Data Visualisation is Open Xerox component which allow you to better understand and show your data.
It is available for any data source and any table. For the moment you can choose among seven visualization types
- histogram: a column chart that represents the distribution of the single variable.
- column chart: graphically similar to the histogram however conveys different information.
- scatterplot: is a visualization type constructed by plotting points in a coordinates system.
- pie chart: a simple chart that displays the categories as the pieces of the circle.
- line chart: similarly to the scatterplot a line chart is a set of points plotted in a coordinates system and the points are connected with a line.
- area chart: is the same concept as line chart but the area under the curve is filled with a color.
- streamgraph: is a type of the stacked area chart however the layers are not aligned to the vertical axis.
This allows you to generate charts from the data.
To open the Data Visualization view click on the chart icon in the upper-right menu.
When opening the Data Visualization view, a welcome page will appear with the short introduction of the available chart types. On the left side you will find a Data Visualization menu which allows you to configure the type of the chart and the data to plot.
You first select the chart type you want to use and then you select the variables that will be used for its generation. To generate a visualization click on the Generate button.
- To create a histogram, pie chart or scatterplot simply choose variables from the select boxes. Some fields may be left empty as they are not mandatory.
- To create a line chart, area chart or streamgraph you need to specify at least two variables: one for horizontal (X) axis and one for vertical (Y) axis. If you wish to display more than one series of data you can select more than one variable using Y axis select box.
- To create a column chart you need to specify one variable for the labels and one which will define the height of the columns. However, if you want to create a stacked column chart you have two different ways to achieve it. You can add one more categorical variable, using Group by field, which will divide each column. The other way it to select more than one variable in the Values select field.
If you do not see some variables in the select boxes it means that the data type is not supported for the selected chart type.
Once a chart is generated an additional “Options” sub-menu appears. It allows you to manipulate the parameters of the visualization - you can see direct changes as you manipulate the parameters.
However, when changing a source variable click on the “Generate” button to regenerate the chart.
To view the chart in full screen, click on the “fullscreen” button in the top-right corner of the visualization.
Besides the styling options which allow you to change the graphical appearance of the visualization e.g. color, shape, size of the elements there are several options available which control more the data being displayed:
- Absolute count: display total count of data in the histogram instead of the relative percentage.
- Sort: sort data by frequency. By default data are sorted by alphabetical order.
- Bins: change the number of intervals for converting the continuous variable into discrete counterparts.
- Null/empty data: if your data contains empty values this option allows displaying them and treating as separate category.
- Jitter: In case many points may have the same coordinates and therefore have the same position on the plot, a small random noise (called jitter) can be added to the coordinates of the points. This allows to distinguish a high concentration of points.
- Stacked: stack different series of data in the chart.
- 100% stacked: translates stacked chart into range (0, 1) so the proportion between series is easier to follow.
- Slices: pie charts cluttered with many slices are often unreadable. This option allows to set the maximal number of slices for the pie chart, all the others data will be grouped into a single others category.
All visualizations are interactive, in order to explore the data and get more details. Often, when you click on the various elements e.g. slices of a pie chart or bars of the bar chart you will see a popup with detailed information of the point/area being displayed. You can also zoom and pan to narrow the visible data space using the same gestures as when interacting with maps: the mouse wheel allows you zoom while click and move the mouse to pan. While zooming you will see a small indicator in the top-right corner which helps you to locate yourself in the data space.
You can export your visualization to share it with the others or save it for your own use. Click on the Export button to open an “Export” sub-menu. There are basically two types of export: static and interactive.
Static export will take a snapshot of currently displayed chart. You can download it as a svg or an image file to embed it in any web page. It is also available as a url that you can copy/paste into your browser.
Interactive export is available to be integrated into a web page with an <object> markup. This will reconstruct the current visualization while preserving all the interactivity e.g. tooltips and zooming. When you use this option, the data must be reloaded by everybody that view this chart and therefore check that such visitors have the rights to read these data, by either adding this people the list of authorized users or making this source public.
If you are the owner of the data an additional “Save” button is available in the Options sub-menu. It allows you to export your visualization and save it as a new web page in the collection of web pages for your data. When clicking on the “save” button a dialog box will open asking you provide a name for the page to be created with this visualization. Additionally, you can select “Add link to the left menu” checkbox to automatically add link to this page in the data menu located in the top-left area of the page.
Sometimes you may want to filter your data before visualizing it. It can be done using Input Query menu located just below the Data Visualization menu on the left.