Something to experiment with when I have an hour or two to spare.
It took more than a couple of hours, but I eventually got basemap working under Windows using the pre-built binaries kindly provided by Christoph Gohlke at:
https://www.lfd.uci.edu/~gohlke/pythonlibs/#basemap
The result didn't look exactly like yours though. See below. It was marginally easier to get things working on a Raspberry Pi, but the results were not dissimilar. When I have another hour or two to spare it looks as though I need to experiment with font sizes?
Jim, I really appreciate you testing this for me, its very useful.
My first point is, the size issue is a problem with the line I have highlighted- try tweaking these parameters- its a little strange to me as to why this happened but i suspect its because those parameters control the "size in absolute dimensions" of the figure. Thus, you may be using a much larger or smaller display screen than me?
Irrespective I need to take it into consideration.
My second point is that your trials and tribulations with getting Basemap installed cannot be ignored. The whole idea of these tutorials are their accessibility. I suspect not many people would have the patience to work so hard to install a library. I just finished a program for my job so now I have more free time i will work on a Cartopy port
![Smiley :)](https://forum.arctic-sea-ice.net/Smileys/default/smiley.gif)
.
Lastly, hopefully with that line fix, now you should have a working program, id like to point out that you can colour the buoys on any parameter within the data by changing the line:
colours=simb_df['air_temp'].values.tolist()
to any numeric variable in the dataset, from this list:
Index(['wdt_counter', 'program_version', 'time_stamp', 'latitude', 'longitude',
'air_temp', 'air_pressure', 'bottom_distance', 'water_temp',
'surface_distance',
...
'dtc_values_186', 'dtc_values_187', 'dtc_values_188', 'dtc_values_189',
'dtc_values_190', 'dtc_values_191', 'buoy_id', 'snow_depth',
'ice_thickness', 'date'],
dtype='object', length=213)
If you wanted to colour on ice thickness for example, the line would be;
colours=simb_df['ice_thickness'].values.tolist()
Dont forget to change the label of the colour legend to reflect
You might not get the results you expect with ice thickness, this is because some days the ice thickness is erroneously calculated and a result bugs the range of the colourmap, ill attach an example image. Considering applying rolling ball smoothing or outlier detection but I always try to avoid data manipulation.
Anyway, hope this helps and thanks for trying to run it