graphs | ️ Generate response time chart images in Upptime
kandi X-RAY | graphs Summary
kandi X-RAY | graphs Summary
This repository contains the package that generates response time graph images.
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QUESTION
I have this code which prints multiple tables
...ANSWER
Answered 2021-Jun-15 at 20:59So, this is a good opportunity to use purrr::map
. You are half way there by applying code to one dataframe.
You can take the code that you have written above and put it into a function.
QUESTION
I have a red and a blue area between some graphs. Where the two areas overlap, I want the area to be hatched in red and blue, i.e. red and blue stripes (like in the picture, but blue and red instead of white and red). So I want to pass the two colors by their color code onto the function. Is this possible with matplotlib.pyplot.fill_between
? Or how could I do this?
ANSWER
Answered 2021-Jun-15 at 14:21You need to add the hatch
argument to your function call to fill_between
As you have not provided an example, it will look something like this:
QUESTION
df
...ANSWER
Answered 2021-Jun-12 at 09:35df = pd.DataFrame({'channel': {0: 'Facebook', 1: 'Bing', 2: 'Google'},
'ratio_customer_to_lead_owner': {0: 2, 1: 1, 2: 6},
'ratio_customer_to_agent': {0: 5, 1: 1, 2: 13}})
df.set_index('channel').T.plot(kind='bar')
QUESTION
I've got a latex document that I publish as a pdf, but I need to share it with reviewers in Word .docx format. I've got some images and a bunch of graphs in tikz format in a separate .tex files in a figures subfolder. I've defined input@path{{figures/}}
so that I don't have to put the path into each \input{blah.tex}
call. This works just fine when I publish the document as a pdf, but when I try to use pandoc to create the docx I get a [WARNING] Could not load include file
error for the .tex files, though the images load fine.
As far as I can tell, pandoc should be able to load files from subfolders and the input@path should set it up (this post discuses how to use pandoc parameters to define the input@path).
I'm sure this is some basic lack of understanding on my part, but here's a minimum non-working example:
example.tex:
...ANSWER
Answered 2021-Jun-12 at 06:57Pandoc does not support the \input@path
parameter. You could open a feature request here.
I suggest to use TeX to compile the TikZ packages into proper graphics, e.g. with the method described in this Q&A, then use \renewcommand
to change \input
to \includegraphics
, which pandoc will understand. This will also allow to make use of the --resource-path
option.
QUESTION
I am following this tutorial to create graphs for an app I am developing, but the app keeps crashing and provides the following error message.
...ANSWER
Answered 2021-Jun-11 at 21:13This line:
QUESTION
I would like to pass data (which is saved as a state) to a react component that graphs that data. That graph should also be able to filter the data.
The data is a nested object structured as follows.
...ANSWER
Answered 2021-Jun-11 at 19:43Primitives, such as integers or Strings are passed down by their value, while Object data-types such as arrays are passed down by their reference.
Here in your example - data
is by passed reference. which makes it mutable.
In React - props should be immutable and top-down. This means that a parent can send whatever prop values it likes to a child, but the child cannot modify its own props. From ReactJS documentation
Whether you declare a component as a function or a class, it must never modify its own props.
One solution is is to pass a copy of your original data
object.
Updated Codepen. You're still mutating props - not a good idea but it works.
Edit: JSON.stringify
is NOT recommended due to it's issues with dates & non-primitive data types. Other ways to deep clone in JS -
How to Deep clone in javascript
QUESTION
I have a plotly graph (figure
) composed of multiple go.Scatter
graphs, added to the graph using fig.add_trace()
.
Some scatters share the same indices, and some don't. When hovering above a connection between two graphs which don't share the same incides I see more than one label.
In the picture you can see an example of this: instead of seeing just the green label or just the blue+red (they compose one unit because they share the same incides), I see both. How can I make it show only one of them?
NOTES:
- When hovering above a spot which isn't a connection between two segments, I do get the desired result: green if I'm above green, and blue+red if I'm above blue+red.
- I tried changing the
hovermode
parameter from the default 'x', but couldn't find a mode that works. The closest option wasclosest
, but using it only shoes one color: green or blue or red and not green or blue+red as desired. - When zooming in enough, it shows the desired labels (but making the user zoom in all the time is, of course, not a solution).
ANSWER
Answered 2021-Jun-11 at 10:24You can set the hoverdistance
manually. Setting it to 2 pixels should solve the problem for you:
QUESTION
I have an app which outputs multiple plots. The app essentially takes some data in a specific form and then splits it and then calculates some proportion tables. It then makes graphs of these various tables. In the app below I am printing out only 'one' plot and it works. The issue comes when I have multiple plots(read below).I did find some answers online on how to do this but I failed to implement them in my code. This is my first shiny app so I am not really able to figure it out.
...ANSWER
Answered 2021-Jun-11 at 08:52QUESTION
ANSWER
Answered 2021-Jun-10 at 16:24You can redraw parts of your first function:
QUESTION
I am trying to use Torch for Label Propagation. I have a dataframe that looks like
...ANSWER
Answered 2021-Jun-10 at 10:00For other readers here, it seems like this is the implementation being asked about in this question.
The method you are using to try to predict labels works with labels for nodes, not edges. To visualize this, I plotted your example data and colored the plot by your Weight
and Label
columns (code to produce plot appended below) where Weight
is the line thickness of the edge and Label
is the color:
In order to use this method, you will need to produce data that looks like this, where each node (denoted by ID
) gets exactly one node_label
:
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