How can one modify the format for the output from a groupby operation in pandas that produces scientific notation for very large numbers?
I know how to do string formatting in python but I’m at a loss when it comes to applying it here.
df1.groupby('dept')['data1'].sum()
dept
value1 1.192433e+08
value2 1.293066e+08
value3 1.077142e+08
This suppresses the scientific notation if I convert to string but now I’m just wondering how to string format and add decimals.
sum_sales_dept.astype(str)
Advertisement
Answer
Granted, the answer I linked in the comments is not very helpful. You can specify your own string converter like so.
In [25]: pd.set_option('display.float_format', lambda x: '%.3f' % x)
In [28]: Series(np.random.randn(3))*1000000000
Out[28]:
0 -757322420.605
1 -1436160588.997
2 -1235116117.064
dtype: float64
I’m not sure if that’s the preferred way to do this, but it works.
Converting numbers to strings purely for aesthetic purposes seems like a bad idea, but if you have a good reason, this is one way:
In [6]: Series(np.random.randn(3)).apply(lambda x: '%.3f' % x) Out[6]: 0 0.026 1 -0.482 2 -0.694 dtype: object