![]() To install pytrends use the pip command pip3 install pytrendsĪs usual it will change the various pendent libraries and will update where necessary. Some of the information is kind of interesting when you look at the related queries and also the distribution of countries. The information presented is based on what searches have been performed over the past 12 months. Here are a couple of screen shots from Google Trends, comparing Relational Database to NoSQL Database. For example, here is a quick example taken from the Google Trends website. Many of you are already familiar with using Google Trends, and if this isn’t something you have looked at before then I’d encourage you to go have a look at their website and to give it a try. The following examples show some ways you can use this library and the focus area I’ll be using is Databases. Pytrends is a library providing an API to Google Trends using Python. Less scientific are examples shown at TOPDB Top Database index and that isn’t meant to be very scientific. ![]() Yes a more rigorous scientific study is needed, and some attempts at this can be seen at. This is just a little fun to see what is possible. It isn’t very scientific or rigorous, so don’t come complaining if what is shown doesn’t match your knowledge and other insights. The examples shown below are just examples of what is possible. Exploring Database trends using Python pytrends (Google Trends)Ī little word of warning before you read the rest of this post.
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