Overview
Dash Blockchain Explorer. Up to block 1562282. BTC price 3.00138 mBTC. USD price $183.490. Market Cap $1909.12 M. Browser support. Angular supports most recent browsers. This includes the following specific versions: Angular's continuous integration process runs unit tests of the framework on all of these browsers for every pull request, using SauceLabs and Browserstack.
A line chart that is rendered within the browser using SVG or VML.Displays tooltips when hovering over points.
Examples
Curving the Lines
You can smooth the lines by setting the curveType
option to function
:
The code to generate this chart is below. Note the use of the curveType: function
option:
Creating Material Line Charts
In 2014, Google announced guidelines intended to support a common look and feel across its properties and apps (such as Android apps) that run on Google platforms. We call this effort Material Design. We'll be providing 'Material' versions of all our core charts; you're welcome to use them if you like how they look.
In 2014, Google announced guidelines intended to support a common look and feel across its properties and apps (such as Android apps) that run on Google platforms. We call this effort Material Design. We'll be providing 'Material' versions of all our core charts; you're welcome to use them if you like how they look.
Creating a Material Line Chart is similar to creating what we'll now call a 'Classic' Line Chart. You load the Google Visualization API (although with the 'line'
package instead of the 'corechart'
package), define your datatable, and then create an object (but of class google.charts.Line
instead of google.visualization.LineChart
).
Note: Material Charts will not work in old versions of Internet Explorer. (IE8 and earlier versions don't support SVG, which Material Charts require.)
Material Line Charts have many small improvements over Classic Line Charts, including an improved color palette, rounded corners, clearer label formatting, tighter default spacing between series, softer gridlines, and titles (and the addition of subtitles).
The Material Charts are in beta. The appearance and interactivity are largely final, but many of the options available in Classic Charts are not yet available in them. You can find a list of options that are not yet supported in this issue.
Also, the way options are declared is not finalized, so if you are using any of the classic options, you must convert them to material options by replacing this line: chart.draw(data, options);
...with this: chart.draw(data, google.charts.Line.convertOptions(options));
Dual-Y Charts
Sometimes you'll want to display two series in a line chart, with two independent y-axes: a left axis for one series, and a right axis for another:
Note that not only are our two y-axes labeled differently ('Temps' versus 'Daylight') but they each have their own independent scales and gridlines. If you want to customize this behavior, use the vAxis.gridlines
and vAxis.viewWindow
options.
In the Material code below, the axes
and series
options together specify the dual-Y appearance of the chart. The series
option specifies which axis to use for each ('Temps'
and 'Daylight'
; they needn't have any relation to the column names in the datatable). The axes
option then makes this chart a dual-Y chart, placing the 'Temps'
axis on the left and the 'Daylight'
axis on the right.
In the Classic code, this differs slightly. Rather than the axes
option, you will use the vAxes
option (or hAxes
on horizontally oriented charts). Also, instead of using names, you will use the index numbers to coordinate a series with an axis using the targetAxisIndex
option.
Plotly Dashboards¶
A dashboard is a collection of plots and images organized with a certain layout. There are two ways to create a Plotly dashboard: using the online creator or programmatically with Plotly's python API.
In Plotly, dashboards can contain plots, text and webpage images. To use the online creator, see https://plotly.com/dashboard/create/. Dashboards are stored in your Plotly account: https://plotly.com/organize
Dashboard Privacy¶
In the same way that a plot
can be public
, private
or secret
, dashboards can also be public
, private
or secret
independent of the plots inside them. So if you're sharing a dashboard
with someone and one or more of your plots are set to private
, they will not show for the other user. For more information about this refer to the Dashboard Privacy Doc.
Initialize a Dashboard¶
Now you can programmatically create and modify dashboards in Python. These dashboards can be uploaded to the Plotly server to join your other dashboards. You can also retrieve dashboards from Plotly.
Let's start by creating a new dashboard. To get a preview of the HTML representation of the dashboard organization - i.e. where the items in the dashboard are located with respect to one another - run the .get_preview()
method in a notebook cell. Everytime you modify your dashboard you should run this to check what it looks like.
Dash Api Documentation Browser 5 0 2 Belt Diagram
IMPORTANT NOTE
: because of the way .get_preview()
works only one cell of the Jupyter notebook can display the preview of the dashboard after running this method. A good setup is to designate one cell to look like my_dboard.get_preview()
and then run that every time you make a change to update the HTML representation of the dashboard. For the purposes of clarity, each modification of the dashboard in this tutorial is clearly shown.