Matplotlib: Specify format of floats for tick labels

All we need is an easy explanation of the problem, so here it is.

I am trying to set the format to two decimal numbers in a matplotlib subplot environment. Unfortunately, I do not have any idea how to solve this task.

To prevent using scientific notation on the y-axis I used ScalarFormatter(useOffset=False) as you can see in my snippet below. I think my task should be solved by passing further options/arguments to the used formatter. However, I could not find any hint in matplotlib’s documentation.

How can I set two decimal digits or none (both cases are needed)? I am not able to provide sample data, unfortunately.


— SNIPPET —

f, axarr = plt.subplots(3, sharex=True)

data = conv_air
x = range(0, len(data))

axarr[0].scatter(x, data)
axarr[0].set_ylabel('$T_\mathrm{air,2,2}$', size=FONT_SIZE)
axarr[0].yaxis.set_major_locator(MaxNLocator(5))
axarr[0].yaxis.set_major_formatter(ScalarFormatter(useOffset=False))
axarr[0].tick_params(direction='out', labelsize=FONT_SIZE)
axarr[0].grid(which='major', alpha=0.5)
axarr[0].grid(which='minor', alpha=0.2)

data = conv_dryer
x = range(0, len(data))

axarr[1].scatter(x, data)
axarr[1].set_ylabel('$T_\mathrm{dryer,2,2}$', size=FONT_SIZE)
axarr[1].yaxis.set_major_locator(MaxNLocator(5))
axarr[1].yaxis.set_major_formatter(ScalarFormatter(useOffset=False))
axarr[1].tick_params(direction='out', labelsize=FONT_SIZE)
axarr[1].grid(which='major', alpha=0.5)
axarr[1].grid(which='minor', alpha=0.2)

data = conv_lambda
x = range(0, len(data))

axarr[2].scatter(x, data)
axarr[2].set_xlabel('Iterationsschritte', size=FONT_SIZE)
axarr[2].xaxis.set_major_locator(MaxNLocator(integer=True))
axarr[2].set_ylabel('$\lambda$', size=FONT_SIZE)
axarr[2].yaxis.set_major_formatter(ScalarFormatter(useOffset=False))
axarr[2].yaxis.set_major_locator(MaxNLocator(5))
axarr[2].tick_params(direction='out', labelsize=FONT_SIZE)
axarr[2].grid(which='major', alpha=0.5)
axarr[2].grid(which='minor', alpha=0.2)

How to solve :

I know you bored from this bug, So we are here to help you! Take a deep breath and look at the explanation of your problem. We have many solutions to this problem, But we recommend you to use the first method because it is tested & true method that will 100% work for you.

Method 1

See the relevant documentation in general and specifically

from matplotlib.ticker import FormatStrFormatter

fig, ax = plt.subplots()

ax.yaxis.set_major_formatter(FormatStrFormatter('%.2f'))

enter image description here

Method 2

If you are directly working with matplotlib’s pyplot (plt) and if you are more familiar with the new-style format string, you can try this:

from matplotlib.ticker import StrMethodFormatter
plt.gca().yaxis.set_major_formatter(StrMethodFormatter('{x:,.0f}')) # No decimal places
plt.gca().yaxis.set_major_formatter(StrMethodFormatter('{x:,.2f}')) # 2 decimal places

From the documentation:

class matplotlib.ticker.StrMethodFormatter(fmt)

Use a new-style format string (as used by str.format()) to format the
tick.

The field used for the value must be labeled x and the field used for
the position must be labeled pos.

Method 3

The answer above is probably the correct way to do it, but didn’t work for me.

The hacky way that solved it for me was the following:

ax = <whatever your plot is> 
# get the current labels 
labels = [item.get_text() for item in ax.get_xticklabels()]
# Beat them into submission and set them back again
ax.set_xticklabels([str(round(float(label), 2)) for label in labels])
# Show the plot, and go home to family 
plt.show()

Method 4

In matplotlib 3.1, you can also use ticklabel_format. To prevents scientific notation without offsets:

plt.gca().ticklabel_format(axis='both', style='plain', useOffset=False)

Method 5

format labels using lambda function

Matplotlib: Specify format of floats for tick labels
3x the same plot with differnt y-labeling

Minimal example

import numpy as np
import matplotlib as mpl
import matplotlib.pylab as plt
from matplotlib.ticker import FormatStrFormatter

fig, axs = mpl.pylab.subplots(1, 3)

xs = np.arange(10)
ys = 1 + xs ** 2 * 1e-3

axs[0].set_title('default y-labeling')
axs[0].scatter(xs, ys)
axs[1].set_title('custom y-labeling')
axs[1].scatter(xs, ys)
axs[2].set_title('x, pos arguments')
axs[2].scatter(xs, ys)


fmt = lambda x, pos: '1+ {:.0f}e-3'.format((x-1)*1e3, pos)
axs[1].yaxis.set_major_formatter(mpl.ticker.FuncFormatter(fmt))

fmt = lambda x, pos: 'x={:f}\npos={:f}'.format(x, pos)
axs[2].yaxis.set_major_formatter(mpl.ticker.FuncFormatter(fmt))

You can also use ‘real’-functions instead of lambdas, of course.
https://matplotlib.org/3.1.1/gallery/ticks_and_spines/tick-formatters.html

Note: Use and implement method 1 because this method fully tested our system.
Thank you 🙂

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

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