Creating Graphs

Create graphs to visualize your data. This page explains basic graph types including histograms, scatter plots, bar charts, and time series plots.

How to Create Graphs

  1. Open Graph Builder tab: Click the "+" button at the top of the screen and select "Graph Builder"
  2. Select dataset: Choose the dataset to graph from the dropdown menu in the header
  3. Select graph type: Click the type of graph you want to display (Histogram, Scatter Plot, Bar Chart, etc.)
  4. Configure settings: Set axes and variables according to the selected graph type
    • Histogram: Variable, number of bins, grouping
    • Scatter plot: X-axis, Y-axis, color coding, size
    • Bar chart: Category, value, aggregation method, sorting
  5. Adjust options: Set filter conditions and additional options as needed

Graphs are displayed in real-time in the preview area on the right, allowing you to explore optimal visualizations while changing settings.

Basic Graphs

Histogram

Displays the distribution of a single numeric variable as a bar graph. Useful for understanding frequency distribution and shape of data, and identifying outliers.

Use cases:

  • Check age distribution
  • Examine test score distribution
  • Understand sales amount distribution

Settings:

  • Variable: Select the numeric column to graph
  • Bins: Specify the number of bars (bins)
  • Group By: Select a category column to display color-coded by group

Histogram of numeric variable distribution created with MIDAS: displays data frequency per bin and visualizes distribution shape and outliers

Scatter Plot

Visualizes the relationship between two numeric variables as points. Discover correlations, patterns, clusters, and outliers. Supports interactive selection, density visualization, and grouping by categorical variables.

Use cases:

  • Examine relationship between height and weight
  • Check correlation between advertising spend and sales
  • View relationship between scores in two exam subjects

Settings:

  • X Axis: Numeric column for horizontal axis
  • Y Axis: Numeric column for vertical axis
  • Color By: Select a category column for color-coded grouping
  • Size By: Select a numeric column to represent with point size

MIDAS Scatter Plot: places two numeric variables on X and Y axes, displaying each data point as a dot. Used for discovering correlations and patterns

Bar Chart

Compares values by category using vertical or horizontal bars. Ideal for comparing categorical data, ranking displays, and showing aggregate statistics (count, sum, average, etc.).

Use cases:

  • Compare sales by product category
  • Display customer count by region
  • Aggregate order count by month

Settings:

  • Category: Column representing categories
  • Value: Numeric column to aggregate
  • Aggregation: Aggregation method (Count, Sum, Average, etc.)
  • Orientation: Vertical or horizontal bars
  • Sort: Sort order

MIDAS Bar Chart: displays values by category as vertical or horizontal bars, with selectable aggregation methods (count, sum, average, etc.)

Time Series Plot

Displays data changes over time as a line chart. Identify trends, seasonality, and patterns. Display multiple time series with different line styles and compare across periods.

Use cases:

  • Check daily sales trends
  • Track monthly visitor changes
  • Observe annual temperature variations

Settings:

  • Time: Column representing date or datetime
  • Value: Numeric column to display
  • Group By: Used when displaying multiple series

MIDAS Time Series Plot: displays data changes along time axis as line chart, visualizing trends and seasonal patterns

Advanced Graphs

Pair Plot

Displays pairwise relationships between multiple numeric variables as a scatter plot matrix. The diagonal shows the distribution of each variable. Useful for exploring correlations and multivariate patterns.

Use cases:

  • Check correlations between multiple measurements at once
  • Understand the overall structure of a dataset

MIDAS Pair Plot: displays pairwise relationships between multiple numeric variables as scatter plot matrix. Shows distribution of each variable on diagonal, allowing simultaneous confirmation of multivariate correlations

Rug Plot

Visualizes the temporal distribution of datetime events. Displays individual events as vertical lines (ticks) on a timeline, with optional intensity curve using moving average.

Use cases:

  • Check timing of log events
  • Visualize concentration of access times

MIDAS Rug Plot: displays temporal distribution of datetime events as vertical lines (ticks) on timeline. Intensity curve using moving average visualizes event concentration

Custom Graph

Creates flexible visualizations based on Grammar of Graphics principles. Build layered plots by combining geometric elements, statistical transformations, and aesthetic mappings.

See the Custom Graph Guide for details.

Graph Operations

Interactive Selection

All graphs support data point selection. Selection methods vary by graph type:

Rectangle Selection (Scatter Plot, Histogram, Rug Plot)

  • Selection mode: Drag mouse to select a range
  • Pan mode: Drag graph to move the display range

Mode toggle buttons are displayed below the graph.

Click Selection (Bar Chart, Time Series Plot, Pair Plot, Custom Graph)

  • Click bars, points, or bins to select
  • Cmd/Ctrl+click to add to selection or deselect

Selected rows are highlighted in other tabs and graphs as well.

Saving Graphs

Graph settings created in Graph Builder are automatically saved to the project as tab state. Graph settings are preserved when you close and reopen the project.

To save a graph as an image:

  1. Add the graph to a Report ("Add to Report" button)
  2. Click the "Export" button for the graph in the Report tab
  3. Save in SVG format

Changing Settings

Graph settings (column selection, filters, display options, etc.) can be changed at any time. Graphs update in real-time when settings are changed.