How do I format axis number format to thousands with a comma in matplotlib?

How can I change the format of the numbers in the x-axis to be like 10,000 instead of 10000?
Ideally, I would just like to do something like this:

x = format((10000.21, 22000.32, 10120.54), "#,###")

Here is the code:

import matplotlib.pyplot as plt

# create figure instance
fig1 = plt.figure(1)
fig1.set_figheight(15)
fig1.set_figwidth(20)

ax = fig1.add_subplot(2,1,1)

x = 10000.21, 22000.32, 10120.54

y = 1, 4, 15
ax.plot(x, y)

ax2 = fig1.add_subplot(2,1,2)

x2 = 10434, 24444, 31234
y2 = 1, 4, 9
ax2.plot(x2, y2)

fig1.show()

Answers:

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Method 1

Use , as format specifier:

>>> format(10000.21, ',')
'10,000.21'

Alternatively you can also use str.format instead of format:

>>> '{:,}'.format(10000.21)
'10,000.21'

With matplotlib.ticker.FuncFormatter:

...
ax.get_xaxis().set_major_formatter(
    matplotlib.ticker.FuncFormatter(lambda x, p: format(int(x), ',')))
ax2.get_xaxis().set_major_formatter(
    matplotlib.ticker.FuncFormatter(lambda x, p: format(int(x), ',')))
fig1.show()

Method 2

The best way I’ve found to do this is with StrMethodFormatter:

import matplotlib as mpl
ax.yaxis.set_major_formatter(mpl.ticker.StrMethodFormatter('{x:,.0f}'))

For example:

import pandas as pd
import requests
import matplotlib.pyplot as plt
import matplotlib as mpl

url = 'https://min-api.cryptocompare.com/data/histoday?fsym=BTC&tsym=USDT&aggregate=1'
df = pd.DataFrame({'BTC/USD': [d['close'] for d in requests.get(url).json()['Data']]})

ax = df.plot()
ax.yaxis.set_major_formatter(mpl.ticker.StrMethodFormatter('{x:,.0f}'))
plt.show()

Method 3

I always find myself on this same page everytime I try to do this. Sure, the other answers get the job done, but aren’t easy to remember for next time! ex: import ticker and use lambda, custom def, etc.

Here’s a simple solution if you have an axes named ax:

ax.set_yticklabels(['{:,}'.format(int(x)) for x in ax.get_yticks().tolist()])

Method 4

Short answer without importing matplotlib as mpl

plt.gca().yaxis.set_major_formatter(plt.matplotlib.ticker.StrMethodFormatter('{x:,.0f}'))

Modified from @AlexG’s answer

Method 5

If you like it hacky and short you can also just update the labels

def update_xlabels(ax):
    xlabels = [format(label, ',.0f') for label in ax.get_xticks()]
    ax.set_xticklabels(xlabels)

update_xlabels(ax)
update_xlabels(ax2)

Method 6

You can use matplotlib.ticker.funcformatter

import numpy as np
import matplotlib.pyplot as plt
import matplotlib.ticker as tkr


def func(x, pos):  # formatter function takes tick label and tick position
    s = '%d' % x
    groups = []
    while s and s[-1].isdigit():
        groups.append(s[-3:])
        s = s[:-3]
    return s + ','.join(reversed(groups))

y_format = tkr.FuncFormatter(func)  # make formatter

x = np.linspace(0,10,501)
y = 1000000*np.sin(x)
ax = plt.subplot(111)
ax.plot(x,y)
ax.yaxis.set_major_formatter(y_format)  # set formatter to needed axis

plt.show()

Method 7

x = [10000.21, 22000.32, 10120.54]

You could use a list comprehension to make a list of labels, and then pass them the plt.xticks.

xlabels = [f'{label:,}' for label in x]
plt.xticks(x, xlabels)

Method 8

If you want original values to appear in ticks, use

plt.xticks(ticks=plt.xticks()[0], labels=plt.xticks()[0])

This will prevent abbreviations like from 3000000 to 1.3 e5 etc. and will show 3000000 (the exact value) in ticks.

Method 9

Easiest way in my opinion:

current_values = plt.gca().get_yticks()
plt.gca().set_yticklabels(['{:,.0f}'.format(x) for x in current_values])

From:
https://queirozf.com/entries/matplotlib-examples-number-formatting-for-axes-labels

All methods was sourced from stackoverflow.com or stackexchange.com, is licensed under cc by-sa 2.5, cc by-sa 3.0 and cc by-sa 4.0