plot-grid | 2D/webgl grid for plots | Graphics library

You could also provide values for wd_rad just lower than 0 and larger than 2*pi using np.where, adding 2*pi for small values and subtracting 2*pi for large values. np.tile(ws, 2) and np.tile(conc, 2) then associate the extended version of wd_rad with the same concentration values. Using also these extended values in interpolate.griddata makes sure the concentration values wrap around at 0 and 2*pi.

As an aside, note that 'jet' is a colormap that looks nice, but is very misleading as it creates yellow highlights at the wrong spots. (Also, converting pandas columns to lists is quite slow and memory consuming, better leave them in their numpy array format.)

The code below supposes that oz in the question is the same array as conc.

The option is to place it in a named list and concatenate the list elements

axes[0] = f1.axes[0] just means that the first element of the axes array is now the axes from the other figure. It does not mean that this axes has anything to do or is even shown in the figure fig.

The linked question's answer shows how to proceed instead: You create a figure with ggplot and add further axes to it and possibly change the positions of the existing ones. This can also be done with seaborn.

You may also try to move (not copy) axes from an existing figure. This is shown in How to plot multiple Seaborn Jointplot in Subplot.

In Can I create AxesSubplot objects, then add them to a Figure instance? the general approach is detailed.

However, note that those are kind of hacks. One would not recommend to move axes around in general, and there are some caveats with the existing solutions. Instead one could ask the maintainers of those libraries to finally provide options to plot with their tool to existing matplotlib figures.

The main problem is that plot1 and plot2 have different aspect ratios. This is plot1:

And this plot2:

You can try to keep the aspect ratio using, i.e. theme(aspect.ratio=1) instead of coord_equal():

you can create a pie-chart with ggplot2 and use grid.arrange