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Perfect
Perfect for what I needed
Great book
This is a fun book for beginners and experienced data scientists.
Good for all levels
I read Murach’s Python for Data Analysis because I work with database administration and data analysis. I am trying to learn more about using about tools to perform the analysis and Python is being used many shops. I had previously used Spyder as a Python IDE, but was not aware of using Juypter Lab as an IDE. Section 2 was entitled âThe critical skills for success on the jobâ and had chapters on obtaining data, cleaning it, preparing it and then analyzing the data. There was information in the chapters that was good for all levels of professionals from beginners to intermediate levels. The explanations of working with Data Frames and JSON data was very helpful. Cleaning data is one of the trickiest parts of data science and there is a chapter on that subject that covers many different data issues including missing data and invalid values. In the analysis sections of the book, you will see how to use regular Python code. You will also get a good introduction to using Pandas, Scikit-Learn and Seaborn libraries. I have worked with linear regression in R and was interested to see how to do the analysis with Python. Chapter 10 dives into this subject and gives thorough coverage of it. Chapter 11 works with multiple regression models which is a fairly advanced and useful technique. Section 4 contains four different cases studies, one per chapter. Each case study is very thorough and gives the readers a lot of details and shows how Python is used in the cases.There are appendices of the book for Windows and MacOS that show how to set up an Anaconda environment so you can work with Python including the Spyder and Juypter âtoolsâ.
Comprehensive Data Analysis
Iâve been looking for a book like Murachâs Python for Data Analysis for a long time, and I was delighted to find that one had been recently published. What sets the book apart from other books that Iâve found on data analysis with Python is that Python for Data Analysis covers all aspects of the process. Itâs a thorough book on how to download data from websites into python and how to visualize the data in a tabular display or graphical using typical add-on libraries such a Panda and Seaborn. Unlike some other books on data analysis with Python, the explanations of how to perform data analysis are thorough rather than terse or with no explanations.The book also shows the use of the Python development interface Juypter Notebooks, which allows you to execute Python statements individually without the use of a debugger, so itâs a simple way to work through the examples one at a time. You can download all of the examples in the book from the publisherâs website along with additional exercises and solutions.Lastly, there are several case studies so you can practice a complete project and compare to the case study solutions that are also provided.
Great
Gentle introduction if you already know another language (eg sql, R). Clear explanations, color diagrams, good content.
Love this book.