Mastering pandas: A complete guide to pandas,from installation to advanced data analysis techniques,2nd Edition
Authors: Ashish Kumar
ISBN-10: 1789343232
ISBN-13: 9781789343236
Publication Date 出版日期: 2019-10-25
Print Length 页数: 674 pages
Book Description
By finelybook
Perform advanced data manipulation tasks using pandas and become an expert data analyst.
pandas is a popular Python library used by data scientists and analysts worldwide to manipulate and analyze their data. This book presents useful data manipulation techniques in pandas to perform complex data analysis in various domains.
An update to our highly successful previous edition with new features,examples,updated code,and more,this book is an in-depth guide to get the most out of pandas for data analysis. Designed for both intermediate users as well as seasoned practitioners,you will learn advanced data manipulation techniques,such as multi-indexing,modifying data structures,and sampling your data,which allow for powerful analysis and help you gain accurate insights from it. With the help of this book,you will apply pandas to different domains,such as Bayesian statistics,predictive analytics,and time series analysis using an example-based approach. And not just that; you will also learn how to prepare powerful,interactive business reports in pandas using the Jupyter notebook.
By the end of this book,you will learn how to perform efficient data analysis using pandas on complex data,and become an expert data analyst or data scientist in the process.
What you will learn
Speed up your data analysis by importing data into pandas
Keep relevant data points by selecting subsets of your data
Create a high-quality dataset by cleaning data and fixing missing values
Compute actionable analytics with grouping and aggregation in pandas
Master time series data analysis in pandas
Make powerful reports in pandas using Jupyter notebooks
contents
1 Introduction to pandas and Data Analysis
2 Installation of pandas and Supporting Software
3 Using NumPy and Data Structures with pandas
4 I/Os of Different Data Formats with pandas
5 Indexing and Selecting in pandas
6 Grouping,Merging,and Reshaping Data in pandas
7 Special Data Operations in pandas
8 Time Series and Plotting Using Matplotlib
9 Making Powerful Reports In Jupyter Using pandas
10 A Tour of Statistics with pandas and NumPy
11 A Brief Tour of Bayesian Statistics and Maximum Likelihood Estimates
12 Data Case Studies Using pandas
13 The pandas Library Architecture
14 pandas Compared with Other Tools
15 A Brief Tour of Machine Learning
