A problem occurred during polynomial regression

import matplotlib.pyplot as plt
import pandas as pd
from sklearn.linear_model import LinearRegression
from sklearn.preprocessing import PolynomialFeatures
import time

path = "C:\\Users\\todgu\\Downloads\\삼각함수표1111.csv"
doc = pd.read_csv(path, encoding = "cp949")
doc = doc.dropna()

def sin(angle):
    y = doc.iloc[:, 3].values
    x = doc.iloc[:, 1].values
    y = y.reshape(-1, 1)
    x = x.reshape(-1, 1)
    
    poly_reg = PolynomialFeatures(degree = 4)
    x_poly = poly_reg.fit_transform(x)
    poly_reg.get_feature_names_out()
    len_reg = LinearRegression()
    len_reg.fit(x_poly, y)

    return len_reg.predict(poly_reg.fit_transform([[angle]]))


def cos(angle):
    y = doc.iloc[:, 4].values
    x = doc.iloc[:, 1].values
    y = y.reshape(-1, 1)
    x = x.reshape(-1, 1)
    
    poly_reg = PolynomialFeatures(degree = 4)
    x_poly = poly_reg.fit_transform(x)
    poly_reg.get_feature_names_out()
    len_reg = LinearRegression()
    len_reg.fit(x_poly, y)

    return len_reg.predict(poly_reg.fit_transform([[angle]]))


def tan(angle):
    y = doc.iloc[:, 5].values
    x = doc.iloc[:, 1].values
    y = y.reshape(-1, 1)
    x = x.reshape(-1, 1)

    poly_reg = PolynomialFeatures(degree = 4)
    x_poly = poly_reg.fit_transform(x)
    poly_reg.get_feature_names_out()
    len_reg = LinearRegression()
    len_reg.fit(x_poly, y)

    return len_reg.predict(poly_reg.fit_transform([[angle]]))

while True:
    print("<삼각함수 잘하는 AI>입니다.")
    print("이용하고자 하는 함수를 선택하세요.")
    print("[1] sin  |  [2] cos  |  [3] tan")
    func = input()
    print("각도를 입력하여 주세요.(90°이하) [뒤로가기]")
    ang = input()
    if ang == "뒤로가기":
        continue
    elif func == "1" or func == "sin":
        print(sin(ang))
    elif func == "2" or func == "cos":
        print(cos(ang))
    elif func == "3" or func == "tan":
        print(tan(ang))
    else:
        print("잘못된 입력값입니다.")

I am getting the following error:

Traceback (most recent call last):
  File "c:\Users\todgu\coding\AIstudy\삼각함수.py", line 65, in <module>
    print(sin(ang))
          ^^^^^^^^
  File "c:\Users\todgu\coding\AIstudy\삼각함수.py", line 23, in sin
    return len_reg.predict(poly_reg.fit_transform([[angle]]))
                           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "C:\Python311\Lib\site-packages\sklearn\utils\_set_output.py", line 140, in wrapped
    data_to_wrap = f(self, X, *args, **kwargs)
                   ^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "C:\Python311\Lib\site-packages\sklearn\base.py", line 915, in fit_transform
    return self.fit(X, **fit_params).transform(X)
           ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "C:\Python311\Lib\site-packages\sklearn\base.py", line 1151, in wrapper
    return fit_method(estimator, *args, **kwargs)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "C:\Python311\Lib\site-packages\sklearn\preprocessing\_polynomial.py", line 322, in fit
    _, n_features = self._validate_data(X, accept_sparse=True).shape
                    ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "C:\Python311\Lib\site-packages\sklearn\base.py", line 604, in _validate_data
    out = check_array(X, input_name="X", **check_params)
          ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "C:\Python311\Lib\site-packages\sklearn\utils\validation.py", line 948, in check_array
    raise ValueError(
ValueError: dtype='numeric' is not compatible with arrays of bytes/strings.Convert your data to numeric values explicitly instead.

I was making a program that outputs the result according to the input value by learning the value of each angle of the trigonometric function.
can anyone help?
I am so tired of this.
I’ve tried changing the datatype, but I’m still getting errors. I have no idea why I am getting the error… ㅠoㅠ

>Solution :

Probally the columns in the CSV file have some non-numerical (str) values. I can’t tell for sure, as I don’t have access to the file, but I imagine it contains data like ‘sin’ or ‘cos’, and it may not be calculating those values and reading them as numbers. You can use the pandas function ‘to_numeric’ to try solving that.

Link: https://pandas.pydata.org/docs/reference/api/pandas.to_numeric.html

Something like:
doc[‘column_name’] = pd.to_numeric(doc[‘column_name’])

I’m also learning data analysis, so not too sure if I could help, hope it does!