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- math_nombres
- 23456790123457... * 1/99² = 0.0001020304050607080910111213141516171819202122232425262728293031323334... 56667686970717273747576777879808182838485868788899091929394959697990001020304050607080910111... Quelle est l'explication de ces particularités. Comment m... 0.000000011234567901234567901234567901230 0.000000090000000000000000000000000000000 0.0000001012345679
- pandas
- Jupyter Notebook" * [[https://mubaris.com/2017-09-25/python-data-analysis-with-pandas|Python Data A... ce.com/introducing-bamboolib-a-gui-for-pandas-4f6c091089e3|Introducing Bamboolib — a GUI for Pandas]] ... s one-liners for popular excel stuff]], Medium 01/09/2020 * [[https://towardsdatascience.com/how-not... ners-that-will-help-you-code-like-a-pro-2ff5e34fee09|Pandas fundamentals every data scientist needs to
- presentation_principes
- boltzmann) 8.31447334956 >>> 2**0.5 1.4142135623730951 >>> (5+2j)*(3-7j) (29-29j) >>> (1.+1./1E6)**1E6 2.7182804690957272 >>> </code> * Les expressions numériques s... haînes ==== <code> >>> s='Mons, le 15 septembre 2009' >>> s[8:] ' 15 septembre 2009' >>> s.find('le') 6 >>> s.split() ['Mons,', 'le', '15', 'septembre',
- tableau_periodique_2011
- listbox=Listbox(element,height=10,width=40,fg="#070942") listbox.pack() #sert à ajuster la fenêtre... 8,3,17,"#00CCFF"], ["Potassium","K",19,39.0963,4,0,"#FF9900"], ["Calcium","Ca",20,40.0... .546,4,10,"#FFCCCC"], ["Zinc","Zn",30,65.409,4,11,"#FFCCCC"], ["Gallium","Ga",31,69.72... 803,6,14,"#9999FF"], ["Polonium","Po",84,209,6,15,"#9999FF"], ["Astate","At",85,210,6,
- matplotlib_simple
- race-animation-in-python-with-matplotlib-477ed1590096|Creating a Bar Chart Race Animation in Python wi... box pad margin - Towards Data Science, Medium, 29/09/2020 * [[https://towardsdatascience.com/everyth... m.com/dataseries/mastering-matplotlib-part-1-a480109171e3|Mastering Matplotlib: Part 1. Understanding ... data visualization libraries]] Soner Yıldırım, 16/09/2022, Medium - Figure and Axes - Some thi
- notions_fondamentales
- r Code More Readable]] (Jonny Jackson, Medium, 24/09/2020) Dans quelques cas, il est intéressant d'éc... thon]] * [[http://stackoverflow.com/questions/3009935/looking-for-a-good-python-tree-data-structure|... towardsdatascience.com/args-kwargs-python-d9c71b220970|*args and **kwargs in Python - Discussing the d... ivad.medium.com/3-tips-for-writing-pythonic-code-b090956a6107|3 Tips For Writing Pythonic Code]] David
- notions_avancees
- nder.edu/python-regular-expressions-cheat-sheet-cd0992c36f6f|Python Regular Expressions — cheat sheet ... ciently-checking-for-an-empty-list-in-python-76b76099fbd3|Efficiently Checking for an Empty List in Py... m/top-12-most-important-python-concepts-24f59945a409|Top 12 most important Python concepts]] Dacus Aug
- ppoo
- w about Python classes!]] George Seif, Medium, 25/09/2019 * [[https://towardsdatascience.com/the-m... y will save you hours of coding]] Matteo, medium, 09/09/2021 * [[https://itnext.io/effortlessly-create-classes-in-python-with-dataclass-19412eada8be
- tableau_periodique_2013
- elembox=Listbox(element,height=32,width=40,fg="#070942") elembox.pack() for item in table[int(... atatypebox=Listbox(fen2,height=32,width=40,fg="#070942") datatypebox.pack() for item in table[0]:
- fit_modele_einstein
- [47.7,0.02], [57.2,0.0365], [67,0.0595], [76.1,0.092], [87,0.147], [100.4,0.24], [113.1,0.378], [126.... [47.7,0.02], [57.2,0.0365], [67,0.0595], [76.1,0.092], [87,0.147], [100.4,0.24], [113.1,0.378], [126.
- rdkit
- Started with the RDKit in Python — The RDKit 2020.09.1 documentation]] * [[https://ctr.fandom.com/wi... com/talks/Mayfield_ChemicalDepiction_RDKITUGM_201609.pdf|Higher Quality Chemical Depictions: Lessons L
- progappchim
- ttp://pubs.acs.org/doi/abs/10.1021/acs.jchemed.6b00973|The Development of Computational Thinking in a ... 94 (9), pp 1217–1224 DOI: 10.1021/acs.jchemed.6b00973 * programmes inspirés de [[http://pubs.acs.or
- trucs_astuces
- ython code in a Pythonic way]], Yong Cui, Medium, 09/03/2021 * [[https://levelup.gitconnected.com/py... d to do the same thing]] Ishaan Gupta, Medium, 05/09/2022 * [[https://towardsdatascience.com/20-newb