![]() ![]() ![]() Though it’s not the prettiest thing in the world (though probably the prettiest colab you’ve seen), I’ve worked hard on making it utterly friendly with all of the emojis (gifs too, if I could) and hidden code (view -> Show/hide code) that just provides an output. The current code on there will provide you with 3 months Google Trends Related KWs data for the UK Furniture Industry.Ĭlearly this is just an example, but you can create a copy of it, hit Runtime -> Run all and also double click to show code to understand exactly what the code does and where to change it (spoiler alert: Don’t think too hard, all instructions are inside the colab□). ![]() Here’s my original Google Trends Analyser Colab My Google Trends Dashboard (Colab)īy slowly understanding the output of each of Ruth and Hülya’s code boxes, combined with my beginner-intermediate level in python, I slowly started to adapt it to my needs. All you have to do is go to Runtime -> run all, and you’ll be able to easily see the output from each box of code and see the code that generates it (disclaimer: I have briefly worked with Jupyter Notebooks which is the same concept but still different). It’s less scary than it sounds, and without ever working with it before, it was quite straightforward to understand with the instructions within provided by these experts. If you’re still not sure you’re ready for checking in the API itself, their articles include the code they’ve used (on Google Colab) for you to play around with by following their user-friendly instructions on your own copy, which I can guarantee I’ve tried & tested.īefore you panic, Google Colab is a way for developers to share their code with each other, a Google Docs for developers if you will. Ruth and Hülya both leveraged the power of the Google Trends API Python Library, PyTrends, and they explain how to use it from scratch so you don’t have to. A better GDS dash & Google Colab, Hülya Çoban (Twitter).Learn how to chart and track Google Trends in Data Studio using Python, Hülya Çoban (SEL).Visualising Python and Google Trends, Ruth Everett.An Introduction to Using Google Trends with Python, Ruth Everett.The wonderful Ruth Everett and Hülya Çoban have both written excellent posts and provided detailed pieces of code for you to try and experiment, as I did: The Solution (V1): Python with Google Colab (Template) Also, making existing code do what YOU want, is actually not too bad of a skill to have. Lucky for us and thanks to them, we won’t be inventing the wheel here. The most active of these Pythonistas which you should definitely be following are Charly Wargnier (founder of SEOPythonistas), JC Chouinard, Greg Bernhardt, Ruth Everett, Koray Tuğberk GÜBÜR, Daniel Heredia Mejias, Moshe Ma-yafit and “The Professor” Elias Dabbas. The SEO industry is really blessed with some of the most brilliant Python minds□□, from the Maestro that was Hamlet Batista (who I dedicate this post and every py-win to), to the brilliant SEO Pythonistas who were also inspired by Hamlet’s legacy, who keep creating amazing tools, scripts and offer tips and support for beginners. 3 (despite constantly working on improving my python skills so these skills can be considered more than “some python□), with a little bit of help from my dev friends back home (outside Twitter) along with a help, guidance and tips from the SEO Community Python thought leaders, also known as the SEO Pythonistas The SEO Pythonistas Learn SOME python, enough to be able to adapt other pieces of code from the SEO community for your specific needs. ![]() Keep calm, learn Python & do it yourself (not easy, but definitely possible).Getting a Python developer to do this for you (if you know one/can afford one).When you really want this information and the straight-forward GDS connector is not an option, a quick Google search would lead you to the understanding that the only way to get this information is by requesting this information directly from the Google Trends API, and the only way to do that is by (Python) coding. The Idea: Using the Google Trends API with Python You can download this information you get per search, but at the end of the day, you’ll probably be on this for a while exporting excels, one per keyword, joining them together, creating a visual or report. Unfortunately, there’s no Google Data Studio connector for Google Trends, so if you’re constantly on the lookout for new breaking content opportunities like me, you constantly reach this little box at the bottom of GTrends after you’ve searched for one keyword at a time per geo, per timeframe. 8 But wait… there’s more! Get my repo here The Challenge: Making the most out of the ‘Related Queries’ box on Google Trends ![]()
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