![]() ![]() Google may change aggregation level for items with very large or very small search volume. ![]() This is not an official or supported API.Can be images, news, youtube or froogle (for Google Shopping results).For example: 'now 1-H' would get data from the last hour.Hourly: 'now #-H' where # is the number of hours from that date to pull data for For example: 'now 7-d' would get data from the last week.For example: 'today 3-m' would get data from today to 3months agoĭaily: 'now #-d' where # is the number of days from that date to pull data for.Specific datetimes, 'YYYY-MM-DDTHH YYYY-MM-DDTHH' example 'T10 T07'īy Month: 'today #-m' where # is the number of months from that date to pull data for Specific dates, 'YYYY-MM-DD YYYY-MM-DD' example ' ' For more information of Timezone Offset, view this wiki page containing about UCT offset.Can also be a list of up to five regions.More detail available for States/Provinces by specifying additional abbreviations.The category starts after cat= and ends before the next & or view this wiki page containing all available categories Find available categories by inspecting the url when manually using Google Trends.You can also use pytrends.suggestions() to automate this."/m/025rw19" is the topic "Iron Chemical Element" to use this with pytrends.Find the encoded topic by using the get_suggestions() function and choose the most relevant one for you.For example "iron" will have a drop down of "Iron Chemical Element, Iron Cross, Iron Man, etc".When using Google Trends dashboard Google may provide suggested narrowed search terms.Suggestions: returns a list of additional suggested keywords that can be used to refine a trend search. Top Charts: returns the data for a given topic shown in Google Trends' Top Charts section. Trending Searches: returns data for latest trending searches shown on Google Trends' Trending Searches section. Related Queries: returns data for the related keywords to a provided keyword shown on Google Trends' Related Queries section. Related Topics: returns data for the related keywords to a provided keyword shown on Google Trends' Related Topics section. Interest by Region: returns data for where the keyword is most searched as shown on Google Trends' Interest by Region section. ![]() ![]() It seems like this would be the only way to get historical, hourly data. It sends multiple requests to Google, each retrieving one week of hourly data. Historical Hourly Interest: returns historical, indexed, hourly data for when the keyword was searched most as shown on Google Trends' Interest Over Time section. Multirange Interest Over Time: returns historical, indexed data similar to interest over time, but across multiple time date ranges. Interest Over Time: returns historical, indexed data for when the keyword was searched most as shown on Google Trends' Interest Over Time section. Pytrends.build_payload(kw_list, cat=0, timeframe='today 5-y', geo='', gprop='') Note: only https proxies will work, and you need to add the port number after the proxy ip address Build Payload Note: the parameter hl specifies host language for accessing Google Trends.
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