Pandas

Putting Pareto’s Principle to work on the Pandas library — Mastering an entire Python library like Pandas can be challenging for anyone. However, if we take a step back and think, do we really need to be aware of every minute detail of a specific library, especially when we live in a world governed by Pareto’s Principle? For those who…

Label Encoding feature engineering techniques from Pandas to BigQuery. — This article is a section of the article ML Feature Engineering: from Pandas to SQL (BigQuery). Label Encoding With Python, the simplest way to achieve label encoding, it is either to use Pandas category codes, or to use scikit-learn LabelEncoder class.

1. Mito — 1. Mito Mito is a spreadsheet front-end for Python. You can call Mito into your Jupyter Notebook and each edit you make in the front-end will generate the equivalent Python. Here is a video demo: To install Mito, use these commands: python -m pip install mitoinstaller python -m mitoinstaller install Then…

In this article we will talk about the new GPU-based APIs applied in the ETL framework to speed-up the preprocessing time in a data… — In this article we will talk about the new GPU-based APIs applied in the ETL framework to speed-up the preprocessing time in a data pipeline. In a world where data quantity is constantly increasing and all companies are basing their financial and operational decisions on data analysis there is a…

Pandas is a software library written specifically for the Python programming language for data manipulation and analysis. With Pandas, we… — Pandas is a software library written specifically for the Python programming language for data manipulation and analysis. With Pandas, we have a different range of methods to manipulate our data; this includes merging Dataframes, joining and concatenating. We’ll look at each of these different methods and how we can apply…

Time Resampling feature engineering techniques from Pandas to BigQuery. — This article is a section of the article ML Feature Engineering: from Pandas to SQL (BigQuery). Time Resampling When working with time series, resampling time on a regular step is common: it allows data to be aligned for shifting rows usage, doing consistent aggregation operations, graphics, and so on. With Pandas, it…

He explains clearly, how to start earning with LH-Crypto from the scratch — He explains clearly, how to start earning with LH-Crypto from the scratch Big news today: LH-Crypto is growing. Welcome the new member of our friendly crypto-family — Red Pandaу! This charming little animal just arrived from far away, as you can judge by his pilot hat, but he let…

Rolling Windows feature engineering techniques from Pandas to BigQuery. — This article is a section of the article ML Feature Engineering: from Pandas to SQL (BigQuery). Rolling windows Rolling Windows without time Feature engineering involves statistics in lot of cases, and rolling aggregations are one of them. A common operation is to build rolling windows over time series, and Pandas has dedicated methods to do so…