Data Analysis libraries: will learn to use Pandas DataFrames, Numpy multi-dimentional arrays, and SciPy libraries to work with a various datasets. We will introduce you to pandas, an open-source ...

Python's simplicity and readability, combined with its extensive libraries, make it an ideal language for data analysis.Among these libraries, Pandas, NumPy, and Matplotlib stand out due to their ...

Data Science for Marketing Analytics: A practical guide to forming a killer marketing strategy through data analysis with Python Abstract: Turbocharge your marketing plans by making the leap from ...

Data Cleaning: In this task, you will use Python to clean a dataset and prepare it for analysis. Choose a messy dataset (e.g., missing values, inconsistent formatting) from the list of "Repositories ...

Python is an ‘equalizer’ which can help every part of a data operation to work together. Python is now the most popular language for data science, used by 15.7 million developers globally. It ...

Python offers various tools and techniques for conducting EDA, including summary statistics, data visualization, and correlation analysis. By visualizing the data using Matplotlib and other ...

Go through the different stages of analytics, from descriptive to prescriptive; Who this book is for. This book is for data analysts and data scientists working in a marketing team supporting ...

• Descriptive Analytics: This involves summarizing historical data to gain insights into past performance and trends. It forms the foundation of many financial reports and dashboards.