I really enjoy this image-charts.com service. Is there a way to add trendlines a line chart? I have attempted to add this parameter
trendlines: { 0: {} } from google (as that is their trendline code and this is powered by google?)
Is there a way to add trendlines a line chart?
Yes, that's what we call a compound chart, follow the 3 steps and you are good to go (note: it will require a Enterprise+ subscription).
You can also use editor.image-charts.com editor to easily edit your static chart (again, if you wish to leverage compound charts you will have to take an Enterprise+ subscription).
Related
I need a graph in Power BI that is a line graph but has more than 2 y-axes.
Each line has to have its own y-axis (own scale and color). The lines are from categories (like an ID) that need to be selectable with a slicer.
I have tried many custom graphs, but none seem to match my requirements. Plotly has functionality to build such graphs, but it is not supported in the python visual and it does not work in the R visual. I tried the plotly.js visual with the https://github.com/plotly/react-chart-editor editor. I could build the right graph but for each "trace" I had to manually filter out the ID's of the separate lines, instead of doing it with a slicer.
Quick attempt with plotly.js in Power BI looks like this:
I'd rather avoid writing my own custom visual, but any advice or tips are welcome.
I am trying to create a medical graph to display the heart rate. It will have the live data on the left part and the prediction forecast on the right. I will get both from the backend API, and I need now to show them as one line on the graph. I am using ReactJs and chart.JS.
Look the picture below to understand better:
(https://i.stack.imgur.com/qWd6H.jpg)tter:
I just tried to do the regression but it will be done from the backend. I am getting from the API two fields: live data: and prediction:
And I need them to add them together.
I think you can use segment option for this. You can change line styles based on datapoint options / value.
Usage example: Link an official example
I'm an advanced R user, but have just started recently using Rcy3 to create better visualisations of my graphs.. problem is I don't know how to add a legend to my figure that would explain the coloring of my nodes.
You may want to look at the app "LegendCreator". It's sort of in the beta stage, but it can be useful particularly for gradient legends. It also supports automation, although generally, you'll want to manually position the legend.
-- scooter
I am attempting to create a pie chart that will display the health status of various systems. This is what the chart currently looks like:
Each data point, in addition to the possible errors messages, has a name in its data.
Is it possible to configure the chart so the system names are shown in the pie chart? In the tooltip for each slice would be preferable, but any solution will work.
You can Add (button at the buttom of the configuration) a second visualization, which will then add another layer around your first visualization.
This is an example for log.level and around it labels.url.full:
If I make a bar chart like this:
bar = Bar(data,labels,tools='Hover')
I can make tooltips like this:
hover = bar.select(dict(type=HoverTool))
hover.tooltips = [
('Grade',' $x'),
('Students',' #Students'),
]
However, when I do variables with '#variable' in the tooltips, I am limited to those specified in data. In normal Bokeh plots, I can have custom variables associated with data points by using a ColumnDataSource. Bar does not support ColumnDataSources. Is there another way to make custom variables available in Bokeh chart tooltips (hover)?
There's is an open PR to add this feature to the charts interface.
It's going to be part of the next bokeh release and also be available through the dev builds (or in the master branch of course) as soon as it gets merged if you need it sooner.
I had the same problem. The trick here is to use GlyphRenderer to make the bar chart aware of the data source. For e.g., you can add a line
bar.select(dict(type=GlyphRenderer)) before hover = bar.select(dict(type=HoverTool)). You can then refer your custom variables using #cat, #zero etc. See the following link for more information and a working example.
https://groups.google.com/a/continuum.io/forum/#!topic/bokeh/-aDPTqDPA3M