dtoolkit.accessor.series.eval#

dtoolkit.accessor.series.eval(s: Series, /, expr: str, **kwargs)[source]#

Evaluate a string describing operations on Series.

This allows eval to run arbitrary code, which can make you vulnerable to code injection if you pass user input to this function.

Parameters:

exprstr: The expression string to evaluate.
**kwargs: See the documentation for pandas.eval() for complete details on the keyword arguments.

Returns:

ndarray, scalar, pandas object

See also

pandas.eval: Evaluate a Python expression as a string using various backends.
pandas.DataFrame.eval: Evaluate a string describing operations on DataFrame columns.
dtoolkit.accessor.series.query: Evaluates a boolean expression to query Series.

Examples

>>> import dtoolkit
>>> import pandas as pd

The name should be set.

>>> s = pd.Series([1, 2, 3], index=["a", "b", "c"], name="col")
>>> s
a    1
b    2
c    3
Name: col, dtype: int64
>>> s.eval("col - 1")
a    0
b    1
c    2
Name: col, dtype: int64
>>> s.eval("d = 4")
a    1
b    2
c    3
d    4
Name: col, dtype: int64
>>> s.eval("col == 1")
a     True
b    False
c    False
Name: col, dtype: bool
>>> s.eval("index == 'c'")
a    False
b    False
c     True
dtype: bool