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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).
464
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:
69
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