**Viz Element Index**

Creating your first Data App is easy and flexible in Toric. We’re continually adding new visual elements (Viz elements) to help you tell your data stories.

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If you’re unsure which element suits your purpose, try reviewing the article Create a Data Visualization.

## Charts in Toric** **

**Dimensions and Measurements**

Most Toric charts work with two-axis dimensions (the labeling axis) and measurements (the value axis). The ** dimension** is the

*axis*you will be measuring on. For example, a “Continent” or a “Location” are examples of data dimensions. The

**is**

*measurement**what and how*you are measuring. For instance, the “number of cases” or the “cost of goods sold” are examples of the measurement axis. The measurement axis is generally measured with Count, Sum, Maximum, Minimum, Average, and Deviation.

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Example data (link to CSV) https://corgis-edu.github.io/corgis/csv/cars/

We may be interested in knowing the carmaker’s average Torque or the max Horsepower by Model in the above table. We may want to know which cars have (on Average) the best horsepower by Driveline. These are all possible charts within the above dataset.

The charts can (like everything in Toric) be combined with other nodes to answer specific questions. For example, here is a plot of best to worst Miles Per Galon for all BMW cars, plotted by their model name and year:

Count - Calculates the number of rows in a table.

Sum - The total amount resulting from adding two or more numbers, amounts, or items.

Min - Produces the minimum value from a set of numbers.

Max - Produces the maximum value from a set of numbers.

Average - Calculates the central value from a set of numbers.

**Bar Charts**

The Bar Chart works best on tabular datasets and is excellent for “bucketing” your data together. In the example below, the average response time for each cost status (bucket) is shown visually (i.e., the average response time for a cost impact of “Yes” is 6.5 days).

To create a Bar Chart, you need to connect the node’s output to the Bar Chart node’s input. The data coming in could be a data source node that contains raw data or the output of a node that is the result of a Dataflow (i.e., calculation, the combination of two data sources). Remember, QuickAdd is the fastest way to connect a new node to a previous node’s output.

Once your data is visible in the Bar Chart node, click the options button on the node’s top right to modify the viz options.

With the configuration options open, you could change what to display in your chart by selecting from the drop down menus. Below are descriptions of each option:

**X-axis**: Select the data you would like to show on the x-axis**Y-axis**: Select the data you would like to show on the y-axis

**Measurement**: Select the metric you would like to use to represent your data. You could select either Count, Sum, Min, Max, or Average (i.e., the example below shows the average response time in days for each cost impact category).

**Order by**: Organize your data by the type of measurement and in ascending or descending order. The*Measure*option will order the Bar Chart by the magnitude of the measurement selected (i.e., average).

Furthermore, select ascending displays the values from smallest to largest magnitude. Contrarily, choose the descending option to show values from biggest to smallest magnitude.

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