Kursinnhold
Tableau Fundamentals
Tableau Fundamentals
1. Introduction to Tableau
2. Tools in Tableau
Dimensions and MeasuresChallenge: Comparing Sales and Profit by StateContinuous and Discrete FieldsChallenge: Identifying the Month with Lowest SalesDimension Filters Measure FiltersChallenge: Finding the Most Profitable Customer in ArtCalculated FieldsChallenge: Comparing California and New York to Other StatesInteractive Dashboards with ParametersChallenge: Finding the Sub-Category with the Most SalesWorking with Sets Challenge: Analyzing Bookcase Profit ConcentrationSets Applications
3. Basic Visualizations
Visualizing Data with HeatmapsChallenge: Identifying Top-Selling Sub-Category by RegionScatter PlotsChallenge: Determining the Highest Sales and Profit by StateTreemapsChallenge: Analyzing the Least Profitable Sub-CategoryCombination ChartsChallenge: Comparing Sales and Profit Trends for PhonesSparklines
Box Plots
A box plot in Tableau provides a compact visualization of the distribution and variability of numerical data, highlighting key statistics like the median, quartiles, and outliers. This chart type is particularly effective for identifying patterns, spotting outliers, and comparing data distributions across categories.
A box plot typically consists of the following components:
Data Insights from Box Plots
To read a box plot correctly, pay attention to the following points:
- If the box is short and the whiskers are short, this may indicate that the data is concentrated in a narrow range and has few outliers:
- If the whiskers are long, this may indicate a large scatter of data and the presence of outliers:
- If the median is offset from the center line of the box, this may indicate a skewed distribution:
Finding points behind the whiskers helps identify outliers and potential anomalies in the data.
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Seksjon 4. Kapittel 6
