gtus 0.1.1

A Python package to collect and analyze Google Trends data for US states.

GTUS - Google Trends for US States

The GTUS package is a Python library designed to collect Google Trends data for specified queries across various U.S. states. It provides functionality to handle multiple queries and states efficiently, while adhering to Google Trends API limitations.

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Features

• Collect trends for one or multiple states.
• Batch processing of queries to avoid API limits.
• Adjustable wait time between requests to manage rate limits.
• Export collected data to Excel and JSON formats.
• Access data in a nested dictionary format for easy manipulation in Python.

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Installation

To use the GTUS package, ensure you have the required dependencies installed. You can install them using pip:

pip install gtus

This will automatically install all required dependencies, including pytrends, pandas, and aiohttp.

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Getting Started

Here's how to start using gtus to collect Google Trends data.

Usage Examples

Importing the Package

To use the GTUS package, import it as follows:

from gtus import GTUS

1. Collect Google Trends Data for US States

Collecting for One State

To collect data for a single state, create an instance of the GTUS class with the desired query and state:

from gtus import GTUS
queries = ["telemedicine", "remote work"]
states = ["TX"]
gtus = GTUS(queries, states, timeframe="2022-01-01 2023-01-01")

# Collect data
gtus.collect_all_trends()

Collecting for Multiple States

To collect data for multiple states, simply provide a list of states:

from gtus import GTUS
queries = ["telemedicine", "remote", "football","dance"]
states = ["CA", "NY", "TX"]
gtus = GTUS(queries, states, timeframe="2020-01-01 
2023-01-01")

# Collect data
gtus.collect_all_trends()

Modifying Wait Time

You can adjust the wait time between requests by specifying the wait_time parameter when creating the GTUS instance. This is useful for managing API rate limits:

gtus = GTUS(queries, states, wait_time=15) # Set wait time to 15 seconds

Collecting for All States

If no states are specified, GTUS will automatically collect data for all US states:

queries = ["remote work", "telehealth"]

# Initialize GTUS object
gtus = GTUS(queries=queries, timeframe="2022-01-01 2023-01-01", wait_time=15)

It is strongly recommended to set the wait_time parameter, especially when collecting data for all states or handling a large number of queries. Failing to do so may result in data being collected for only a subset of queries or certain states due to Google's API rate limits.

Saving Data

Exporting to Excel

To save the collected data to an Excel file, use the export_to_excel method:

gtus.export_to_excel("google_trends_data.xlsx")

Exporting to JSON

To save the collected data to a JSON file, use the export_to_json method:

gtus.export_to_json("google_trends_data.json")

Accessing Data in Python

The data collected can be accessed in a nested dictionary format. After exporting to JSON, you can load the data and access it as follows:

import json
#Load the JSON data
with open("google_trends_data.json") as f:
data = json.load(f)
#Accessing data
print(data["CA"]["telemedicine"]) # Get telemedicine data for California

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Dependencies

• pandas
• pytrends
• aiohttp

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Contributing

Contributions are welcome! Please submit issues or pull requests via GitHub.

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License

This project is licensed under the MIT License. See the LICENSE file for more information.

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Start exploring Google Trends data with GTUS today!