Picture 1 of 1
Stock photo
Picture 1 of 1
Stock photo
Hands-On Data Analysis with Pandas : A Python Data Science Handbook for Data Collection, Wrangling, Analysis, and Visualization, 2nd Edition by Stefanie Molin (2021, Trade Paperback)
Great Book Prices Store (364203)
98.1% positive feedback
Price:
$68.67
Free shipping
Returns:
14 days returns. Buyer pays for return shipping. If you use an eBay shipping label, it will be deducted from your refund amount.
Condition:
Hands-On Data Analysis with Pandas - Second Edition: A Python data science handbook for data collection, wrangling, analysis, and visualization, ISBN 1800563450, ISBN-13 9781800563452, Brand New, Free shipping in the US
- Buy It NowHands-On Data Analysis with Pandas - Second Edition: A Python data science ha...
Oops! Looks like we're having trouble connecting to our server.
Refresh your browser window to try again.
About this product
Product Identifiers
PublisherPackt Publishing, The Limited
ISBN-101800563450
ISBN-139781800563452
eBay Product ID (ePID)22050090943
Product Key Features
Number of Pages788 Pages
LanguageEnglish
Publication NameHands-On Data Analysis with Pandas : A Python Data Science Handbook for Data Collection, Wrangling, Analysis, and Visualization, 2nd Edition
SubjectData Visualization, Data Processing, Databases / Data Mining
Publication Year2021
TypeTextbook
AuthorStefanie Molin
Subject AreaComputers
FormatTrade Paperback
Dimensions
Item Length3.6 in
Item Width3 in
Additional Product Features
Edition Number2
Intended AudienceTrade
Table Of ContentTable of Contents Introduction to Data Analysis Working with Pandas DataFrames Data Wrangling with Pandas Aggregating Pandas DataFrames Visualizing Data with Pandas and Matplotlib Plotting with Seaborn and Customization Techniques Financial Analysis - Bitcoin and the Stock Market Rule-Based Anomaly Detection Getting Started with Machine Learning in Python Making Better Predictions - Optimizing Models Machine Learning Anomaly Detection The Road Ahead
SynopsisGet to grips with pandas by working with real datasets and master data discovery, data manipulation, data preparation, and handling data for analytical tasks Key Features Perform efficient data analysis and manipulation tasks using pandas 1.x Apply pandas to different real-world domains with the help of step-by-step examples Make the most of pandas as an effective data exploration tool Book Description Extracting valuable business insights is no longer a 'nice-to-have', but an essential skill for anyone who handles data in their enterprise. Hands-On Data Analysis with Pandas is here to help beginners and those who are migrating their skills into data science get up to speed in no time. This book will show you how to analyze your data, get started with machine learning, and work effectively with the Python libraries often used for data science, such as pandas, NumPy, matplotlib, seaborn, and scikit-learn. Using real-world datasets, you will learn how to use the pandas library to perform data wrangling to reshape, clean, and aggregate your data. Then, you will learn how to conduct exploratory data analysis by calculating summary statistics and visualizing the data to find patterns. In the concluding chapters, you will explore some applications of anomaly detection, regression, clustering, and classification using scikit-learn to make predictions based on past data. This updated edition will equip you with the skills you need to use pandas 1.x to efficiently perform various data manipulation tasks, reliably reproduce analyses, and visualize your data for effective decision making - valuable knowledge that can be applied across multiple domains. What you will learn Understand how data analysts and scientists gather and analyze data Perform data analysis and data wrangling using Python Combine, group, and aggregate data from multiple sources Create data visualizations with pandas, matplotlib, and seaborn Apply machine learning algorithms to identify patterns and make predictions Use Python data science libraries to analyze real-world datasets Solve common data representation and analysis problems using pandas Build Python scripts, modules, and packages for reusable analysis code Who this book is for This book is for data science beginners, data analysts, and Python developers who want to explore each stage of data analysis and scientific computing using a wide range of datasets. Data scientists looking to implement pandas in their machine learning workflow will also find plenty of valuable know-how as they progress. You'll find it easier to follow along with this book if you have a working knowledge of the Python programming language, but a Python crash-course tutorial is provided in the code bundle for anyone who needs a refresher. Table of Contents Introduction to Data Analysis Working with Pandas DataFrames Data Wrangling with Pandas Aggregating Pandas DataFrames Visualizing Data with Pandas and Matplotlib Plotting with Seaborn and Customization Techniques Financial Analysis - Bitcoin and the Stock Market Rule-Based Anomaly Detection Getting Started with Machine Learning in Python Making Better Predictions - Optimizing Models Machine Learning Anomaly Detection The Road Ahead, Get to grips with pandas by working with real datasets and master data discovery, data manipulation, data preparation, and handling data for analytical tasks Key Features Perform efficient data analysis and manipulation tasks using pandas 1.x Apply pandas to different real-world domains with the help of step-by-step examples Make the most of pandas as an effective data exploration tool Book Description Extracting valuable business insights is no longer a 'nice-to-have', but an essential skill for anyone who handles data in their enterprise. Hands-On Data Analysis with Pandas is here to help beginners and those who are migrating their skills into data science get up to speed in no time. This book will show you how to analyze your data, get started with machine learning, and work effectively with the Python libraries often used for data science, such as pandas, NumPy, matplotlib, seaborn, and scikit-learn. Using real-world datasets, you will learn how to use the pandas library to perform data wrangling to reshape, clean, and aggregate your data. Then, you will learn how to conduct exploratory data analysis by calculating summary statistics and visualizing the data to find patterns. In the concluding chapters, you will explore some applications of anomaly detection, regression, clustering, and classification using scikit-learn to make predictions based on past data. This updated edition will equip you with the skills you need to use pandas 1.x to efficiently perform various data manipulation tasks, reliably reproduce analyses, and visualize your data for effective decision making - valuable knowledge that can be applied across multiple domains. What you will learn Understand how data analysts and scientists gather and analyze data Perform data analysis and data wrangling using Python Combine, group, and aggregate data from multiple sources Create data visualizations with pandas, matplotlib, and seaborn Apply machine learning algorithms to identify patterns and make predictions Use Python data science libraries to analyze real-world datasets Solve common data representation and analysis problems using pandas Build Python scripts, modules, and packages for reusable analysis code Who this book is for This book is for data science beginners, data analysts, and Python developers who want to explore each stage of data analysis and scientific computing using a wide range of datasets. Data scientists looking to implement pandas in their machine learning workflow will also find plenty of valuable know-how as they progress. You'll find it easier to follow along with this book if you have a working knowledge of the Python programming language, but a Python crash-course tutorial is provided in the code bundle for anyone who needs a refresher., Knowing how to work with data to extract insights generates significant value. This book will help you to develop data analysis skills using a hands-on approach and real-world data. You'll get up to speed with pandas 1.x in no time and build some software engineering skills in the process, vastly expanding your data science toolbox.
All listings for this product
Be the first to write a review
