hipdf.DataFrame.eval

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hipdf.DataFrame.eval#

22 min read time

Applies to Linux

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.

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
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