045 Ft + 5% VAT)
The price is estimated because at the time of ordering we do not know what conversion rates will apply to HUF / product currency when the book arrives. In case HUF is weaker, the price increases slightly, in case HUF is stronger, the price goes lower slightly.
- Discount 10% (cc. 1 265 Ft off)
- Discounted price 11 383 Ft (10 841 Ft + 5% VAT)
Subcribe now and take benefit of a favourable price.
Subscribe
12 647 Ft
Availability
Estimated delivery time: In stock at the publisher, but not at Prospero's office. Delivery time approx. 3-5 weeks.
Not in stock at Prospero.
Why don't you give exact delivery time?
Delivery time is estimated on our previous experiences. We give estimations only, because we order from outside Hungary, and the delivery time mainly depends on how quickly the publisher supplies the book. Faster or slower deliveries both happen, but we do our best to supply as quickly as possible.
Product details:
- Edition number 1
- Publisher Chapman and Hall
- Date of Publication 11 June 2024
- ISBN 9781032750293
- Binding Paperback
- No. of pages112 pages
- Size 234x156 mm
- Weight 240 g
- Language English
- Illustrations 59 Illustrations, color; 59 Line drawings, color; 1 Tables, black & white 595
Categories
Short description:
This book is aimed at pre-university students and complete novices to programming. After introducing Python as a powerful calculator, simple programming constructs are covered and the NumPy, MatPlotLib and SymPy modules (libraries) are introduced.
MoreLong description:
A Simple Introduction to Python is aimed at pre-university students and complete novices to programming. The whole book has been created using Jupyter notebooks. After introducing Python as a powerful calculator, simple programming constructs are covered, and the NumPy, MatPlotLib and SymPy modules (libraries) are introduced. Python is then used for Mathematics, Cryptography, Artificial Intelligence, Data Science and Object Oriented Programming.
The reader is shown how to program using the integrated development environments: Python IDLE, Spyder, Jupyter notebooks, and through cloud computing with Google Colab.
Features:
- No prior experience in programming is required.
- Demonstrates how to format Jupyter notebooks for publication on the Web.
- Full solutions to exercises are available as a Jupyter notebook on the Web.
- All Jupyter notebook solution files can be downloaded through GitHub.
GitHub Repository of Data Files and a Jupyter Solution notebook: https://github.com/proflynch/A-Simple-Introduction-to-Python
Jupyter Solution notebook web page: https://drstephenlynch.github.io/webpages/A-Simple-Introduction-to-Python-Solutions.html
MoreTable of Contents:
1. Python as a Powerful Calculator. 1.1. BODMAS. 1.2. Fractions: Symbolic Computation. 1.3. Powers (Exponentiation) and Roots. 1.4. The Math Library (Module) Chapter. 2. Simple Programming With Python. 2.1. Lists, Tuples, Sets and Dictionaries. 2.2. Defining Functions (Programming). 2.3. For and While Loops. 2.4. Conditional Statements, If, Elif, Else. 3. The Turtle Library. 3.1. The Cantor Set Fractal. 3.2. The Koch Snowflake. 3.3. A Bifurcating Tree. 3.4. The Sierpinski Triangle. 4. NumPy and MatPlotLib. 4.1. Numerical Python (Numpy). 4.2. MatPlotLib. 4.3. Scatter Plots. 4.4. Surface Plots. 5. Google Colab, SymPy and GitHub. 5.1. Google Colab. 5.2. Formatting Notebooks. 5.3. Symbolic Python (Sympy). 5.4. GitHub. 6. Python for Mathematics. 6.1. Basic Algebra. 6.2. Solving Equations. 6.3. Functions (Mathematics). 6.4. Differentiation and Integration (Calculus). 7. Introduction to Cryptography. 7.1. The Caesar Cipher. 7.2. The XOR Cipher. 7.3. The Rivest-Shamir-Adleman (RSA) Cryptosystem. 7.4. Simple RSA Algorithm Example. 8. An Introduction to Artificial Intelligence. 8.1. Artificial Neural Networks. 8.2. The And/Or and XOR Gate Anns. 8.3. The Backpropagation Algorithm. 8.4. Boston Housing Data. 9. An Introduction to Data Science. 9.1. Introduction to Pandas. 9.2. Load, Clean and Preprocess the Data. 9.3. Exploring the Data. 9.4. Violin, Scatter and Hexagonal Bin Plots. 10. An Introduction to Object Oriented Programming. 10.1. Classes and Objects. 10.2. Encapsulation. 10.3. Inheritance. 10.4. Polymorphism.
More
