




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
lowercase__				:     Optional[Any] 		=						pd.read_csv(
    "https://s3.us-west-2.amazonaws.com/public.gamelab.fun/dataset/"
    "position_salaries.csv"
)
lowercase__				:     List[str] 		=						dataset.iloc[:, 1:2].values
lowercase__				:     Dict 		=						dataset.iloc[:, 2].values


lowercase__		,       lowercase__		,       lowercase__		,       lowercase__				:     Dict 		=						train_test_split(X, y, test_size=0.2, random_state=0)


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


def 						lowerCamelCase__    (		):







	'''simple docstring'''





	plt.scatter(_A     ,	_A     ,	color="red"							)
	plt.plot(_A     ,	pol_reg.predict(poly_reg.fit_transform(_A							)							)     ,	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






def 						lowerCamelCase__    (		_A							):







	'''simple docstring'''





	snake_case_		    =     len(_A							)
	for i in range(_A							):
		for j in range(i + 1     ,	_A							):
			if numbers[j] < numbers[i]:
				snake_case_    ,      snake_case_		    =     numbers[j], numbers[i]
	return numbers


if __name__ == "__main__":
		lowercase__				:     int 		=						input("Enter numbers separated by a comma:\n").strip()
		lowercase__				:     Any 		=						[int(item) for item in user_input.split(",")]
		print(exchange_sort(unsorted))
