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How can I get xticklabel and yticklabel bold when activating LaTeX text rendering with Times New Roman font in Python matplotlib?

I am trying to generate a figure with LaTeX text rendering activated. I want to use Time New Roman font for all the texts in the figure (including the mathematical texts) and I encounter some problems when trying to make the xticklabel and yticklable bold, here is what I have:
import numpy as np
from matplotlib import rc,rcParams
from pylab import *
tmpData = np.random.random( 100 )
rcParams.update({
"text.usetex": True,
"font.family": "serif",
"font.serif": ["Times"],
'font.weight': 'bold'})
rcParams['text.latex.preamble'] = [r'\usepackage{fontspec} \usepackage{newtxtext,newtxmath}']
#create figure
f = figure(figsize=(10,10))
ax = gca()
plot(np.arange(100), tmpData, label=r'\textbf{Line 1}', linewidth=2)
ylabel(r'\textbf{Y-AXIS}', fontsize=20)
xlabel(r'\textbf{X-AXIS}', fontsize=20)
ax.xaxis.set_tick_params(labelsize=20)
ax.yaxis.set_tick_params(labelsize=20)
legend()
I understand that the problem may due to the fact that the xticklabels on the x axis should really be interpreted as mathematical texts, but I am still struggling with this...
Can anyone help me with this? Thanks in advance!

Add this code above legend()
ylabs = [ f"{ilab:<.1f}" for ilab in ax.get_yticks()]
xlabs = [ f"{ilab:<.0f}" for ilab in ax.get_xticks()]
ax.set_yticklabels(ylabs, weight='bold', size=20)
ax.set_xticklabels(xlabs, weight='bold', size=20)
output is here.

matplotlib xtick color and background in jupyter inside of vsc

Please consider this code. I use it for generating two figures.
The first figure is generated with the code exactly as it follows, while the second includes the two commented lines for changing the colour of xtick and ytick.
If I save the two figures, I get what I expect. However, the "previews" in the Jupyter notebook are different. See below.
from cycler import cycler
import matplotlib as mpl
from matplotlib import rc
import matplotlib.pyplot as plt
import numpy as np
%matplotlib inline
# rc("backend", "pdf")
rc("font", **{"family": "sans-serif", "sans-serif":["Helvetica"], "size":8})
## for Palatino and other serif fonts use:
rc("font", **{"family":"serif", "serif":["Palatino"], "size":8})
rc("text", usetex=True)
rc("figure", **{"dpi": 300})
rc("lines", **{"linewidth": 0.5, "markersize": 2})
rc("axes", **{"edgecolor": "gray", "facecolor":"white",
"linewidth": 0.3, "labelsize": 8, "labelcolor": "gray",
"grid": True})
rc("grid", **{"color": "gray", "linestyle": ":", "linewidth": 0.1})
rc("legend", **{"markerscale": 0.7, "fontsize": 6, "framealpha": 0.9, "frameon":True, "edgecolor": "lightgray"})
# rc("xtick", **{"color": "gray"})
# rc("ytick", **{"color": "gray"})
color_c = cycler("color", ["k"])
style_c = cycler("linestyle", ["-", "--", ":", "-."])
marker_c = cycler("marker", ["", ".", "o"])
cycler_cms = color_c * marker_c * style_c
image_width = 2.5
image_height = image_width / 1.618
# test style_cms
plt.rc("axes", prop_cycle=cycler_cms)
fig, ax = plt.subplots(figsize=(image_width, image_height))
n_lines = 4 # len(cycler_cms)
x = np.linspace(0, 8, 101)
y = np.cos(np.arange(n_lines)+x[:,None])
ax.plot(x, y)
ax.legend([f"$line_{{{i}}}$" for i in range(n_lines)])
The following is obtained with the two lines commented out.
The following is obtained setting to "gray" the colour property of xtick and ytick
For comparison, this is the saved file corresponding to the second figure (with the dark background):
The Jupyter notebook is run inside of the latest version of VSC, with all the pluings updated.
Is there any way to have the "preview" equal to the what I save? May be a specific backend, I don't know... I tried a few...
PS.
I know I can solve this specific issue by setting figure.facecolor to white, but my question concerns how to get the exact previews of what I will save for any rc parameters.

How to solve " 'PathCollection' object has no attribute 'yaxis' " error?

I'm a MSc Student and I used to make graphs and plots with commercial packages like OriginPro, Excel and Matlab. Although these softwares provide a great user experience, there are some major disadvantages as they are specific OS dependent and, in general, very expensive.
Hence, I started to learn Python using matplotlib library with VS Code, however I'm having some problems with some library functions and statements that seems to be standard from matplotlib and numPy, but it doesnt work.
For example, I'm making some templates for scatter plots and I can't control minor ticks because it doesn't recognize the statements xaxix and yaxix:
Sample of the code:
import numpy as np
import matplotlib.pyplot as plt
from matplotlib.ticker import MultipleLocator, AutoMinorLocator
.
.
.
fig = plt.figure(figsize=(x_pixels/my_dpi, y_pixels/my_dpi), dpi=my_dpi)
ax = plt.scatter(x*format_x, y*format_y, s = size, alpha = transparency, color = color, label = legend_text)
.
.
.
# Major Ticks
plt.tick_params(axis = 'both', which = 'major', length = majorT_length, direction = majorT_direction, color = majorT_color, labelsize = label_size, top = 'on', right = 'on')
# Minor Ticks
plt.minorticks_on()
plt.tick_params(axis='both', which='minor', length = minorT_length, direction = minorT_direction, color = minorT_color, top = 'on', right = 'on')
ax.yaxis.set_minor_locator(AutoMinorLocator(2))
ax.xaxis.set_minor_locator(AutoMinorLocator(2))
# Figure Layout
plt.tight_layout()
plt.savefig(output_file, dpi=my_dpi, bbox_inches=borders)
plt.show()
and the Terminal show this error:
File "c:/Users/luagu/Desktop/Python Matplotlib Training/Scatter_Template.py", line 128, in <module>
ax.yaxis.set_minor_locator(AutoMinorLocator(2))
AttributeError: 'PathCollection' object has no attribute 'yaxis'
What I'm doing wrong?
Thanks in advance!

You wrote ax = plt.scatter but your ax here is an artist returned by the scatter method, not an Axes object. What you want to do is:
plt.scatter(...)
...
ax = plt.gca()
ax.yaxis.set_minor_locator(AutoMinorLocator(2))
ax.xaxis.set_minor_locator(AutoMinorLocator(2))

How to use Font Awesome symbol as marker in matplotlib

Is it possible to use a font-awesome icon as a marker in a scatterplot with matplotlib?
Or is it possible to use it as a font and put the icon as a 'text'?
This question has originally been asked here, but has been closed for an unknown reason. Since I consider it a valid and useful problem, which hasn't been addressed anywhere on Stackoverflow and sure deserves an answer, I will simply ask it again.

FontAwesome is available from here.
It provides its icons as vector graphics and as well as as otf-font.
Use FontAwesome otf font
Matplotlib cannot natively read vector graphics, but it can load otf-fonts.
After downloading the FontAwesome package you can access the font via a matplotlib.font_manager.FontProperties object, e.g.
fp = FontProperties(fname=r"C:\Windows\Fonts\Font Awesome 5 Free-Solid-900.otf")
Create texts
The FontProperties can be the input for matplotlib text objects
plt.text(.6, .4, "\uf16c", fontproperties=fp)
Unfortunately, using the FontAwesome ligatures is not possible. Hence the individual symbols need to be accessed via their UTF8 key. This is a little cumbersome, but the cheatsheet can come handy here. Storing those needed symbols in a dictionary with a meaningful name may make sense.
Example:
from matplotlib.font_manager import FontProperties
import matplotlib.pyplot as plt
fp1 = FontProperties(fname=r"C:\Windows\Fonts\Font Awesome 5 Brands-Regular-400.otf")
fp2 = FontProperties(fname=r"C:\Windows\Fonts\Font Awesome 5 Free-Solid-900.otf")
symbols = dict(cloud = "\uf6c4", campground = "\uf6bb", hiking = "\uf6ec",
mountain = "\uf6fc", tree = "\uf1bb", fish = "\uf578",
stackoverflow = "\uf16c")
fig, (ax, ax2) = plt.subplots(ncols=2, figsize=(6.2, 2.2), sharey=True)
ax.text(.5, .5, symbols["stackoverflow"], fontproperties=fp1, size=100,
color="orange", ha="center", va="center")
ax2.stackplot([0,.3,.55,.6,.65,1],[.1,.2,.2,.2,.2,.15],[.3,.2,.2,.3,.2,.2],
colors=["paleturquoise", "palegreen"])
ax2.axis([0,1,0,1])
ax2.text(.6, .4, symbols["mountain"], fontproperties=fp2, size=16, ha="center")
ax2.text(.09, .23, symbols["campground"], fontproperties=fp2, size=13)
ax2.text(.22, .27, symbols["hiking"], fontproperties=fp2, size=14)
ax2.text(.7, .24, symbols["tree"], fontproperties=fp2, size=14,color="forestgreen")
ax2.text(.8, .33, symbols["tree"], fontproperties=fp2, size=14,color="forestgreen")
ax2.text(.88, .28, symbols["tree"], fontproperties=fp2, size=14,color="forestgreen")
ax2.text(.35, .03, symbols["fish"], fontproperties=fp2, size=14,)
ax2.text(.2, .7, symbols["cloud"], fontproperties=fp2, size=28,)
plt.show()
Create markers
Creating a lot of texts like above is not really handy. To have the icons as markers would be nicer for certain applications. Matplotlib does have the ability to use utf symbols as markers, however, only through the mathtext functionality. Getting an otf font to be used as mathfont in matplotlib was unsuccessful in my trials.
An alternative is to create a matplotlib.path.Path from the symbol. This can be done via a matplotlib.textpath.TextToPath instance, which is unfortunately undocumented. The TextToPath has a method get_text_path taking a fontproperty and a string as input and returning the vertices and codes from which to create a Path. A Path can be used as a marker, e.g. for a scatter plot.
v, codes = TextToPath().get_text_path(fp, \uf6fc)
path = Path(v, codes, closed=False)
plt.scatter(..., marker=path)
Some example:
import numpy as np; np.random.seed(32)
from matplotlib.path import Path
from matplotlib.textpath import TextToPath
from matplotlib.font_manager import FontProperties
import matplotlib.pyplot as plt
fp = FontProperties(fname=r"C:\Windows\Fonts\Font Awesome 5 Free-Solid-900.otf")
symbols = dict(cloud = "\uf6c4", campground = "\uf6bb", hiking = "\uf6ec",
mountain = "\uf6fc", tree = "\uf1bb", fish = "\uf578",
stackoverflow = "\uf16c")
fig, ax = plt.subplots()
def get_marker(symbol):
v, codes = TextToPath().get_text_path(fp, symbol)
v = np.array(v)
mean = np.mean([np.max(v,axis=0), np.min(v, axis=0)], axis=0)
return Path(v-mean, codes, closed=False)
x = np.random.randn(4,10)
c = np.random.rand(10)
s = np.random.randint(120,500, size=10)
plt.scatter(*x[:2], s=s, c=c, marker=get_marker(symbols["cloud"]),
edgecolors="none", linewidth=2)
plt.scatter(*x[2:], s=s, c=c, marker=get_marker(symbols["fish"]),
edgecolors="none", linewidth=2)
plt.show()

Adding to ImportanceOfBeingErnest's great answer: you can easily get the UTF keys by using the fontawesome Python package.
Install via pip:
pip install fontawesome
Usage:
import fontawesome as fa
# icons dict converts to correct utf-8 code:
fa.icons['thumbs-up']

Matplotlib multi-colored title [duplicate]

Is there a way in matplotlib to partially specify the color of a string?
Example:
plt.ylabel("Today is cloudy.")
How can I show "today" as red, "is" as green and "cloudy." as blue?

I only know how to do this non-interactively, and even then only with the 'PS' backend.
To do this, I would use Latex to format the text. Then I would include the 'color' package, and set your colors as you wish.
Here is an example of doing this:
import matplotlib
matplotlib.use('ps')
from matplotlib import rc
rc('text',usetex=True)
rc('text.latex', preamble='\usepackage{color}')
import matplotlib.pyplot as plt
plt.figure()
plt.ylabel(r'\textcolor{red}{Today} '+
r'\textcolor{green}{is} '+
r'\textcolor{blue}{cloudy.}')
plt.savefig('test.ps')
This results in (converted from ps to png using ImageMagick, so I could post it here):

Here's the interactive version. Edit: Fixed bug producing extra spaces in Matplotlib 3.
import matplotlib.pyplot as plt
from matplotlib import transforms
def rainbow_text(x,y,ls,lc,**kw):
"""
Take a list of strings ``ls`` and colors ``lc`` and place them next to each
other, with text ls[i] being shown in color lc[i].
This example shows how to do both vertical and horizontal text, and will
pass all keyword arguments to plt.text, so you can set the font size,
family, etc.
"""
t = plt.gca().transData
fig = plt.gcf()
plt.show()
#horizontal version
for s,c in zip(ls,lc):
text = plt.text(x,y,s+" ",color=c, transform=t, **kw)
text.draw(fig.canvas.get_renderer())
ex = text.get_window_extent()
t = transforms.offset_copy(text._transform, x=ex.width, units='dots')
#vertical version
for s,c in zip(ls,lc):
text = plt.text(x,y,s+" ",color=c, transform=t,
rotation=90,va='bottom',ha='center',**kw)
text.draw(fig.canvas.get_renderer())
ex = text.get_window_extent()
t = transforms.offset_copy(text._transform, y=ex.height, units='dots')
plt.figure()
rainbow_text(0.05,0.05,"all unicorns poop rainbows ! ! !".split(),
['red', 'orange', 'brown', 'green', 'blue', 'purple', 'black'],
size=20)

Extending Yann's answer, LaTeX coloring now also works with PDF export:
import matplotlib
from matplotlib.backends.backend_pgf import FigureCanvasPgf
matplotlib.backend_bases.register_backend('pdf', FigureCanvasPgf)
import matplotlib.pyplot as plt
pgf_with_latex = {
"text.usetex": True, # use LaTeX to write all text
"pgf.rcfonts": False, # Ignore Matplotlibrc
"pgf.preamble": [
r'\usepackage{color}' # xcolor for colours
]
}
matplotlib.rcParams.update(pgf_with_latex)
plt.figure()
plt.ylabel(r'\textcolor{red}{Today} '+
r'\textcolor{green}{is} '+
r'\textcolor{blue}{cloudy.}')
plt.savefig("test.pdf")
Note that this python script sometimes fails with Undefined control sequence errors in the first attempt. Running it again is then successful.

After trying all the methods above, I return back to my stupid but easy method, using plt.text. The only problem is that you need to adjust the spaces between each word. You may need to adjust the positions several times, but I still like this way, because it
saves you from installing tex compilers,
does not require any special backends, and
free you from configuring matplotlib rc and configure back, or it may slows down your other plots, due to usetex=True
import matplotlib.pyplot as plt
fig, ax = plt.subplots()
label_x = -0.15
ax.text(label_x, 0.35, r"Today", color='red', rotation='vertical', transform=ax.transAxes)
ax.text(label_x, 0.5, r"is", color='green', rotation='vertical', transform=ax.transAxes)
ax.text(label_x, 0.55, r"cloudy", color='blue', rotation='vertical', transform=ax.transAxes)