Skip to content
Switch branches/tags

Latest commit


Git stats


Failed to load latest commit information.
Latest commit message
Commit time

Advanced Analysis with GIS


A one-day class reinforcing the skills necessary to leverage a geographic information system (GIS) to clean, process, and visualize NYC Parks data. The class will introduce key concepts and skills necessary to use a GIS for data analysis, reinforcing the problem ideation and process mapping skills taught in Introduction to Data Analysis. Working collaboratively in small groups, participants will develop an analytical question they explore throughout the class, presenting their data story at the end of class for constructive feedback.

Target Audience

Employees of all levels of responsibility with a command of Microsoft Excel and SQL for sorting, filtering, aggregating, transforming, and visualizing data to tell a true and compelling story, ideally through Excel for Data Analysis I, Excel for Data Analysis II, and Advanced Analysis with SQL. No familiarity with GIS is necessary for this class as we will be introducing and practicing key concepts in class. Participants should complete Introduction to Data Analysis prior to attending this class for an introduction to problem ideation and process mapping.


  • Introduce key concepts necessary for working with geographic information systems (GIS)
  • Demonstrate advanced techniques with GIS for data analysis
  • Reinforce and practice best practices in exploratory data analysis
  • Reinforce brainstorming, problem ideation, and process mapping skills introduced in previous classes
  • Practice presenting true and compelling data stories to peers
  • Cultivate an attitude of curiosity to foster a culture of data-driven inquiry

Participant Development Areas

Conceptualizing: Self-directed collaborative scoping of analytics problem and process

Skill Development: Loading, analyzing, and visualizing NYC Parks spatial data

Integrating: Investigate context using NYC Parks resources

Communicating: Project pitch with content critique in order to foster an entrepreneurial mindset with respect to developing and communicating analytical work

Language Objective: Demonstrate proficiency of key data skills with little to no assistance or instruction

Learning Objectives

  • Participants will be familiar with the key concepts of a geographic information system (GIS)
  • Participants will be experienced in the key steps of exploratory data analysis using GIS
  • Participants will be familiar with the techniques of advanced data analysis with GIS
  • Participants will be practiced in using the techniques of brainstorming, problem ideation, and process mapping to scope and execute an analytical question
  • Participants will be practiced presenting analytical findings and describing the key steps in their analysis to their peers
  • Participants will have an increased curiosity about how data can be leveraged for operational awareness and program success


  • Introduction and Housekeeping (Eric)
  • Getting Started (Manon)
    • Opening QGIS
    • Adding shapefiles to QGIS
  • Data types (Manon)
    • The attribute table
  • Styling Features (Manon)
    • Opening the Layer Styling panel
    • Basic styles
    • Labels
  • Your turn 1 (Manon)
  • What did we just do? (Eric)
  • GIS Overview (Eric)
    • GIS definitions
    • Layers
    • Vector data
  • Shapefiles (Eric)
    • What makes up a shapefile?
    • Limitations
  • Adding Second Layer (Eric)
    • Add data using the Data Warehouse
    • What is the difference between a shapefile and a database layer?
  • Why use a database? (Eric)
    • What is a spatial database?
  • Layer ordering (Eric)
  • Break
  • 5 Data Analytics Tasks (Manon)
  • Filtering (Manon)
    • Download Parks 311 data
    • Filter by complaint type
    • Filter by complaint type and borough
  • Zoom/Pan (Manon)
    • Zoom tools
    • Pan tool
  • Exporting Data (Manon)
    • Exporting shapefile
    • Exporting CSV
  • Your Turn 2 (Manon)
  • Projections (Eric)
    • Basic definition
    • Mercator
    • Projection distortions
    • Remember: 4326 and 2263
  • Identifying and Selecting Points (Eric)
    • Identifying points
    • Select by drawing
    • Export selected features
  • Project Ideation (Manon)
    • Example database tables
    • Generate ideas
    • Create groups based on the ideas
  • Process Mapping (Manon)
    • Give groups a chance to write out a possible process
  • B Block Wrapup (Manon)
  • Lunch
  • C Block Intro (Manon)
  • Proxy Setup (Eric)
  • Basic Spatial Joins (Eric)
    • What joins could we do?
    • Count 311 requests by borough
    • Graduated style for a choropleth
  • Your turn 3 (Eric)
  • Project Work (Manon)
  • Break
  • Overview of Maps (Eric)
    • General reference, thematic, cartogram
  • Base Maps (Eric)
    • QuickMapServices
    • Parks Basemap
  • Cartographic principles (Manon)
    • Hierarchy
    • Colors
    • Scale
  • Print Layout (Manon)
    • Add map
    • Add title
    • Add legend
    • Export to PDF
    • Mention Parks maps guidelines
  • Project Work/Presentations (Manon/Eric)
  • Class Wrap-Up (Eric)

Exercise Descriptions

  1. Styling borough polygons including labels
  2. Filter 311 data to one borough, style the result and export to a new shapefile
  3. Count 311 data by community district, make a choropleth

Classroom Setup


Slides for advanced class in analysis with GIS




No releases published


No packages published