Labs
Contents
Labs#
The labs will teach you practical skills on how to process and analyze spatial and spatio-temporal data. The acquired skills can be broadly grouped into the following categories: 1) working with data in the cloud; 2) pre-processing the data for analysis (data cleaning, data scaling); 3) data visualizations; 4) data analysis.
Lab Sections#
The labs are held once a week on Monday and Tuesday. Please, see the Syllabus for the most up-to-date lab schedule. The attendance is taken and is counted towards your participation grades.
Integrated Development Environment#
The labs will utilize Google Colab, which enables writing and executing Python code in your browser with zero configuration. The notebook environment is highly interactive and allows to streamline typical spatial analysis tasks, while also allowing to document your code and present it out-of-the-box.
If you are interested in running the code localy on your laptop or PC, you can follow the set-up instructions available here. Alternatively, you can set up a containerised version of Python environment, like the one designed for Geographic Data Science Book.
Submitting the Lab#
The labs from the previous week must be submitted before the start of the lab section the following week. Please submit your finished work as a zip archive with the following two files: YourName_lab01.ipynb (Google colab notebook) and Yourname_lab01.pdf (exported print-to-pdf file) via GauchoSpace dropboxes.
Lab Materials#
week |
topic |
data |
workbook |
template |
|---|---|---|---|---|
1 |
Google Colab IDE, Markdown and Python |
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2 |
Working with data, grouping and summarizing data, filtering data, histograms, spatial joins |
Wildfire Perimeters in California |
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3 |
Geovisualization, Mapping and PPA Centrography |
Weather by State, Tokyo Photographs |
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4 |
Inferential Statistics for Penguins |
Seaborn penguins and taxis data |
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5 |
Means, Correlations and Autocorrelation: Moral Statistics of France |
Guerry Moral Statistics Data |
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6 |
Assessing the Spatial Distribution of AirBnb listings in metropolitan areas |
InsiderAirbnb Data |
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7 |
Clustering the blocks of Cincinnati |
Cincinnati Crime Data from GeoDa |
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8 |
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9 |