





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

# Splitting the dataset into the Training set and Test set
from sklearn.model_selection import train_test_split

# Fitting Polynomial Regression to the dataset
from sklearn.preprocessing import PolynomialFeatures

# Importing the dataset
_snake_case  :   int						   =  pd.read_csv(
    'https://s3.us-west-2.amazonaws.com/public.gamelab.fun/dataset/'
    'position_salaries.csv'
)
_snake_case  :   Optional[Any]						   =  dataset.iloc[:, 1:2].values
_snake_case  :   str						   =  dataset.iloc[:, 2].values


_snake_case   ,			_snake_case   ,			_snake_case   ,			_snake_case  :   Optional[Any]						   =  train_test_split(X, y, test_size=0.2, random_state=0)


_snake_case  :   List[str]						   =  PolynomialFeatures(degree=4)
_snake_case  :   Tuple						   =  poly_reg.fit_transform(X)
_snake_case  :   List[str]						   =  LinearRegression()
pol_reg.fit(X_poly, y)

def   a_   (			):
   plt.scatter(lowerCAmelCase_,     lowerCAmelCase_,     color='red'     )
   plt.plot(lowerCAmelCase_,     pol_reg.predict(poly_reg.fit_transform(lowerCAmelCase_     )     ),     color='blue'     )
   plt.title('Truth or Bluff (Linear Regression)'     )
   plt.xlabel('Position level'     )
   plt.ylabel('Salary'     )
   plt.show()


if __name__ == "__main__":
     viz_polymonial()

     # Predicting a new result with Polymonial Regression
     pol_reg.predict(poly_reg.fit_transform([[5.5]]))
     # output should be 132148.43750003








from collections.abc import Sequence

def   a_   (			lowerCAmelCase_				:      Sequence[float],     lowerCAmelCase_				:      bool = False     ):
   if not arr:
      return 0

   __lowerCAmelCase							     =     0 if allow_empty_subarrays else float('-inf'     )
   __lowerCAmelCase							     =     0.0
   for num in arr:
      __lowerCAmelCase							     =     max(0 if allow_empty_subarrays else num,     curr_sum + num     )
      __lowerCAmelCase							     =     max(lowerCAmelCase_,     lowerCAmelCase_     )

   return max_sum


if __name__ == "__main__":
     from doctest import testmod

     testmod()

     _snake_case  :   Optional[Any]						   =  [-2, 1, -3, 4, -1, 2, 1, -5, 4]
     print(F"""{max_subarray_sum(nums) = }""")

