We've seen some basic tasks done with pandas series and DataFrames. Let's move on to more interesting applications. In this chapter, we'll revisit some topics discussed previously, regarding applying functions in arithmetic to a multivariate object and handling missing data in pandas.
-
Book Overview & Buying
-
Table Of Contents
-
Feedback & Rating
Hands-On Data Analysis with NumPy and pandas
By :
Hands-On Data Analysis with NumPy and pandas
By:
Overview of this book
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 Python’s 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 Python’s 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.
Table of Contents (8 chapters)
Preface
Free Chapter
Setting Up a Python Data Analysis Environment
Diving into NumPY
Operations on NumPy Arrays
pandas are Fun! What is pandas?
Arithmetic, Function Application, and Mapping with pandas
Managing, Indexing, and Plotting
Other Books You May Enjoy
Customer Reviews
