Belly Button Biodiversity

Live Link: https://plotly-petralee-2019.herokuapp.com/

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 your dashboard.

• Create a PIE chart that uses data from your 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 chart.

  

• Create a Bubble Chart that uses data from your 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/

• 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