Data Management for Natural Scientists: A Practical Guide to Data Extraction and Storage Using Python

Data Management For Natural Scientists Offers A Practical Guide For Scientific Processing Of Data. It Covers The Way From “getting Hands On” Experimental Results To Ensuring Their Use For Addressing Various Scientific Questions. Code Snippets Are Provided In Order To Introduce The Proposed Workstream And To Demonstrate The Adjustability To Specific Challenges. Frontmatter -- Acknowledgment -- Contents -- 1 Presenting The Challenge -- 2 Python Quick Start -- 3 The Steps Of Data Processing -- 4 From Experimental Files To Data -- 5 From Data To Information -- 6 Where To Put Data And Information -- 7 How To Visualize Data And Information -- 8 Responding To Lessons Learned -- 9 Where To Go From Here -- 10 Conclusion -- A Packaging A Custom Module -- B Comments To Tables And Columns Via Sqlalchemy -- C A Word On Version Control Systems -- D Overview Of Utilized Python And Package Versions -- E Extracting Data Via Pd.read_csv -- F Installation Of An Odbc Driver -- List Of Figures -- Bibliography -- Index Matthias Hofmann. Issued Also In Print. Mode Of Access: Internet Via World Wide Web. In English.