1864 John Snow's Cholera Map Re-creation - Documentation

Project goal:

The main goal of this project is to recreate the interative version of Dr. John Snow's map with other supportive charts using D3 and javscript.

Tools used:

Data:

As part of this project, the following data files were provided to begin the project.

The project is available on github. Here is the link.

Design process:

  1. Following the viewing of the data file, I created a basic initial sketch of my visualization dashboard along with the additional charts to demonstrate how I can interact with all the plots while visualizing any graph.
    Initial Design
  2. Since I was given a variety of requirements, I initially started by plotting a graph to visualize the timeline graph using the Deathdays.csv file to determine which day had the most fatalities. To view this, I create a basic histogram graph as per the design.
  3. The streets.json and pumps.csv files were then used to plot the street paths and pumps, respectively.
  4. Later, I used the same histogram graph to view the death rate by age group using the deaths_age_sex.csv file. And, using the sex information I created a pie chart and x,y coordinates helped in plotting the datapoints on the map.
  5. Then I began incorporating the relationships between the various plots. I had to modify the ids of the map datapoints and use 3 classes with spaces to interact with additional plots because I had 3 additional charts to support the map. Additionally, the interactions between the additional plots couldn't be established.

Rationale of design choices:

  1. Charts selection - This visualization demonstrates a pie chart and two supporting bar plots. Since histograms are frequently used to examine trends over time, I decided to use one to symbolize the daily fatalities.
    The agegroup was displayed using the same logic. I used a pie chart to show the distribution of male and female fatalities since gender was the category.
  2. Color selection - For a series of colors, I chose a color pallete from coolors website and for the same I checked for color blindness using the Daltonize Chrome-plugin.
    I used the same color for female and male on female and male datapoints, respectively, to represent the differences between the various datapoints on the map based on category. I initially tried using cool colors for this, but the white background of the map made it difficult to see the entire set of datapoints. I had to replace these colors with others that were contrasty and bright.
    And, blue color was used to represent the water pumps.

Challenges:

Findings:

The 1854 pandemic and the COVID pandemic had a similar distribution. When timeline plot-1 is examined, the death distribution is extremely high during the mid-time point. Future trends may be comprehended when this distribution plot is taken into account. Additionally, it can be deduced that both children and the elderly are the most affected, which may be because they lack immunity. Other progressive illnesses and a person's life style could also contribute to old age mortality.

References:




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