Q. 1) Write a script to create “cricket.xml” file with multiple elements as shown below:
<CricketTeam>
<Team country=”Australia”>
<player>__</player>
<runs></runs>
<wicket></wicket>
</Team>
</CricketTeam>
Write a script to add multiple elements in “cricket.xml” file of category, country=”India”. [Marks 15]
<?php
// Function to create initial cricket.xml file with Australia team
function create_cricket_xml() {
$doc = new DOMDocument();
$doc->formatOutput = true;
$cricketTeam = $doc->createElement('CricketTeam');
$doc->appendChild($cricketTeam);
$team = $doc->createElement('Team');
$team->setAttribute('country', 'Australia');
$cricketTeam->appendChild($team);
$player = $doc->createElement('player', 'Player Name');
$team->appendChild($player);
$runs = $doc->createElement('runs', '0');
$team->appendChild($runs);
$wicket = $doc->createElement('wicket', '0');
$team->appendChild($wicket);
$doc->save('cricket.xml');
echo "cricket.xml file created with Australia team.<br><br>";
}
// Function to add multiple elements in cricket.xml file of category country="India"
function add_elements_to_cricket_xml() {
$doc = new DOMDocument();
$doc->load('cricket.xml');
$cricketTeam = $doc->documentElement;
$indiaTeam = $doc->createElement('Team');
$indiaTeam->setAttribute('country', 'India');
// Add multiple elements for India team
for ($i = 1; $i <= 3; $i++) {
$player = $doc->createElement('player', "Player $i");
$indiaTeam->appendChild($player);
$runs = $doc->createElement('runs', rand(10, 100)); // Random runs
$indiaTeam->appendChild($runs);
$wicket = $doc->createElement('wicket', rand(0, 5)); // Random wickets
$indiaTeam->appendChild($wicket);
}
$cricketTeam->appendChild($indiaTeam);
$doc->save('cricket.xml');
echo "Elements added to cricket.xml file for India team.<br><br>";
}
// Create cricket.xml file with Australia team if it doesn't exist
if (!file_exists('cricket.xml')) {
create_cricket_xml();
}
// Add elements for India team
add_elements_to_cricket_xml();
?>
Q. 2) Consider the following dataset :
Write a Python script for the following :
i. Read the dataset and perform data cleaning operations on it.
ii. ii. Tokenize the comments in words. iii. Perform sentiment analysis and find the percentage of
positive, negative and neutral comments..
import pandas as pd
from textblob import TextBlob
Read the dataset
df = pd.read_csv('covid_2021_1.csv')
Data cleaning operations (if needed)
Tokenize the comments in words
def tokenize_comments(comment):
return TextBlob(comment).words
df['tokenized_comments'] = df['comment'].apply(tokenize_comments)
Perform sentiment analysis
def get_sentiment(comment):
analysis = TextBlob(comment)
if analysis.sentiment.polarity > 0:
return 'Positive'
elif analysis.sentiment.polarity == 0:
return 'Neutral'
else:
return 'Negative'
df['sentiment'] = df['comment'].apply(get_sentiment)
Calculate percentage of positive, negative, and neutral comments
sentiment_counts = df['sentiment'].value_counts(normalize=True) * 100
print("Percentage of Comments by Sentiment:")
print(sentiment_counts)