![]() If you don’t have those, just pip install them as well. Note: when we check the documentation for PyTrends, it says that it requires Requests, LXML, and Pandas. Your development environment should be ready to go now! Just go to your terminal and type sudo -H python -m ensurepip. If you don’t have pip installed in your machine, Python is now able to install it without any extra tool. The next step is to install PyTrends using pip install pytrends. You’ll be able to verify the installation with python3 -version command. ![]() With Homebrew package manager installed, you can now install the last version of Python by using the command brew install python3. To check if that’s the case, enter python -v into your terminal.įor those of you who don’t have any version of python installed or want to upgrade, we recommend using Homebrew, instructions are inside the link. If you’re using Mac, you probably already have a version of Python installed on your machine. Now that we know the basics, let’s start writing our PyTrends Script: 1. How to Build a Google Trends Scraper with PyTrends So we’ll have to account for those factors in our scraper. 100 represents the highest point and 0 represents the lack of data.ĭoesn’t seem so stable now, does it? As we can see, after getting into the market, fidget spinners exploded in popularity and then rapidly decreased in popularity.īesides timeframe, region, categories and platform will influence the trends data, so make sure to understand what you’re looking for before doing any analysis. We have to remember that the graph is showing us data based on the highest point over 12 months. Instead, it shows these trends in a graph that’s scaled based on the highest peak of interest over the time period we specify.Īs an example, let’s look for ‘fidget spinner’ in the US:Īccording to the graph, the interest in fidget spinners has been constant and quite high, right? Well… that’s when it gets tricky. It does not show any search volume for the keywords. Google Trends is a tool that represents, well, trends. With that said, there are a few things to understand about Google Trends before actually writing our code. Instead, we can easily automate the reports for a list of keywords in a few seconds or minutes using PyTrends, and because PyTrends is a Python API, using the tool is effortless to use. This is a good method until you have a list of hundreds of keywords.Ĭhecking each one by hand will result in a lot of wasted time. You can enter each keyword one by one and track different timeframes. So why would you complicate the process by building a script? Well, like most things in web scraping, it comes down to time and scalability. It has all the features you’ll need to run your analysis and it has a clear interface. There’s no problem with using Google Trends’ website as it is. Why Using PyTrends Instead of Google Trends Interface? To get more out of the tool, today we’ll build a simple Google Trends scraper using PyTrends, an unofficial Google Trends API. Google Trends data is adjusted, so the term may be used in that region, but it’s more popular in other regions.With more than 40.000 searches happening in Google per second, Google Trends is a powerful tool that allows us to visualize searching behavior and uncover trends in Web Search, Google News, Google Images, Google Shopping, and YouTube.Ī sample of that size can provide a lot of insights to inform a business marketing strategy, which products or services to focus on, identify interests based on location, and much more. If a region on the map isn’t highlighted, it doesn’t mean there's no interest. In the Regional interest section, click the United States on the map.Currently, Google Trends only provides metros for some countries. Metros are geographical areas that generally correspond to metropolitan areas. To the right of the map, you also see a list of regions or cities ranked according to the term’s popularity. Hover over a region to get more details on search volume in a region. Search term popularity is relative to the total number of Google searches performed at a specific time, in a specific location. ![]() The color intensity represents the percentage of searches for the leading search term in a particular region. If you compare search terms, you see a map of the world shaded according to the term’s popularity. Darker shades indicate where your term has a higher probability of being searched. When you search for a term in Google Trends, you see a map showing areas where your term is popular.
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