This workshop will introduce methods for working with geospatial data in QGIS, a popular open-source desktop GIS program that runs on both PCs and Macs as well as linux computers. Participants will learn how to load, query and visualize point, line and polygon data. We will also introduce basic methods for processing spatial data, which are the building blocks of spatial analysis workflows. Coordinate reference systems and map projections will also be introduced.
Consulting Areas: R, Stata, LaTeX, Data Manipulation and Cleaning, Data Sources, Data Visualization, Geospatial Data, Maps & Spatial Analysis, R Programming, Surveys, Sampling & Interviews, Text Analysis, Web Scraping, Regression Analysis, Means Tests, Excel, Git or Github, QGIS, RStudio, Stata
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Geospatial data are an important component of data visualization and analysis in the social sciences, humanities, and elsewhere. The Python programming language is a great platform for exploring these data and integrating them into your research.
This month's "welcome back" meetup & pizza social is hosted by the D-Lab! We'll meet in the D-Lab Collaboratory and learn about the D-Lab's services, trainings, and spaces. Plus, of course, opportunities to chat with other folks on campus about what they're doing with GIS & mapping.
Geospatial data are an important component of data visualization and analysis in the social sciences, humanities, and elsewhere. The R programming language is a great platform for exploring these data and integrating them into your research. This workshop focuses on fundamental operations for reading, writing, manipulating and mapping raster data, which typically represents geographic information in a grid of regular sized cells.
Geospatial data are an important component of data visualization and analysis in the social sciences, humanities, and elsewhere. The R programming language is a great platform for exploring these data and integrating them into your research. This workshop focuses on fundamental operations for reading, writing, manipulating and mapping vector data, which encodes location as points, lines and polygons.
I’m a D-Lab GSR and a graduate student in The Goldman School’s Master of Public Policy/The I School’s Graduate Certificate in Applied Data Science. I have 5 years of experience working on data problems in government and nonprofits. I’m interested in social policy, program evaluation, and computational methods. Python is my principal language, but I’ve developed experience using and teaching a variety of other tools, including R, Excel, Tableau, and JavaScript. I deeply enjoy teaching data science methods and am excited to be a part of the D-Lab.
Geospatial data are an important component of data visualization and analysis in the social sciences, humanities, and elsewhere. The Python programming language is a great platform for exploring these data and integrating them into your research.
Geospatial data are an important component of data visualization and analysis in the social sciences, humanities, and elsewhere. The R programming language is a great platform for exploring these data and integrating them into your research. This workshop focuses on fundamental operations for reading, writing, manipulating and mapping raster data, which typically represents geographic information in a grid of regular sized cells.
This workshop will introduce methods for working with geospatial data in QGIS, a popular open-source desktop GIS program that runs on both PCs and Macs as well as linux computers. Participants will learn how to load, query and visualize point, line and polygon data. We will also introduce basic methods for processing spatial data, which are the building blocks of spatial analysis workflows. Coordinate reference systems and map projections will also be introduced.