fagan2888/belly-button-biodiversity

Full-Stack Data Analysis to Build an Interactive Dashboard Exploring the Belly Button Biodiversity DataSet Using Plotly.js, Flask and Heroku

Belly-Button-Biodiversity

Background

Full-Stack Data Analysis to build an interactive dashboard exploring the Belly Button Biodiversity Dataset using Plotly.js, Flask and Heroku

Objectives

Step 1 - Plotly.js

Use Plotly.js to build interactive charts for the dashboard

• Create a Pie Chart that uses data from the samples route (/samples/<sample>) to display the top 10 samples
  • Use sample_values as the values for the Pie Chart
  • Use otu_ids as the labels for the Pie Chart
  • Use otu_labels as the hovertext for the Pie Chart

• Create a Bubble Chart that uses data from the samples route (/samples/<sample>) to display 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

• Display the sample metadata from the route /metadata/<sample>

  • Display each key/value pair from the metadata JSON object somewhere on the page

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

• Adapt the Gauge Chart from https://plot.ly/javascript/gauge-charts/ to plot the Weekly Washing Frequency obtained from the route /wfreq/<sample>

  • Modify the example gauge code to account for values ranging from 0 - 9
  • Update the chart whenever a new sample is selected

Step 2 - Heroku

Deploy the Flask App to Heroku

• Use the provided SQLite file for the database

Heroku Deployment:

https://belly-button-biodiversity2019.herokuapp.com/

Step 3 - Flask API

Use Flask API code to serve the data needed for the plots

• Test the routes by visiting each one in the browser