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Lab 3 – 2

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Task 3: Child Poverty and Adult Education Across U.S. Counties This visualization is a scatterplot created using ACS data. The x-axis shows the poverty rate for related children under 18, and the y-axis shows the percent of young adults ages 25–44 with less than a high school diploma. Each point represents a county, and the color indicates the level of child poverty. Average reference lines divide the chart into four quadrants to help compare patterns. Discussion (1) Relationship between child poverty and adult education The quadrant scatterplot reveals a clear pattern in how child poverty and adult education are related across U.S. counties. Counties that fall in the higher child poverty quadrants tend to also show higher percentages of young adults without a high school diploma. This clustering suggests that lower educational atta...
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Lab 3 – 1

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Task 1: NHL Career Points Leader This scatterplot shows the relationship between NHL players’ career goals and career assists. Wayne Gretzky and Mario Lemieux are highlighted to emphasize how they stand out relative to other players in overall point production. Task 2: Quadrant Chart of NHL Goals and Shots This quadrant chart shows the relationship between NHL players’ career goals and total shots taken. Average reference lines divide the scatterplot into four quadrants, making it easier to compare player performance relative to league averages. The chart helps identify players with high scoring production, high scoring efficiency, and lower overall performance in a clear and intuitive way. Comparison of Task 1 and Task 2 Visualizations The scatterplot in Task 1 is most effective for exploring the data. It shows the relationship between two player statistics using one point per player, which makes it easy to see the overall patter...
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Lab 2 – 2

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This section uses COVID-19 case data for Illinois counties, including the City of Chicago, to demonstrate how different visualization techniques support different analytical goals. While both tasks use the same dataset, each visualization emphasizes a different way of understanding the data. Task 4: COVID-19 Cases by County (Dot Chart) The dot chart displays total COVID-19 cases for Illinois counties and the City of Chicago, with each geographic unit represented as a single point on a shared horizontal scale. This design allows for quick and direct comparison across counties. To improve readability and focus on meaningful patterns, the chart is filtered to include only counties with more than 5,000 cases. Applying this threshold reduces visual clutter and highlights counties with the highest case counts, making differences between counties easier to identify. Overall, the dot chart is effective for ranking and comparing case totals across many geographic units. Tas...
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Lab 2 – 1

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This section presents Tasks 1–3 from Lab 2, based on Chapters 4 and 6 of Communicating Data with Tableau . These tasks use ratios, ranking, and distribution-based visualizations to examine recycling behavior and refuse production across New York City community districts and boroughs. The visualizations follow examples from the textbook and are implemented using Tableau. Task 1: Ratio of Recycling to Refuse by Community District The data show recycling and refuse collection for New York City community districts, organized by borough. By expressing this information as a recycle-to-refuse ratio, the chart allows districts of different sizes to be compared fairly. The pattern shows that recycling performance varies across boroughs and also among districts within the same borough, revealing spatial differences that are not clear from total amounts alone. Task 2: Ranked Recycling to Refuse Ratio This view uses the same recycling and refuse data but orders community di...
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Lab 1

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Lab 1: Column Chart Example from Chapter 2 (Figure 2-12) This lab is based on Chapter 2 of the book Communicating Data with Tableau by Ben Jones. The goal of this chapter is to understand the Tableau interface and learn how data can be explored and communicated using basic visualizations. The New York Boroughs dataset was used to create a column chart that compares population across different boroughs. This chart makes it easy to see which boroughs have higher or lower population values. The exercise demonstrates how drag-and-drop tools in Tableau can be used to quickly create clear and effective charts for communicating data patterns. Lab 1: Population Density Map of New York Boroughs (Figure 2-13) This map follows the example shown in Chapter 2, Figure 2-13 of the book Communicating Data with Tableau by Ben Jones. The map displays population density across the New York boroughs, allowing spatial differences to be seen more clearly than in a chart. Colo...
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EAE 552 Geovisualization Created by Himansi Bhatt Hello Class! This webpage serves as a portfolio for EAE 552 coursework. Department of Earth, Atmosphere and Environment Northern Illinois University Lab 1 Lab 2 – 1 Lab 2 – 2 Lab 3 – 1 Lab 3 – 2
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