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Less successful test #3: plt.savefig('filename.svg') This also cannot be opened in powerpoint or Google Slides, with the same issue as above. Less successful test #4: plt.savefig('filename.pdf') and then converting to png on the command line: convert -density 300 filename.pdf filename.png.
To answer on why your code did not work, when you called the function 'h', you did not pass any parameter, hence this return the function definition or the memory location pointer of the function. Even if you had passed rr to h, h was not handled to convert it into an iterable.
I found that the myfun is called. If I add plt.show() in myfun, it can plot in the correct subplot, but nothing in the other one. And, if plt.show() is added in the end, nothing but two pairs of axis are plotted. I think the problem is that the figure is not transferred to the main function successfully.
Check the following example: For the first graph y=x+1 is plotted because a=1 was defined earlier. As expected. For the second graph and the first plot command it should be the same but y=2*x+1 is plotted instead (twice). In the third graph when a=1 is explicitely specified it is plotted as expected. Why is gnuplot ignoring a=1 for the second ...
plt.plot(x, y) This lets you plot just one figure with (x,y) coordinates. If you just want to get one graphic, you can use this way. Method 2. ax = plt.subplot() ax.plot(x, y) This lets you plot one or several figure(s) in the same window. As you write it, you will plot just one figure, but you can make something like this:
So the relationship between the markersize of a line plot and the scatter size argument is the square. In order to produce a scatter marker of the same size as a plot marker of size 10 points you would hence call scatter( .., s=100). import matplotlib.pyplot as plt. fig,ax = plt.subplots()
Joe Kington's excellent answer is already 4 years old, Matplotlib has incrementally changed (in particular, the introduction of the cycler module) and the new major release, Matplotlib 2.0.x, has introduced stylistic differences that are important from the point of view of the colors used by default.
11. You can save to a figure that is 1920x1080 (or 1080p) using: fig = plt.figure(figsize=(19.20,10.80)) You can also go much higher or lower. The above solutions work well for printing, but these days you want the created image to go into a PNG/JPG or appear in a wide screen format. answered Nov 6, 2019 at 13:09.
An axes-level plot can be done using seaborn.ecdfplot. A figure-level plot can be done use sns.displot with kind='ecdf'. See How to use markers with ECDF plot for other options. It’s also possible to plot the empirical complementary CDF (1 - CDF) by specifying complementary=True. Tested in python 3.11, pandas 1.5.2, matplotlib 3.6.2, seaborn ...
There is also this workaround in case you want to change the size without using the figure environment. So in case you are using plt.plot() for example, you can set a tuple with width and height. import matplotlib.pyplot as plt plt.rcParams["figure.figsize"] = (20,3) This is very useful when you plot inline (e.g., with IPython Notebook).