Become a Python Data Analyst: Perform exploratory data analysis and gain insight into scientific computing using Python
By 作者: Alvaro Fuentes
ISBN-10 书号: 1789531705
ISBN-13 书号: 9781789531701
Release Finelybook 出版日期: 2018-08-31
pages 页数: (178 )
The Book Description robot was collected from Amazon and arranged by Finelybook
Python is one of the most common and popular languages preferred by leading data analysts and statisticians for working with massive datasets and complex data visualizations.
Become a Python Data Analyst introduces Python’s most essential tools and libraries necessary to work with the data analysis process, right from preparing data to performing simple statistical analyses and creating meaningful data visualizations.
In this book, we will cover Python libraries such as NumPy, pandas, matplotlib, seaborn, SciPy, and scikit-learn, and apply them in practical data analysis and statistics examples. As you make your way through the chapters, you will learn to efficiently use the Jupyter Notebook to operate and manipulate data using NumPy and the pandas library. In the concluding chapters, you will gain experience in building simple predictive models and carrying out statistical computation and analysis using rich Python tools and proven data analysis techniques.
By the end of this book, you will have hands-on experience performing data analysis with Python.
1: THE ANACONDA DISTRIBUTION AND JUPYTER NOTEBOOK
2: VECTORIZING OPERATIONS WITH NUMPY
3: PANDAS - EVERYONE'S FAVORITE DATA ANALYSIS LIBRARY
4: VISUALIZATION AND EXPLORATORY DATA ANALYSIS
5: STATISTICAL COMPUTING WITH PYTHON
6: INTRODUCTION TO PREDICTIVE ANALYTICS MODELS
What You Will Learn
Explore important Python libraries and learn to install Anaconda distribution
Understand the basics of NumPy
Produce informative and useful visualizations for analyzing data
Perform common statistical calculations
Build predictive models and understand the principles of predictive analytics
Alvaro Fuentes is a Data Scientist with more than 12 years of experience in analytical roles, he holds a M.S. in Applied Mathematics and a M.S. in Quantitative Economics. He worked for many years in the Central Bank of Guatemala as an Economic Analyst, building models for economic and financial data. He founded Quant Company to provide consulting and training services in Data Science topics and has been a consultant for many projects in fields such as: Business, Education, Psychology, Mass Media, among others. For the past 3 years he also has taught many courses (online in different platforms and in-site) to hundreds of students from around the world in topics like Data Science, Mathematics, Statistics, Machine Learning, R and Python programming.He is a big Python fan and has been using it routinely for five years for analyzing data, building models, producing reports, making predictions and build interactive applications that transform data into intelligence. Alvaro’s technical skills include Python scientific computing stack, R programming, Spark, PostgreSQL, MS Excel, machine learning, artificial intelligence applications, statistical analysis, econometrics and mathematical modeling.Bayesian Statistics is a topic in which he has both professional and teaching experience. Having solved practical problems in his consulting practice applying Bayesian methods to solve problems in both academia and industry.