DB Analytics Tools

Databases Analytics Tools is a Python open source micro framework for data analytics. DB Analytics Tools is built on top of Psycopg2, Pyodbc, Pandas, Matplotlib and Scikit-learn. It helps data analysts to interact with data warehouses as traditional databases clients.

Why adopt DB Analytics Tools ?

Easy to learn : It is high level API and doesn't require any special effort to learn.
Real problems solver : It is designed to solve real life problems of the Data Analyst.
All in One : Support queries, Data Integration, Analysis, Visualization and Machine Learning.

Core Components

#	Component	Description	How to import
0	db	Database Interactions (Client)	`import db_analytics_tools as db`
1	dbi	Data Integration & Data Engineering	`import db_analytics_tools.integration as dbi`
2	dba	Data Analysis	`import db_analytics_tools.analytics as dba`
3	dbviz	Data Visualization	`import db_analytics_tools.plotting as dbviz`
4	dbml	Machine Learning & MLOps	`import db_analytics_tools.learning as dbml`

Install DB Analytics Tools

Dependencies

DB Analytics Tools requires Python, Psycopg2, Pyodbc, Pandas, SQLAlchemy and Streamlit.

pip install db-analytics-tools

Get Started

Setup client

As traditional databases clients, we need to provide database server ip address and port and credentials.

# Import DB Analytics Tools
import db_analytics_tools as db

# Database Infos & Credentials
ENGINE = "postgres"
HOST = "localhost"
PORT = "5432"
DATABASE = "postgres"
USER = "postgres"
PASSWORD = "admin"

# Setup client
client = db.Client(host=HOST, port=PORT, database=DATABASE, username=USER, password=PASSWORD, engine=ENGINE)

Data Query Language

query = """
----- GET DATA -----
select *
from public.transactions
order by transaction_id;
"""

dataframe = client.read_sql(query=query)
print(dataframe.head())

   transaction_id  client_id product_name product_category  quantity  unitary_price  amount
             1        101    Product A       Category 1         5          100.0   500.0
             2        102    Product B       Category 2         3           50.0   150.0
             3        103    Product C       Category 1         2          200.0   400.0

Implement SQL based ETL

ETL API is in the integration module db_analytics_tools.integration.

# Import Integration module
import db_analytics_tools.integration as dbi

# Setup ETL
etl = dbi.ETL(client=client)

Get started with the UI

DB Analytics Tools UI is a web-based GUI. No need to code, all you need is a JSON config file.

db_tools start --config config.json --address 127.0.0.1 --port 8050

Documentation

Documentation available on https://joekakone.github.io/db-analytics-tools.

Maintainer

DB Analytics Tools is maintained by Joseph Konka. Joseph is a Data Science Professional with a focus on Python based tools.