- This is the personal project for unit 15(Interactive-Visualizations-and-Dashboards) of Data Visualization and Analytics(graded A+).
- Build an interactive dashboard to explore the Belly Button Biodiversity DataSet. For more details, see here.
- A snapshot of the app:
- The app website for this project: https://belly-botton-biodiversity.herokuapp.com/
- The tools used in this project: plotly.js, D3.js, SQLAlchemy, flask,SQLite.
- Select a sample from upperleft corner pf the dashboard, the belly-button-biodiversity related data will be visualized in three different, complementary plots: a Pie plot, a scatter plot, and a gauge chart.
- To play the app locally, clone the repo, install the packages, and run "python app.py" in command line.
In this assignment, you will build an interactive dashboard to explore the Belly Button Biodiversity DataSet.
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.
-
You are welcome to create any layout that you would like for your dashboard. An example dashboard page might look something like the following.
Deploy your Flask app to Heroku.
-
You can use the provided sqlite file for the database.
-
Ask your Instructor and TAs for help!
The following task is completely optional and is very advanced.
-
Adapt the Gauge Chart from https://plot.ly/javascript/gauge-charts/ to plot the Weekly Washing Frequency obtained from the route
/wfreq/<sample>
-
You will need to modify the example gauge code to account for values ranging from 0 - 9.
-
Update the chart whenever a new sample is selected
Use Flask API starter code to serve the data needed for your plots.
- Test your routes by visiting each one in the browser.
-
Don't forget to
pip install -r requirements.txt
before you start your server. -
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.
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