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Hemant Singh

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Comparing Visualization Types for Your Data

Hemant Singh

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  • Sep 4, 2018
  • 3 Min read
  • 55 Views
  • Sep 4, 2018
  • 3 Min read
  • 55 Views
Data

Plot Data Over a Continuous Interval

Line Graph

  • Use: Analyse how the data has changed over time
  • Y axis datatype: Quantitative value
  • X axis datatype: Timescale, continuous interval, series of intervals
  • Purpose: Patterns in graph helps in predicting trends

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Histogram

  • Use: Visualize distribution of data over intervals
  • Y axis datatype: Frequency of quantitative value per individual interval
  • X axis datatype : Timescale, series of intervals
  • Purpose:
    • Find the distribution pattern
    • Identify unusual values
    • Find gaps in value ranges

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Bar Chart/Column Graph

  • Use: Compare variable across categories
  • The columns/bars can be vertical or horizontal
  • Y axis datatype: Discrete value scale
  • X axis datatype: Comparison of categories
  • Purpose
    • Answer the questions like "How many in a category/bucket?"
    • Compare categories

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Bubble Chart

  • Use: Compare multiple variables across categories
  • Points are plotted on a Cartesian coordinate system
  • Each point represents a category or a label and are generally distringuished by colors
  • Area (not the radius) of the circle represents third variable
  • Y axis datatype: One variable
  • X axis datatype: Second Variable
  • Radius of bubble: Third variable
  • Purpose
    • Comparison of three or four variables (color can also be used to denote a variable like category )
    • Find patterns and correlations
    • Get an overview of multi variable data

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Multi-set Bar Chart

  • Use: Plot more than one data series and group them together under categories
  • The bars are plotted similar to a bar chart
  • Colors of the bars denote different data set
  • Y axis datatype: Discrete value scale
  • X axis datatype: Categories
  • Purpose
    • Comparison of grouped variables across categories

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Stacked Area Chart

  • Use: Plot more than one data series
  • The point of one data series becomes the starting point for another series, so they stack up
  • It does not work on negative values
  • Y axis datatype: Value scale
  • X axis datatype: Intervals for data series
  • Purpose
    • Compare multiple variables changing over an interval
    • Compare the changes of different variables at different point
    • Find relations / patterns between variables

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Radar Chart

  • Use: Plot multi variable data radially for good visual comparison
  • Each variable has its own axis which is radial
  • All axes have center as the common origin
  • All axes have equal distance and common scale
  • All points are connected together to form a polygon
  • Purpose
    • Compare multi-variable data
    • Find similar variables and outliers
    • Find high and low scorers

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