This is my data frame I'm trying to plot:
my_dic = {'stats': {'apr': 23083904,
'may': 16786816,
'june': 26197936,
}}
my_df = pd.DataFrame(my_dic)
my_df.head()
This is how I plot it:
ax = my_df['stats'].plot(kind='bar', legend=False)
ax.set_xlabel("Month", fontsize=12)
ax.set_ylabel("Stats", fontsize=12)
ax.ticklabel_format(useOffset=False) #AttributeError: This method only works with the ScalarFormatter.
plt.show()
The plot:
I'd like to control the scientific notation. I tried to suppress it by this line as was suggested in other questions plt.ticklabel_format(useOffset=False)
but I get this error back - AttributeError: This method only works with the ScalarFormatter
. Ideally, I'd like to show my data in (mln).
If you want to disable both the offset and scientific notaion, you'd use ax. ticklabel_format(useOffset=False, style='plain') .
Use a string literal to suppress scientific notation Use the string literal syntax f"{num:. nf}" to represent num in decimal format with n places following the decimal point.
Python has a defined syntax for representing a scientific notation. So, let us take a number of 0.000001234 then to represent it in a scientific form we write it as 1.234 X 10^-6. For writing it in python's scientific form we write it as 1.234E-6. Here the letter E is the exponent symbol.
Adding this line helps to get numbers in a plain format but with ',' which looks much nicer:
ax.get_yaxis().set_major_formatter(
matplotlib.ticker.FuncFormatter(lambda x, p: format(int(x), ',')))
And then I can use int(x)/
to convert to million or thousand as I wish:
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