Do you have unstructured geographic data and need to make a map? This class introduces essential strategies for cleaning data in preparation for visualization and analysis with GIS software platforms. We will use data scraped from a personal CitiBike user account as a test case for learning data remediation strategies for GIS analysis.
Software: |
Google Sheets and Geocode by AwesomeTable (note: Data Services does not support this add-on, but you are encouraged to add it to your Sheets account in advance of the class)
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Duration: |
60 min |
Room description:
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Some tutorials are held remotely and require NYU sign on to access, while others are held in person, without a remote component. Please note the correct modality and location of the tutorial when registering
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Prerequisites: |
Basic familiarity with Google Sheets formulas |
Skills Taught / Learning Outcomes: |
- Identify meaningful units of analysis in order to structure data for mapping
- Manipulate data in order to visualize and process it within various GIS platforms
- Deploy essential formulas like CONCAT, COUNTIF, WEEKDAY, and others in order to clean up unwieldy data
- Ascertain the value of establishing date, number, and categorical string variable types of data
- Structure data to maximize the success rate of existing cloud-based geocoding APIs
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Class Materials: |
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Related Classes: |
Data Cleaning Using OpenRefine
Introduction to ArcGIS (ArcMap)
Data Cleaning and Management with Python
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Additional Training Materials: |
Cleaning up your Excel 2013 data via LinkedIn Learning (NYU NetID required) |
Feedback: |
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