pandas.DataFrame.eval¶
-
DataFrame.
eval
(expr, inplace=False, **kwargs)[source]¶ Evaluate a string describing operations on DataFrame columns.
Operates on columns only, not specific rows or elements. This allows eval to run arbitrary code, which can make you vulnerable to code injection if you pass user input to this function.
Parameters: expr : str
The expression string to evaluate.
inplace : bool, 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.
New in version 0.18.0..
kwargs : dict
Returns: ndarray, scalar, or pandas object
The result of the evaluation.
See also
DataFrame.query
- Evaluates a boolean expression to query the columns of a frame.
DataFrame.assign
- Can evaluate an expression or function to create new values for a column.
pandas.eval
- Evaluate a Python expression as a string using various backends.
Notes
For more details see the API documentation for
eval()
. For detailed examples see enhancing performance with eval.Examples
>>> df = pd.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