Whatever your project size is, we will handle it well with all the standards fulfilled! We are here to give 100% satisfaction.
For job seekers, please visit our Career Page or send your resume to hr@actowizsolutions.com
The internet is flooded with innumerable information relating to how to scrape data. But hardly any information is available on how to scrape TV show episodes for IMDb ratings. If you are the one looking for the same, then you are at the right place. This blog will give you stepwise information on the scraping procedure.
Let’s scrape the IMDb movie ratings along with their details using Python’s BeautifulSoup library.
Below is the module list needed to scrape from IMDB
First, navigate through the season 1-page series. It will comprise the list of season episodes. Series 1 will appear like this:
Now, get the page URL. It will appear like this.
http://www.imdb.com/title/tt1439629/episodes?season=1
‘tt1439629’ is the show’s ID. If you aren’t using Community, then this id will be different.
Next, to request content from the web server, we will use get(). We will then store the server response in the variable response. Then, we will check for a few lines. Within the response lies the webpage’s HTML code.
Create a BeautifulSoup object to parse the response.text. Now, assign this object to html_soup. The html.parser argument signifies that we will perform parsing with the help of Python’s built-in HTML parser.
The variables that we obtain here are
In the above image, if you notice attentively, you will find that the information that we require is in <div class="info" ...> </div>
The yellow part contains tags of the code. At the same time, the green ones are the data that we are trying to extract.
Now, from the page, capture all the instances of <div class="info" ...> </div>
find_all will return a ResultSet object which comprises a list of 25
<div class="info" ...> </div>
Extraction of Required Variables
Now, we will extract the data from episode_containers for an individual episode.
For the title, we require a title attribute from < a > tag.
It lies within the meta tag under the content attribute.
It lies within the < div > tag with the class airdate. If we stripe to remove whitespace, we can easily obtain test attributes.
It lies within the < div > tag with the class ipl-rating-star__rating. It also uses text attributes.
It includes the same tag. The only difference is that it lies within different classes.
Here we will perform the same thing as we did for the airdate but only will change the class.
Repeat the same for each episode and season. It will require two ‘for’ loops. For per season loop, adjust the range() based on the season numbers you want to scrape.
To make a function numeric, we will use replace() to remove the ‘,’ , ‘(‘, and ‘)’ from total_votes
Apply the function and change the type to int using astype()
Now the available data is ready for analysis.
Ensure to save it
CTA: For more information, contact Actowiz Solutions now! You can also reach us for all your mobile app scraping and web scraping services requirements.
Learn effective techniques to Scrape Google Maps POI Data safely, avoid IP blocks, and gather accurate location-based insights for business or research needs.
Learn how to build a scalable Amazon web crawler using Python in 2025. Discover techniques, tools, and best practices for effective product data extraction.
Actowiz Solutions' report unveils 2024 Black Friday grocery discounts, highlighting key pricing trends and insights to help businesses & shoppers save smarter.
This report explores women's fashion trends and pricing strategies in luxury clothing by analyzing data extracted from Gucci's website.
Leverage tyre pricing and market intelligence to gain a competitive edge, optimize strategies, and drive growth in the global tire industry.
Explore how data scraping optimizes ferry schedules and cruise prices, providing actionable insights for businesses to enhance offerings and pricing strategies.
Crumbl is growing sweeter with every bite! Check out thier recently opened locations and see how they are bringing their famous cookies closer to you with our web scraping services. Have you visited one yet
Web scraping enables businesses to access and analyze detailed product specifications from Costco, including prices, descriptions, availability, and reviews. By leveraging this data, companies can gain insights into customer preferences, monitor competitor pricing, and optimize their product offerings for better market performance.