This solution will work for axes level plots produced with matplotlib
, seaborn
, and pandas.DataFrame.plot
.
The main idea would be to separate the problem into small pieces:
Get the flag as an array into the script. E.g.
def get_flag(name):
path = "path/to/flag/{}.png".format(name)
im = plt.imread(path)
return im
Position an image at a certain position in a plot. This can be accomplished using an OffsetImage
. An example can be found on the matplotlib page. Best use a function which takes the name of the country and the position as arguments and generates an AnnotationBbox
with the OffsetImage
inside.
Drawing the barplot using ax.bar
. To set the country names as ticklabels, use ax.set_ticklabels(countries)
. Then for every country place the OffsetImage
from above using a loop.
(coord, 0)
and xybox=(0., -16.)
can be adjusted to place the image annotations at any location.
The final result may then look something like this:
import numpy as np
import matplotlib.pyplot as plt
from matplotlib.offsetbox import OffsetImage,AnnotationBbox
def get_flag(name):
path = "data/flags/Flags/flags/flags/24/{}.png".format(name.title())
im = plt.imread(path)
return im
def offset_image(coord, name, ax):
img = get_flag(name)
im = OffsetImage(img, zoom=0.72)
im.image.axes = ax
ab = AnnotationBbox(im, (coord, 0), xybox=(0., -16.), frameon=False,
xycoords='data', boxcoords="offset points", pad=0)
ax.add_artist(ab)
countries = ["Norway", "Spain", "Germany", "Canada", "China"]
valuesA = [20, 15, 30, 5, 26]
fig, ax = plt.subplots()
ax.bar(range(len(countries)), valuesA, width=0.5,align="center")
ax.set_xticks(range(len(countries)))
ax.set_xticklabels(countries)
ax.tick_params(axis='x', which='major', pad=26)
for i, c in enumerate(countries):
offset_image(i, c, ax)
plt.show()
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