[python] Format y axis as percent

I have an existing plot that was created with pandas like this:

df['myvar'].plot(kind='bar')

The y axis is format as float and I want to change the y axis to percentages. All of the solutions I found use ax.xyz syntax and I can only place code below the line above that creates the plot (I cannot add ax=ax to the line above.)

How can I format the y axis as percentages without changing the line above?

Here is the solution I found but requires that I redefine the plot:

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

data = [8,12,15,17,18,18.5]
perc = np.linspace(0,100,len(data))

fig = plt.figure(1, (7,4))
ax = fig.add_subplot(1,1,1)

ax.plot(perc, data)

fmt = '%.0f%%' # Format you want the ticks, e.g. '40%'
xticks = mtick.FormatStrFormatter(fmt)
ax.xaxis.set_major_formatter(xticks)

plt.show()

Link to the above solution: Pyplot: using percentage on x axis

This question is related to python pandas matplotlib plot

The answer is


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

I ended up using FuncFormatterinstead (and also stripped the uneccessary trailing zeroes as suggested here):

import pandas as pd
import numpy as np
from matplotlib.ticker import FuncFormatter

df = 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 using FuncFormatter for label formatting: it's reliable, and versatile.

enter image description here


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

plt.gca().set_yticklabels(['{:.0f}%'.format(x*100) for x in plt.gca().get_yticks()]) 

Or if you are using Latex as the axis text formatter, you have to add one backslash '\'

plt.gca().set_yticklabels(['{:.0f}\%'.format(x*100) for x in plt.gca().get_yticks()]) 

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

import pandas as pd
import numpy as np

df = pd.DataFrame(np.random.randn(100,5))

# you get ax from here
ax = df.plot()
type(ax)  # matplotlib.axes._subplots.AxesSubplot

# manipulate
vals = ax.get_yticks()
ax.set_yticklabels(['{:,.2%}'.format(x) for x in vals])

enter image description here


I propose an alternative method using seaborn

Working code:

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

enter image description here


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

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

inside the FuncFormatter() and combined with a lambda expression.

All wrapped:

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

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

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

import matplotlib.ticker as mtick

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

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