Python Data Science Handbook

The generation and use of data in society has seen exponential growth in recent years. The emergent field of data science, concerned with understanding and analyzing this data, can be applied to appli

This text provides a comprehensive and concise description of the basic concepts of Complex Network theory. It focuses on the scientific opportunities provided by the appearance of big-data and descri

Go from messy, unstructured artifacts stored in SQL and NoSQL databases to a neat, well-organized dataset with this quick reference for the busy data scientist. Understand text mining, machine learnin

Data Science has become one of the hottest fields in technology. Firms worldwide are scrambling to find developers with data science skills to work on projects ranging from social media marketing to m

This book is for programmers, scientists, and engineers who have knowledge of the Python language and know the basics of data science. It is for those who wish to learn different data analysis methods

This handbook presents an indispensable compilation of fundamental facts and figures about the Earth. It brings together reliable physical, chemical, biological and historical data in a series of 145 easy to read tables, supplemented by maps, charts and colour plates. Eleven sections cover topics spanning the Earth's geosphere, hydrosphere, atmosphere and biosphere, with one section focusing on other bodies in the Solar System. Full references for the original data sources are provided to enable users to access further detail, and the appendix provides practical information on units and conversion factors. Compact and easy to use, this handy book provides a time-saving first point of reference for researchers, students and practitioners in the Earth and Environmental Sciences. It allows scientists easy access to basic information on topics outside their specialisation, and is also a convenient resource for non-scientists such as economists, policy makers and journalists.

處理大量資料的基本工具「這本書提供了清晰且易於遵循的範例，幫助您設置與使用最重要的資料科學和機器學習工具。」—Anne BonnerContent Simplicity創辦人和CEOPython是許多研究人員的首選工具，它擁有豐富的儲存、操作及洞察資料的程式庫。這些資源散布在資料科學的領域中，藉由本書，您可以一次獲得這些資源，包括Ipython、NumPy、Pandas、Matplotlib、Scikit-Learn和其它相關的工具。對於熟悉Python，需要處理大量資料的資料科學家和資料處理人員來說，這是一本非常有價值的案頭書。可以有效率地處理每天面對的問題，像是操作、轉換及清理資料，視覺化不同形式的資料，建立統計學或機器學習模型等。藉由本書，你將可以學習到：‧IPython和Jupyter：提供資料科學家使用的Python計算環境‧NumPy：在Python中進行高效儲存及操作密集資料陣列的ndarrys‧Pandas：在Python中進行對於標籤式/欄位式的資料高效率儲存與操作‧Matplotlib：在Python中進行彈性範圍的資料視覺化功能‧Scikit-Learn：提供機器學習演算法以及簡潔的Python實作