Google Trends is a great source for insight, but the tool can be a bit limiting. For instance, it is only possible to download daily search data three months at a time. Google Trends will give you weekly data for up to a year at a time, and after that only monthly data. Since the data is provided in an index format, we need to adjust the independent indexes. So how can we merge the quarterly time series into a yearly time series with daily data?
The three graphs show the problem of merging quarterly data directly. By using the weekly data as a benchmark we can create an accurate index with daily data.
Step 1
Download the data in 90-day increments. In this example I assume that we want a whole year worth of daily data, that means four csv files to merge.- Report (1).csv: January - March 2012
- Report (2).csv: April - June 2012
- Report (3).csv: July - September 2012
- Report (4).csv: October - December 2012
Step 2
Download the weekly data for the same year.- Report (5).csv: January - December 2012
Step 3
Merge the daily data files into one Excel spreadsheet. Leave a gap in between each quarter so you remember where the adjustment must be made.Step 4
This is where we need to adjust the indexes based on the weekly data file we downloaded. We will do this based on the weekly time series data for the whole year we also downloaded. At the start of each quarter, write the corresponding index value from the weekly data. Then calculate the percentage change between the days and add that to the new index value. Repeat for each quarter and you have created a new yearly index with daily data.
19 comments:
Do you have an example file for this?
Thanks a lot!
Hey there, I have tried following these instructions and have a challenge where the previous value is 0, since you can not divide by zero how does one avoid this problem?
I would suggest simply ignoring it. Another approach is to use the differentiated values. I did a comparison of the differentiated time series before and after reindexing, and the impact is minimal.
For those interested in getting deeper into using Google Trends, I'm building on an R-script for data collection. https://gist.github.com/321k/823cce9769e58bc14214
nice solution. but what about the 'join' in between the 90-day series? i suppose it's the price you pay!
Here's an example file that combines 90 days of daily data during 2013 for the search term "Quora".
https://www.dropbox.com/sh/8j57o6q0ioqjmnc/AADDxNMJyvugHsDxcS9hNoOHa
So this process would be interpolation of data?
Hi Erik, I need some guidance as to how it is done. Specifically, I've downloaded search data for the keyword "real estate" for 2013, and in obtaining the weekly SVI date begins from 6th Jan 2013-12 Jan 2013 rather than 1 Jan 2013. My question is....in having to enter the value of the index into the corresponding value in the first of each quarter, the values are different, i.e. does it necessarily matter?
Thanks in advance.
Hi, I made a Windows program that will do this automatically for you. You just need to manually download the csv files.
https://github.com/knguyen1/WPF.Google.Trends.Combinator
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For those of you using R, here's a working example that you can copy paste (as long as you have the libraries listed up top installed). https://github.com/321k/Google-Trends/blob/master/Daily%20data%20example.R
Ho can i manually download 90-day data (daily) from the year 2015? I tried shifting the dates but it always go automatically to 2008 to present.
PLEASE INSTRUCT ME HOW TO CONVERT WEEKLY DATA, SAY BETWEEN 2011:Q1-2016:Q2 TO QUARTERLY DATA? THAT IS, I AM LOOKING FOR A GOOGLE TREND NUMBER FOR EACH QUARTER.
Thanks!
But when using this method, I get adjusted values that are larger than 100. How can I solve this problem?
Hey,
I have some trouble following your instructions. Just to be sure, what you do is you take the weekly value for the first week of the quarter and afterwards you multiply all the daily percentage changes (relative to the first day of the week from which you got the the weekly value). That is the procedure you do for every quarter of the time period right? So you basically only use four of the weekly values per year? Also what do you do if you want daily data for more than 10 years (for which you only get monthly data). do you simply use the monthly data instead of the weekly data (so the monthly values for january, april, july, october)?
Unfortunately the example file is not accessible anymore.
Also could you explain why this is the right way to reindex?
Also related to this problem: the R code you developed which does this automatically does not work anymore because the googletrends urls changed (or at least that is what I think what happened). Do you know of any quick fix or alternative R code?
I would be very very glad if you could help me out.
Thank you very much in advance.
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