Day 36 of 180 Days of Data Viz Learning #jfdi

I’m doing some form of data visualization learning for 180 days because I need to #JFDI.  See post explaining how and why I’m doing this.

Just as a note to myself – huge improvements on Tableau performance and optimization.

The Wall Street Journal Guide to Information Graphics: The Dos and Don’ts of Presenting Data, Facts, and Figures

Chapter 3 Ready Reference (Math) Reading – Three Takeways
  • Median is useful for ranking outcomes.  Mode helps focus on typical outcome.  Standard deviation shows how tightly data is dispersed along mean.  Highly volatile stock has a high standard deviation.
  • A log scale allows you to include values that span orders of magnitude.  Using a log scale for timeline on x-axis allows you to show more detail in the short term on chart.
  • Y-axis on log scale adjusts the grid so that incremental change at different values of y-axis reflects its relative significance.

Day 35 of 180 Days of Data Visualization Learning #jdfi

I’m doing some form of data visualization learning for 180 days because I need to #JFDI.  See post explaining how and why I’m doing this.

Code Learning:

Creating Tables and Manipulating Data with SQL – Treehouse

Three Takeaways

  • DDL: Data definition language – > schema
  • DML: Data manipulation language -> CRUD
  • Set sql_safe_updates = 0; to safe mode off.  sql_safe_updates = 1; to safe mode on

Reading and Learning Data Visualization Theoretically/Critically:

The Wall Street Journal Guide to Information Graphics: The Dos and Don’ts of Presenting Data, Facts, and Figures

Chapter 2 Chart Smart Reading – Three Takeaways

  • For showing tables, use thin line rules every three to five entries to help reader follow numbers. Wide tables need one every three lines. Shading can be used to help call out columns. This makes it less daunting than a table with just grid lines.
  • Avoid using partial icons in a pictogram, eg a half of a person or a airplane is disturbing and illegible
  • Don’t use different version of a symbol to represent same variables, combinations are distracting. Instead use one with a different shade to represent the variables

Day 34 of 180 Days of Data Visualization #jfdi #catchup #doneisbetterthanperfect

Nathan Yau Data Points: Visualization That Means Something – reading first few chapters

  • There’s value in looking at data beyond the mean, median, or total because those measurements tell you only a small part of the story.  A lot of the time, aggregates or values that just tell you where the middle of a distribution is hide the interesting details that you could actually focus on for decision making and storytelling.
  • Example of showing stacked matrices month over month year over year to demonstrate and compare trends and keep visuals clear

Day 33 of 180 Days of Data Visualization #jfdi #catchup #doneisbetterthanperfect

I’m doing some form of data visualization learning for 180 days because I need to #JFDI.  See post explaining how and why I’m doing this.

Tableau Parameters Training

Three Takeaways

  • Parameters allow for using sliders and other elements of interactivity that can be applied throughout workbook.
  • Provides a single output to reference field
  • Works well with sets.

Day 32 of a 180 Days of Data Visualization #jfdi #catchup #doneisbetterthanperfect

I’m doing some form of data visualization learning for 180 days because I need to #JFDI.  See post explaining how and why I’m doing this.

Tableau Filters Training 

Filters

  • Context Filter so all other subsequent filters will be on a subcategory
  • Appy to Worksheets to stretch functionality of a filter, esp in context of a dashboard
  • Poor use of filters one of the biggest causers of bad performance in workbooks

Day 31 of 180 Days of Data Visualization #jfdi

I’m doing some form of data visualization learning for 180 days because I need to #JFDI.  See post explaining how and why I’m doing this.

*Catch-up post. #doneisbetterthanperfect

The Wall Street Journal Guide to Information Graphics: The Dos and Don’ts of Presenting Data, Facts, and Figures 

Takeaways

  • Use colors in flow charts, workplan bars, and callouts on visual timelines.
  • User spider charts for comparisons among all data points
    • -> esp when there might be recurring patterns in dataset.

Day 30 of 180 Days of Data Viz Learning #jfdi

I’m doing some form of data visualization learning for 180 days straight because I need to #JFDI.  See post explaining how and why I’m doing this.

Tableau Mapping Tutorials

Three Takeways:

  • Importance of managing hierarchies in custom mapping data
  • Drawing custom polygons with lat and long coordinates
  • Workflow Example
    • Point ID -> Path — tells Tableau what order to connect dots in
    • Polygon ID -> Detail — separates which coordinates belong to where
    • Subpolygon -> Detail — metadata
    • Area Name -> Color –groups polygons

Note to self for open datasets: http://tableaumapping.bi/