To scrape data from Google Trends, use the Google Trends API. Extract information for several search phrases provided in a Google Sheet, configure time intervals for more frequent returns, choose categories, and specify locations. Downloadable file formats include HTML, JSON, CSV, Excel, XML, and others.
Google Trends data scraper is developed to extract necessary information such as keyword, time zone, property, etc.
Keyword, start time, end time, time zone, resolution, property, category, Geo location, etc.
This Google Trends data can be used to analyze variation in categories, resolution, start time, etc.
The crawlers are 90% ready to work. With a few clicks, it becomes as easy as copying and pasting the content.
Step 1: Initiate Advance Search
Provide search queries for any search result URLs for scraping data from Google Trends
Step 2: Downloading
You can download the data in any required format such as CSV, HTML, Excel, JSON.
Step 3: Scheduling the crawler
Schedule the crawler on an hourly basis, weekly, or regularly to stay updated on Dropbox.
Google Trends data scraper allows you to search for the data that you can categorize depending on the various factors. Google Trends scraper can be used to scrape Google trends data using Python based on the requirements you mention from filtering on the Google Trends category page. It is possible to sort the filter as per the requirements and You may copy the relevant URL and put it in the Initial URL tab in the Edit PDE view after selecting the criteria for the data you require.
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