How to change the font size on a matplotlib plot

You can use plt.rcParams["font.size"] for setting font_size in matplotlib and also you can use plt.rcParams["font.family"] for setting font_family in matplotlib. Try this example:

import matplotlib.pyplot as plt
plt.style.use('seaborn-whitegrid')

label = [1,2,3,4,5,6,7,8]
x = [0.001906,0.000571308,0.0020305,0.0037422,0.0047095,0.000846667,0.000819,0.000907]
y = [0.2943301,0.047778308,0.048003167,0.1770876,0.532489833,0.024611333,0.157498667,0.0272095]


plt.ylabel('eigen centrality')
plt.xlabel('betweenness centrality')
plt.text(0.001906, 0.2943301, '1 ', ha='right', va='center')
plt.text(0.000571308, 0.047778308, '2 ', ha='right', va='center')
plt.text(0.0020305, 0.048003167, '3 ', ha='right', va='center')
plt.text(0.0037422, 0.1770876, '4 ', ha='right', va='center')
plt.text(0.0047095, 0.532489833, '5 ', ha='right', va='center')
plt.text(0.000846667, 0.024611333, '6 ', ha='right', va='center')
plt.text(0.000819, 0.157498667, '7 ', ha='right', va='center')
plt.text(0.000907, 0.0272095, '8 ', ha='right', va='center')
plt.rcParams["font.family"] = "Times New Roman"
plt.rcParams["font.size"] = "50"
plt.plot(x, y, 'o', color='blue')

Use plt.tick_params(labelsize=14)

Here is what I generally use in Jupyter Notebook:

# Jupyter Notebook settings

from IPython.core.display import display, HTML
display(HTML("<style>.container { width:95% !important; }</style>"))
%autosave 0
%matplotlib inline
%load_ext autoreload
%autoreload 2

from IPython.core.interactiveshell import InteractiveShell
InteractiveShell.ast_node_interactivity = "all"


# Imports for data analysis
import pandas as pd
import matplotlib.pyplot as plt
pd.set_option('display.max_rows', 2500)
pd.set_option('display.max_columns', 500)
pd.set_option('display.max_colwidth', 2000)
pd.set_option('display.width', 2000)
pd.set_option('display.float_format', lambda x: '%.3f' % x)

#size=25
size=15
params = {'legend.fontsize': 'large',
          'figure.figsize': (20,8),
          'axes.labelsize': size,
          'axes.titlesize': size,
          'xtick.labelsize': size*0.75,
          'ytick.labelsize': size*0.75,
          'axes.titlepad': 25}
plt.rcParams.update(params)

The changes to the rcParams are very granular, most of the time all you want is just scaling all of the font sizes so they can be seen better in your figure. The figure size is a good trick but then you have to carry it for all of your figures. Another way (not purely matplotlib, or maybe overkill if you don't use seaborn) is to just set the font scale with seaborn:

sns.set_context('paper', font_scale=1.4)

DISCLAIMER: I know, if you only use matplotlib then probably you don't want to install a whole module for just scaling your plots (I mean why not) or if you use seaborn, then you have more control over the options. But there's the case where you have the seaborn in your data science virtual env but not using it in this notebook. Anyway, yet another solution.

I just wanted to point out that both the Herman Schaaf's and Pedro M Duarte's answers work but you have to do that before instantiating subplots(), these settings will not affect already instantiated objects. I know it's not a brainer but I spent quite some time figuring out why are those answers not working for me when I was trying to use these changes after calling subplots().

For eg:

import matplotlib.pyplot as plt
plt.rcParams.update({'font.size': 6,})
fig, ax = plt.subplots()
#create your plot
plt.show()

or

SMALL_SIZE = 8
MEDIUM_SIZE = 10
BIGGER_SIZE = 12

plt.rc('font', size=SMALL_SIZE)          # controls default text sizes
plt.rc('xtick', labelsize=SMALL_SIZE)    # fontsize of the tick labels
plt.rc('ytick', labelsize=SMALL_SIZE)    # fontsize of the tick labels
fig, ax = plt.subplots()
#create your plot
plt.show()

It is mentioned in a comment but deserves its own answer:

Modify both figsize= and dpi= in conjunction to adjust the figure size and the scale of all text labels:

fig, ax = plt.subplots(1, 1, figsize=(8, 4), dpi=100)

(or shorter:)

fig, ax = plt.subplots(figsize=(8, 4), dpi=100)

It's a bit tricky:

1. figsize actually controls the scale of the text relative to the plot extent (as well as the aspect ratio of the plot).

2. dpi adjusts the size of the figure within the notebook (keeping constant the relative scale of the text and the plot aspect ratio).

I wrote a modified version of the answer by @ryggyr that allows for more control over the individual parameters and works on multiple subplots:

def set_fontsizes(axes,size,title=np.nan,xlabel=np.nan,ylabel=np.nan,xticks=np.nan,yticks=np.nan):
    if type(axes) != 'numpy.ndarray':
        axes=np.array([axes])
    
    options = [title,xlabel,ylabel,xticks,yticks]
    for i in range(len(options)):
        if np.isnan(options[i]):
            options[i]=size
        
    title,xlabel,ylabel,xticks,yticks=options
    
    for ax in axes.flatten():
        ax.title.set_fontsize(title)
        ax.xaxis.label.set_size(xlabel)
        ax.yaxis.label.set_size(ylabel)
        ax.tick_params(axis='x', labelsize=xticks)
        ax.tick_params(axis='y', labelsize=yticks)