Hands-On Data Analysis with NumPy and pandas
出 版 商：Packt Publishing
出版日期：2018/06/29
About This Book
Explore the tools you need to become a data analyst
Discover practical examples to help you grasp data processing concepts
Walk through hierarchical indexing and grouping for data analysis
Who This Book Is For
Hands-On Data Analysis with NumPy and Pandas is for you if you are a Python developer and want to take your first steps into the world of data analysis. No previous experience of data analysis is required to enjoy this book.
What You Will Learn
Understand how to install and manage Anaconda
Read, sort, and map data using NumPy and pandas
Find out how to create and slice data arrays using NumPy
Discover how to subset your DataFrames using pandas
Handle missing data in a pandas DataFrame
Explore hierarchical indexing and plotting with pandas
In Detail
Python, a multi-paradigm programming language, has become the language of choice for data scientists for visualization, data analysis, and machine learning.
Hands-On Data Analysis with NumPy and Pandas starts by guiding you in setting up the right environment for data analysis with Python, along with helping you install the correct Python distribution. In addition to this, you will work with the Jupyter notebook and set up a database. Once you have covered Jupyter, you will dig deep into Pythonˇs NumPy package, a powerful extension with advanced mathematical functions. You will then move on to creating NumPy arrays and employing different array methods and functions. You will explore Pythonˇs pandas extension which will help you get to grips with data mining and learn to subset your data. Last but not the least you will grasp how to manage your datasets by sorting and ranking them.
By the end of this book, you will have learned to index and group your data for sophisticated data analysis and manipulation.
Style and approach
A step-by-step approach, taking you through the different concepts and features of Data Analysis using Python libraries and tools.
Fix everyday testing problems in Python with the help of this solution-based guide
Explore the tools you need to become a data analyst
Discover practical examples to help you grasp data processing concepts
Walk through hierarchical indexing and grouping for data analysis
Who This Book Is For
Hands-On Data Analysis with NumPy and Pandas is for you if you are a Python developer and want to take your first steps into the world of data analysis. No previous experience of data analysis is required to enjoy this book.
What You Will Learn
Understand how to install and manage Anaconda
Read, sort, and map data using NumPy and pandas
Find out how to create and slice data arrays using NumPy
Discover how to subset your DataFrames using pandas
Handle missing data in a pandas DataFrame
Explore hierarchical indexing and plotting with pandas
In Detail
Python, a multi-paradigm programming language, has become the language of choice for data scientists for visualization, data analysis, and machine learning.
Hands-On Data Analysis with NumPy and Pandas starts by guiding you in setting up the right environment for data analysis with Python, along with helping you install the correct Python distribution. In addition to this, you will work with the Jupyter notebook and set up a database. Once you have covered Jupyter, you will dig deep into Pythonˇs NumPy package, a powerful extension with advanced mathematical functions. You will then move on to creating NumPy arrays and employing different array methods and functions. You will explore Pythonˇs pandas extension which will help you get to grips with data mining and learn to subset your data. Last but not the least you will grasp how to manage your datasets by sorting and ranking them.
By the end of this book, you will have learned to index and group your data for sophisticated data analysis and manipulation.
Style and approach
A step-by-step approach, taking you through the different concepts and features of Data Analysis using Python libraries and tools.
Fix everyday testing problems in Python with the help of this solution-based guide
