marinebon / py-dwc-viz Goto Github PK

This looks like a great package of nice tools! As I'm working more and more with DwC data, either during reformatting or extracting using pyobis, I find myself rewriting this little bit of code in all my notebooks to make a simple map of observations. It got me thinking, is this something that would be appropriate to be added to this package?

Something like py-dwc-viz.dwc_make_map(DataFrame), where DataFrame contains decimalLongitude and decimalLatitude, at a minimum.

import matplotlib.pyplot as plt
import geopandas as gpd

  # read into geopandas dataframe for plotting
gdf = gpd.GeoDataFrame(
    df, 
    geometry=gpd.points_from_xy(df.decimalLongitude, df.decimalLatitude),
    crs = "epsg:4326",
    )


fig, ax = plt.subplots(figsize=(20,10))

gdf.plot(ax=ax, markersize=5, zorder=10, legend=True)

world = gpd.read_file(gpd.datasets.get_path('naturalearth_lowres'))

world = world.to_crs(gdf.crs)

world.plot(ax=ax, color='lightgrey', edgecolor='white', zorder=1)

ax.set_axis_off()

plt.show()

I think this package could be made more usable (and useful) if published on PyPI and/or Conda-Forge.

I wonder if there is a better way to visualize a distribution of different taxa.
A plot of taxa counts is common (example below).

However, taxa fall into a tree structure, and a visualization that includes this nuance would be more informative.
Something like:

Potentially useful references:

• ETETree : python toolkit for visualizing tree structures

I think it would be great to set-up a task-list of things to accomplish for this project. That will help us get started with things easier and faster.