Python for Data Analysis: A Step By Step Guide to Master the Basics of Data Analysis in Python Using Pandas, Numpy And Ipython

by Andrew Park

If you want to learn more about Data Analysis or how to master it with the Python Programming Language, then keep reading.

Everyone talks about data today. You have probably come across the term "data" more times than you can remember in one day. Data as a concept is so wide. One thing that is true about data is that it can be used to tell a story. The story could be anything from explaining an event to predicting the future.

Data is the future. Businesses, governments, organizations, criminals-everyone needs data for some reason. Entities are investing in different data approaches to help them understand their current situation, and use it to prepare for the unknown. The world of technology as we know it is evolving towards an open-source platform where people share ideas freely. This is seen as the first step towards the decentralization of ideas and eliminating unnecessary monopolies. Therefore, the data, tools, and techniques used in the analysis are easily available for anyone to interpret data sets and get relevant explanations.

Many tools can be used for Data Analysis. For this reason, the ultimate choice often becomes a challenge for most people. To set you on the right path, the first step is to decide which language you want to learn, then build from there. Beginner programmers struggle with this a lot.

With Python for Data Analysis you will learn about the main steps that are needed to correctly implement Data Analysis and the procedures to help you extract the right insights from the right data. Some of the topics that we will discuss inside include:
What Data Analysis is all about and why businesses are investing in this sectorThe 5 steps of a Data Analysis
Pandas, Jupyter and PyTorchThe 7 Python libraries that make Python one of the best choices for Data AnalysisNeural NetworkHow Data Visualization and Matplotlib can help you to understand the data you are working with.Some of the main industries that are using data to improve their business with 14 real-world applicationsAnd Much More

While most books focus on how to implement advanced predictive models, this book takes the time to explain the basic concepts and all the necessary steps to correctly implement Data Analysis, including Data Visualization and providing practical examples and simple coding scripts. Don't miss the opportunity to learn more about these topics.

Even if you never used Data Analysis, learning it is easier than it looks, you just need the right guidance. This practical guide provides all the knowledge you need in a simple and practical way. Regardless of your previous experience, you will learn the steps of Data Analysis, how to implement them in Python, and the most important real-world applications.

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• Format: Paperback
• Language: English
• ISBN: 167646106X
• ISBN13: 9781676461067
• Release Date: December 2019
• Publisher: Independently Published
• Length: 152 Pages
• Weight: 0.57 lbs.
• Dimensions: 0.3" x 6.0" x 9.0"