Video Description
Delve into the fundamentals of the platform: Python, IPython, and the Jupyter Notebook while exploring data analysis tasks on real-world datasets
About This Video
- Learn the basics of Python in the Jupyter Notebook
- Analyze and visualize data with pandas, NumPy, matplotlib, and seaborn
- Perform highly-efficient numerical computations with Numba, Cython, and ipyparallel
In Detail
Python is a user-friendly and powerful programming language. IPython offers a convenient interface to the language and its analysis libraries, while Jupyter Notebook is a rich environment, well-adapted to data science and visualization. Together, these open-source tools are widely used by beginners and experts around the world, and in a huge variety of fields and endeavors. This course is a beginner-friendly guide to the Python data analysis platform. After an introduction to the Python language, IPython, and Jupyter Notebook, you will learn how to analyze and visualize data on real-world examples, how to create graphical user interfaces for image processing in Notebook, and how to perform fast numerical computations for scientific simulations with NumPy, Numba, Cython, and ipyparallel. By the end of this course, you will be able to perform in-depth analyses of all sorts of data.
The code bundle for the video course is available at - https://github.com/PacktPublishing/Learning-IPython-for-Interactive-Computing-and-Data-Visualization
Table of Contents
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Chapter 1 : Getting Started with IPython
- The Course Overview 00:03:43
- Installing Python with Anaconda 00:07:09
- Introducing the Notebook 00:08:34
- A Crash Course on Python 00:09:23
- More on Python Functionalities 00:10:57
- Ten Jupyter/IPython Essentials - I 00:13:50
- Ten Jupyter/IPython Essentials - II 00:10:54
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Chapter 2 : Interactive Data Analysis with pandas
- Exploring a Dataset in the Notebook 00:10:14
- Manipulating Data 00:10:25
- Complex Operations 00:06:06
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Chapter 3 : Numerical Computing with NumPy
- A Primer to Vector Computing 00:02:45
- Creating and Loading Arrays 00:04:46
- Basic Array Manipulations 00:04:51
- Computing with NumPy Arrays 00:12:20
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Chapter 4 : Interactive Plotting and Graphical Interfaces
- Choosing a Plotting Backend 00:04:53
- matplotlib and seaborn Essentials 00:08:35
- Image Processing 00:04:08
- Chapter 5 : High-Performance and Parallel Computing
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Chapter 6 : Customizing IPython
- Creating a Custom Magic Command 00:01:57
- Writing a New Jupyter Kernel 00:03:36
- Displaying Rich HTML Elements in the Notebook 00:05:22