Python

Data Engineering Bootcamp 2024 (Week 2) Mage & GCP ETL orchestation

Is Mage a realistic alternative to Airflow? Discover Mage AI for data ETLs, the next gen data engineering tool for streaming pipelines and notebook like pipelines

Data Engineering Bootcamp 2024 (Week 1) Docker & Terraform

Learn the basics of Docker and Terraform from scratch to enhance your Data Engineering projects. Containerize your data pipelines and manage your infrastructure as code.

Plot your GIS data with GeoPandas and Plotnine. A single glance insightful visualization

Learn how to use GeoPandas and Plotnine to create high impact and insightful visualization with Python.

Python protocols. When to use them in your projects to abstract and decoupling

What are Python Protocols and when to use them to complement or sustitute abstract classes and MixIns.

Boosting Python development speed with Ruff: An all-in-one lightning fast linter

Discover how you can 10x to 100x improve your linter and pre-commit checks by adding Ruff module and rules to your project.

Measure FWHM from image with Python

How to Measure Full Width at Half Maximum (FWHM) from an Image in Python: A Step-by-Step Guide.

Add new not nullable column while working with SQLModel and Alembic migrations.

Enhance your database skills: Learn how to add a not nullable column using SQLModel and Alembic Migrations.

Shadowing your Plotnine lines in Python. Forecasting confidence interval geom_ribbon.

Plot your confidence intervals easily

Pydantic parse objects with parse_obj and parse_obj_as methods

Effortless Data Parsing: Deep dive into Pydantic's parse_obj and parse_obj_as methods.

Polars: Filter rows and columns based on percentage of NAs / nulls

Optimizing Data Cleanup: Filtering Rows by Null Percentage in Python Polars. Manage NAs with precision.

Mastering Python Polars json manipulation. Do it in an easy and robust way!

Unlock the Full Potential of Polars for Seamless JSON Data Handling.

Sort in Python Polars. Arrange your DataFrames and Series

Efficient Data Arrangement: Learn to Sort DataFrames and Series Seamlessly with Python Polars.

How to upper strip in Python

Strip uppercases in Python strings. Elevate Your Python Basics: A Beginner's tip with strip() and string.ascii_uppercase.

Fix the error: cannot import name 'MultiHostDsn' from 'pydantic.networks'

The error message 'cannot import name multihostdsn from pydantic.networks' is caused for the new Pydantic v2 conflicting with the Pydantic v1. Fix it by reading this post!

Efficient Column Selection in Polars: Utilizing Polars Selectors for Python DataFrame Manipulation

Mastering Column Selection in Python. Polars Selectors for Efficient DataFrame Handling.

Polars new feature. Suggest more efficient Polars method for apply lambda functions

Using apply with lambda functions is less performant than the native Polars API functions. Now, you are warned about it and are presented with a more efficient alternative.

Select datetime columns matching time zones with Python Polars selectors. Calculate offset with the new dst_offset.

Unlocking the Power of Python Polars: A Comprehensive Guide to Selecting and Manipulating Datetime Columns with Selectors and dst_offset.

How to create a Streamlit datetime slider.

Creating an interactive datetime Slider with Python Streamlit. As easy as pie

New Streamlit Chat. Conversational app with st.chat_message and st.chat_input

Revolutionize Conversational App Development: A Guide to Building Chat-based Applications with Streamlit and GPT.

Pydantic discriminated unions. Some examples to simplify data structures and ensure type safety

Powerful type validation and discriminated Unions with Pydantic: Simplify data structures and ensure type safety. We are showcasing a few straightforward examples.