The Art of Plotting is a complete, clear guide to creating compelling plots for film. Integrate plot, characterization, and exposition to make stories real. Learn with examples from new and classic movies examine great plots in action. Plot must be as much about the emotions of the characters as it is about the events of the story. That’s the message of The Art of Plotting, which teaches screenwriters how to integrate plot, characterization, and exposition to make stories compelling. Using examples from recent and classic movies, author Linda J. Cowgill demonstrates how the plot springs naturally from the characters—and how that technique makes audiences connect with the story on a more intimate level. Examples include American Beauty, Shakespeare in Love, Erin Brockovich, Spider-Man, Chinatown, Jaws, and more. Easy exercises reveal common plot problems and help writers overcome them. Clear and easy to understand and to use, The Art of Plotting shows exactly how great plotting evolves from characters caught in life-changing conflicts—and how to create great plots driven by that idea.

For many researchers, Python is a first-class tool mainly because of its libraries for storing, manipulating, and gaining insight from data. Several resources exist for individual pieces of this data science stack, but only with the Python Data Science Handbook do you get them all—IPython, NumPy, Pandas, Matplotlib, Scikit-Learn, and other related tools. Working scientists and data crunchers familiar with reading and writing Python code will find this comprehensive desk reference ideal for tackling day-to-day issues: manipulating, transforming, and cleaning data; visualizing different types of data; and using data to build statistical or machine learning models. Quite simply, this is the must-have reference for scientific computing in Python. With this handbook, you’ll learn how to use: IPython and Jupyter: provide computational environments for data scientists using Python NumPy: includes the ndarray for efficient storage and manipulation of dense data arrays in Python Pandas: features the DataFrame for efficient storage and manipulation of labeled/columnar data in Python Matplotlib: includes capabilities for a flexible range of data visualizations in Python Scikit-Learn: for efficient and clean Python implementations of the most important and established machine learning algorithms

Discover how to create stories that build suspense, reveal character, and engage your audience with this ultimate guide to writing. When it comes to writing bestsellers, it’s all about the plot. Trouble is, plot is where most writers fall down—but you don’t have to be one of them. With this book, you’ll learn how to create stories that build suspense, reveal character, and engage readers—one scene at a time. Celebrated writing teacher and author Martha Alderson has devised a plotting system that’s as innovative as it is easy to implement. With her foolproof blueprint, you’ll learn to devise a successful storyline for any genre. She shows how to: -Use the power of the Universal Story -Create plot lines and subplots that work together -Effectively use a scene tracker for maximum impact -Insert energetic markers at the right points in your story -Show character transformation at the book’s climax This is the ultimate guide for you to write page-turners that sell!

Represent and analyze data using Plots to find actionable insights using Julia programming Key FeaturesLearn to use static and interactive plots to explore data with JuliaBecome well versed with the various plotting attributes needed to customize your plotsCreate insightful and appealing plots using data interactions, animations, layouts, and themesBook Description The Julia programming language offers a fresh perspective into the data visualization field. Interactive Visualization and Plotting with Julia begins by introducing the Julia language and the Plots package. The book then gives a quick overview of the Julia plotting ecosystem to help you choose the best library for your task. In particular, you will discover the many ways to create interactive visualizations with its packages. You'll also leverage Pluto notebooks to gain interactivity and use them intensively through this book. You'll find out how to create animations, a handy skill for communication and teaching. Then, the book shows how to solve data analysis problems using DataFrames and various plotting packages based on the grammar of graphics. Furthermore, you'll discover how to create the most common statistical plots for data exploration. Also, you'll learn to visualize geographically distributed data, graphs and networks, and biological data. Lastly, this book will go deeper into plot customizations with Plots, Makie, and Gadfly—focusing on the former—teaching you to create plot themes, arrange multiple plots into a single figure, and build new plot types. By the end of this Julia book, you'll be able to create interactive and publication-quality static plots for data analysis and exploration tasks using Julia. What you will learnCreate interactive plots with Makie, Plots, Jupyter, and PlutoCreate standard statistical plots and visualize clustering resultsPlot geographically distributed and biological dataVisualize graphs and networks using GraphRecipes and GraphPlotsFind out how to draw and animate objects with Javis, Plots, and MakieDefine plot themes to reuse plot visual aspect customizationsArrange plots using Plots, Makie, and Gadfly layout systemsDefine new plot types and determine how Plots and Makie show objectsWho this book is for Data analysts looking to explore Julia's data visualization capabilities will find this book helpful, along with scientists and academics who want to generate and communicate knowledge and improve their teaching material. This data visualization book will also interest Julia programmers willing to delve into the language plotting ecosystem and improve their visualization skills. Basic programming knowledge is assumed — but the book will introduce you to Julia's important features. Familiarity with mathematical and statistical concepts will help you make the most of some of the chapters.