Part 2: Working With Projections & Spatial Queries
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Students will learn about the different ways in which entities in the real world are represented as geographic data.
This workshop will focus on organizing, coding, and analyzing qualitative data using ATLAS.ti, a qualitative data analysis (QDA) software program for which D-Lab provides support.
This is a two-part series for qualitative researchers interested in learning about MAXQDA, a qualitative data analysis (QDA) software program for which D-Lab provides substantive support.
This is a two-part series for qualitative researchers interested in learning about MAXQDA, a qualitative data analysis (QDA) software program for which D-Lab provides substantive support.
For this workshop, we'll provide an introduction to visualization with Python.
Pandas is a Python package providing fast, flexible, and expressive data structures designed to make working with 'relational' or 'labeled' data both easy and intuitive.
In Visualization in Excel, we will cover the fundamentals of visualization in Excel, including a checklist of considerations that should go into every visualization.
This class will cover the basics of Excel, from simple formulas (SUM, COUNTIF) to more complex Excel features like Macros and the Data Analysis ToolPak.
This class will cover the basics of Excel, from simple formulas (SUM, COUNTIF) to more complex Excel features like Macros and the Data Analysis ToolPak.