What is this book about? The book will take you on a journey through the evolution of data analysis explaining each step in the process in a very simple and easy to understand manner. You will learn ...

Originally developed for data science applications written in Python, R, and Julia, Jupyter Notebook is useful in all kinds of ways for all kinds of projects: The most common use cases for Jupyter ...

Filtering out records with invalid publishing years. Handling missing values by dropping rows with missing book names and checking for duplicate entries. Exploring unique values in each column to ...

using basic features, and performing data analysis interactively. Anaconda is a popular Python distribution that comes with Jupyter Notebook pre-installed. Download and install Anaconda Open Anaconda ...

It supports a variety of languages, with Python being the most ... and evaluation. Jupyter Notebooks are ideal for performing exploratory data analysis (EDA). You can load data into Pandas DataFrames ...

The core of R was developed during the 1970s and since then, many libraries (such as the Tidyverse for data manipulation ... Similarly, writing Python is much easier using an interactive notebook tool ...

Jupyter notebooks can handle multiple programming languages, but we will be focusing on Python 3 ... of how to use Jupyter Notebooks by yourself and set us up for the next section, which steps through ...