Hands-On Exploratory Data Analysis with Python
Data is a collection of discrete objects, events, and facts in the form of numbers, text,
pictures, videos, objects, audio, and other entities. Processing data provides a great deal
of information. But the million-dollar question is—how do we get meaningful information
from data? The answer to this question is Exploratory Data Analysis (EDA), which is the
process of investigating datasets, elucidating subjects, and visualizing outcomes. EDA is an
approach to data analysis that applies a variety of techniques to maximize specific insights
into a dataset, reveal an underlying structure, extract significant variables, detect outliers
and anomalies, test assumptions, develop models, and determine best parameters for
future estimations.
This book, Hands-On Exploratory Data Analysis with Python, aims to
provide practical knowledge about the main pillars of EDA, including data cleansing, data
preparation, data exploration, and data visualization. Why visualization? Well, several
research studies have shown that portraying data in graphical form makes complex
statistical data analyses and business intelligence more marketable.