Customising font options in matplotlib and Seaborn.

customise_matplotlib_font.py

import sys, os, optparse
import pandas as pd
import matplotlib
import matplotlib.pyplot as plt
import seaborn as sns
from matplotlib.lines import Line2D

# may be necessary if you have to add fonts to the path (probably only applies if you've installed new ones)
matplotlib.font_manager._rebuild()
import matplotlib.font_manager
fe = matplotlib.font_manager.FontEntry(
    fname='/Users/baileythegreen/Library/Fonts/',
    name='Nordik')
matplotlib.font_manager.fontManager.ttflist.insert(0, fe) # or append is fine
matplotlib.rcParams['font.family'] = fe.name # = 'your custom ttf font name'


# A different method for the same thing?

#matplotlib.font_manager.findSystemFonts(fontpaths=None, fontext='ttf')
#font_dirs = ['/Users/baileythegreen/Library/Fonts/', ]
#font_files = matplotlib.font_manager.findSystemFonts(fontpaths=font_dirs)
#font_list = matplotlib.font_manager.createFontList(font_files)
#matplotlib.font_manager.fontManager.ttflist.extend(font_list)

matplotlib.rcParams['font.family'] = 'Nordik'

# I matched the colours to my text colour, which is not black
COLOR = "#3A4E7E"
matplotlib.rcParams['text.color'] = COLOR
matplotlib.rcParams['axes.labelcolor'] = COLOR
matplotlib.rcParams['xtick.color'] = COLOR
matplotlib.rcParams['ytick.color'] = COLOR
#matplotlib.rcParams['fontname'] = '/Users/baileythegreen/Library/Fonts/Nordik.ttf'

# Load in some data, here represented by the variable 'data'

    a4_dims = (11.75, 9)
    fig, ax = plt.subplots(figsize=a4_dims)
    #hist = sns.histplot(data, x = "data", hue = "sex", hatch = "/", palette = {'female': "#0080FF", 'male': "#800080"}, multiple = "layer", bins = 100, linewidth=.5, stat = "count", edgecolor = "none")
    hist = sns.histplot(data[data["sex"] == "female"], x = "data", element = "step", color = "#0080FF", ax = ax, edgecolor = "none", bins = "auto", linewidth=.5, stat = "count", alpha = .5)
    hist = sns.histplot(data[data["sex"] == "male"], x = "data", element = "step", hatch = "+", ax = ax, edgecolor = "#6A459F", color = "#6A459F", bins = "auto", linewidth=.5, stat = "count", alpha = .7)
    sns.despine(fig)
    #hist.set(xlabel = "%s minor allele frequencies" % opts.cohort_name)
    plt.xlabel(xlabel = "x-axis label", fontsize = 18, fontname = 'Nordik', fontstyle = 'normal', fontweight = "regular")
    plt.ylabel("Count", fontsize = 18, fontname = 'Nordik', fontstyle = 'normal')
    plt.ticklabel_format(style = 'plain', axis = 'y')
    a = Line2D([], [], color = "#0080FF", label = "Female", marker = "o")
    b = Line2D([], [], color = "#6A459F", label = "Male", marker = "o")
    plt.legend(handles = (a, b), loc = "upper right", fontsize = 18, title_fontsize = "18")
    plt.tick_params(axis = "x", labelsize = 14, bottom = False, top = False)
    plt.tick_params(axis = "y", labelsize = 14, left = False, right = False)

NB. Not all of the lines at the top are required, but I am not sure which ones are optional. I just know this combination worked.

I have left the plot code, even though it was for a specific thing, because it also shows how you can specify font in the different commands.