This is a Python-specific PyCharm IDE question regarding the viewing of resulting output plots (in this case, from the Seaborn library). I am looking for a more user-friendly form of displaying my plots external to creating a new window (then exiting that window and opening the next window...) every time I want to view my output plots. In this case, I would also like to avoid any sort of web-dependent output. An example of the incredibly ugly and down-right brutal way in which I currently generate then view plots is as follows:   import matplotlib.pyplot as plt fig, ax = plt.subplots() ## plot plot plot plt.show()   I also put myself through this in other viz libraries such as matplotlib. While I am aware of the sequential output formatting of Jupyter NoteBooks, I prefer working through PyCharm's environment and would like any answers to be geared toward the PyCharm IDE. Any and all suggestions are certainly welcome. Ideally, I will be provided the most sufficient way to view my plots across any library, but library-specific answers are absolutely welcome as well.
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After these instructions in the Python interpreter one gets a window with a plot:  from matplotlib.pyplot import * plot([1,2,3]) show() # other code   Unfortunately, I don't know how to continue to interactively explore the figure created by show() while the program does further calculations.  Is it possible at all? Sometimes calculations are long and it would help if they would proceed during examination of intermediate results.
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I mean something like  showing the frequencies of a user's public contributions on GitHub.    I really like this kind of chart, as I think that they display the intended data in a really nice and easy to see way, but I have no clue what they are called, so I can't look for a library to help me generate them. Can someone tell me the name of this type of graph / chart?
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I'm interested in using Blender for producing images, 3d files, or calculating geometry on a server.  Can I make blender run a python script without opening a GUI?  If not, can I incorporate Blender's python API into my own python script without running a GUI?
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I'm using Ubuntu 20.04 LTS. I've recently installed Matplotlib for Python 3.9 and when I try to plot a graph it gives me the error: Matplotlib is currently using agg, which is non-GUI backend, so cannot show the figure.  Do I have to install something else for it to work?
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I have some Python code that works correctly when I use python.exe to run it, but fails if I use pythonw.exe.       def runStuff(commandLine):         outputFileName = 'somefile.txt'         outputFile = open(outputFileName, "w")          try:             result = subprocess.call(commandLine, shell=True, stdout=outputFile)         except:             print 'Exception thrown:', str(sys.exc_info()[1])      myThread = threading.Thread(None, target=runStuff, commandLine=['whatever...'])     myThread.start()   The message I get is:       Exception thrown: [Error 6] The handle is invalid   However, if I don't specify the 'stdout' parameter, subprocess.call() starts okay.  I can see that pythonw.exe might be redirecting output itself, but I can't see why I'm blocked from specifying stdout for a new thread.
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Lots of people use a main tool like Excel or another spreadsheet, SPSS, Stata, or R for their statistics needs. They might turn to some specific package for very special needs, but a lot of things can be done with a simple spreadsheet or a general stats package or stats programming environment.  I've always liked Python as a programming language, and for simple needs, it's easy to write a short program that calculates what I need. Matplotlib allows me to plot it.  Has anyone switched completely from, say R, to Python? R (or any other statistics package) has a lot of functionality specific to statistics, and it has data structures that allow you to think about the statistics you want to perform and less about the internal representation of your data. Python (or some other dynamic language) has the benefit of allowing me to program in a familiar, high-level language, and it lets me programmatically interact with real-world systems in which the data resides or from which I can take measurements. But I haven't found any Python package that would allow me to express things with "statistical terminology" – from simple descriptive statistics to more complicated multivariate methods.  What can you recommend if I wanted to use Python as a "statistics workbench" to replace R, SPSS, etc.?  What would I gain and lose, based on your experience?
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I want to install the PyCharm IDE by JetBrains for Python (free community edition).  I managed to , but I do not know how to install it. Can you please help me?
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I'm trying out  with gnuplot to generate the data.  This works by having pgfplots write some stuff to an external file, run gnuplot on the file, and then use the generated data to plot the graph.  The problem I'm having is that I get different behaviour under xelatex as pdflatex or lualatex.  In xelatex, the data file is littered with ^^I whereas in the other two formats these are tabs.  It appears that the code ^^I is getting stored as a macro which then gets written out to the file, so possibly there's something funny going on with the ^^I syntax: xelatex is reading it literally.  Indeed, when I do \show\pgfplots@TAB (the macro in question) then for pdflatex and lualatex then I get a literal tab whereas for xelatex I get ^^I.  So how do I get a tab in xelatex?  And why isn't \gdef\pgfplots@TAB{^^I} working?  (The previous line in the code, by the way, is \catcode`\^^I=12 - I don't know if that has anything to do with it.)
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I'm trying to figure out a good workflow for developing scripts and add-ons in Blender. Here's what I'm currently doing as I try my luck with a PyNode add-on:   Open blender Create a text editor panel Open my script (external text file) Edit my script in a nice external editor Reload the script Save the .blend file Run the script   Now that I can see what my code does, this Blender instance has been modified, so I can't (make changes to my script and) run my script again. So I do this:   Close blender Open blender with the .blend from step 6 and repeat steps 4-7, over and over and over..   Is there a better workflow for this sort of thing?
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I have been through the process of installing matplotlib on my Ubuntu 12.04 computer. However, when I try to run a test program, I get the following error:   Traceback (most recent call last):   File "../py33/test.py", line 2, in &lt;module&gt;     import matplotlib.pyplot as plt ImportError: No module named 'matplotlib'   I am trying a sample program from matplotlib's website (basic_example). I just don't understand why it says there is not module matplotlib, even though I have definitely installed it (using sudo apt-get install python-matplotlib, and have done sudo apt-get build-dep python-matplotlib; I also tried pip install matplotlib, as I was told to do that, after installing Python itself, if I wanted to install other binaries).
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I'm writing a generic script which involves writing shapefiles to a directory which are then merged together. After writing the files out to the Output folder, I'm trying to get the saga:mergeshapeslayers algorithm to merge all the files in the Output folder. I have used the Model Builder and although it is helpful to an extent, I find that it is used for specific purposes whereas I am attempting to make a script for generic purposes.   Code:  ##Test=name ##Select_folder=folder ##Result=output vector  import os import glob  path_1 = Select_folder path = path_1 os.chdir(path)  def function():      output = glob.glob(path_1 + './*.shp')     x = 0      while output[x]:         for fname in glob.glob("*.shp"):             outputs_1 = processing.runandload("qgis:fieldcalculator", output[x], 'Number', 1, 10, 0, True, 1 , "C:\Users\Me\Desktop\Output\\"  + fname)             multiple_0 = glob.glob("*.shp")             x = x + 1          if x + 1 &gt; len(output):             processing.runalg("saga:mergeshapeslayers", output[0], ";".join(multiple_0) , Result)             break         else:             continue  if path_1:     function() else:    pass
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Does anyone know of a tool that I can use to generate a set of data with known correlations (and to put the icing on the cake - output this in json,csv,txt or some common format)?  I am working on some data visualizations and want to evaluate which ones can more easily allow a user to spot correlations - visually.
121103
Is there a GUI IDE for programming python just like java has netbeans?  I wanted one where we could drag &amp; drop test boxes &amp; labels just as we do in swing components using netbeans or eclipse.  Or is there an add-on present in either netbeans or eclipse itself?
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In 2.7x and earlier we have .  The setting can still be set via the python api (bpy.context.scene.render.display_mode), but I can't seem to find it in the gui anywhere. Is it still there? If so, where is it?
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How can I create a ColorRamp for a Cycles material through Python?  I am able to create a new shader output node with nodes.new(type='ShaderNodeOutputMaterial'). Searching online, I see that it is only possible through C code (however, these pages dates back several years).  Is there a way to fake a ColorRamp (maybe with multiple Math nodes in greater/less than mode) or create a ColorRamp for a Cycles material through Python?
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I need large set (20 and more) of contrasted and easily visually-distinguishable colors for coloring different datasets on a scientific plot (the set of colors should not include white or black, and colors should be as bright as possible).   The plot is generated programmatically and intended to be included in a presentation which will be displayed using a projector.   Are there any ready-made sets of colors for such a task (I need colors as a set of RGB values)?   Or maybe there is some algorithm which generates such a set of colors programmatically (I use  for plot generation)?  P.S. The plot itself may look, for example, similar to this one:
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How would I setup  to recognize import arcpy?   I'd like to use PyCharm to develop and debug geoprocessing tool.