Update README.md

README.md

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-# Tamil News Articles Dataset
+# HinduTamil News Articles Dataset
 
 ## Overview
 This dataset contains news articles in Tamil language scraped from the Hindu Tamil news website. Each article includes its title, author, city, published date, and text.
@@ -25,14 +25,19 @@ This dataset was created to provide a comprehensive collection of Tamil news art
 ## Data Sources and collection method
 The data in this dataset was collected from the Hindu Tamil news website (https://www.hindutamil.in/news/tamilnadu/).
 Data was collected from the website using web scraping techniques.
-I used the requests library in Python to send HTTP requests to the website and BeautifulSoup for parsing the HTML content.
-Articles were scraped iteratively from multiple pages, with each page containing a list of articles.
-The article URLs were extracted from the HTML content of each page and then visited to retrieve the article details.
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+- Sending HTTP Requests: The requests library in Python was utilized to send HTTP GET requests to the Hindu Tamil news website. These requests fetched the HTML content of each webpage.
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+- Parsing HTML Content: The BeautifulSoup library parsed the HTML content, enabling the extraction of specific elements from each webpage. This included gathering article URLs, titles, authors, published dates, and main article text.
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+- Iterative Scraping: Data was scraped iteratively from multiple pages of the website. Each webpage typically displayed a list of articles, and the URLs for each article were extracted. Subsequently, each article URL was visited to extract detailed information.
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+- Handling Errors and Timeouts: Error and timeout handling was implemented using try-except blocks to ensure smooth operation during the scraping process.
 
 ## Data Cleaning and Preprocessing
 
-Duplicate entries were removed based on the article URL.
-NaN values were handled by removing rows containing NaN values, depending on the context.
+Duplicate entries were removed based on the published date.
+NaN values were handled by removing rows containing NaN values.
 Irrelevant information such as author's comments, footer text, and advertisements were filtered out from the article text.
 Published dates were extracted from the article content and formatted into a standardized date-time format.