Learn how to chart and track Google Trends in Data Studio using Python

Channel:
United Kingdom Colin Boyd SEO
Subscribers:
4,200
Published on ● Video Link: https://www.youtube.com/watch?v=iNmk8ICxUM8


Category:
Guide
Duration: 3:15
718 views
2

Reported today on Search Engine Land

For the full article visit: http://feeds.searchengineland.com/~r/searchengineland/~3/OQr1-0EkG7Y/learn-how-to-chart-and-track-google-trends-in-data-studio-using-python-329119

Learn how to chart and track Google Trends in Data Studio using Python

Google Trends is a free and incredibly useful tool that provides search interests, popular keywords and hot topics in a lot of languages for different platforms such as web search, Youtube or Google Shopping. Regardless of the marketing channel, it can be a very helpful tool to get valuable insights and make meaningful choices for the next steps of your project.

Basically, it gives the data on the relative popularity of a keyword from 2004 to the present, which is really cool! (Relative popularity means the ratio of your search term interest to the interests of all keywords searched on Google.)

Everything is great so far, but analyzing Google Trends data at scale is mostly not practical. Many of us don't use it much because it seems like a tedious job to search for keywords on the website and get data points one by one. So how can we use Google Trends in a more effective way?

In this article, my aim is to show you the pytrends library in Python and what benefits you can get from it in your data analysis. I will also explain the connection between Google Spreadsheets and Jupyter Notebook in order to import data into Google Data Studio to share it with others easily. For example, while analyzing Search Console data on Data Studio dashboard, wouldn't it be nice to have Google Trends data on the same page? If your answer is yes, let's dig in!

3 topics I will cover in this article:

Coding with Pytrends library and exploring its featuresConnecting Jupyter Notebook to Google Spreadsheets with gspread libraryImporting data into Google Data Studio

System requirements to use the Pytrends Library

Python 2.7+ and Python 3.3+ Requires Requests, lxml, Pa



Other Videos By Colin Boyd SEO


2020-02-13Why laptops could be facing the end of the line
2020-02-13Huawei to US: Look at your own history of spying before accusing us
2020-02-13Kirsten Gillibrand outlines new Data Protection Agency to take on Big Tech
2020-02-13Satoshi Nakaboto: ‘Pro-Bitcoin candidate Andrew Yang drops out of US presidential race’
2020-02-13What I learned about PR pitching from the reporters I keep spamming
2020-02-13Google Confirms: No Core Update via @martinibuster
2020-02-13How can I speed up a Windows 10 laptop?
2020-02-13Amazon Echo Buds review: Alexa in your ear with Bose noise reduction
2020-02-12One third of plant and animal species could be extinct in 50 years due to climate change - CNET
2020-02-12Pokemon Home launches on Switch and mobile - CNET
2020-02-12Learn how to chart and track Google Trends in Data Studio using Python
2020-02-12Project xCloud game streaming preview starts on iOS devices - CNET
2020-02-12Microsoft Wonder Bar: Apple Touch Bar gets competition in Windows 10X - CNET
2020-02-12Facebook taps Reuters to help tackle misinformation
2020-02-12Mobile World Congress 2020 has been canceled
2020-02-12The Essential Phone’s amazing track record of software updates is over
2020-02-12Mobile World Congress 2020 has been canceled over coronavirus fears
2020-02-12GSMA officially cancels MWC 2020 amid coronavirus outbreak - CNET
2020-02-12Scientists discover 'baby giant planet' cosmically close to Earth - CNET
2020-02-12BP wants to somehow eliminate its greenhouse gas emissions
2020-02-12The world’s biggest phone show has been canceled due to coronavirus concerns