https://github.com/lin-jun-xiang/pyga4
📊Python Google Analytics 4 (GA4) Data Extraction and Analysis Toolkit
https://github.com/lin-jun-xiang/pyga4
bigquery free ga ga4 google-analytics google-analytics-python-api python
Last synced: about 1 year ago
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📊Python Google Analytics 4 (GA4) Data Extraction and Analysis Toolkit
- Host: GitHub
- URL: https://github.com/lin-jun-xiang/pyga4
- Owner: Lin-jun-xiang
- License: mit
- Created: 2023-09-15T08:56:53.000Z (over 2 years ago)
- Default Branch: main
- Last Pushed: 2023-09-22T01:10:08.000Z (over 2 years ago)
- Last Synced: 2024-04-23T23:14:35.677Z (about 2 years ago)
- Topics: bigquery, free, ga, ga4, google-analytics, google-analytics-python-api, python
- Language: Python
- Homepage: https://lin-jun-xiang.github.io/pyga4/
- Size: 2.86 MB
- Stars: 4
- Watchers: 2
- Forks: 2
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
Awesome Lists containing this project
README
[English version](README.md) | [Chinese version README.md](README.zh-TW.md)
[Documents](https://lin-jun-xiang.github.io/pyga4/) | [Pypi](https://pypi.org/project/pyga4/)
## Overview
- [Overview](#overview)
- [Introduction](#introduction)
- [How to Stream GA4 Data to Bigquery in Real-time?](#how-to-stream-ga4-data-to-bigquery-in-real-time)
- [Features](#features)
- [How to Use?](#how-to-use)
- [Download the Package](#download-the-package)
- [Connect to Your Bigquery](#connect-to-your-bigquery)
- [Connect to GA4 Tables](#connect-to-ga4-tables)
- [Evaluate Query Cost with dry run](#evaluate-query-cost-with-dry-run)
- [Analyze User Properties](#analyze-user-properties)
- [Analyze Device Properties](#analyze-device-properties)
- [Analyze Events](#analyze-events)
---
## Introduction
* `pyGA4` is a Python toolkit designed for **extracting, processing, and analyzing** data from **Google Analytics 4 (GA4)**.
* Whether you're a digital marketing professional, a data analyst, or anyone interested in gaining insights from GA4 data, this package simplifies the process of working with your GA4 data.
## How to Stream GA4 Data to Bigquery in Real-time?
First, we assume that everyone has already integrated GA4 data into their respective platform websites (there are many online tutorials).
Next, we will use a free third-party service to stream data into Bigquery. For detailed instructions, please refer to the [official documentation](https://support.google.com/analytics/answer/9823238?hl=en#zippy=%2Cin-this-article).
If successful, you will see tables in Bigquery similar to the following (`analytics_xxxx`), [ref](https://analyticscanvas.com/knowledge-base/ga4-bigquery-export-tutorial-002-querying-event-params/):
## Features
- **Query Cost Estimation**: Provides the Bigquery `dry run` feature to estimate query cost before execution.
- **Data Extraction**: Easily connect to your GA4 property, retrieve data, and save it for analysis.
- **Data Preprocessing**: Prepare and clean your GA4 data for analysis with built-in data preprocessing functions.
- **Custom Queries**: Execute custom queries to filter and aggregate data based on your specific needs.
- **Data Analysis**: Perform various types of analysis, including user behavior analysis, conversion tracking, and more.
- **Data Visualization**: Create informative visualizations and reports to communicate your findings effectively.
- **Simple Integration**: Seamlessly integrate `pyGA4` into your data pipeline or analytics workflow.
## How to Use?
For more features, please refer to the [package documentation](https://lin-jun-xiang.github.io/pyga4/).
### Download the Package
```
pip install pyga4
```
### Connect to Your Bigquery
```python
from google.cloud import bigquery
client = bigquery.Client()
# Or you can use:
# client = bigquery.Client.from_service_account_json(
# './private/service-project-data-dev-01d11c742ba1.json'
# )
```
### Connect to GA4 Tables
```python
from pyga4.model import Ga4Table
# Use your project_id, dataset_name (analytics_xxxx)
ga4_table = Ga4Table(client, PROJECT_ID, DATASET_NAME)
# Show the tables list in dataset, e.g., analytics_date1, analytics_date2
table_id_list = ga4_table all_tables_list
print(table_id_list)
# Select the table you want to analyze
ga4_table.table_id = 'events_intraday_20200812'
```
### Evaluate Query Cost with dry run
```python
# Query with dry run:
ga4_table.query_config.dry_run = True
query = f"""
SELECT event_timestamp FROM `..`
"""
results = ga4_table.query(query) # return None, but you can see the query usage!
```
### Analyze User Properties
**Query User ID and Country List**
```python
# User attribute
user_id_list = ga4_table.user_id_list
user_country_list = ga4_table.geo_country_list
```
**Query User ID and Country Distribution**
```python
from pyga4.analytic import UserAnalytic
# UserAnalytic
user_analytic = UserAnalytic(ga4_table)
countries_dist = user_analytic.countries_distribution
userid_dist = user_analytic.user_id_distribution
```
### Analyze Device Properties
```python
# DeviceAnalytic
device_analytic = DeviceAnalytic(ga4_table)
mobile_brand_dist = device_analytic.mobile_brand_distribution
```
### Analyze Events
```python
# EventAnalytic
event_analytic = EventAnalytic(ga4_table)
page_loc_dist = event_analytic.pages_distribution
```