import math
import pandas as pd

class Person:
    def __init__(self, city, jobTitle, yearOfExperience, salary):
        self.city = city
        self.jobTitle = jobTitle
        self.yearOfExperience = yearOfExperience
        self.salary = salary


class KB:
    def findCoL(self, city):
        cost_of_living_data = pd.read_csv("ColData.csv")
        # get first row
        colCitiesList = cost_of_living_data.iloc[:, 0].tolist()
        index = colCitiesList.index(city)
        return cost_of_living_data.iloc[index, 2]

    def percentageByExperience(self, yearOfExperience):
        if yearOfExperience >= 0 and yearOfExperience <= 5:
            return -10
        elif yearOfExperience > 5 and yearOfExperience < 15:
            return 5
        elif yearOfExperience >= 15 and yearOfExperience < 25:
            return 19
        elif yearOfExperience >= 25:
            return 28

    def predictSalary(self, person):
        percentage = self.percentageByExperience(person.yearOfExperience)
        salary = person.salary
        salaryByExperience = (salary * (1 + (percentage / 100)))
        return salaryByExperience


7397fb595c939cd0c91335a6b65e9e4da22601df
<mask token>


class KB:
    <mask token>

    def percentageByExperience(self, yearOfExperience):
        if yearOfExperience >= 0 and yearOfExperience <= 5:
            return -10
        elif yearOfExperience > 5 and yearOfExperience < 15:
            return 5
        elif yearOfExperience >= 15 and yearOfExperience < 25:
            return 19
        elif yearOfExperience >= 25:
            return 28

    def predictSalary(self, person):
        percentage = self.percentageByExperience(person.yearOfExperience)
        salary = person.salary
        salaryByExperience = salary * (1 + percentage / 100)
        return salaryByExperience

<mask token>


class KB:

    def findCoL(self, city):
        cost_of_living_data = pd.read_csv('ColData.csv')
        colCitiesList = cost_of_living_data.iloc[:, 0].tolist()
        index = colCitiesList.index(city)
        return cost_of_living_data.iloc[index, 2]

    def percentageByExperience(self, yearOfExperience):
        if yearOfExperience >= 0 and yearOfExperience <= 5:
            return -10
        elif yearOfExperience > 5 and yearOfExperience < 15:
            return 5
        elif yearOfExperience >= 15 and yearOfExperience < 25:
            return 19
        elif yearOfExperience >= 25:
            return 28

    def predictSalary(self, person):
        percentage = self.percentageByExperience(person.yearOfExperience)
        salary = person.salary
        salaryByExperience = salary * (1 + percentage / 100)
        return salaryByExperience

<mask token>


class Person:

    def __init__(self, city, jobTitle, yearOfExperience, salary):
        self.city = city
        self.jobTitle = jobTitle
        self.yearOfExperience = yearOfExperience
        self.salary = salary


class KB:

    def findCoL(self, city):
        cost_of_living_data = pd.read_csv('ColData.csv')
        colCitiesList = cost_of_living_data.iloc[:, 0].tolist()
        index = colCitiesList.index(city)
        return cost_of_living_data.iloc[index, 2]

    def percentageByExperience(self, yearOfExperience):
        if yearOfExperience >= 0 and yearOfExperience <= 5:
            return -10
        elif yearOfExperience > 5 and yearOfExperience < 15:
            return 5
        elif yearOfExperience >= 15 and yearOfExperience < 25:
            return 19
        elif yearOfExperience >= 25:
            return 28

    def predictSalary(self, person):
        percentage = self.percentageByExperience(person.yearOfExperience)
        salary = person.salary
        salaryByExperience = salary * (1 + percentage / 100)
        return salaryByExperience

import math
import pandas as pd


class Person:

    def __init__(self, city, jobTitle, yearOfExperience, salary):
        self.city = city
        self.jobTitle = jobTitle
        self.yearOfExperience = yearOfExperience
        self.salary = salary


class KB:

    def findCoL(self, city):
        cost_of_living_data = pd.read_csv('ColData.csv')
        colCitiesList = cost_of_living_data.iloc[:, 0].tolist()
        index = colCitiesList.index(city)
        return cost_of_living_data.iloc[index, 2]

    def percentageByExperience(self, yearOfExperience):
        if yearOfExperience >= 0 and yearOfExperience <= 5:
            return -10
        elif yearOfExperience > 5 and yearOfExperience < 15:
            return 5
        elif yearOfExperience >= 15 and yearOfExperience < 25:
            return 19
        elif yearOfExperience >= 25:
            return 28

    def predictSalary(self, person):
        percentage = self.percentageByExperience(person.yearOfExperience)
        salary = person.salary
        salaryByExperience = salary * (1 + percentage / 100)
        return salaryByExperience

import math
import pandas as pd

class Person:
    def __init__(self, city, jobTitle, yearOfExperience, salary):
        self.city = city
        self.jobTitle = jobTitle
        self.yearOfExperience = yearOfExperience
        self.salary = salary


class KB:
    def findCoL(self, city):
        cost_of_living_data = pd.read_csv("ColData.csv")
        # get first row
        colCitiesList = cost_of_living_data.iloc[:, 0].tolist()
        index = colCitiesList.index(city)
        return cost_of_living_data.iloc[index, 2]

    def percentageByExperience(self, yearOfExperience):
        if yearOfExperience >= 0 and yearOfExperience <= 5:
            return -10
        elif yearOfExperience > 5 and yearOfExperience < 15:
            return 5
        elif yearOfExperience >= 15 and yearOfExperience < 25:
            return 19
        elif yearOfExperience >= 25:
            return 28

    def predictSalary(self, person):
        percentage = self.percentageByExperience(person.yearOfExperience)
        salary = person.salary
        salaryByExperience = (salary * (1 + (percentage / 100)))
        return salaryByExperience

