TS Plot Tool Icon

TS Plot Tool

Last modified: February 22, 2021

One Tool Example

TS Plot has a One Tool Example. Visit Sample Workflows to learn how to access this and many other examples directly in Alteryx Designer.

The TS Plot tool provides a number of different univariate time series plots that are useful in both better understanding the time series data and determining how to proceed in developing a forecasting model.

The available plots are a basic time series plot to help assess whether the original time series needs to be transformed and whether there are outliers in the series; a seasonal plot that allows for an assessment of the existence and nature of any seasonality in the series; a seasonal deviation plot that allows for an assessment of whether the underlying nature of the time series varies across seasons; autoregression function and partial autoregression function plots to help determine the nature of any underlying autocorrelation and in assessing the possible needs in terms of data differencing for the creation of an ARIMA model; and a time series decomposition plot that allows for a visual examination of the original data, the trend in the data, the seasonality in the data, and information about the residuals once seasonality and trend have been taken into account. The time series decomposition plot is based on using the non-parametric regression (loess) R function stl().

A more detailed description of the plots and methods provided by this tool can be found in Chapters 2 and 6 of Hyndman and Athanasopoulos's online book Forecasting: Principals and Practice.

This tool uses the R tool. Go to Options > Download Predictive Tools and sign in to the Alteryx Downloads and Licenses portal to install R and the packages used by the R tool. Visit Download and Use Predictive Tools.

Connect an Input

The TS Plot tool requires a Designer data stream.

Configure the Tool

Configuration Tab

Use the Configuration tab to set the controls for the time series plot.

  • Select the target field: Select the field from the data stream for which you wish to create a time series plot. Measurements for this field need to be made at regular time intervals (for example, daily, monthly, quarterly, etc.).
  • Target field frequency: Choose the time interval for the observations of the target field.
  • Series starting period (optional)...: This option allows the user to specify the starting period of the time series, which is reflected in the forecast plot by setting The year the series starts and The week, month (numeric), or quarter of the series start. If Target Field Frequency is set to Hourly, Daily (all days), or Daily (weekdays only), this option is not available.
  • Plot type: Select the plot type.

Graphics Options Tab

Use the Graphics Options tab to set the controls for the output plot.

  • Plot size: Select inches or centimeters for the size of the graph.
  • Graph resolution: Select the resolution of the graph in dots per inch: 1x (96 dpi), 2x (192 dpi), or 3x (288 dpi).
    • Lower resolution creates a smaller file and is best for viewing on a monitor.
    • Higher resolution creates a larger file with better print quality.
  • Base font size (points): Select the size of the font in the graph.

View the Output

Connect a Browse tool to each output anchor to view the results.

  • R anchor: An Alteryx R-Graph object that can be used to assist in the creation of custom reports.
  • I anchor: An interactive HTML dashboard consisting of plots and metrics. Select the different graphical elements to interact with the visualizations and reveal more information, values, metrics, and analytics.

Expected Behavior: Plot Calculations

The forecast plot uses a default date for calculations if any of the following configuration settings are used:

  • Target Field Frequency is set to Hourly, Daily (all days), or Daily (weekdays only).
  • Target Field Frequency is set to Weekly, Monthly, Quarterly, or Annually and the Series starting period is not set.

The default date used might vary, making the calculation appear random.

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