Seaborn / Matplotlib: How to repress scientific no

问题:

Simple example below for this issue which I just can't solve.

N.B. Some other Seaborn plotting methods seems to have arguments to repress the exponential form but seemingly not factorplots. I tried some Matplotlib solutions including those suggested in this similar question but none work. Also this is not a dupe of this question. I use factorplots very frequently and ideally want to find a proper solution as opposed to a workaround.

data = {'reports': [4, 24, 31, 2, 3],'coverage': [35050800, 54899767, 57890789, 62890798, 70897871]}
df = pd.DataFrame(data)
df

Produces this dataframe:

    coverage    reports
0   35050800    4
1   54899767    24
2   57890789    31
3   62890798    2
4   70897871    3

And then this Seaborn code:

sns.factorplot(y="coverage", x="reports", kind='bar', data=df, label="Total") 

Produces this plot:

Is there a way to get the y axis to display an appropriate numeric scale based on the coverage values?

回答1:

It looks like the following line solves the issue:

plt.ticklabel_format(style='plain', axis='y')

Here is the documentation link.

回答2:

Following line solved the issue for me (addition to Tony's answer)

sns.plt.ticklabel_format(style='plain', axis='y',useOffset=False)