Pull and merge data from the Google Trends for Health API

This code has no license. Theodore L Caputi (Copyright 2020) retains all rights over all code in this package. Unauthorized use, including reuse, modification, and distribution, is forbidden.

Functionality

The main function of the package is theo_timeline, a function that pulls and merges data from the Google Trends API and saves a single CSV file for each term (dates on the index and geographies as the columns). Note that multiple files will be created if multiple timeframes are requested. An example script would be:

from gtrends import timeline

timeline.theo_timeline(
    terms = ['cat', 'cat + food'],
    names = ['cat', 'food'],
    start = '2018-01-01',
    end = '2020-02-01',
    timeframe_list = ['month'],
    geo_country_list = ['US', 'CA'],
    worldwide = False,
    timestep_years = 1,
    batch_size = 2,
    us_states = False,
    outpath = "/path/to/output/directory",
    creds = "/path/to/info.py"
)

This script would pull monthly data for the search terms cat and cat + food for both the US and Canada between 1 Jan 2018 and 1 Feb 2020, and then reformat that data into two CSV files (cat_month.csv and food_month.csv, respectively). Each of these CSV files would be formatted such that the first column (timestamp) gives the month and the second and third columns (US and CA) give search queries for the US and Canada, respectively.

Getting Started

Note: This package assumes use of Python 3.X and pip3. It works on Linux and Windows OS.

(1) Request tarball (gtrends.tar.gz) from tcaputi@gmail.com

(2) Run the command:

pip install --upgrade /path/to/gtrends.tar.gz

(3) Install dependencies using the command:

pip install -r /path/to/gtrends/requirements.txt

(4) Create a creds file setting your own parameters (DISCOVERY_URL, API_KEY)

(5) Begin using the package! The merged output will be in the directory you named as outpath.