Data Visualization on a Dashboard Assignment
Order ID 53563633773 Type Essay Writer Level Masters Style APA Sources/References 4 Perfect Number of Pages to Order 5-10 Pages Description/Paper Instructions
Data Visualization on a Dashboard Assignment
Prompt
On the dashboard, you must establish a data table that displays an unfiltered view of the Austin Animal Center Outcomes data set. You’ve also been asked to add a geolocation chart to the dashboard to assist the client in visualizing the data. Refer to the Module Six resources for more information on the dash components for data tables and the geolocation chart.Open the ModuleSixMilestone.ipynb file, which contains the Grazioso Salvare dashboard’s beginning code. This file should be uploaded to Apporto and opened with the Jupyter Notebook application. Make sure you go over all of the startup code you were given. Keep a close eye on the import commands and the comments that explain what each block of code accomplishes.
Update the code to generate an interactive data table on the dashboard that displays the Austin Animal Center Outcomes data set in its raw form. You’ll use your previous CRUD Python module from Project One to run a “retrieve all” query and pull the data in from MongoDB to create your table. This data retrieval will be used to access the MongoDB database, which is the “model” element of your MVC approach. Make that the username and password for the “aacuser” account are hardcoded.Note: Depending on the speed of your internet connection, it may take a few minutes for the data table to fully render and show.
When building the interactive data table, keep your client in mind. Consider adding further features to the table, such as restricting the number of rows displayed, enabling advanced pagination, enabling sorting, and so on. Review the data tables resources in Module Six to assist you in selecting and configuring these features.
To your existing dashboard, add a geolocation chart that shows data from the interactive data table.
The function that sets up data access for the geolocation chart and calls the Leaflet function is given to you: update map:# Austin, TX is at [30.75,-97]. fun update map(viewData): dff = pd.DataFrame.from dict(viewData) .48]
return [ dl.Map(style=’width’: ‘1000px’,’height’: ‘500px’, center=[30.75,-97.48], zoom=10, zoom=10, zoom=10, zoom=10, zoom=10, zoom=10, zoom=10, zoom=10, zoom=10, zoom=10, zoom=10, zoom=10, zoom=10, zoom=10, zoom=10, zoom=10, zoom=10 children=[ dl.TileLayer(id=”base-layer-id”), dl.TileLayer(id=”base-layer-id”), dl.TileLayer(i
# Tooltip and popup for the marker
dl.Marker(position=[30.75,-97.48], children=[ dl.Tooltip(dff.iloc[0,4]), dl.Popup([ html.H1(“Animal Name”), html.P(dff.iloc[1,9]) ])You’ll need to add the appropriate statements to the layout to organize this function into your dashboard code. These statements are necessary to ensure that the geolocation chart has a place in your design. Here’s an example of a sentence:
html.Div( id=’map-id’, className=’col s12 m6′, ) html.Div( id=’map-id’, className=’col s12 m6′, ) html.Div( I
You’ll also need to include the geolocation chart’s right callback functions. These will seem identical to the user authentication and data table callback functions. The following is an example of a callback routine:
@app.callback
( [Input(‘datatable-id’, “derived viewport data”)], Output(‘map-id’, “children”))
Note: By default, the Leaflet geolocation chart will display the first row of the data table. It is sufficient to check that your geolocation chart is set up correctly if the first row of your chart reflects the position of the dog.
Finally, run the IPYNB file and take a screenshot of your dashboard to prove that it was successfully executed. The interactive data table should be populated with the Austin Animal Center Outcomes data from MongoDB, and your geolocation chart should indicate the location of the first dog in the table. In addition, the screenshot should show your unique identification (generated in the Module Five assignment).
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