#Google trends api install#
#Google trends api code#
#Google trends api series#
#Google trends api free#

Other less used parameters: Parameters such as grpop can also be used, which establishes a filter based on the search (news, images, etc.

We can use abbreviations like ES or even more specific areas. In the case of the example, we would extract the data of the last 12 months, but we can also use all for a complete history or specific dates.

Timeframe: We indicate the date from which we want to extract the data.

Later we will see how we can get the most out of this parameter. These categories are referenced with specific numbers.

#Google trends api series#

Cat: I think this is something really interesting, since Google Trends classifies your queries based on a series of specific or thematic categories.Words_list: It will take into account the list of words that we have associated with the previous variable.pytrends.build_payload(words_list, cat=0, timeframe='today 6-m', geo='ES') Basically, we add here what elements this tool must take into account when requesting information. The third line is made up of much more specific parameters to make the request. In the second line we establish a variable, where we can put one or more words to analyze. For example, in order to avoid SSL errors on the request. Request_args: It allows us to add other types of parameters.Backoff_factor: A delay is created between attempts.Retries: Number of attempts to connect to the server.Proxies: In case many requests are made, proxies can be used to avoid Google blocking us.Timeout: We set a timeout for the request in case there are problems with the server.As you can see in the example above, different language combinations can also be used depending on the request you make.

hl: Language we will use in Google Trends.

In this case, we only indicate the language to access Google Trends, but there are many more parameters that can be used: 1. The TrendReq() function allows us to do a first filtering of the data that we are going to request.

#Google trends api code#

pytrends.build_payload(lista_palabras, cat=0, timeframe='today 6-m', geo='ES')Īs you can see, it consists of 3 lines of code that, even if you don’t know anything about Python, you can easily understand. #We add all the parameters we want to the request (filtered)Ħ. #We establish a list variable that includes the word or words that we want to analyzeĤ. #We connect with Google Trends and pass some base parametersģ. Much of this information is available in the Pytrends documentation, but I’ll try to explain it in a simple way: 1. In order to extract data from Google Trends with Python, we need several lines of code that include the parameters that we mentioned before. These parameters help us to specify and filter our search much more. On the other hand, all of the above use certain parameters that are practically common among all of them. We will analyze later what we can do with each one and we will see the result through our notebook in Google Colab. These allow us to know almost completely what can be done with Pytrends and the data that we can obtain. In order to continue advancing and to be able to extract all the data we want from Google Trends, we must take into account what we can call API methods.īasically, these are parameters that we use to define what we want to do with the request we make and to obtain a response. When executing the previous code we will see how different packages and libraries are installed. #Importamos las librerías que vamos a utilizar

#Google trends api install#

To start with, we need to install pytrends in our Google Colab notebook and import the libraries we need. It allows us to extract data of all kinds related to the interest of users in a specific topic or query.Īs in Google’s own tool, we can extract i nformation at a global or geolocated level, in specific time periods and even based on our own categorization of queries. Pytrends is an unofficial Google Trends API for Python. If you want more information about the origin and the data it shows, you will find it here. This tool presents samples of the requested data from the year 2004 to the present day, although it began to work a few years later, in 2006.

#Google trends api free#

Google Trends is a completely free tool where you can analyze the interest of a specific word or query over a specific period of time, either globally or geolocated.

How can we use the information obtained in the data extraction with Pytrends?.

What possibilities do the categories established by Google Trends offer us?.