Started in 2008, CarDekho.com is one of India’s leading car search companies. This company helps users in making car purchases that are appropriate for them. This website and app have enhanced automotive content like comparisons, expert reviews, detailed specifications and pricing, images, and videos of all car models and brands accessible in India.
CarDekho.com has links with several auto manufacturers, more than 4,000 car dealers, and several financial institutions for helping customers with vehicle purchases.
The company offers several technology tools to car dealers and OE manufacturers. The website’s vision lies in building an entire ecosystem for dealers, consumers, car manufacturers, and associated businesses.
Several years ago, owing to the Great Recession, the automotive sector was in hazardous conditions. Therefore, for several market players, it is all about their survival. Nowadays, the business environment has significantly changed. The automobile industries are full of business opportunities owing to the rising demands for cars and auto parts in developing countries and automotive design models. Moreover, several growing businesses are inclined to do web scraping to grab these market opportunities.
By scraping data from the CarDekho portal, businesses get detailed insights that help them make proper decision-making strategies.
Here, in this article, we will brie the web scraping methods for the automotive industry. We will discuss essential tools and techniques to collect enormous amounts of data.
The chances for autoportal.com web scraping are significant for businesses in the respective sector. It helps understand consumer buying trends. Specific crawling and web scraping services and software enable data retrieval from multiple platforms to generate customer-centric data and process as per the client’s specifications. This process converts enormous amounts of unstructured data into a structured form used for analyzing and storing by customized web scraping services.
Companies mostly scrape data from autoportal.com websites to obtain the resources needed to design futuristic vehicles. They scrape car parts reviews, auto manufacturer reviews, and consumer feedback to understand customers’ interests and develop the cars accordingly. In today’s era, each vehicle component can be optimized and customized per customer requirements. Data retrieved based on customer behavior and feedbacks allow businesses to improve safety, performance, and other features.
Scraping data from the autoportal.com website helps in generating powerful insights to affect various aspects of the manufacturing process. The data collected relative to consumers’ sentiment delivers feedback for car design developments. This data is predictive analyzed to enhance manufacturing simulation and make the upcoming design more valuable.
From the generation to conceptual design and after-the-market solutions, this data helps enhance the operational efficiency in vehicles’ designs, manufacturing, and maintenance.
When scraping data from the CarDekho website, automotive designers can easily find defects faster than ever. This innovative technology enhances efficiency and minimizes cost. In the design & manufacturing industries, errors are more expensive at each successive stage of production. This latest software helps detect mistakes even if the component is still in the design stage. It thereby reduces the costs.
The massive data analysis helps car owners to boost their car performance and minimize maintenance costs. Companies usually retrieve data from warranty repairs to conduct cost-performance research.
Web scraping from autoportal.com website can support the automotive industry in multiple ways:
It encompasses data collection, cleaning, and analysis stage.
The source of data is the CarDekho. The Python version used is 3.7.0.
For data collection from the CarDekho website, we are using BeautifulSoup 4v0.01. The first step is importing modules.
Every used vehicle list on an individual webpage has URLs with specific IDs. All the essential data lies within the main_left HTML section.
Now, we define the process_new() function to extract data for a single vehicle.
We will define function update() that scrapes data for listing. The purpose of this function is to find vehicles that get sold.
Now, it’s time to run the function with existing IDs
By running the following script, we will start building a local database.
Before running the update() function, we will list IDs, including Available, instead of Sold or Expired.
After the data collection process, the local database has 22,645 rows of data. After the cleaning process, we obtained
We exclude those still available for sale and those not private motors from the list.
Next, we took the number of days each vehicle took for sold.
Now, a local database creates a new column, make. The objective was to extract make from the make_model column.
Next, we create a new column segment and apply it to brands in their respective parts.
Next, we replace the rows that are empty or contain Nil.
Now export data to a .csv file for analysis.
For data analysis, first, we import the modules
Next, .csv file is read as Pandas DataFrame. The column headers are updated.
Now, we use a scatterplot to look at data plotting days to sell against depreciation.
The output is
Also, we break the main Dataframe into multiple Dataframes.
We plot various segments sequentially for a visual check.
The output chart in .gif is below.
Conclusion: We hope you have a clear idea of how to scrape data from theautoportal.com
website and gather the data effectively. Our car data scraping services can extract various information on car prices and other car-related information.
For more information, contact iWeb Data Scraping now! You can also reach us for all your web scraping service and mobile app data scraping service requirements.
