Add Panopticon Example Workbooks to your Server
Altair EmployeePanopticon Real Time (visualization server) ships with a number of ready-made example workbooks and dashboards. These are delivered in the form of a bundle file with the file extension .EXZ called Examples.exz. A Panopticon bundle file can contain one or several workbooks, one or several folders with workbooks, and optionally also data files that are used in the workbooks - provided that the datafiles were uploaded to the server (as opposed to accessed via a file path link or a web URL). This means that a bundle file is a portable file format that makes it easy to move workbooks from one system to another or to use as an offline backup of a selected set of workbooks.
The workbooks included in Examples.exz are a quick way of getting an understanding of what kind of dashboard displays and analytical interactivity Panopticon Real Time provides. They are also great materials for self-tutoring. Make a copy of any example workbook and then re-create a dashboard by investigating and copying the settings used in the example.
Panopticon distributes this in a zip format containing a number of different files. Unpack the zip file into a folder to access files shown in the image below. You see, for example, product documentation PDFs, the large panopticon.war file (the actual software that installs on Apache Tomcat), and a file called Examples.exz (marked in yellow in the image below).
Panopticon bundle files – such as Examples.exz – are added to the Panopticon server by importing it though the browser user interface.
The recommended best practice is to first create a dedicated folder for the examples – for example named “Examples”.
To import Examples.exz into a folder, right-click the folder and select Import Bundle.
You can either browse to the Examples.exz file or drag and drop it to the import dialog.
When the bundle import is done, the folder you to which you imported the files should show the following workbook icons:
To assure that you have the latest version of these examples and also any new example workbook added recently, make a fresh upload of the examples as part of installing any new release of Panopticon Real Time.
Description of the examples: Below is a list that briefly describes each of the example workbooks and what they contain, in Alphabetic Order.
Bond Maturity Screening is showing example displays of fixed income asset management data and uses a theme with dark background.
BP Oil Spill Time Line is a single dashboard example focusing on time series combination visualizations and steps through playback of historic data.
Combination Graphs demonstrate examples of what kind of displays you can create using the Combination Graphs with Numeric axis, Text Category axis, and Time axis.
CrossTab is showing various ways of organizing visualizations by rows and columns. For example, cross tabbing can be used to create a grid of several identically configured visualizations for different combinations of two or more category dimension. Cross tabbing is sometimes referred to as trellising.
Displaying Spreads is a single dashboard example showing how to use a Spread Graph, to visualize the differences between two numeric variables across time.
Equity Analysis is showing example displays of equity asset management data and uses a Theme with dark background.
Equity Universe Screening is showing equity market data – performance and market value of 1750 stocks. The example serves to show the differences between a regular table on the one hand, and visualizations such as Treemap and scatter plot on the other, in term of overview and understanding of the data.
Financial Time Series is an example with two dashboards. The first dashboard exemplifies 4 different visualization types used with daily values for trade price and volume of an equity. The second dashboard is showing how non-market hours can be handled in time series visualizations.
GDP per Capita is a single dashboard example that compares visualizations of nation specific data using choropleth map, map plot, scatterplot with map image background, a Treemap and a stacked bar graph.
How to Actions has 11 dashboards in total and is packed with useful examples on the topics of parameters, actions and action controls. This is a very good source of information for learning about how to create more dynamic and interactive workbooks.
How to Auto Parameterize is a single dashboard example that demonstrates a simplified way of setting parameters, which you can use when a parameter and a data column have identical names.
How to Color showcases the color palettes that ship with Panopticon’s default Light Theme. It also shows how to use coloring by hexadecimal RGB-code, how to use alpha blending and visualization background images.
How to Conflate Time Series Datasets shows how to make settings for conflation, also called time barring, on time series transformed dataset. Conflation is useful for achieving conformity and regularity in the timestamps, or for reducing excess granularity in the data and aggregating the data in the time dimension.
How to Drill shows a Treemap with a deep (5-level) hierarchy, and how different settings for Level of Details give different user experiences.
How to Filter shows examples of filter controls in a filter box, filtering values (include or exclude) by right-clicking directly in a visualization, and how to add one or several constant (fixed) filter on a visualization.
How to Maps summarizes the options available for geographic visualization (geoviz). The examples include a choropleth map drawn from SVG path data, and several map plot visualizations featuring different mark shapes, shape colors, shape color alpha blending, shape sizes, and connector lines of different kinds.
How to Non Additive is an example describing how to use the feature of external aggregates, which means provisioning aggregated data as part of the data source instead of having Panopticon dynamically calculate aggregate values. This is useful for scenarios where the aggregated values cannot be calculated as sums, averages, products or ratios, but are the result of much more complex calculations. This applies to for example Value at Risk analysis in capital investment activities.
How to OrderBook Transform shows an example of the kind of input data you use with the special OrderBook transform in Panopticon. The OrderBook transform takes market order data for a given instrument, and with the Order Book Graph visualization, the order book depth across time is visualized.
How to Panel Layout shows how you can use panels to achieve more flexibility and choice in the dashboard layout for the end-user. All visualization parts can be dynamically maximized to occupy the entire dashboard. If a visualization part is within a panel, then the maximized size will be limited by the panel. Then panel it self can also be maximized.
How to PDF contains some information about creating ad-hoc PDF reports from dashboards.
How to Pivot & Unpivot shows how to use the transforms for Pivoting and Unpivoting data. Pivoting a dataset takes value names from the values in one column, creates a new column for each unique value found, and fills the column with values from another column but the same source row. Unpivot does the exact opposite. Pivot makes a dataset wider, Unpivot makes a dataset longer.
How to Python contains code examples about what you can do with Python transforms or how to use Python as a data source, and some information on how to set up the integration between Panopticon and Python, using Pyro.
How to R contains code examples about what you can do with R transforms or how to use R as a data source, and some information on how to set up the integration between Panopticon and R, using Rserve.
How to Reference Lines has a focus on a feature that is specific to the Time Series visualizations, namely Reference Lines.
How to Retrieve Text XML JSON has five dashboards that each has an example retrieving data from URLs on the web.
How to Time Window has a focus on using the special Time Filter, which sets special parameters called TimeWindowStart, TimeWindowEnd and Snapshot. It also shows playback or step-through of historic data, moving average calculation and the features Time Axis Minimum Range and Time Axis Increment Step.
How to use JS Dashboard Part has a specific focus on explaining how the JavaScript part can be used. The JavaScript part can listen for changes to Panopticon parameter values and update its content (read). It can have interactive content that lets you update a Panopticon parameter with a value shown in the JavaScript part (write). It can display data from a Panopticon data table (load data).
How to Use Time Series Data Formats is an example that shows alternatives for handling data gaps (missing values) in time series. The options available are to fill with zero, fill with previous, or linear interpolation across the gap. On dashboard number two in the example, you will see the problem of having multiple series where there is data in each series for each day, but the hours part of the timestamps are not aligned. In consequence, each timestamp of each series is identified as a unique time slice in the timeseries transformed dataset, and each series will have missing values for any time slice created from a timestamp in any of the other series.
NanoExecutions is showing trade execution data for an instrument with nanosecond precision in the timestamps. One dashboard is showing all trade executions in a three hour time window and one dashboard is showing intra-second details for one selected second. The purpose of this example is to show that Panopticon is capable of handling nanosecond precision (nine decimals to the second). This is particularly interesting for post-trade retrospective best-execution analysis of historic data. Note that the Panopticon dashboards are NOT capable of updating at nanosecond intervals.
Olympics is a single dashboard example that shows some simple examples using a non-complex dataset. It is a good example to start exploring as a beginner user of Panopticon.
Order Book is an example that has a lot it common with the How to OrderBook Transform example. However, the Order Book example was created at a time when the OrderBook Transform feature did not exist.
OrderBook History shows the market order book for an instrument across a 30 minute time window at 10 second time-bars, with an orderbook depth limit of 10 levels, in an Order Book Graph. We also have an orderbook ladder and timeseries charts showing volume-weighted average price difference between bid and ask prices, and volumes at each price level. Playback through the timeseries is displayed in an orderbook price ladder visualization.
PortfolioPerformance shows a dataset representing an equities investment portfolio, diversified across different market industries. The performance of the portfolio as a whole and per industry across a year on a day by day basis is shown in timeseries graphs, and the performance to-date per each individual equity is showing in a Treemap.
ServerMonitor is the only real-life usable example in the bundle. The first dashboard in the workbook contains instructions for how to properly install and prepare the ServerMonitor workbook to make it show data about your server.
Shopping Basket Analysis is a simple example that is showing retail sales shopping basket product combinations.
Supermarket Sales Summary is a an entry-level example that shows classic tabular display of data, summary charts and more detailed analytics graphs.
US Border Crossings shows a dataset which describes changes over time, but it does not use any timeseries graphs. Instead, this example uses time buckets, where by chronologically sorted text categories are generated on the basis of date-time values.
US Treasury Yield Curves is a capital markets related example showing yield curves over time for bonds.
VizGuide is last in the alphabetically ordered list of example workbooks, but it is one of the most used examples. It has 47 (!) dashboards and shows at least one example of every graph type available in Panopticon.