For anyone facing issue with the "open(file_name) as ..." Using Pandas rather than the csv library

import csv
#csv library is used for importing datasets
#generally stored as Excel datasheets.

# #before importing the dataset, it is crucial to first investigate on our own so that we can acquaint ourselves with the data.
# 1) names of columns and rows.
# 2) any noticeable missing data.
# 3) types of values(numeric or category).
# Investigating these will allow us to think more in depth about our analysis and what information is of use to us. This will also help us in planning out how we will be importing the data in our python notebook.

# In[47]:

#creating empty lists based on the columns in the dataset.

# In[48]:

import pandas as pd
df=pd.read_csv(r'C:\Users\jai yadav\OneDrive\Desktop\college assignments\python-portfolio-example-solution\insurance.csv')

# In[49]:

class PatientsInfo:
    # init method that takes in each list parameter
    def __init__(self, patients_ages, patients_sexes, patients_bmis, patients_num_children, 
                 patients_smoker_statuses, patients_regions, patients_charges):
        self.patients_ages = patients_ages
        self.patients_sexes = patients_sexes
        self.patients_bmis = patients_bmis
        self.patients_num_children = patients_num_children
        self.patients_smoker_statuses = patients_smoker_statuses
        self.patients_regions = patients_regions
        self.patients_charges = patients_charges

    # method that calcules the average ages of the patients in insurance.csv
    def analyze_ages(self):
        # initialize total age at zero
        total_age = 0
        # iterate through all ages in the ages list
        for age in self.patients_ages:
            # sum of the total age
            total_age += int(age)
        # return total age divided by the length of the patient list
        return ("Average Patient Age: " + str(round(total_age/len(self.patients_ages), 2)) + " years")

    # method that calculates the number of males and females in insurance.csv
    def analyze_sexes(self):
        # initialize number of males and females to zero
        females = 0
        males = 0
        # iterate through each sex in the sexes list
        for sex in self.patients_sexes:
            # if female add to female variable
            if sex == 'female':
                females += 1
            # if male add to male variable
            elif sex == 'male':
                males += 1
        # print out the number of each
        print("Number of females: ", females)
        print("Number of males: ", males)

    # method to find each unique region patients are from
    def unique_regions(self):
        # intialize empty list
        unique_regions = []
        # iterate through each region in regions list
        for region in self.patients_regions:
            # if the region is not already in the unique regions list
            # then add it to the unique regions list
            if region not in unique_regions: 
        # return unique regions list
        return unique_regions

    # method to find average yearly medical charges for patients in insurance.csv
    def average_charges(self):
        # initalize total_charges variable
        total_charges = 0
        # iterate through charges in patients charges list
        # add each charge to total_charge
        for charge in self.patients_charges:
            total_charges += float(charge)
        # return the average charges rounded to the hundredths place
        return ("Average Yearly Medical Insurance Charges: " +  
                str(round(total_charges/len(self.patients_charges), 2)) + " dollars.")
    # method to create dictionary with all patients information
    def create_dictionary(self):
        self.patients_dictionary = {}
        self.patients_dictionary["age"] = [int(age) for age in self.patients_ages]
        self.patients_dictionary["sex"] = self.patients_sexes
        self.patients_dictionary["bmi"] = self.patients_bmis
        self.patients_dictionary["children"] = self.patients_num_children
        self.patients_dictionary["smoker"] = self.patients_smoker_statuses
        self.patients_dictionary["regions"] = self.patients_regions
        self.patients_dictionary["charges"] = self.patients_charges
        return self.patients_dictionary

# In[50]:

patient_info = PatientsInfo(ages, sexes, bmis, no_children, smoker_status, regions, insurance_charge)

# In[51]:


# In[52]:


# In[53]:


# In[54]: