1.2 2907 dc xml [Apollo neben der getöteten Schlange Python] Appenzeller, Heinrich 1854-1921 (DE-588)1077747780 früherer Eigentümer fmo Geßner, Salomon 1730-1788 (DE-588)118538969 Gessner, Heinrich 1768-1813 (DE-588)116600217 Drucker prt Gessner Offizin, Zürich (DE-588)1090670109 Drucker prt image 1802 zxx Martin Bircher/Bruno Weber: Salomon Gessner, Zürich 1982, S. 190 Paul Leemann-van Elck: Salomon Gessner, Zürich 1930, S. 268, Nr. 30 und S. 307-308 Aus dem "Oeuvre de Salomon Gessner" Aus der Schenkung Heinrich Appenzeller, 1912 Blatt stockfleckig Apollon Gott Der vorliegende Druck befindet sich im gebundenen, posthum publizierten Buch "Oeuvre de Salomon Gessner Tom. I." (Signatur: AWQ 193) Das vorliegende Blatt gehört zur zehnteiligen Folge "III", die Landschaftsdarstellungen verschiedenen Formats mit den mythologischen Figuren enthält und erstmals 1769-1771 publiziert wurde. Das Blatt wurde von Gessner mit "1771" datiert Titel gemäss Appenzellers handschriftlicher Notiz auf dem Blatt http://dx.doi.org/10.3931/e-rara-37384 (swissbib)200468138-41slsp_network 200468138 (NEBIS)010416997EBI01 alma:41SLSP_UZB/bibs/990104169970205508 https://eu03.alma.exlibrisgroup.com/discovery/delivery/41SLSP_UZB:UZB/12463499290005508 990104169970205508 1 dc xml 《Python 数据分析》第三版 Wes McKinney text O'Reilly Media, Inc. 2025 2025 chi (CaSebORM)9798341656734 (CKB)39169548800041 9798341656734 alma:41SLSP_UZB/bibs/99118232787505508 99118232787505508 2 dc xml 《Python 机器学习食谱》第二版 Chris Albon, Kyle Gallatin text O'Reilly Media, Inc. 2025 2025 chi (CaSebORM)9798341658110 (CKB)39169576900041 9798341658110 alma:41SLSP_UZB/bibs/99118233252105508 99118233252105508 3 dc xml 《Python 概论》，第 4 版 Steve Holden, Alex Martelli, Paul McGuire, Anna Martelli Ravenscroft text O'Reilly Media, Inc. 2025 2025 chi (CaSebORM)9798341656840 (CKB)39169577100041 9798341656840 alma:41SLSP_UZB/bibs/99118233278505508 99118233278505508 4 dc xml 《Python 编程》，第 4 版 Mark Lutz text O'Reilly Media, Inc. 2025 2025 chi (CaSebORM)9798341659612 (CKB)39249360300041 9798341659612 alma:41SLSP_UZB/bibs/99118233164105508 99118233164105508 5 dc xml 《学习 Python》第 5 版 Mark Lutz text O'Reilly Media, Inc. 2025 2025 chi (CaSebORM)9798341656963 (CKB)39169554100041 9798341656963 alma:41SLSP_UZB/bibs/99118232508205508 99118232508205508 6 dc xml 《高性能 Python》第二版 Micha Gorelick, Ian Ozsvald text O'Reilly Media, Inc. 2025 2025 chi (CaSebORM)9798341657946 (CKB)39169556400041 9798341657946 alma:41SLSP_UZB/bibs/99118232775005508 99118232775005508 7 dc xml 『Learning Python 第6版』 Mark Lutz text O'Reilly Media, Inc. 2025 2025 jpn (CaSebORM)9798341634367 (CKB)37999947500041 9798341634367 alma:41SLSP_UZB/bibs/99118232967605508 99118232967605508 8 dc xml 20 Python libraries you aren't using (but should) / Twenty Python libraries you aren't using (but should) Hattingh, Caleb, author. text 2016 eng eng The Python ecosystem is vast and far-reaching in both scope and depth. Starting out in this crazy, open-source forest is daunting, and even with years of experience, it still requires continual effort to keep up-to-date with the best libraries and techniques. This report helps you explore some of the lesser known Python libraries and tools, including third-party modules and several extremely useful tools in the standard library that deserve more attention. What makes this collection different from other lists online? Author Caleb Hattingh diligently spent time finding and testing hidden gems that fit several criteria: easy to install and use, cross-platform, applicable to more than one domain, and not yet popular but likely to become so soon. You will likely discover at least a couple of cool libraries that will assist you in your everyday Python activities, no matter your specialization. This report examines: Little-known standard library modules: collections , contextlib , concurrent.futures , logging , and sched Flit for simplifying the process of submitting a Python package to the Python Package Index (PyPI) Colorama and begins for making your command-line applications friendlier for users Pyqtgraph and pywebview for creating graphical user interfaces (GUIs) Watchdog , psutil , and ptpython for working closely with the operating system Hug for exposing APIs for other users' programs to consume Arrow and parsedatetime for working with dates and times Third-party general-purpose libraries: Boltons , Cython , and the awesome-python curated list Description based on online resource; title from title page (viewed February 20, 2018). QA76.73.P98 005.133 Python (Computer program language) Libraries (Computer program subroutines) Object-oriented programming (Computer science) (CKB)4100000002521755 (Safari)9781492037866 (OCoLC)1023864063 (WaSeSS)IndRDA00115331 (CaSebORM)9781492037866 (OCoLC)on1023864063 9781492037866 1492037869 9781491967928 1491967927 alma:41SLSP_UZB/bibs/99118233460805508 99118233460805508 9 dc xml 21-day business analysis bootcamp with Python & Power BI. Madhavan, Govindakumar, instructor. Packt Publishing, publisher. moving image 2025 eng In this 4-hour course, you'll journey through Business Analysis with Python and Power BI, learning essential concepts like process mapping, risk management, and Python for data analysis. You'll also get hands-on experience in using Power BI for visualizations, driving data-driven decision-making in business contexts. What I will be able to do after this course Understand core concepts of Business Analysis Learn to apply Python for business data analysis Master Power BI for creating professional reports Effectively communicate insights using business analysis tools Implement elicitation techniques to gather stakeholder requirements Course Instructor(s) Govindakumar Madhavan brings over 25 years of experience in Technology, Business Operations, and Strategy, specializing in fraud detection and service analytics. He has won global awards in Leadership Excellence, Customer Experience, and Artificial Intelligence and has been featured in CIO Review Magazine. Who is it for? This course is ideal for aspiring Business Analysts, Data Analysts, Project Managers, or anyone eager to learn Business Analysis concepts using Python and Power BI. Prior experience with Python and Power BI is beneficial but not mandatory. OCLC-licensed vendor bibliographic record. QA76.9.I52 001.4/226028566 Information visualization Visual analytics Data mining Business intelligence Python (Computer program language) (CaSebORM)9781807422530 (CKB)44573971600041 (OCoLC)1565467400 (OCoLC-P)1565467400 1-80742-253-4 alma:41SLSP_UZB/bibs/99118234636405508 99118234636405508 10 11 true 2026-05-16T03:25:01+0200