google-trends

问题 Google Trends Explore returns relative values of rising topics. As well as top queries in each category. They are not very telling because +2,400% may occur in the trends rising from 10 to 240 queries, while more important trends are missing, like those that rose from 100K to 200K queries. This could be a great tool for research, but how to extract (recalculate, etc.) absolute numbers of queries for these items from Google Trends? It is not in its basic interface; only if find some

问题 just wondering if there is a script to import data from google trends into a google sheet. Basically, I would like to trigger such script daily to know the rising trends for a given topic and I am not sure if there is such solution available. Else, is there any solution to perform this task? Many thanks! 回答1: You may refer with this sample code snippet on how to use Google Apps Script for querying Google trends. For example, this function read input from the spreadsheet and sanitize it, then

问题 just wondering if there is a script to import data from google trends into a google sheet. Basically, I would like to trigger such script daily to know the rising trends for a given topic and I am not sure if there is such solution available. Else, is there any solution to perform this task? Many thanks! 回答1: You may refer with this sample code snippet on how to use Google Apps Script for querying Google trends. For example, this function read input from the spreadsheet and sanitize it, then

问题 I am using pytrends library to extract google trends and i am getting the following error: Addition/subtraction of integers and integer-arrays with Timestamp is no longer supported. Instead of adding/subtracting n , use n * obj.freq timeframes = [] datelist = pd.date_range('2004-01-01', '2018-01-01', freq="AS") date = datelist[0] while date <= datelist[len(datelist)-1]: start_date = date.strftime("%Y-%m-%d") end_date = (date+4).strftime("%Y-%m-%d") timeframes.append(start_date+' '+end_date)

来源： https://stackoverflow.com/questions/49732639/pytrends-google-trends-daily-freq

来源： https://stackoverflow.com/questions/49732639/pytrends-google-trends-daily-freq

问题 I use pytrends to automatically download data in csv from google trend. The code i used is below. In this case, i am downloading a monthly google trend data from 2008 to present. from pytrends.request import TrendReq from urllib.parse import unquote from dateutil.relativedelta import relativedelta import datetime import pytrends google_username = "xxxxx@gmail.com" google_password = "xxxxx" search_term = unquote('%2Fm%2F07gyp7') google_trend = TrendReq(google_username, google_password, custom

问题 I use pytrends to automatically download data in csv from google trend. The code i used is below. In this case, i am downloading a monthly google trend data from 2008 to present. from pytrends.request import TrendReq from urllib.parse import unquote from dateutil.relativedelta import relativedelta import datetime import pytrends google_username = "xxxxx@gmail.com" google_password = "xxxxx" search_term = unquote('%2Fm%2F07gyp7') google_trend = TrendReq(google_username, google_password, custom

问题 I have been working with Google Trends recently using Python's pytrends. And I have been experiencing the following error during random requests: Response did not parse. See server response for details. Sorry, our systems are a little stressed out right now and need to take a deep breath. Please try again in a few moments. Upon searching I discovered that this was related to the Google Trends Quota limits. For example, this discusses about the mentioned issue. But in my case, I have been

问题 I have downloaded a CSV file from Google Trends which presents data in this format: Top cities for golden globes City,golden globes New York (United States),100 Los Angeles (United States),91 Toronto (Canada),69 Top regions for golden globes Region,golden globes United States,100 Canada,91 Ireland,72 Australia,72 There are 3-4 of these groups separated by whitespace. The first line of each group contains text I want to use as a key, followed by a list of dictionaries I need associated with