#LEARNING CURVE PLOTTING GRAPHPAD PRISM 8 LICENSE#.#LEARNING CURVE PLOTTING GRAPHPAD PRISM 8 SOFTWARE#.You can standardise this across your work by creating a function which adds the fill between given some input such as the axis instance and data. Some of the other features such as filling will need to be done on a per plot basis. To view a list of all the available options just call print plt.rcParams from an interactive terminal. If your want to set defaults so all your plots look the same then you should generate a custom matplotlibrc file or use style. import matplotlib.pyplot as pltįrom matplotlib.ticker import MultipleLocator, FormatStrFormatter Here is a really simple example that addresses 4 of your points. Matplotlib is almost infinitely flexible so you can do almost anything with it and if it doesn't exist you can write it yourself! Obviously the defaults are bland, this is because everyone has there own idea of what is "nice" so it is pointless to impose a predefined style. Maybe this gives an idea of how to change things in the plots. Many of the things set here can be set as defaults for matplotlib. This is not exactly as in the question, but everything can be tuned towards that direction. # change the color of the top and right spines to opaque gray # change the edge color (bluish and transparentish) and thickness
# change the fill into a blueish color with opacity. make the fill transparent and less offensive in colour.It is easy to understand that we need to do a lot of changes in order to be able to show this to a less-engineering-minded audience. (Just a comment: The X-axis limits in the original image do not take the cyclicity of the data into account.) # create some fictive access data by hourĪx.set_xlabel('Time of posting (US EST)')Īx.set_ylabel('Percentage of Frontpaged Submissions')Īx.set_title('Likelihood of Reaching the Frontpage') Then doing what you want is easier, even though there is a steepish learning curve in the beginning. In my opinion the most difficult thing is to decide what you want. The source code is available, and even it can be changed quite easily by the user.The object model enables the user to change almost everything and introduce complex new features.There are simple ways to change the default settings, see:.
This is - necessarily - a compromise, and the illustrations are not something you would print in a magazine or show in an advertisement. matplotlib tries to produce clear illustrations for scientific purposes. This is really a matter of taste, and also a matter of target audience.
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