/Data-Visualization-Dashboard

Interactive dashboard created with Javascript, Bootstrap 4 HTML and CSS, D3.js, and Plotly.js

Primary LanguageJavaScriptMIT LicenseMIT

Data Visualization Dashboard Analysis

Webpage Level 1: https://diannejardinez.github.io/Data-Visualization-Dashboard/lvl1

Webpage Level 2: https://diannejardinez.github.io/Data-Visualization-Dashboard

Dashboard Level 1

Objective: Creating an interactive dashboard that allows for displaying dataset for a specific value using Javascript, Bootstrap 4 HTML and CSS, D3.js, and Plotly.js.

Website includes:

  • Belly Button Biodiversity dataset filtered by Participant ID through dropdown selection
  • Dataset displayed through Bar Chart
  • Dataset displayed through Bubble Chart

Dashboard Level 2

Objective: Creating an interactive dashboard that allows for displaying dataset for a specific value using Javascript, Bootstrap 4 HTML and CSS, D3.js, and Plotly.js.

Website includes:

  • Belly Button Biodiversity dataset filtered by Participant ID through dropdown selection
  • Dataset displayed through Bar Chart
  • Dataset displayed through Gauge Chart
  • Dataset displayed through Bubble Chart

Data Visualization Dashboard Instructions

In this assignment, you will build an interactive dashboard to explore the Belly Button Biodiversity dataset, which catalogs the microbes that colonize human navels.

The dataset reveals that a small handful of microbial species (also called operational taxonomic units, or OTUs, in the study) were present in more than 70% of people, while the rest were relatively rare.

Step 1: Plotly

  1. Use the D3 library to read in samples.json.

  2. Create a horizontal bar chart with a dropdown menu to display the top 10 OTUs found in that individual.

  • Use sample_values as the values for the bar chart.

  • Use otu_ids as the labels for the bar chart.

  • Use otu_labels as the hovertext for the chart.

  1. Create a bubble chart that displays each sample.

  • Use otu_ids for the x values.

  • Use sample_values for the y values.

  • Use sample_values for the marker size.

  • Use otu_ids for the marker colors.

  • Use otu_labels for the text values.

  1. Display the sample metadata, i.e., an individual's demographic information.

  2. Display each key-value pair from the metadata JSON object somewhere on the page.

  3. Update all of the plots any time that a new sample is selected.

Additionally, you are welcome to create any layout that you would like for your dashboard. An example dashboard is shown below:

Advanced Challenge Assignment (Optional)

The following task is advanced and therefore optional.

  • Adapt the Gauge Chart from https://plot.ly/javascript/gauge-charts/ to plot the weekly washing frequency of the individual.

  • You will need to modify the example gauge code to account for values ranging from 0 through 9.

  • Update the chart whenever a new sample is selected.

Deployment

Deploy your app to a free static page hosting service, such as GitHub Pages or Heroku. Submit the links to your deployment and your GitHub repo.

Here is a guide to deploying your app Heroku.

Hints

  • Use console.log inside of your JavaScript code to see what your data looks like at each step.

  • Refer to the Plotly.js documentation when building the plots.

About the Data

Hulcr, J. et al.(2012) A Jungle in There: Bacteria in Belly Buttons are Highly Diverse, but Predictable. Retrieved from: http://robdunnlab.com/projects/belly-button-biodiversity/results-and-data/

© 2019 Trilogy Education Services