This lesson is part of Software Carpentry workshops and teach an introduction to plotting and programming using python. This lesson is an introduction to programming in Python for people with little or no previous programming experience. It uses plotting as its motivating example, and is designed to be used in both Data Carpentry and Software Carpentry workshops. This lesson references JupyterLab, but can be taught using a regular Python interpreter as well. Please note that this lesson uses Python 3 rather than Python 2.

Principles of Economics covers scope and sequence requirements for a two-semester introductory economics course. The authors take a balanced approach to micro- and macroeconomics, to both Keynesian and classical views, and to the theory and application of economics concepts. The text also includes many current examples, which are handled in a politically equitable way.

Principles of Macroeconomics covers the scope and sequence requirements of most introductory macroeconomics courses. The text also includes many current examples, which are handled in a politically equitable way. The outcome is a balanced approach to both Keynesian and classical views, and to the theory and application of economics concepts.

Principles of Microeconomics covers the scope and sequence of most introductory microeconomics courses. The text includes many current examples, which are handled in a politically equitable way. The outcome is a balanced approach to the theory and application of economics concepts.

Principles of Microeconomics for AP Courses covers the scope and sequence for a one-semester Advance Placement Microeconomics course. The book is on the example textbook list for the AP course here. The text also includes many current examples, including; the Keystone Pipeline, Occupy Wall Street, and debates over the minimum wage.

This lesson in part of Software Carpentry workshop and teach novice programmers to write modular code and best practices for using R for data analysis. an introduction to R for non-programmers using gapminder data The goal of this lesson is to teach novice programmers to write modular code and best practices for using R for data analysis. R is commonly used in many scientific disciplines for statistical analysis and its array of third-party packages. We find that many scientists who come to Software Carpentry workshops use R and want to learn more. The emphasis of these materials is to give attendees a strong foundation in the fundamentals of R, and to teach best practices for scientific computing: breaking down analyses into modular units, task automation, and encapsulation. Note that this workshop will focus on teaching the fundamentals of the programming language R, and will not teach statistical analysis. The lesson contains more material than can be taught in a day. The instructor notes page has some suggested lesson plans suitable for a one or half day workshop. A variety of third party packages are used throughout this workshop. These are not necessarily the best, nor are they comprehensive, but they are packages we find useful, and have been chosen primarily for their usability.

James Powell, Dylan Johnson, Timothy Mandzyuk, Daniel Waybright, Alex Shocklee, and Nicholas Taylor (Los Alamos National Laboratory) present 'A keyphrase suggestion engine for semi-automated document characterization' during the Short Talk and Demo session at the Fantastic Futures ai4LAM 2023 annual... This item belongs to: movies/fantastic-futures-annual-international-conference-2023-ai-for-libraries-archives-and-museums-02.

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