cudf.DataFrame.eval#

DataFrame.eval(expr: str, inplace: bool = False, **kwargs)#

Evaluate a string describing operations on DataFrame columns.

Operates on columns only, not specific rows or elements.

Parameters
exprstr

The expression string to evaluate.

inplacebool, default False

If the expression contains an assignment, whether to perform the operation inplace and mutate the existing DataFrame. Otherwise, a new DataFrame is returned.

**kwargs

Not supported.

Returns
DataFrame, Series, or None

Series if a single column is returned (the typical use case), DataFrame if any assignment statements are included in expr, or None if inplace=True.

Notes

Difference from pandas:

  • Additional kwargs are not supported.

  • Bitwise and logical operators are not dtype-dependent. Specifically, & must be used for bitwise operators on integers, not and, which is specifically for the logical and between booleans.

  • Only numerical types are currently supported.

  • Operators generally will not cast automatically. Users are responsible for casting columns to suitable types before evaluating a function.

  • Multiple assignments to the same name (i.e. a sequence of assignment statements where later statements are conditioned upon the output of earlier statements) is not supported.

Examples

>>> df = cudf.DataFrame({'A': range(1, 6), 'B': range(10, 0, -2)})
>>> df
   A   B
0  1  10
1  2   8
2  3   6
3  4   4
4  5   2
>>> df.eval('A + B')
0    11
1    10
2     9
3     8
4     7
dtype: int64

Assignment is allowed though by default the original DataFrame is not modified.

>>> df.eval('C = A + B')
   A   B   C
0  1  10  11
1  2   8  10
2  3   6   9
3  4   4   8
4  5   2   7
>>> df
   A   B
0  1  10
1  2   8
2  3   6
3  4   4
4  5   2

Use inplace=True to modify the original DataFrame.

>>> df.eval('C = A + B', inplace=True)
>>> df
   A   B   C
0  1  10  11
1  2   8  10
2  3   6   9
3  4   4   8
4  5   2   7

Multiple columns can be assigned to using multi-line expressions:

>>> df.eval(
...     '''
... C = A + B
... D = A - B
... '''
... )
   A   B   C  D
0  1  10  11 -9
1  2   8  10 -6
2  3   6   9 -3
3  4   4   8  0
4  5   2   7  3