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
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Answer
This is a few months late, but I have created PR#6251 with matplotlib to add a new PercentFormatter
class. With this class you just need one line to reformat your axis (two if you count the import of matplotlib.ticker
):
import ... import matplotlib.ticker as mtick ax = 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 do PercentFormatter(1.0)
.
The other two parameters allow you to set the number of digits after the decimal point and the symbol. They default to None
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.