Interactive Data Visualization with Python

Therefore, before we begin coding for and creating these interactive features,
let's take a quick look at some of the most popular interactive data visualization
Python libraries that exist. In the previous chapters, we looked at two built-in
Python ...

Author: Abha Belorkar

Publisher: Packt Publishing Ltd

ISBN: 1800201060

Category: Computers

Page: 362

View: 213

Create your own clear and impactful interactive data visualizations with the powerful data visualization libraries of Python Key Features Study and use Python interactive libraries, such as Bokeh and Plotly Explore different visualization principles and understand when to use which one Create interactive data visualizations with real-world data Book Description With so much data being continuously generated, developers, who can present data as impactful and interesting visualizations, are always in demand. Interactive Data Visualization with Python sharpens your data exploration skills, tells you everything there is to know about interactive data visualization in Python. You'll begin by learning how to draw various plots with Matplotlib and Seaborn, the non-interactive data visualization libraries. You'll study different types of visualizations, compare them, and find out how to select a particular type of visualization to suit your requirements. After you get a hang of the various non-interactive visualization libraries, you'll learn the principles of intuitive and persuasive data visualization, and use Bokeh and Plotly to transform your visuals into strong stories. You'll also gain insight into how interactive data and model visualization can optimize the performance of a regression model. By the end of the course, you'll have a new skill set that'll make you the go-to person for transforming data visualizations into engaging and interesting stories. What you will learn Explore and apply different interactive data visualization techniques Manipulate plotting parameters and styles to create appealing plots Customize data visualization for different audiences Design data visualizations using interactive libraries Use Matplotlib, Seaborn, Altair and Bokeh for drawing appealing plots Customize data visualization for different scenarios Who this book is for This book intends to provide a solid training ground for Python developers, data analysts and data scientists to enable them to present critical data insights in a way that best captures the user's attention and imagination. It serves as a simple step-by-step guide that demonstrates the different types and components of visualization, the principles, and techniques of effective interactivity, as well as common pitfalls to avoid when creating interactive data visualizations. Students should have an intermediate level of competency in writing Python code, as well as some familiarity with using libraries such as pandas.

Data Visualization Basics with Python

"In this Data Visualization Basics with Python training course, expert author Randy Olson will teach you how to create effective data visualizations in Python.

Author: Randy Olson

Publisher:

ISBN:

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View: 264

"In this Data Visualization Basics with Python training course, expert author Randy Olson will teach you how to create effective data visualizations in Python. This course is designed for users that already have some experience with programming in Python. You will start by learning about the basics of data visualization, including types of charts, common pitfalls and good practices in data visualization, and data sources. Finally, Randy will teach you about matplotlib, including how to use matplotlib in the Jupyter Notebook, matplotlib styles, and subplots and small multiples. Once you have completed this computer based training course, you will have learned a number of tips, tricks, and best practices for creating effecting data visualizations in Python. Working files are included, allowing you to follow along with the author throughout the lessons."--Resource description page.

Data Visualization with Python for Beginners Visualize Your Data Using Pandas Matplotlib and Seaborn

What this book aims to do... This book is written with one goal in mind - to help beginners overcome their initial obstacles to learning Data Visualization using Python. A lot of times, newbies tend to feel intimidated by coding and data.

Author: Ai Publishing

Publisher: AI Publishing LLC

ISBN: 9781733042680

Category: Computers

Page: 280

View: 415

Data Visualization using Python for Beginners Are you looking for a hands-on approach to learn Python for Data Visualization Fast? Do you need to start learning Python for Data Visualization from Scratch? This book is for you. This book works as guide to present fundamental Python Libraries and basis related to Data Visualization using Python. Data science and data visualization are two different but interrelated concepts. Data science refers to the science of extracting and exploring data in order to find patterns that can be used for decision making at different levels. Data visualization can be considered as a subdomain of data science where you visualize data with the help of graphs and tables in order to find out which data is most significant and can help in the identification of important patterns. This book is dedicated to data visualization and explains how to perform data visualization on a variety of datasets using various data visualization libraries written in the Python programming language. It is suggested that you use this book for data visualization purposes only and not for decision making. For decision making and pattern identification, read this book in conjunction with a dedicated book on machine learning and data science. We will start by digging into Python programming as all the projects are developed using it, and it is currently the most used programming language in the world. We will also explore the most-famous libraries for Data Visualization such as Pandas, Numpy, Matplotlib, Seaborn, etc . What this book offers... You will learn all about python in three modules, one for Plotting with Matplotlib, one for Plotting with Seaborn, and a final one Pandas for Data Visualization. All three modules will contain hands-on projects using real-world datasets and a lot of exercises. Clear and Easy to Understand Solutions All solutions in this book are extensively tested by a group of beta readers. The solutions provided are simplified as much as possible so that they can serve as examples for you to refer to when you are learning a new skill. What this book aims to do... This book is written with one goal in mind - to help beginners overcome their initial obstacles to learning Data Visualization using Python. A lot of times, newbies tend to feel intimidated by coding and data. The goal of this book is to isolate the different concepts so that beginners can gradually gain competency in the fundamentals of Python before working on a project. Beginners in Python coding and Data Science does not have to be scary or frustrating when you take one step at a time. Ready to start practicing and visualizing your data using Python? Click the BUY button now to download this book Topics Covered: Basic Plotting with Matplotlib Advanced Plotting with Matplotlib Introduction to the Python Seaborn Library Advanced Plotting with Seaborn Introduction to Pandas Library for Data Analysis Pandas for Data Visualization 3D Plotting with Matplotlib Interactive Data Visualization with Bokeh Interactive Data Visualization with Plotly Hands-on Project Exercises Click the BUY button and download the book now to start learning and coding Python for Data Visualization. ** MONEY BACK GUARANTEE BY AMAZON ** If you aren't satisfied, for more information about the amazon refund service please go to the amazon help platform or contact us by sending an email at [email protected] **GET YOUR COPY NOW, the price will be 19.99$ soon**

Data Visualization with Python

Even though this is a beginner level course on data visualization, experienced developers will be able to improve their Python skills by working with real-world data.

Author: Mario Döbler

Publisher: Packt Publishing Ltd

ISBN: 1789951194

Category: Computers

Page: 368

View: 714

Understand, explore, and effectively present data using the powerful data visualization techniques of Python programming. Key Features Study key visualization tools and techniques with real-world data Explore industry-standard plotting libraries, including Matplotlib and Seaborn Breathe life into your visuals with exciting widgets and animations using Bokeh Book Description Data Visualization with Python reviews the spectrum of data visualization and its importance. Designed for beginners, it’ll help you learn about statistics by computing mean, median, and variance for certain numbers. In the first few chapters, you’ll be able to take a quick tour of key NumPy and Pandas techniques, which include indexing, slicing, iterating, filtering, and grouping. The book keeps pace with your learning needs, introducing you to various visualization libraries. As you work through chapters on Matplotlib and Seaborn, you’ll discover how to create visualizations in an easier way. After a lesson on these concepts, you can then brush up on advanced visualization techniques like geoplots and interactive plots. You'll learn how to make sense of geospatial data, create interactive visualizations that can be integrated into any webpage, and take any dataset to build beautiful visualizations. What’s more? You'll study how to plot geospatial data on a map using Choropleth plot and understand the basics of Bokeh, extending plots by adding widgets and animating the display of information. By the end of this book, you’ll be able to put your learning into practice with an engaging activity, where you can work with a new dataset to create an insightful capstone visualization. What you will learn Understand and use various plot types with Python Explore and work with different plotting libraries Learn to create effective visualizations Improve your Python data wrangling skills Hone your skill set by using tools like Matplotlib, Seaborn, and Bokeh Reinforce your knowledge of various data formats and representations Who this book is for Data Visualization with Python is designed for developers and scientists, who want to get into data science or want to use data visualizations to enrich their personal and professional projects. You do not need any prior experience in data analytics and visualization, however, it'll help you to have some knowledge of Python and familiarity with high school level mathematics. Even though this is a beginner level course on data visualization, experienced developers will be able to improve their Python skills by working with real-world data.

Data Visualization with Python and Matplotlib

Some of the less popular charts are not included. By the time a student is done with this series, they should be able to visualize just about any data set with ease, as well as make it look visually appealing.

Author:

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"This course covers every major chart that Matplotlib is capable of providing. Some of the less popular charts are not included. By the time a student is done with this series, they should be able to visualize just about any data set with ease, as well as make it look visually appealing. This course is taught step by step throughout the entire course. There is no written line that is not covered, so students will not be left trying to decypher lines of code. Topics and charts included are: Line graphs, scatter plots, stack plots, pie charts, bar charts, 3D lines, 3D wire_frames, 3D bar charts, 3D scatter plots, geographic maps, live updating graphs, and managing multiple graphs on the same figure / combining graphs."--Resource description page.

Python for Data Visualization

Build accurate, engaging, and easy-to-generate data visualizations using the popular programming language Python.

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Build accurate, engaging, and easy-to-generate data visualizations using the popular programming language Python.

Mastering Python Data Visualization

Generate effective results in a variety of visually appealing charts using the plotting packages in PythonAbout This Book- Explore various tools and their strengths while building meaningful representations that can make it easier to ...

Author: Kirthi Raman

Publisher:

ISBN: 9781783988327

Category: Computers

Page: 372

View: 679

Generate effective results in a variety of visually appealing charts using the plotting packages in PythonAbout This Book- Explore various tools and their strengths while building meaningful representations that can make it easier to understand data- Packed with computational methods and algorithms in diverse fields of science- Written in an easy-to-follow categorical style, this book discusses some niche techniques that will make your code easier to work with and reuseWho This Book Is ForIf you are a Python developer who performs data visualization and wants to develop existing knowledge about Python to build analytical results and produce some amazing visual display, then this book is for you. A basic knowledge level and understanding of Python libraries is assumed.What You Will Learn- Gather, cleanse, access, and map data to a visual framework- Recognize which visualization method is applicable and learn best practices for data visualization- Get acquainted with reader-driven narratives and author-driven narratives and the principles of perception- Understand why Python is an effective tool to be used for numerical computation much like MATLAB, and explore some interesting data structures that come with it- Explore with various visualization choices how Python can be very useful in computation in the field of finance and statistics- Get to know why Python is the second choice after Java, and is used frequently in the field of machine learning- Compare Python with other visualization approaches using Julia and a JavaScript-based framework such as D3.js- Discover how Python can be used in conjunction with NoSQL such as Hive to produce results efficiently in a distributed environmentIn DetailPython has a handful of open source libraries for numerical computations involving optimization, linear algebra, integration, interpolation, and other special functions using array objects, machine learning, data mining, and plotting. Pandas have a productive environment for data analysis. These libraries have a specific purpose and play an important role in the research into diverse domains including economics, finance, biological sciences, social science, health care, and many more. The variety of tools and approaches available within Python community is stunning, and can bolster and enhance visual story experiences.This book offers practical guidance to help you on the journey to effective data visualization. Commencing with a chapter on the data framework, which explains the transformation of data into information and eventually knowledge, this book subsequently covers the complete visualization process using the most popular Python libraries with working examples. You will learn the usage of Numpy, Scipy, IPython, MatPlotLib, Pandas, Patsy, and Scikit-Learn with a focus on generating results that can be visualized in many different ways. Further chapters are aimed at not only showing advanced techniques such as interactive plotting; numerical, graphical linear, and non-linear regression; clustering and classification, but also in helping you understand the aesthetics and best practices of data visualization. The book concludes with interesting examples such as social networks, directed graph examples in real-life, data structures appropriate for these problems, and network analysis.By the end of this book, you will be able to effectively solve a broad set of data analysis problems.Style and approachThe approach of this book is not step by step, but rather categorical. The categories are based on fields such as bioinformatics, statistical and machine learning, financial computation, and linear algebra. This approach is beneficial for the community in many different fields of work and also helps you learn how one approach can make sense across many fields

Data Analysis and Visualization Using Python

Analyze Data to Create Visualizations for BI Systems Dr. Ossama Embarak. E.
Count the ... Data Set Summary In [13]: df.groupby('Animal')['Age'].describe() Data
Visualization Python provides numerous methods for data visualization. Various.

Author: Dr. Ossama Embarak

Publisher: Apress

ISBN: 1484241096

Category: Computers

Page: 374

View: 841

Look at Python from a data science point of view and learn proven techniques for data visualization as used in making critical business decisions. Starting with an introduction to data science with Python, you will take a closer look at the Python environment and get acquainted with editors such as Jupyter Notebook and Spyder. After going through a primer on Python programming, you will grasp fundamental Python programming techniques used in data science. Moving on to data visualization, you will see how it caters to modern business needs and forms a key factor in decision-making. You will also take a look at some popular data visualization libraries in Python. Shifting focus to data structures, you will learn the various aspects of data structures from a data science perspective. You will then work with file I/O and regular expressions in Python, followed by gathering and cleaning data. Moving on to exploring and analyzing data, you will look at advanced data structures in Python. Then, you will take a deep dive into data visualization techniques, going through a number of plotting systems in Python. In conclusion, you will complete a detailed case study, where you’ll get a chance to revisit the concepts you’ve covered so far. What You Will Learn Use Python programming techniques for data science Master data collections in Python Create engaging visualizations for BI systems Deploy effective strategies for gathering and cleaning data Integrate the Seaborn and Matplotlib plotting systems Who This Book Is For Developers with basic Python programming knowledge looking to adopt key strategies for data analysis and visualizations using Python.

INTERACTIVE DATA VISUALIZATION WITH PYTHON

Author: JIACHENG. YAO

Publisher:

ISBN: 9781789956542

Category:

Page:

View: 714


Python Data Visualization Solutions

"Effective visualization can help you get better insights from your data, and help you make better and more informed business decisions.

Author: Dimitry Foures

Publisher:

ISBN:

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View: 711

"Effective visualization can help you get better insights from your data, and help you make better and more informed business decisions. This video starts by showing you how to set up matplotlib and other Python libraries that are required for most parts of the course, before moving on to discuss various widely used diagrams and charts such as Gantt Charts. As you will go through the course, you will get to know about various 3D diagrams and animations. As maps are irreplaceable to display geo-spatial data, this course will show you how to build them. In the last section, we'll take you on a thorough walkthrough of incorporating matplotlib into various environments and how to create Gantt charts using Python. With practical, precise, and reproducible videos, you will get a better understanding of the data visualization concepts, how to apply them, and how you can overcome any challenge while implementing them."--Resource description page.

Data Visualization Recipes with Python and Matplotlib 3

"Creating custom visualizations with Matplotlib on real-world data can be tricky, sometimes with a lot of different features and complex code.

Author: Harish Garg

Publisher:

ISBN:

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View: 585

"Creating custom visualizations with Matplotlib on real-world data can be tricky, sometimes with a lot of different features and complex code. As a data analyst or a data scientist, you don't want to get bogged down. You really want to get those Data visualizations in front of the audience. This course cuts down all the complexities and unnecessary details. It boils it down to the things you really need to get those visualizations going quickly and efficiently. The course gives you practical recipes to do what exactly needs to be done in the minimum amount of time. All the examples are based on real-world data with practical visualization solutions. By the end of the course, you'll be able to get the most out of data visualizations where Matplotlib 3 is concerned."--Resource description page.

Data Visualization Recipes in Python

If you are struggling in your day-to-day data analysis tasks, then this is the right course for you. This fast-pace guide follows a recipe-based approach, each video focusing on a commonly-faced issue.

Author: Theodore Petrou

Publisher:

ISBN:

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View: 987

"Visualization is a critical component in exploratory data analysis, as well as presentations and applications. If you are struggling in your day-to-day data analysis tasks, then this is the right course for you. This fast-pace guide follows a recipe-based approach, each video focusing on a commonly-faced issue. This course covers advanced and powerful time series capabilities so you can dissect by any possible dimension of time. It introduces the Matplotlib library, which is responsible for all of the plotting in pandas, at the same time focusing on the pandas plot method and the Seaborn library, which is capable of producing aesthetically pleasing visualizations not directly available in pandas. This course guides you, as if you were looking over the shoulder of an expert, through practical situations that you are highly likely to encounter."--Resource description page.

Data Visualization with Python for Beginners

Learn to visualize data from scratch with Python AI Sciences OU. §. Data.
Science. and. Data. Visualization. Data science and data visualization are two
different but interrelated concepts. Data science refers to the science of extracting
and ...

Author: AI Sciences OU

Publisher: Packt Publishing Ltd

ISBN: 1801813507

Category: Computers

Page: 280

View: 213

This book works as a guide to present fundamental Python libraries and basics related to data visualization using Python Key Features Detailed introductions to several data visualization libraries such as Matplotlib and Seaborn Guided instructions to more advanced data visualization skills such as 3D plotting or interactive visualization Hands-on projects for interactive practice designed to cement your new skills in practical memory Book Description Data science and data visualization are two different but interrelated concepts. Data science refers to the science of extracting and exploring data to find patterns that can be used for decision making at different levels. Data visualization can be considered a subdomain of data science. You visualize data with graphs and tables to find out which data is most significant and help identify meaningful patterns. This book is dedicated to data visualization and explains how to perform data visualization on different datasets using various data visualization libraries written in the Python programming language. It is suggested that you use this book for data visualization purposes only and not for decision making. For decision making and pattern identification, read this book in conjunction with a dedicated book on machine learning and data science. We will start by digging into Python programming as all the projects are developed using it, and it is currently the most used programming language in the world. We will also explore some of the most famous libraries for data visualization, such as Pandas, NumPy, Matplotlib, and Seaborn. You will learn all about Python in three modules—plotting with Matplotlib, plotting with Seaborn, and a final one, Pandas for data visualization. All three modules will contain hands-on projects using real-world datasets and a lot of exercises. By the end of this course, you will have the knowledge and skills required to visualize data with Python all on your own. The code bundle for this course is available at https://www.aispublishing.net/book-data-visualization What you will learn Begin visualizing data with Matplotlib Explore the Python Seaborn library for advanced plotting Analyze data with the Pandas library Expand your visualization skills with Pandas Plot in three dimensions with Matplotlib Practice interactive data visualization with Bokeh and Plotly Complete several hands-on projects Who this book is for This book is written with one goal in mind—to help beginners overcome their initial obstacles in learning data visualization using Python. This book aims to isolate the different concepts so that beginners can gradually gain competency in the fundamentals of Python before working on a project. As such, no prior experience is required.

Data Visualization with Python and JavaScript

Data Visualization with Python and JavaScript Data Python Visualization and
JavaScript with Scrape, Clean, Explore &. OREILLY Learn how to turn raw data
into rich, interactive Web Visualizations With the powerful combination of Python
and ...

Author: Kyran Dale

Publisher: "O'Reilly Media, Inc."

ISBN: 1491920548

Category: Computers

Page: 592

View: 739

Learn how to turn raw data into rich, interactive web visualizations with the powerful combination of Python and JavaScript. With this hands-on guide, author Kyran Dale teaches you how build a basic dataviz toolchain with best-of-breed Python and JavaScript libraries—including Scrapy, Matplotlib, Pandas, Flask, and D3—for crafting engaging, browser-based visualizations. As a working example, throughout the book Dale walks you through transforming Wikipedia’s table-based list of Nobel Prize winners into an interactive visualization. You’ll examine steps along the entire toolchain, from scraping, cleaning, exploring, and delivering data to building the visualization with JavaScript’s D3 library. If you’re ready to create your own web-based data visualizations—and know either Python or JavaScript— this is the book for you. Learn how to manipulate data with Python Understand the commonalities between Python and JavaScript Extract information from websites by using Python’s web-scraping tools, BeautifulSoup and Scrapy Clean and explore data with Python’s Pandas, Matplotlib, and Numpy libraries Serve data and create RESTful web APIs with Python’s Flask framework Create engaging, interactive web visualizations with JavaScript’s D3 library

Data Science and Machine Learning Series

Master probability distributions, normal distributions, and multivariate normal distributions. Also here are all of Advait Jayant's highly-rated videos on O'Reilly, including the full Data Science and Machine Learning Series .

Author: Advait Jayant

Publisher:

ISBN:

Category:

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View: 310

Master probability distributions, normal distributions, and multivariate normal distributions. Also here are all of Advait Jayant's highly-rated videos on O'Reilly, including the full Data Science and Machine Learning Series .

Python Data Visualization Cookbook

The following actions demonstrate how to do this: $ git clone https://github.com/
google/google-visualization-python.git $ cd google-visualization-python/ $ sudo
python setup.py install Note that we have to become a super user (that is, gain ...

Author: Igor Milovanovic

Publisher: Packt Publishing Ltd

ISBN: 1784394947

Category: Computers

Page: 302

View: 470

Over 70 recipes to get you started with popular Python libraries based on the principal concepts of data visualization About This Book Learn how to set up an optimal Python environment for data visualization Understand how to import, clean and organize your data Determine different approaches to data visualization and how to choose the most appropriate for your needs Who This Book Is For If you already know about Python programming and want to understand data, data formats, data visualization, and how to use Python to visualize data then this book is for you. What You Will Learn Introduce yourself to the essential tooling to set up your working environment Explore your data using the capabilities of standard Python Data Library and Panda Library Draw your first chart and customize it Use the most popular data visualization Python libraries Make 3D visualizations mainly using mplot3d Create charts with images and maps Understand the most appropriate charts to describe your data Know the matplotlib hidden gems Use plot.ly to share your visualization online In Detail Python Data Visualization Cookbook will progress the reader from the point of installing and setting up a Python environment for data manipulation and visualization all the way to 3D animations using Python libraries. Readers will benefit from over 60 precise and reproducible recipes that will guide the reader towards a better understanding of data concepts and the building blocks for subsequent and sometimes more advanced concepts. Python Data Visualization Cookbook starts by showing how to set up matplotlib and the related libraries that are required for most parts of the book, before moving on to discuss some of the lesser-used diagrams and charts such as Gantt Charts or Sankey diagrams. Initially it uses simple plots and charts to more advanced ones, to make it easy to understand for readers. As the readers will go through the book, they will get to know about the 3D diagrams and animations. Maps are irreplaceable for displaying geo-spatial data, so this book will also show how to build them. In the last chapter, it includes explanation on how to incorporate matplotlib into different environments, such as a writing system, LaTeX, or how to create Gantt charts using Python. Style and approach A step-by-step recipe based approach to data visualization. The topics are explained sequentially as cookbook recipes consisting of a code snippet and the resulting visualization.

Python Data Visualization Cookbook

... Acquisition Editor James Jones Lead Technical Editor Ankita Shashi
TechnicalEditors Pratik More Amit Ramadas Ritika Singh Copy Editors Brandt D'
Mello Janbal Dharmaraj Deepa Nambiar Python DataVisualization Cookbook
Credits.

Author: Igor Milovanović

Publisher: Packt Publishing Ltd

ISBN: 1782163379

Category: Computers

Page: 280

View: 673

This book is written in a Cookbook style targeted towards an advanced audience. It covers the advanced topics of data visualization in Python.Python Data Visualization Cookbook is for developers that already know about Python programming in general. If you have heard about data visualization but you don't know where to start, then this book will guide you from the start and help you understand data, data formats, data visualization, and how to use Python to visualize data.You will need to know some general programming concepts, and any kind of programming experience will be helpful, but the code in this book is explained almost line by line. You don't need maths for this book, every concept that is introduced is thoroughly explained in plain English, and references are available for further interest in the topic.

Learning Python Data Visualization

Python 2.7on Windowspipand easy_install are included with Python's
WindowsInstaller by default.First, we willneedthe lxml library. Now, on Windows,
the lxml library is a very popular C based XML parser and writer library for Python
libraries ...

Author: Chad Adams

Publisher: Packt Publishing Ltd

ISBN: 1783553340

Category: Computers

Page: 212

View: 248

If you are a Python novice or an experienced developer and want to explore data visualization libraries, then this is the book for you. No prior charting or graphics experience is needed.

Mastering Matplotlib 2 x

Understand and build beautiful and advanced plots with Matplotlib and Python Key Features Practical guide with hands-on examples to design interactive plots Advanced techniques to constructing complex plots Explore 3D plotting and ...

Author: Benjamin Walter Keller

Publisher: Packt Publishing Ltd

ISBN: 1789618177

Category: Computers

Page: 214

View: 239

Understand and build beautiful and advanced plots with Matplotlib and Python Key Features Practical guide with hands-on examples to design interactive plots Advanced techniques to constructing complex plots Explore 3D plotting and visualization using Jupyter Notebook Book Description In this book, you’ll get hands-on with customizing your data plots with the help of Matplotlib. You’ll start with customizing plots, making a handful of special-purpose plots, and building 3D plots. You’ll explore non-trivial layouts, Pylab customization, and more about tile configuration. You’ll be able to add text, put lines in plots, and also handle polygons, shapes, and annotations. Non-Cartesian and vector plots are exciting to construct, and you’ll explore them further in this book. You’ll delve into niche plots and visualize ordinal and tabular data. In this book, you’ll be exploring 3D plotting, one of the best features when it comes to 3D data visualization, along with Jupyter Notebook, widgets, and creating movies for enhanced data representation. Geospatial plotting will also be explored. Finally, you’ll learn how to create interactive plots with the help of Jupyter. Learn expert techniques for effective data visualization using Matplotlib 3 and Python with our latest offering -- Matplotlib 3.0 Cookbook What you will learn Deal with non-trivial and unusual plots Understanding Basemap methods Customize and represent data in 3D Construct Non-Cartesian and vector plots Design interactive plots using Jupyter Notebook Make movies for enhanced data representation Who this book is for This book is aimed at individuals who want to explore data visualization techniques. A basic knowledge of Matplotlib and Python is required.

Python for Data Analysis

Presents case studies and instructions on how to solve data analysis problems using Python.

Author: Wes McKinney

Publisher: "O'Reilly Media, Inc."

ISBN: 1449319793

Category: Computers

Page: 452

View: 718

Presents case studies and instructions on how to solve data analysis problems using Python.