Interestingly, too, despite having set the axis to be off, they are also showing up in the figure inside of the Jupyter notebook output. %config InlineBackend.figure_format = 'retina' I am using these added magic functions in Jupyter for the rendering of my figures: %matplotlib inline I am a little confused however why this seems to get so distorted for the Jupyter notebook output.Īny links to helpful resources such as documentation, tutorial, or examples would be greatly appreciated. The notebook combines live code, equations, narrative text, visualizations, interactive. This makes sense and consequently explains the small height variation in the figure output in P圜harm. The Jupyter Notebook is a web-based interactive computing platform. So this suggests that the coordinates for the inset axis for Alaska and Hawaii is (for the y coordinate). Guam_ax = continental_states_ax.inset_axes() Puerto_rico_ax = continental_states_ax.inset_axes() # create two inset plots for the extra regions Hawaii_ax = continental_states_ax.inset_axes() The code that is originally used to construct the figure (containing all of the inset axes) is: fig, continental_states_ax = plt.subplots(figsize=(20, 10))Īlaska_ax = continental_states_ax.inset_axes() How can I fix this/why is this occurring? Make sure that you already have Anaconda (or alternatively, the base Python. Plot_states(df, column='STATEFP', extra_regions=True, labels='both', cmap='copper_r') Īs you can see, there is a significant amount of stretching that distorts the figure once it is output despite the fact that the function is using the same code. 3.1 Python language tutorial using P圜harm. I then run the same code: from geostates.shapefiles import load_states However when I run this same code in a Jupyter notebook I first import the package from TestPyPI using: %pip install -i geostates=0.1.2.8 Plot_states(df, column='STATEFP', extra_regions=True, labels='both', cmap='copper_r') When I run this code in P圜harm (using plt.show() for testing): from geostates.shapefiles import load_states P圜harm is ideal for Python programmers and maintaining Notebooks as part of a Python. The code is the same for each so I am guessing this might have something to do with how they plots are being displayed in different environments? JupyterLab is Jupyters next-gen web-based development environment. ![]() Various types of docker images are available. I prefer to use P圜harm myself, but in some situations JupyterLab could be the best choice. Once I package the project, upload it to the TestPyPI repo, and then install it and run it in a Jupyter notebook locally I get a very different output than when I run/test it in P圜harm. JupyterLab is a web-based interactive development environment for Jupyter notebooks, code, and data. I am writing a Python package that contains a function that creates a plot of the United States.
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