Module 6 - Proportional Symbols and Bivariate Choropleth

     This week's module explored visualizing data using proportional symbols. We were tasked to create a map depicting gains and losses in the job market using proportional symbology. The dataset was split between positive and negative values, so I used two separate layers as ArcGIS cannot represent negative values properly using proportional symbols. The first layer represented job market gains, represented in blue, while the second layer showed losses, represented in red. To ensure proportional symbology worked correctly for the losses, I used the Field Calculator in the Attribute Table to convert all negative values to positive. This allowed the symbol sizes to reflect the magnitude of the losses accurately.

 

Module 5 - Analytical Data

     The goal of this week's module was to create an infographic based on two potentially causally related health variables obtained from the County Health Rankings & Roadmaps program. The variables I chose to visualize were reported insufficient sleep and average mentally unhealthy days per month. 

     

    I placed a column along each side of the infographic and placed my charts in these. In the middle are the choropleth maps of my chosen variables. I ensured every element was consistent in color, using either a shade of purple from the insufficient sleep choropleth map or a shade of blue from the mental health choropleth map. I made the text white or black depending on the lightness of the background to ensure readability and ensured the background colors consisted of muted hues as to not distract from the main elements of the infographic. 

    For my bar graph, I chose to plot the top 3 and bottom 3 counties, as well as the US average for comparison. Because of my variable unit mismatch I calculated an “Insufficient sleep-weighted mental health burden” by using the formula [ (Insufficient Sleep% / 100) x Average bad mental health days ] for each county. I kept the purple color scheme the same and gave the number 1 county the same color as the darkest shade of the choropleth color ramp.

Module 4 - Color Concepts & Choropleth Mapping

     This week's module involved examining RGB and HSV color ramps in ArcGIS Pro as well as exploring effective choropleth mapping. Three methods of creating color ramps were examined: linear progression, adjusted progression, and the website ColorBrewer.

 

    Left to right: Linear progression, adjusted progression and ColorBrewer

    The linear and adjusted progression color ramps are more mathematically consistent, following a uniform or modified stepwise increase in RGB values. In contrast, the ColorBrewer color ramp has non-uniform stepwise intervals, suggesting that ColorBrewer does not follow a mathematical pattern, but is instead designed in a way where the hues are easily distinguishable from one another. The ColorBrewer color ramp is visually distinct from the calculated progression ramps as its hues have greater contrast, which makes class distinctions clearer. The linear and adjusted color ramps appear visually similar, especially in the darker hues. The adjusted color ramp compensates for this with its increased intervals for darker hues, but does not have the same intentional hue contrast found in the ColorBrewer color ramp.

    The last section of the module tasked us with creating a choropleth map of population change in a state of our choosing. I chose to map population change in Colorado, using the Natural Breaks method.

  

     I chose Natural Breaks because the population-based data had natural variation with an uneven distribution of observations in the histogram. The Natural Breaks method considers how the data is clustered, which is useful in mapping data with natural variations. I chose a blue to red diverging color scheme and reversed the values to depict a gain (blue) to loss (scale). A blue to red color ramp allows for clear differentiation between increases and decreases and the colors blue and red suit the natural associations between gain and loss. I added Colorado's average population change for context, and changed the legend’s labels from “x% - x%” to “x% to x%” for readability.