I found this function super useful in my dissertation and more generally in my work. What it does is take x,y coordinates and a set of strings and annotates a scatterplot using those labels. For example, here’s a figure from my dissertation where I use it to annotate a plot of regression leverage by year. I jitter the points a little to provide legibility to the text labels, but basically it’s just a call like annoscatter(df.year, df.leverage, df.district_id).
Not sure if there’s a more elegant solution to this using matplotlib, but I really like how it looks, especially since there’s also passthrough keyword dictionaries implemented like seaborn. Not sure if @mwaskom would take a PR for something as simple as this, though.
import matplotlib.pyplot as plt
def annoscatter(x,y, text, marker='.', markersize=1,
ax = None, fig = None, color='k',
fig_kw = dict(),
scatter_kw = dict(), ann_kw=dict()):
if ax is None:
if fig is None:
fig = plt.figure(**fig_kw)
ax = plt.gca()
if not (marker is '' or markersize == 0):
scatter_kw['marker'] = marker
scatter_kw['s'] = markersize
ax.scatter(x,y, **scatter_kw)
else:
scatter_kw['alpha'] = 0
ax.scatter(x,y,**scatter_kw)
if isinstance(color, str):
colors = [color]*len(x)
else:
colors = list(color)
for xi,yi,string,c in zip(x,y,text,colors):
ax.annotate(s=string, xy=(xi,yi), color=c, **ann_kw)
return ax
python