Charts

General information

Brick provide wide possibility of data visualization with different dashboards, they are:
  • bar plot for tracking changes over time or comparing different groups
  • box plot for showing distributions, identifying outliers or finding differences between categories
  • scatter plot for showing relationship between two variables and exploring patterns of this relationship
  • heatmap plot for visualizing concentration of values in two dimensions
  • histogram plot for showing distributions
  • line plot to visualize changes over time or to display data over numerical axis
  • pie chart to show parts of the whole
  • treemap for organizing hierarchical data
  • Gantt chart for planning and scheduling processes, based on time and resources needed
  • radar chart (the same as spider chart) to visualize multidimensional data

Description

Brick Locations

Bricks → Views → Charts

Brick Parameters

  • Plotting speed optimization
    • Choose this option if you want to build your plots more fast but will lose a bit in resolution.
  • Add a chart
    • To add a new
    • Diagram Type
      • Specify type of dashboard to plot on. There are: bar, box, scatter, heatmap, histogram, line, pie, treemap, gantt, radar.
    • Chart Name
      • A name for the chart
      Then, for different type of charts there are different parameters that are needed to be filled.
      bar
      • X column
        • The column that would be on the x (horizontal) axis
      • Y column
        • The column that would be on the y (vertical) axis
      • Group by
        • The column by which divide the bars
      • Aggregation
        • Different type of aggregation: count, mean, max, min, sum, median, mode.
      box
      • Сolumns
        • The column which would be represented on the plot
      • Group column
        • The column by which the values would be grouped
      • Show outliers
        • Turn parameter on to show dots which are out of IQR
      • Display as a violin
        • Turn parameter on to show it in the violin form
      scatter
      • X column
        • The column that would be on the x (horizontal) axis
      • Y column
        • The column that would be on the y (vertical) axis
      • Size
        • Can be chosen for either value or column
      • Color
        • Can be chosen for either value or column
      • Opacity
        • The level of opacity varies from 0.1 to 1
      • Linear approximation
        • Turn parameter on to show the line trend
      heatmap
      • X column
        • The column that would be on the x (horizontal) axis
      • Y column
        • The column that would be on the y (vertical) axis
      • Aggregation
        • Different type of aggregation: count, mean, max, min, sum, median, mode.
      histogram
      • Columns
        • Columns for plotting dashboards
      • Show Distribution
        • Turn parameter on to show distribution of selected data
      • Show rug
        • Turn parameter on to show rug
      line
      • X column
        • The column that would be on the x (horizontal) axis
      • Y column
        • The column that would be on the y (vertical) axis
      • Group by
        • The column by which divide the bars
      • Show data points
        • Turn on to show points as well as line
      pie
      • Columns Hierarchy
        • You can insert pie chart inside of another chart and you can order them in any way
      treemap
      • Data Column
        • Column which contains values
      • Labels Column
        • Column which maps label to a data
      • Aggregation
        • Different type of aggregation: count, mean, max, min, sum, median, mode.
      • Parent Column
        • Column which maps the parent to a label
      Gantt
      • Date Column
        • Column with a date values in it
      • Event Column
        • Column which contains names of events
      • Color Column
        • Column with colours for each event
      radar
      • Categories Column
        • Column that consists ranking in different categories
      • Names Column
        • Column that consists names of the items
  • Open dashboard view
    • Shows all the plots that have been built. In this view it is possible to download a png file, zoom a plot, autoscale or reset axes.

Brick Inputs/Outputs

  • Inputs
    • Brick takes the data to plot

Example of usage

Let's consider the binary classification problem. The inverse target variable takes two values - survived (0) - good or non-event case / not-survived (1) - bad or event case. The general information about predictors is represented below:
  • passengerid (category) - ID of passenger
  • name (category) - Passenger's name
  • pclass (category) - Ticket class
  • sex (category) - Gender
  • age (numeric) - Age in years
  • sibsp (numeric) - Number of siblings / spouses aboard the Titanic
  • parch (category) - Number of parents / children aboard the Titanic
  • ticket (category) - Ticket number
  • fare (numeric) - Passenger fare
  • cabin (category) - Cabin number
  • embarked (category) - Port of Embarkation
Let’s move to some visualizations.
  1. First one will be scatter plot with settings listed below with result:
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  1. We will show a bar chart where on x axis we put sex column and for y axis survived column.
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  1. We build a pie chart for pclass:
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  1. We will build a box plot for fare column
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  1. We will show how to build a heatmap plot:
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  1. To plot a Treemap chart we need to create some synthetic data, the data and chart build will be presented below:
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  1. Next example will be associated with a radar chart, for this example we also need to create some synthetic data. Let’s visualize results we have:
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