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PetraLee2019 / repository
Full-Stack Data Analysis to Build an Interactive Dashboard Exploring the Biodiversity Dataset
Live Link: https://plotly-petralee-2019.herokuapp.com/
Full-Stack Data Analysis to build an interactive dashboard exploring the Belly Button Biodiversity Dataset using Plotly.js, Flask and Heroku.
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
Deploy the Flask App to Heroku
Use Flask API code to serve the data needed for the plots
Selected from shared topics, language and repository description—not editorial ratings.
bigbluey /
Full-Stack Data Analysis to Build an Interactive Dashboard Exploring the Belly Button Biodiversity DataSet Using Plotly.js, Flask and Heroku