Automated Google Trends downloader.
gtrends is a python library that eases the process of downloading Google Trend data. Google Trends is a service offered by Google which allows access to aggregate query volume data for specific search terms, over specific periods of time. This volume data is represented as a fraction of the total query volume on the given day or week.
Users with Google accounts can download these data into csv files, however there are several caveats which make the data difficult to process. The data only come in daily granularity up until 3 months worth of data, after which they become weekly. Even worse, Google normalizes the data, so that the largest percent query volume in the time series is set to an integer ‘100,’ with all other values set to smaller integer values. This makes it difficult, for example, to collect several files and splice them together (such as to maintain a daily granularity via shorter time periods), since the data are on difference scales.
gtrends solves this by allowing developers to extract data with either weekly or daily granularity, on the same timescale, and most importantly, with the same over-all scale.
gtrends only contains one function, collectTrends(). It can be used by the following:
username = "myGoogleUsername" password = "myGooglePassword" terms = ["foo", "bar", "baz"] startDt = datetime.datetime(year=2015, month=1, day=1) endDt = datetime.datetime(year=2015, month=2, day=1) trends = gtrends.collectTrends(username, password, terms, startDt, endDt)
where trends is a list of lists, downloaded with data:
date,foo,bar,baz 1/1/2015,16.667,83.333,16.667 1/2/2015,16.667,83.333,16.667 1/3/2015,16.667,83.333,16.667 1/4/2015,16.667,83.333,16.667 1/5/2015,16.667,66.667,16.667 1/6/2015,16.667,66.667,16.667 1/7/2015,16.667,83.333,16.667 1/8/2015,16.667,83.333,16.667 1/9/2015,16.667,83.333,16.667 1/10/2015,16.667,83.333,16.667 ... 1/30/2015,16.667,83.333,16.667 1/31/2015,16.667,100.00,16.667
The dates are of type datetime, and the numbers are floats rounded to 3 decimal places.
With the optional argument granularity, the granularity can be changed from the default of daily, to weekly. granularity takes a string of either 'd' or 'w' corresponding to daily or weekly, respectively.
sum, is an optional argument of type boolean. With this, the data of multiple terms can be summed together into one column. Default is False.
savePath takes a string for a path to save the resultant csv. If left as the default None, no file is saved.
When the data is normalized at the end, this is done by the largest value, across all terms (if more than one). Therefore all term values are to scale between terms.
Install via pip with:
pip install gtrends
This has so far only been tested on Python 2.7.
Please create an issue in the issue tracker.
Copyright (c) 2015 Eric Salina
Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the “Software”), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions:
The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software.
THE SOFTWARE IS PROVIDED “AS IS”, WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.
Data Source: Google Correlate (http://www.google.com/trends)