Numerical Data Manipulation¶
Let us continue with our journey to learn the basics of computer programming with Python. In this chapter we will primarily focus on more advanced features to make your programs more efficient, focusing on numerical data manipulation.
We are giving special attention to numerical data manipulation because it is the raw material used to build many engineering and management applications. In engineering, numerical data is the basis to optimize manufacturing and logistic processes, simulate fluid dynamics, or design mechanical structures. Traditionally, the complex models and calculations required to manipulate data were performed using calculators, or made by hand, but nowadays, the quality and safety of engineering solutions relies on computer programming almost entirely. In management, numerical data manipulation enables better decision-making through forecasting, risk assessment, and resource allocation. From financial modeling to inventory management, the capacity to quickly and accurately process numerical data is invaluable. Thus, mastering numerical data manipulation is a fundamental technical skill in both engineering and management contexts.
Objectives¶
The main objectives of this chapter are:
📂 Learn the concepts behind tabular data and how to use advanced data input and outputs in your programs.
🧮 Get familiar with the Numpy library and how to use it to solve common management engineering and management problems.
🚀 Are you excited about leveling up your game with Python? Let’s go!
These are the main topics that we will cover in this chapter:
1️⃣ Introduction to advanced data input and output.¶
Tutorials¶
Introduction to Data Manipulation and Analysis: Get familiar with key concepts surrounding data manipulation.
Iterables II: Learn about Dictionaries and cool tricks to manipulate complex iterable objects.
Class Notes¶
Iterables II: Lecture notes and exercises.
Code cards¶
2️⃣ Introduction to structured input and output data formats.¶
Tutorials¶
File Formats: Get familiar with popular data file formats like CSV and JSON.
Class Notes¶
File Formats: Lecture notes and exercises.
3️⃣ Data streaming and serial communication.¶
Tutorials¶
Serial Communication: Learn how to communicate with external devices using serial communication.
Class Notes¶
Serial Communication: Hands on assignment: Template programs and related code cards.
Code cards¶
4️⃣ Data manipulation and analysis with Pandas.¶
Tutorials¶
Introduction to Pandas: Learn how to work with structured data using Python.
Data Analysis with Pandas: Learn the basics of databases and relational models.
Class Notes¶
Pandas Basics: Lecture class notes and exercises.
Class exercises¶
5️⃣ Numerical data manipulation with Numpy.¶
Tutorials¶
Introduction to Numpy: Get familiar with the Numpy library and Numpy Arrays.
Linear Algebra with Numpy: Learn how to solve linear algebra problems with Numpy.