pandas.eval — pandas 0.16.2 documentation (original) (raw)

expr : str or unicode

The expression to evaluate. This string cannot contain any Pythonstatements, only Python expressions.

parser : string, default ‘pandas’, {‘pandas’, ‘python’}

The parser to use to construct the syntax tree from the expression. The default of 'pandas' parses code slightly different than standard Python. Alternatively, you can parse an expression using the'python' parser to retain strict Python semantics. See theenhancing performance documentation for more details.

engine : string, default ‘numexpr’, {‘python’, ‘numexpr’}

The engine used to evaluate the expression. Supported engines are

• 'numexpr': This default engine evaluates pandas objects using
  numexpr for large speed ups in complex expressions with large frames.
• 'python': Performs operations as if you had eval‘d in top
  level python. This engine is generally not that useful.

More backends may be available in the future.

truediv : bool, optional

Whether to use true division, like in Python >= 3

local_dict : dict or None, optional

A dictionary of local variables, taken from locals() by default.

global_dict : dict or None, optional

A dictionary of global variables, taken from globals() by default.

resolvers : list of dict-like or None, optional

A list of objects implementing the __getitem__ special method that you can use to inject an additional collection of namespaces to use for variable lookup. For example, this is used in thequery() method to inject theindex and columnsvariables that refer to their respective DataFrameinstance attributes.

level : int, optional

The number of prior stack frames to traverse and add to the current scope. Most users will not need to change this parameter.

target : a target object for assignment, optional, default is None

essentially this is a passed in resolver