- Simple and powerful syntax to make common charts with minimal code.
- Highly flexible plotting for deep customization.
- Sensible defaults but easy to configure as needed.
- Easily extendable via familiar D3.js syntax.
- labels: (optional) array of strings specifying the label for each dataset applied to the legend.
- datasets: array of objects specifying the data associated with each label. Each dataset is configured with
yvalues, and (optional)
zvalues (size of the points). Each dataset can also take an array of
labels(to represent points with words), a
color, and a boolean parameter
line(to indicate if a line should be drawn through the points).
timeline takes an array of objects specifying events to be included in the timeline. Each object is configred with a
date string and a
- labels: array of strings specifying the label for each dataset applied to the legend.
- groups: array of strings specifying the groups for the x-axis.
- datasets array of objects specifying the data associated with each label. Each dataset is configured with numeric
valuesand (optionally) a
hist takes an array of numeric values for which to create the histogram.
values: array of numeric values which define the size of the slices of the pie chart.
labels: (optional) array of string labels used for the legend.
Charts can be optionally configured.
yLab take string values for the x and y axis labels.
title takes a string for a chart title.
width are used to define the dimensions of the SVG.
selector is used to determine which DOM element the SVG will be attached to.
legend is a boolean value which can be used to exclude the default legend (where applicable).
Charts can easily be extended with D3 syntax. Each D3xter chart has a
canvas attribute which returns the SVG on which the chart is drawn. D3 syntax can be applied to this
canvas as it would be to any SVG. Charts also have
yMap attributes. These are functions which map values from the data domain/range to the appropriate x/y values.
Use with Python
Want to use this syntax to generate charts in Python? Check out PyDexter!