This is a few months late, but I have createdPR#6251 with matplotlib to add a newPercentFormatter class. With this class you just need one line to reformat your axis (two if you count the import ofmatplotlib.ticker):

import ...import matplotlib.ticker as mtickax = df['myvar'].plot(kind='bar')ax.yaxis.set_major_formatter(mtick.PercentFormatter())

PercentFormatter() accepts three arguments,xmax,decimals,symbol.xmax allows you to set the value that corresponds to 100% on the axis. This is nice if you have data from 0.0 to 1.0 and you want to display it from 0% to 100%. Just doPercentFormatter(1.0).

The other two parameters allow you to set the number of digits after the decimal point and the symbol. They default toNone and'%', respectively.decimals=None will automatically set the number of decimal points based on how much of the axes you are showing.

Update

PercentFormatter was introduced into Matplotlib proper in version 2.1.0.

pandas dataframe plot will return theax for you, And then you can start to manipulate the axes whatever you want.

import pandas as pdimport numpy as npdf = pd.DataFrame(np.random.randn(100,5))# you get ax from hereax = df.plot()type(ax)  # matplotlib.axes._subplots.AxesSubplot# manipulatevals = ax.get_yticks()ax.set_yticklabels(['{:,.2%}'.format(x) for x in vals])

Jianxun's solution did the job for me but broke the y value indicator at the bottom left of the window.

I ended up usingFuncFormatterinstead (and also stripped the uneccessary trailing zeroes as suggestedhere):

import pandas as pdimport numpy as npfrom matplotlib.ticker import FuncFormatterdf = pd.DataFrame(np.random.randn(100,5))ax = df.plot()ax.yaxis.set_major_formatter(FuncFormatter(lambda y, _: '{:.0%}'.format(y)))

Generally speaking I'd recommend usingFuncFormatter for label formatting: it's reliable, and versatile.

For those who are looking for the quick one-liner:

plt.gca().set_yticklabels([f'{x:.0%}' for x in plt.gca().get_yticks()])

or, if you've saved yourmatplotlib.axes.Axes object into variableax:

ax.set_yticklabels([f'{x:.0f}%' for x in ax.get_yticks()])

this assumes

• import:from matplotlib import pyplot as plt
• Python >=3.6 for f-String formatting. For older versions, replacef'{x:.0%}' with'{:.0%}'.format(x)

I'm late to the game but I just realize this:ax can be replaced withplt.gca() for those who are not using axes and just subplots.

Echoing @Mad Physicist answer, using the packagePercentFormatter it would be:

import matplotlib.ticker as mtickplt.gca().yaxis.set_major_formatter(mtick.PercentFormatter(1))#if you already have ticks in the 0 to 1 range. Otherwise see their answer

I propose an alternative method usingseaborn

Working code:

import pandas as pdimport seaborn as snsdata=np.random.rand(10,2)*100df = pd.DataFrame(data, columns=['A', 'B'])ax= sns.lineplot(data=df, markers= True)ax.set(xlabel='xlabel', ylabel='ylabel', title='title')#changing ylables ticksy_value=['{:,.2f}'.format(x) + '%' for x in ax.get_yticks()]ax.set_yticklabels(y_value)

You can do this in one line without importing anything:plt.gca().yaxis.set_major_formatter(plt.FuncFormatter('{}%'.format))

If you want integer percentages, you can do:plt.gca().yaxis.set_major_formatter(plt.FuncFormatter('{:.0f}%'.format))

You can use eitherax.yaxis orplt.gca().yaxis.FuncFormatter is still part ofmatplotlib.ticker, but you can also doplt.FuncFormatter as a shortcut.

Based on the answer of @erwanp, you can use theformatted string literals of Python 3,

x = '2'percentage = f'{x}%' # 2%

inside theFuncFormatter() and combined with alambda expression.

All wrapped:

ax.yaxis.set_major_formatter(FuncFormatter(lambda y, _: f'{y}%'))

Another one line solution if the yticks are between 0 and 1:

plt.yticks(plt.yticks()[0], ['{:,.0%}'.format(x) for x in plt.yticks()[0]])

add a line of code

ax.yaxis.set_major_formatter(ticker.PercentFormatter())

• python
• pandas
• matplotlib
• plot