Hands-On Data Analysis with Pandas: Efficiently perform data collection,wrangling,analysis,and visualization using Python
Authors: Stefanie Molin
ISBN-10: 1789615321
ISBN-13: 9781789615326
Publication Date 出版日期: 2019-07-26
Print Length 页数: 740 pages
Book Description
By finelybook
Get to grips with pandas-a versatile and high-performance Python library for data manipulation,analysis,and discovery
Data analysis has become a necessary skill in a variety of positions where knowing how to work with data and extract insights can generate great value for companies.
This book will show you how to analyze your data and get started with machine learning in Python using the powerful pandas library. We will extend pandas offerings with other Python libraries such as matplotlib,NumPy,and scikit-learn to perform each phase and operation of data analysis tasks. You will learn data wrangling,how to manipulate your data,clean it,visualize it,find patterns,and make predictions based on the past data using real-world examples. You will learn how to conduct data analysis,and then take our analyses a step further as we explore some applications of anomaly detection,regression,clustering,and classification.
Towards the end of the book,you will be able to use pandas to ensure the veracity of your data,visualize it for effective decision-making,and reliably reproduce analyses across multiple datasets.
What you will learn
Understand how data analysts and scientists think about gathering and understanding data
Perform data analysis and data wrangling in Python
Combine,grouping,and aggregating data from multiple sources
Create data visualizations with pandas and matplotlib
Learn how to apply machine learning algorithms to make predictions and look for patterns.
Use Python Data Science libraries to analyze real-world datasets.
Use pandas to solve several common data representation and analysis problems
contents
1 Introduction to Data Analysis
2 Working with Pandas DataFrames
3 Data Wrangling with Pandas
4 Aggregating Pandas DataFrames
5 Visualizing Data with Pandas and Matplotlib
6 Plotting with Seaborn and Customization Techniques
7 Financial Analysis – Bitcoin and the Stock Market
8 Rule-Based Anomaly Detection
9 Getting Started with Machine Learning in Python
10 Making Better Predictions – Optimizing Models
11 Machine Learning Anomaly Detection
12 The Road Ahead
