Mastering Python Data Analysis

Become an expert at using Python for advanced statistical analysis of data using real-world examples About This Book Clean, format, and explore data using graphical and numerical summaries Leverage the IPython environment to efficiently analyze data with Python Packed with easy-to-follow examples to develop advanced computational skills for the analysis of complex data Who This Book Is For If you are a competent Python developer who wants to take your data analysis skills to the next level by solving complex problems, then this advanced guide is for you. Familiarity with the basics of applying Python libraries to data sets is assumed. What You Will Learn Read, sort, and map various data into Python and Pandas Recognise patterns so you can understand and explore data Use statistical models to discover patterns in data Review classical statistical inference using Python, Pandas, and SciPy Detect similarities and differences in data with clustering Clean your data to make it useful Work in Jupyter Notebook to produce publication ready figures to be included in reports In Detail Python, a multi-paradigm programming language, has become the language of choice for data scientists for data analysis, visualization, and machine learning. Ever imagined how to become an expert at effectively approaching data analysis problems, solving them, and extracting all of the available information from your data? Well, look no further, this is the book you want! Through this comprehensive guide, you will explore data and present results and conclusions from statistical analysis in a meaningful way. You’ll be able to quickly and accurately perform the hands-on sorting, reduction, and subsequent analysis, and fully appreciate how data analysis methods can support business decision-making. You’ll start off by learning about the tools available for data analysis in Python and will then explore the statistical models that are used to identify patterns in data. Gradually, you’ll move on to review statistical inference using Python, Pandas, and SciPy. After that, we’ll focus on performing regression using

成為使用Python進行高級統計分析的專家，並使用實際案例進行學習

關於本書

使用圖形和數值摘要來清理、格式化和探索數據
利用IPython環境高效地使用Python進行數據分析
提供易於理解的示例，以開發複雜數據分析的高級計算技能

本書適合對Python庫應用於數據集的基礎有一定了解的Python開發人員，希望通過解決複雜問題來提升數據分析能力的讀者。

你將學到什麼

讀取、排序和映射各種數據到Python和Pandas
識別模式以便理解和探索數據
使用統計模型發現數據中的模式
使用Python、Pandas和SciPy進行傳統統計推斷
使用聚類檢測數據中的相似性和差異性
清理數據以使其有用
在Jupyter Notebook中工作，生成可用於報告的出版級圖形

詳細內容

Python是一種多範式編程語言，已成為數據科學家在數據分析、可視化和機器學習方面的首選語言。你是否想過如何成為有效處理數據分析問題、解決問題並從數據中提取所有可用信息的專家？那麼，這本書就是你需要的！

通過這本全面的指南，你將探索數據並以有意義的方式呈現結果和結論。你將能夠快速而準確地進行實際的排序、減少和後續分析，並充分理解數據分析方法如何支持業務決策。你將首先學習Python中可用的數據分析工具，然後探索用於識別數據模式的統計模型。逐漸地，你將繼續使用Python、Pandas和SciPy進行統計推斷。之後，我們將專注於使用回歸進行分析。