cudf.DataFrame.exp#

DataFrame.exp()#

Get the exponential of all elements, element-wise.

Exponential is the inverse of the log function, so that x.exp().log() = x

Returns
DataFrame/Series/Index

Result of the element-wise exponential.

Examples

>>> import cudf
>>> ser = cudf.Series([-1, 0, 1, 0.32434, 0.5, -10, 100])
>>> ser
0     -1.00000
1      0.00000
2      1.00000
3      0.32434
4      0.50000
5    -10.00000
6    100.00000
dtype: float64
>>> ser.exp()
0    3.678794e-01
1    1.000000e+00
2    2.718282e+00
3    1.383117e+00
4    1.648721e+00
5    4.539993e-05
6    2.688117e+43
dtype: float64

exp operation on DataFrame:

>>> df = cudf.DataFrame({'first': [-1, -10, 0.5],
...                      'second': [0.234, 0.3, 10]})
>>> df
   first  second
0   -1.0   0.234
1  -10.0   0.300
2    0.5  10.000
>>> df.exp()
      first        second
0  0.367879      1.263644
1  0.000045      1.349859
2  1.648721  22026.465795

exp operation on Index:

>>> index = cudf.Index([-1, 0.4, 1, 0, 0.3])
>>> index
Float64Index([-1.0, 0.4, 1.0, 0.0, 0.3], dtype='float64')
>>> index.exp()
Float64Index([0.36787944117144233,  1.4918246976412703,
              2.718281828459045, 1.0,  1.3498588075760032],
            dtype='float64')