![]() ![]() Simply click on the link to claim your free PDF. If you have already purchased a print or Kindle version of this book, you can get a DRM-free PDF version at no cost. Suggestions and FeedbackĬlick here if you have any feedback or suggestions. He is also the founder of LinearData- a leading online resource in the field of data science which has over 30,000 unique website hits. Matplotlib Plotting Cookbook Īs a formally educated data scientist with a master’s degree in data science from the prestigious King’s College London, Kevin works as a data scientist with a digital healthcare startup - Connido Limited in London where he is primarily involved with building the descriptive, diagnostic and predictive analytic pipelines. Matplotlib for Python Developers - Second Edition Code in ActionĬlick on the following link to see the Code in Action: We also provide a PDF file that has color images of the screenshots/diagrams used in this book. With the following software and hardware list you can run all code files present in the book (Chapter 1-8). Some exposure to Python programming will be helpful, but prior experience with Bokeh is not required. This book is well suited for data scientists and data analysts who want to perform interactive data visualization on their web browsers using Bokeh. For example, Chapter02.įollowing is what you need for this book: If you feel this book is for you, get your copy today!Īll of the code is organized into folders. Building and hosting applications on the Bokeh server.Using layouts and widgets to visually enhance your plots and add a layer of interactivity.Creating plots using different data structures like NumPy and Pandas.Creating plots using glyphs, the fundamental building blocks of Bokeh.Installing Bokeh and understanding its key concepts.This book covers the following exciting features: This book gets you up to speed with Bokeh - a popular Python library for interactive data visualization. The standard approach to adding interactivity would be to use paid software such as Tableau, but the Bokeh package in Python offers users a way to create both interactive and visually aesthetic plots for free. Interactive web plotting for Python using Bokeh What is this book about?Īdding a layer of interactivity to your plots and converting these plots into applications hold immense value in the field of data science. Then we run the command git merge new-branch to merge the new feature into the master branch.This is the code repository for Hands-On Data Visualization with Bokeh, published by Packt. ![]() Once the feature is complete, the branch can be merged back into the main code branch.įirst we run git checkout master to change the active branch back to the master branch. This will change the active branch to the new branch: $ git checkout new-branchĪt this point, commits can be made on the new branch to implement the new feature. To start working on the new branch we first need to run the command git checkout new-branch. Once a feature branch is finished and merged into the main branch, the changes in it become the main branch, until you merge a new feature branch into the main branch.Īt this point we have created a new branch, but are still located on the source branch. You're branching out a new set of changes from the main branch. ![]() A branch is like a tag, and the commits are shared. Note: Behind the scenes, Git does not actually create a new set of commits to represent the new branch. a set of changes has been committed on the feature branch – it is ready to be merged back into the master branch (or other main code line branch depending on the workflow in use). Other modern but centralized version control systems like Subversion require commits to be made to a central repository, so a nimble workflow with local branching and merging is atypical.Ī commonly used branching workflow in Git is to create a new code branch for each new feature, bug fix, or enhancement.Įach branch compartmentalizes the commits related to a particular feature. Official support for Python 3. In legacy Version Control Systems (like CVS) the difficulty of merging restricted it to advanced users. 3.2.0: Bokeh Version 3.2.0(June 2023) is a minor milestone of Bokeh project. This fundamentally improves the development workflow for most projects by encouraging smaller, more focused, granular commits, subject to rigorous peer review. Git's distributed nature encourages users to create new branches often and to merge them regularly as a part of the development process - and certain Git workflows exploit this extensively. ![]()
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