19.Visualization02.Dashboards

1. Use cases: in which situations should I use this method?

• Dashboards are used to evaluate data associations, create predictions through underlying machine learning, collect additional data, and monitor the quality of ongoing data collection efforts

2. Input: what kind of data does the method require?

• A dataframe

3. Algorithm: how does the method work?

Model mechanics

Describing in words

• Dashboards are panels that facilitate understanding the information generated, showing essential metrics and indicators to achieve objectives and goals.
• When directed at individuals without data science training, the display f concepts such as risk should use display mechanisms that have been previously deemed effective
  • Pictograms and waffle plots - see waffle

Describing in images

Describing with code

Breaking down equations

Reporting guidelines

Data science packages

• waffle
• Shinydashboard
• DASH

Suggested companion methods

Learning materials

1. Books

2. Articles

4. Output: how do I interpret this method's results?

Mock conclusions or most frequent format for conclusions reached at the end of a typical analysis.

Tables, plots, and their interpretation

5. SporeData-specific

Templates

Data science functions