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How do I change the backend in CoCalc to show a matplotlib scatter graph?

I have a program that is working fine locally, but I need to use it in CoCalc on the cloud to share with a group. Everything works fine until the end, when I want to create a scatter graph, in standard way. There are a bunch of other specs, but essentially, it's just
plt.scatter(x, y, color = 'blue')
plt.show()
Nothing tricky. But in Cocalc, it tells me "UserWarning: Matplotlib is currently using agg, which is a non-GUI backend, so cannot show the figure."
Here are the imports from the beginning of the file:
import nltk
import pandas as pd
import matplotlib.pyplot as plt
import numpy as np
I've searched for this error and tried the solutions I've found, such as importing tkinter. So, for instance, if I change the headers to
import nltk
import tkinter as tk
import pandas as pd
import matplotlib
matplotlib.use('TkAgg')
import matplotlib.pyplot as plt
import numpy as np
I get a different error: "Cannot load backend 'TkAgg' which requires the 'tk' interactive framework, as 'headless' is currently running."
I've seen instructions about pip installations and such, but a) I'm not sure the installations would make everything work for my group, and b) CoCalc generally has most of the standard packages ready to go, so maybe that's not the problem?
Obviously, I'm not experienced with these issues, so help is much appreciated.

If you're using a Jupyter notebook in CoCalc, then the above will just work fine. Here's an example:
https://cocalc.com/wstein/support/matplotlib-scatter-in-jupyter
If you're writing all of your code as part of a Python program (so, e.g., .py files) and running this from a Terminal, CoCalc will also fully support Tk and this working! However, you have to start a new X11 desktop session in CoCalc by clicking +New --> "Linux Graphical X11 Desktop", then run your Python program from the terminal in the upper left. You'll see any windows that pop up in the main window off to the right.
See https://cocalc.com/wstein/support/scatter-matplotlib-x11

How can I display an image on VS Code and PyCharm?

I want to choose the best IDE for Python programming so I'm testing different softwares but I have problem.
When I try this code blocks on VS Code I don't see any error but the image is not showing
import matplotlib.pyplot as plt
import matplotlib.image as mpimg
image = mpimg.imread('exit-ramp.jpg')
plt.imshow(image)
VS Code
When I try run the same code on PyCharm I see some errors
PyCharm
But when I run the same code on Jupyter Notebook it works. What can I do?

Bro, try that:
import matplotlib.pyplot as plt
import matplotlib.image as mpimg
image = mpimg.imread('exit-ramp.jpg')
plt.imshow(image)
plt.show()
i've made a test in my vscode.
Few weeks ago i used a lot pycharm... but i get some library errors with pandas and pycharm its a little bit heavy.
VSCODE its light and i didnt get any library error that i had with pycharm.

I believe this is a backend problem to be changed in matplotlib. If you start your Python shell whether you are in a bash shell or in vscode, you should use a backend that will show the plot. Otherwise the plt.show() call is required.
So, one solution is to change the backend either manually in you Python shell or when starting the Python shell as explained here below.
Note, however, that I always use the qt5 backend but got the same issue as yours: no plot appears. I changed to the Qt5Agg backend and it worked for me (providing PyQt5 is installed).
So, first solution, you can try to set the backend when starting the Python shell:
ipython --pylab Qt5Agg
You should use a GUI backend amongst the possible backend. If you do not known, try to replace Qt5Agg by auto
The second solution consists in changing the backend manually once in the Python shell:
import matplotlib as plt
plt.use('Qt5Agg')

Right click on your code -> Run current file in interactive window.

Pycharm Jupyter Interactive Matplotlib

Interactive matplotlib plotting is already a thing, but does not work properly in Pycharm, when used within a jupyter notebook.
The %matplotlib notebook does not work (throws no error, but I get <IPython ... JavaScript object> instead of a plot. If I plot normally (also with or without plt.show()) I just get a png and cannot interact in any way (even if, e.g., sliders are visible).
I couldn't find any answers elsewhere to this exact problem. It might be working in the browser version of jupyter, but I would like to stick to using PyCharm.
Pycharm v 2017.3 Community Edition

You can try:
import matplotlib
matplotlib.use('Qt5Agg')
import matplotlib.pyplot as plt
Instead of importing only the peplos.
It's a trick I found on forum of Jetbrains
https://intellij-support.jetbrains.com/hc/en-us/community/posts/115000736584-SciView-in-PyCharm-2017-3-reduces-functionality-of-Matplotlib It works for me. With this, you skip actually the Sciview and plot in a normal matplotlib window

Matplotlib not displaying image

I am trying to use matplotlib to view an image in ipython. However, I solely obtain a description of the image as opposed to seeing the actual image:
>>> import numpy as np
>>> import matplotlib.pyplot as plt
>>> plt.imshow(an_array)
Out[4]: <matplotlib.image.AxesImage at 0x7fb626f063d0>
This is with the backend set to Qt5Agg or TkAgg in .matplotlibrc
I have the same issues whether or not I am working in a conda virtual environment
I am running: Scientific Linux release 6.8 (Carbon), Python 2.7.13, Anaconda 4.3.0 (64-bit)
I have had similar issues on my local computer running MacOSX
I would be most grateful for any advice,
Thanks
Rob

Add %matplotlib inline before import matplotlib.pyplot as plt to enable automatic visualization of your plots when the cell has finished executing.
Note, however, that this works just in iPython notebooks. Normally, you'd need to call plt.show() (without any arguments) to visualize the plots.

Plotting window doesn't show up with pylab [duplicate]

I just installed matplotlib in Ubuntu 9.10 using the synaptic package system.
However, when I try the following simple example
>>> from pylab import plot;
>>> plot([1,2,3],[1,2,3])
[<matplotlib.lines.Line2D object at 0x9aa78ec>]
I get no plot window. Any ideas on how to get the plot window to show?

You can type
import pylab
pylab.show()
or better, use ipython -pylab.
Since the use of pylab is not recommended anymore, the solution would nowadays be
import matplotlib.pyplot as plt
plt.plot([1,2,3])
plt.show()

pylab.show() works but blocks (you need to close the window).
A much more convenient solution is to do pylab.ion() (interactive mode on) when you start: all (the pylab equivalents of) pyplot.* commands display their plot immediately. More information on the interactive mode can be found on the official web site.
I also second using the even more convenient ipython -pylab (--pylab, in newer versions), which allows you to skip the from … import … part (%pylab works, too, in newer IPython versions).

Try this:
import matplotlib
matplotlib.use('TkAgg')
BEFORE import pylab

The code snippet below works on both Eclipse and the Python shell:
import numpy as np
import matplotlib.pyplot as plt
# Come up with x and y
x = np.arange(0, 5, 0.1)
y = np.sin(x)
# Just print x and y for fun
print x
print y
# Plot the x and y and you are supposed to see a sine curve
plt.plot(x, y)
# Without the line below, the figure won't show
plt.show()

Any errors show up? This might an issue of not having set the backend. You can set it from the Python interpreter or from a config file (.matplotlib/matplotlibrc) in you home directory.
To set the backend in code you can do
import matplotlib
matplotlib.use('Agg')
where 'Agg' is the name of the backend. Which backends are present depend on your installation and OS.
http://matplotlib.sourceforge.net/faq/installing_faq.html#backends
http://matplotlib.org/users/customizing.html

Modern IPython uses the "--matplotlib" argument with an optional backend parameter. It defaults to "auto", which is usually good enough on Mac and Windows. I haven't tested it on Ubuntu or any other Linux distribution, but I would expect it to work.
ipython --matplotlib

If you encounter an issue in which pylab.show() freezes the IPython window (this may be Mac OS X specific; not sure), you can cmd-c in the IPython window, switch to the plot window, and it will break out.
Apparently, future calls to pylab.show() will not freeze the IPython window, only the first call. Unfortunately, I've found that the behavior of the plot window / interactions with show() changes every time I reinstall matplotlib, so this solution may not always hold.

If you are starting IPython with the --pylab option, you shouldn't need to call show() or draw(). Try this:
ipython --pylab=inline

--pylab no longer works for Jupyter, but fortunately we can add a tweak in the ipython_config.py file to get both pylab as well as autoreload functionalities.
c.InteractiveShellApp.extensions = ['autoreload', 'pylab']
c.InteractiveShellApp.exec_lines = ['%autoreload 2', '%pylab']

If you are user of Anaconda and Spyder then best solution for you is that :
Tools
-->
Preferences
-->
Ipython console
-->
Graphic Section
Then in the Support for graphics (Matplotlib) section:
select two avaliable options
and in the Graphics Backend:
select Automatic

Another possibility when using easy_install is that you need to require the most recent version of matplotlib.
Try:
import pkg_resources
pkg_resources.require("matplotlib")
before you import matplotlib or any of its modules.