How to solve an inequality that contains standard deviation in python?

I have the past 19 days of stock price stored in the pd.dataframe and I am trying to find out the price P that is smaller than (mean - 2.5*standard deviation), where mean and standard deviation are calculated based on P and the past 19 days prices.

The inequality will be something like below:

P < mean - 2.5*standard deviation

I am assuming using solve in SciPy, but I got the error 'loop of ufunc does not support argument 0 of type Add which has no callable sqrt method' when calling np.std().

This is the demo code:

from sympy.solvers import solvefrom sympy import Symbolx = Symbol('x')solve(x-np.mean([1,2,3,x])-np.std([1,2,3,x]), x)

Error message:

---------------------------------------------------------------------------AttributeError                            Traceback (most recent call last)AttributeError: 'Add' object has no attribute 'sqrt'The above exception was the direct cause of the following exception:TypeError                                 Traceback (most recent call last)Input In [71], in <cell line: 4>()      2 from sympy import Symbol      3 x = Symbol('x')----> 4 solve(x-np.mean([1,2,3,x])-np.std([1,2,3,x]), x)File ~/opt/anaconda3/lib/python3.9/site-packages/numpy/core/fromnumeric.py:3645, in std(a, axis, dtype, out, ddof, keepdims, where)   3642     else:   3643         return std(axis=axis, dtype=dtype, out=out, ddof=ddof, **kwargs)-> 3645 return _methods._std(a, axis=axis, dtype=dtype, out=out, ddof=ddof,   3646                      **kwargs)File ~/opt/anaconda3/lib/python3.9/site-packages/numpy/core/_methods.py:214, in _std(a, axis, dtype, out, ddof, keepdims, where)    212     ret = ret.dtype.type(um.sqrt(ret))    213 else:--> 214     ret = um.sqrt(ret)    216 return retTypeError: loop of ufunc does not support argument 0 of type Add which has no callable sqrt method

Or maybe are there any other better methods?