mpl-flags

National flags for Matplotlib.

There is no good documentation available yet. Hopefully, this blog post will help you get started.

https://leejjoon.github.io/jjl-mpl-blog/posts/mpl-20240318-mpl-flags/

Flags data

mpl-flags contains the flag data in vector format readily usable with Matplotlib. The original flags data are in svg format, and are converted to matplotlib's Path data using mpl-simple-svg-parser. mpl-flags does not contain the original svg files, only the converted data in numpy format (vertices and codes).

The flag data is collected from various sources. Currently, it includes flags from

Google's noto color emoji font : https://github.com/googlefonts/noto-emoji
circle-flags : https://github.com/HatScripts/circle-flags
flag-icons : https://github.com/lipis/flag-icons

Different sources can render the flags differently.

No gradient support

Some flags includes gradient, which is currently not supported by mpl-flags, so they will result in incorrect details.

noto: ['BZ', 'EC', 'FK', 'GS', 'GT', 'MX', 'NI', 'PM', 'TA', 'VG']
4x3, 1x1 : ['BZ', 'FK', 'GS', 'GT', 'MX', 'NI', 'VG']

Check the above post for the impact of no gradient in these flags.

The gradient support is work in progress.

Usage

from mpl_flags import Flags

flags = Flags("noto_waved") # You initialize the Flags class specifying what kind of
                            # flags you like to use.
                            # `noto_waved` is flags from google's noto emoji fonts.

fig, ax = plt.subplots(figsize=(3, 3))
flags.show_flag(ax, "KR")

from matplotlib.offsetbox import AnnotationBbox

flags = Flags("noto_original")

fig, ax = plt.subplots(figsize=(3, 3))
da = flags.get_drawing_area("KR", wmax=100)
ab = AnnotationBbox(da, (0.5, 0.5), frameon=True,
                    box_alignment=(0.5, 0.5))
ax.add_artist(ab)

Installation

You can install using pip:

pip install mpl_flags

Development Installation