Python Data Cleaning and Preparation Best Practices A Practical Guide in Python for Organizing and Handling Data from Various Sources and Formats

Take your data preparation skills to the next level by converting any type of data asset into a structured, properly formatted, and readily usable dataset

Key Features

• Maximize the value of your data with effective data-cleaning methods
• Transform your data skills with strategies for handling structured and unstructured data
• Learn to elevate the quality of your data products by testing and validating your data pipelines

Book Description

Data professionals face several challenges in effectively leveraging data in today's data-driven world. One of the main challenges is the low quality of data products, caused by data that is inaccurate, incomplete, or inconsistent. Another significant challenge is the lack of skills among data professionals to analyze unstructured data, missing valuable insights that are difficult or impossible to obtain from structured data alone. To tackle these challenges, you will go on a journey to the upstream data pipeline, which includes the ingestion of data from various sources, validation and profiling of the data for high-quality end tables, and writing the data to different sinks. Subsequently, you will acquire knowledge on handling structured data by performing essential tasks like cleaning and encoding datasets and handling missing values and outliers. The journey concludes by demystifying the manipulation of unstructured data with simple techniques that unlock their potential. You will be introduced to a variety of natural language processing techniques, from tokenization to vector models, as well as techniques for structuring images, videos, and audio. By the end of the book, you will have achieved mastery of the techniques of data cleaning and preparation for both structured and unstructured data.

What you will learn

• Ingest data from different sources and write them to required sinks
• Profile and validate data pipelines for better quality control
• Master grouping, merging, and joining structured data
• Handle missing values and outliers in structured datasets
• Implement techniques to manipulate and transform time series data
• Apply structure to text, image, voice and other unstructured data

Who this book is for

Whether you're a Data Analyst, Data Engineer, Data Scientist, or any data professional who relishes the task of data preparation and cleaning, this book is for you. It's an ideal resource for upskilling in data cleaning concepts and expanding your knowledge across all types of data, from tabular to audio and video. Working knowledge of Python programming is needed to get the most out of the book]]>