Charan H U charanhu

## file.html
<!DOCTYPE html>
<html>

<head>
  <title>OCR PDFs and images directly in your browser</title>
  <meta name="viewport" content="width=device-width, initial-scale=1.0">
  <script defer data-domain="tools.simonwillison.net" src="https://plausible.io/js/script.js"></script>
  <script type="module">
    import pdfjsDist from 'https://cdn.jsdelivr.net/npm/pdfjs-dist@4.0.379/+esm';
    pdfjsLib.GlobalWorkerOptions.workerSrc =

## man.py
# Example 1: getattr() function
class Person:
    def __init__(self, age):
        self.age = age

# create a Person object with age 36
person = Person(36)

# get the value of the attribute 'age'
print('The age of Person ',getattr(person, 'age', 40))

## python5.py
# 31,female,25.74,0,no,southeast
input_data = (31,1,25.74,0,1,0)

#changing input_data to a numpy array
input_data_as_numpy_array=np.asarray(input_data)

#reshape the array
input_data_reshaped=input_data_as_numpy_array.reshape(1,-1)

prediction=regressor.predict(input_data_reshaped)

## python4.py
# prediction on the test data
test_data_prediction= regressor.predict(X_test)

r2_test=metrics.r2_score(Y_test, test_data_prediction)
print('R squared value: ', r2_test)

## python3.py
# predictio on the training data
training_data_prediction= regressor.predict(X_train)

# R squared value
r2_train=metrics.r2_score(Y_train, training_data_prediction)
print('R squared value: ', r2_train)

## python2.py
# loading the linear regression model
regressor = LinearRegression()

regressor.fit(X_train, Y_train)

## python1.py
X = insurance_dataset.drop(columns='charges', axis=1)
Y = insurance_dataset['charges']
X_train, X_test, Y_train, Y_test=train_test_split(X, Y, test_size=0.2, random_state=2)

## python.py
# encoding sex column
insurance_dataset.replace({'sex':{'male':0, 'female':1}}, inplace=True)

# encoding smoker column
insurance_dataset.replace({'smoker':{'yes':0, 'no':1}}, inplace=True)

# encoding region column
insurance_dataset.replace({'region':{'southeast':0, 'southwest':1, 'northeast':2, 'northwest':3}}, inplace=True)

## indexuse.html
<!doctype html>
<html lang="en">

<head>
  <meta charset="utf-8">
  <title>Diamond Life</title>
  <base href="/">
  <meta name="viewport" content="width=device-width, initial-scale=1">
  <!-- <link rel="icon" type="image/x-icon" href="favicon.ico"> -->
  <link rel="stylesheet" href="https://cdn.jsdelivr.net/npm/bootstrap@4.6.1/dist/css/bootstrap.min.css">

## SQL6.sql
INSERT INTO CONSTRAINT_DEMO2 VALUES
(1,'AAA',22,'BBB'),
(2,'BBB',23,'CCC'),
(3,'CCC',24,'DDD'),
(4,'DDD',22,'AAA');
	<!DOCTYPE html>
	<html>

	<head>
	<title>OCR PDFs and images directly in your browser</title>
	<meta name="viewport" content="width=device-width, initial-scale=1.0">
	<script defer data-domain="tools.simonwillison.net" src="https://plausible.io/js/script.js"></script>
	<script type="module">
	import pdfjsDist from 'https://cdn.jsdelivr.net/npm/pdfjs-dist@4.0.379/+esm';
	pdfjsLib.GlobalWorkerOptions.workerSrc =
	# Example 1: getattr() function
	class Person:
	def __init__(self, age):
	self.age = age

	# create a Person object with age 36
	person = Person(36)

	# get the value of the attribute 'age'
	print('The age of Person ',getattr(person, 'age', 40))
	# 31,female,25.74,0,no,southeast
	input_data = (31,1,25.74,0,1,0)

	#changing input_data to a numpy array
	input_data_as_numpy_array=np.asarray(input_data)

	#reshape the array
	input_data_reshaped=input_data_as_numpy_array.reshape(1,-1)

	prediction=regressor.predict(input_data_reshaped)
	# prediction on the test data
	test_data_prediction= regressor.predict(X_test)

	r2_test=metrics.r2_score(Y_test, test_data_prediction)
	print('R squared value: ', r2_test)
	# predictio on the training data
	training_data_prediction= regressor.predict(X_train)

	# R squared value
	r2_train=metrics.r2_score(Y_train, training_data_prediction)
	print('R squared value: ', r2_train)
	# loading the linear regression model
	regressor = LinearRegression()

	regressor.fit(X_train, Y_train)
	X = insurance_dataset.drop(columns='charges', axis=1)
	Y = insurance_dataset['charges']
	X_train, X_test, Y_train, Y_test=train_test_split(X, Y, test_size=0.2, random_state=2)
	# encoding sex column
	insurance_dataset.replace({'sex':{'male':0, 'female':1}}, inplace=True)

	# encoding smoker column
	insurance_dataset.replace({'smoker':{'yes':0, 'no':1}}, inplace=True)

	# encoding region column
	insurance_dataset.replace({'region':{'southeast':0, 'southwest':1, 'northeast':2, 'northwest':3}}, inplace=True)
	<!doctype html>
	<html lang="en">

	<head>
	<meta charset="utf-8">
	<title>Diamond Life</title>
	<base href="/">
	<meta name="viewport" content="width=device-width, initial-scale=1">
	<!-- <link rel="icon" type="image/x-icon" href="favicon.ico"> -->
	<link rel="stylesheet" href="https://cdn.jsdelivr.net/npm/bootstrap@4.6.1/dist/css/bootstrap.min.css">
	INSERT INTO CONSTRAINT_DEMO2 VALUES
	(1,'AAA',22,'BBB'),
	(2,'BBB',23,'CCC'),
	(3,'CCC',24,'DDD'),
	(4,'DDD',22,'AAA');