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Visualizing data - getting started

Figlinq can create rich, interactive plots that are automatically and permanently connected to the underlying data. You can save/export the plots as high-quality images to use in your publications, and include them in future-proof smart manuscripts that allow others to reuse your data.

Chart Editor

Creating plots

(as well as data processing/analysis) happens in the Chart Editor. The chart editor has three key sections:

  1. Data grid. This is where you can import, arrange, process and analyze your data.
  2. plot. This section shows the final interactive plot. It is automatically updated when data or any plot property is changed, so that the up-to-date version is always shown.
  3. Chart properties & actions. This is where you can add traces, adjust properties of the plot and traces, use themes, fit curves and export (download) plots and data in multiple formats.
Chart editor area

To create a plot, Figlinq uses a chart editor that needs some data in a spreadsheet (grid). This data can be imported, but for now we just type in some data. Start by logging in to your account, which will bring you to the chart editor, at create.figlinq.com/create.

Getting started

This short tutorial describes how to create your first plot and save it for future use.

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From the '+ Create' button in the top bar of your browser window, choose 'Chart'.

Create plot

Figlinq now presents you an empty data grid Unnamed grid 1 similar to the one below, showing an empty area 'Click to enter Chart title' where the plot will be drawn and its menus to the left, where plot properties can be set and actions can be chosen

Create plot

The second column from the left shows a button +Trace and an area where the traces will appear: Trace your data.

As a start we will create a simple bar plot. In the Unnamed grid 1, enter x-values 1, 2 and 3 in the A-colum on row 1 through 3, and the sample y-values 1, 4, 9 in column B.

Create plot

Now it is time to create a trace that represents your grid data as bars. Click the +Trace. Default, the trace type is Scatter. Click on the text Scatter to bring up an overview of available trace types. Click on the Bar icon. Notice, by the way, that hovering over the icon reveals a hidden menu that links to tutorials and basic examples for that trace type.

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Now that you have chosen the Bar trace type, you can select two data columns in the grid that hold your plot data.

Use the popup Choose data... for the X axis and select column A. Use the popup Choose data... for the Y axis and select column B.

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Your simple bar plot is ready!

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Maybe you want to change the name of the trace as shown in Structure > Traces from trace 0 to something more descriptive. This is done using styling[link].

Figlinq content is only retained when saved. Save often To save, press the Save button in the left sidebar.

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Figlinq is a bit of a character when it comes to saving its contents, so keep the following in mind:

  • grid and figures are stored in the top level folder, for you to later put them in the right subfolder(s).
  • grid and trace files are indistinguishable to Figlinq by virtue of not having an identifying file extension.
  • although you are free to create your own logic, we suggest adding 'data' to the grid file name; eg. 'my first figure' would hold the traces, 'my first figure data' holds the grid(s).
  • if you forget to use two different file names and try to save both the grid and the traces using 'my first figure' as a file name, you get a non-descript error that a file already exists.
  • the text editor handling the Chart and Grid names is not perfect yet, so click the pen icon to fully erase the pre-defined file name.
  • when saving under a new name, first click the radio button, then the pen icon, then enter the new name (as clicking the 'new' radio button will erase everything already typed).
  • when the 'Existing Chart' is ticked, your previous file by that name is silently overwritten.
  • the file name is CASE SenSItiVE, so using capital letters can be the source of a lot of frustration!
  • under Advanced options you can set this plot as your template for future work.
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You have now experienced the bare basics of creating a plot. From here, you can explore other trace types or add and change features[link]. Below you can read a concise explanation of several concepts you will encounter when using Figlinq.

Traces

Figlinq's plots are based on the concept of traces. A trace is the basic unit of a plot that is linked to a data series. Although most plots contain a single trace type (e.g. scatter, bar or line), different types can also be combined together in a single plot. For instance, a bar trace can be combined with a line trace. Each trace can be independently styled and associated with different x and y axes of the plot, or share a single axis. Figlinq features over 40 different interactive trace types, which can be mixed together to create rich, beautiful plots.

Subplots

Apart from combining multiple traces in a single plot, it is also possible to create multiple subplots that share a single plot area (canvas) and are stored in a single plot file. Subplots are useful for creating sets of related plots, for creating plots with split axes, or for creating insets that may, for example, show a magnified portion of the main plot. See subplot documentation.

Data grid

Each Figlinq plot is associated with at least one data grid (and multiple grids can be associated with a single plot). The source of data for any trace is a column in the associated data grid(s). This is different than, for instance, in Microsoft Excel or in Google Sheets, where the data source can be specified as a range of cells (e.g. A1:A24) in the worksheet. As a consequence, when multiple data series reside in the same column (e.g. underneath each other), they will all be included in any trace that is associated with this column, which generally leads to undesired and corrupted plots.

A single data series (e.g. X values for a scatter trace) should thus occupy a single column in the data grid, and this column should not include any other data series (e.g. Y values).

Styling plots

Most elements of each plot (e.g. background, axes, title, etc.) and trace (e.g. line color, point size, etc.) can be independently styled. Different trace types share most of the style parameters, but some traces have additional unique styling options.

Themes

Charts created in Figlinq can inherit their style from global or personal themes. Global themes are built into the application and available to all users. Personal themes can be added by any user, for her/his private use, and also shared with collaborators. Personal themes are, in essence, just regular plots, but it is possible to apply their style to other plots. Using themes, it is thus possible to make the style of many different plots consistent, without having to manually change every style parameter.

Curve fitting

Chart editor allows fitting lines and curves to traces using a number of built-in functions (e.g. linear, quadratic or polynomial), as well as custom, multiparameter functions. It is, in principle, possible to fit any custom function using the built-in equation editor. After the curve fitting operation, the resulting curve is added, as a new (scatter) trace, to the current plot, such that it can be independently styled.

Adding annotations

You can add different types of annotations to your plot. Currently supported annotations are text, shapes (lines, arrows, rectangles, circles or ellipses) and images. Each annotation can be anchored relative to the plot axes, so that it is automatically scaled and repositioned when a plot is interactively explored or magnified. Each annotation can also be independently styled.

Exporting plots and data

Charts can be exported and downloaded as raster images of arbitrary resolution (in .jpg or .png format) or as vector graphics (in .pdf, .svg, .emf, .webp or .eps format). Charts can also be exported as HTML packages and viewed offline. Data files can be exported in .xls or .csv formats, and additionally in JSON format that is compatible with most data processing applications and languages.