Geospatial Data in R: Part 3, Raster Data

Raster data are used to represent geographic phenomena that are present and can be measured anywhere in a study area, like elevation, temperature, rainfall, land cover, soil type, etc. These data are a valuable resource for social scientists, planners, and engineers as well as natural scientists. This workshop will introduce basic raster concepts and methods for working with raster data in R. Participants will learn how to import and store raster data as spatial objects. We will explore methods for plotting rasters and manipulating raster data values.

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Geospatial Data in R: Part 2

Geospatial data are an important component of social science and humanities data visualization and analysis. The R programming language is a great platform for exploring these data and integrating them into a research project. 

Geospatial Data in R, part 2: Geoprocessing and analysis

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Geospatial Data in R: Part 1

Geospatial data are an important component of social science and humanities data visualization and analysis. The R programming language is a great platform for exploring these data and integrating them into your research. 

Geospatial Data in R, part I: Getting started with spatial data objects

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Python Fundamentals: Part 4

This four-part, interactive workshop series is your complete introduction to programming Python for people with little or no previous programming experience. By the end of the series, you will be able to apply your knowledge of basic principles of programming and data manipulation to a real-world social science application.

Part 4 Topics: We will applying the skills learned during previous sessions to a real world social science example.

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Python Fundamentals: Part 3

This four-part, interactive workshop series is your complete introduction to programming Python for people with little or no previous programming experience. By the end of the series, you will be able to apply your knowledge of basic principles of programming and data manipulation to a real-world social science application.

Part 3 Topics:

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Python Fundamentals: Part 2

Part 2 Topics:

  • Lists
  • Loops
  • Conditionals
  • Functions
  • Scope

Knowledge requirements: Python Fundamentals: Part 1 or equivalent prior knowledge

Registration note: To participate in multiple parts of this series, please be sure to register for each day separately.

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Python Fundamentals: Part 1

This four-part, interactive workshop series is your complete introduction to programming Python for people with little or no previous programming experience. By the end of the series, you will be able to apply your knowledge of basic principles of programming and data manipulation to a real-world social science application.

Part 1 Topics:

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The available spaces and the waitlist for this event are both full.

ArcGIS Online: Part 2

This 2-part workshop will introduce ESRI's ArcGIS Online (AGOL), a web based platform for creating online maps, processing geospatial data and doing spatial analysis. Part 2 will focus on ways to share geospatial data hosted on AGOL using ESRI Story Maps, Operations Dashboards, and custom programming.

Knowledge Requirements: Basic knowlege of ArcGIS Online similar to that provided by part 1 of this series.Technology Requirements: A laptop and valid calnet id are needed to follow along with the tutorial.

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ArcGIS Online: Part 1

This 2-part workshop will introduce ESRI's ArcGIS Online (AGOL), a web based platform for creating online maps, processing geospatial data and doing spatial analysis. Part 1 will provde a hands-on overview of uploading data to AGOL, creating web maps, and symbolizing mapped data by attribute values. Part I will also introduce the tools for geoprocessing and spatial analysis. 

Knowledge Requirements: No prior experience is assumed or required.Technology Requirements: A laptop and valid calnet id are needed to follow along with the tutorial.

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Basics of Excel: Part 3

Visualization in Excel: In Visualization in Excel, we will cover the fundamentals of visualization in Excel, including a checklist of considerations that should go into every visualization. We will also go through step by step instructions on how to make horizontal bar charts, slope graphs, butterfly charts, the good kind of pie charts, icon arrays, and how to graph confidence intervals. We will not be using Microsoft Office default colors.

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