OneCompiler

Hslip27

115

Q1]

<!DOCTYPE html> <html> <head> <title>File Content Copier</title> </head> <body> <?php if ($_SERVER["REQUEST_METHOD"] == "POST") { $sourceFileName = $_POST["sourceFileName"]; $destinationFileName = $_POST["destinationFileName"]; 
    // Read content from the source file
    $fileContent = file_get_contents($sourceFileName);

    // Write content to the destination file
    file_put_contents($destinationFileName, $fileContent);

    echo "Content from '$sourceFileName' has been copied to '$destinationFileName'.";
}
?>

<h2>File Content Copier</h2>
<form method="post" action="<?php echo $_SERVER['PHP_SELF'];?>">
    Source File Name: <input type="text" name="sourceFileName"><br>
    Destination File Name: <input type="text" name="destinationFileName"><br>
    <input type="submit" value="Copy Content">
</form>
</body> </html>

Q2]
import pandas as pd
from sklearn.preprocessing import OneHotEncoder, LabelEncoder

Create a dataset data.csv

data = {'Country': ['USA', 'India', 'UK', 'Canada', 'India', 'USA'],
'Purchased': ['Yes', 'No', 'Yes', 'No', 'Yes', 'No']}
df = pd.DataFrame(data)

a. Apply OneHot coding on Country column

onehot_encoder = OneHotEncoder(sparse=False)
onehot_encoded = onehot_encoder.fit_transform(df[['Country']])
onehot_df = pd.DataFrame(onehot_encoded, columns=['Country_' + country for country in onehot_encoder.get_feature_names_out(['Country'])])
df = pd.concat([df, onehot_df], axis=1)
df.drop(columns=['Country'], inplace=True)

b. Apply Label encoding on Purchased column

label_encoder = LabelEncoder()
df['Purchased'] = label_encoder.fit_transform(df['Purchased'])

Display the modified dataset

print("Modified Dataset:")
print(df)