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- math_nombres
- 3456790123456790123457... * 1/99² = 0.000102030405060708091011121314151617181920212223242526272829303132333435363738394041424344454647484950515253545556575859606162636465666768697071727374757... 79808182838485868788899091929394959697990001020304050607080910111... Quelle est l'explication de ces ... 000 0.000067901234567901234567901234567901230 0.000500000000000000000000000000000000000 0.000567901234
- progappchim
- 0 km de [[https://www.openstreetmap.org/node/337510526#map=9/51.1561/33.0579|Konotop]] !!** </note> Le cours "Programmation appliquée à la chimie" de bac... [http://www.academie-sciences.fr/pdf/rapport/rads_0513.pdf|Rapport de l’Académie des sciences - L’ense... [[http://www.wto.org/english/res_e/statis_e/its2005_e/its05_toc_e.htm]] * Nations particulières
- notions_fondamentales
- le is better than complex]] Yang Zhou, Medium, 03/05/2021 * [[https://towardsdatascience.com/the-art... tionnaires ([[https://www.python.org/dev/peps/pep-0584/|/pep-0584]]. === Références diverses === * [[https://www.datacamp.com/community/tutorials/pytho... hon3]] by Maxence LQ, Python in Plain English, 25/05/2021 * [[https://ibexorigin.medium.com/have-mer
- calcul_matriciel_2012
- )) s.append(t) z.append(p) fen05=Tk() r = Dif_matrix(s,z) for i in range ... j in range (len(r[0])): b = Label(fen05, text= "%.2f" % r[i][j]) b.grid(row=i... )) s.append(t) z.append(p) fen05=Tk() r = Sum_matrix(s,z) for i in range ... j in range (len(r[0])): b = Label(fen05, text= "%.2f" % r[i][j]) b.grid(row=i
- random_walk_2d-simple
- xo,yo,xn,yn,width=1,fill='black') sleep(0.050) # attends 50 ms entre chaque segment c
- solvents_data_class
- Solvent("butanol secondary", 88.8, -114.7, 26, 0.805, 16.56, 9999, 9999, 9999, "C4H10O")) solvent_list... ) #solvent_list.append(Solvent("benzyl alcohol", 205.4, -15.3, 100, 1.045, 13.1, 9999, 9999, 9999, "un... e", 110.6, -94.9, 4, 0.867, 2.38, 1.4969, 0.43, 0.05, "C7H8")) solvent_list.append(Solvent("water", 10... methyl formamide", 153, -61, 58, 0.944, 36.7, 1.4305, 3.86, 9900, "C3H7NO")) solvent_list.append(Solve
- tableau_periodique_2011
- ,3,0,"#FF9900"], ["Magnesium","Mg",12,24.3050,3,1,"#FFFF33"], ["Aluminium","Al",13,26.... .62,5,1,"#FFFF33"], ["Yttrium","Y",39,88.9059,5,2,"#FFCCCC"], ["Zirconium","Zr",40,91.... 7,5,7,"#FFCCCC"], ["Rhodium","Rh",45,102.9055,5,8,"#FFCCCC"], ["Palladium","Pd",46,106... 3,5,17,"#00CCFF"], ["Cesium","Cs",55,132.9054,6,0,"#FF9900"], ["Baryum","Ba",56,137.32
- matplotlib_simple
- return s1*e1 tvals = arange(0., 5., 0.05) # arange (importé) permet de définir un tableau ... n Seaborn library?]] Tirendaz Academy, Medium, 07/05/2022 * [[https://manimplotlib.readthedocs.io/en... -to-visualize-your-data-with-matplotlib-16bc33747e05|5 Powerful Tricks to Visualize Your Data with Mat... ade of blue forever)]] Callum Ballard, Medium, 22/05/2020 * [[https://towardsdatascience.com/creativ
- presentation_principes
- >>> Navogadro=6.02214199E23 >>> kboltzmann=1.3806505E-23 >>> print(Navogadro*kboltzmann) 8.31447334956... return s1*e1 tvals = arange(0., 5., 0.05) #plot(tvals, my_func(tvals)) #show() plot(tvals... Numb bonds = 12.0107 6 C x= 0.956 y= -0.086 z= -0.056 15.9994 8 O x= 0.488 y= -1.374 z= 0.299 1.00794 ... 0.64 z= 0.672 1.00794 1 H x= 0.584 y= 0.177 z= -1.05 1.00794 1 H x= 2.049 y= -0.08 z= -0.052 1.00794 1
- fit_modele_einstein
- s expérimentales (T, Cv) : liste_data=[ [12.9,0.00053], [16.1,0.00081], [19.8,0.00138], [24.1,0.00257]... [41.3,0.0133], [47.7,0.02], [57.2,0.0365], [67,0.0595], [76.1,0.092], [87,0.147], [100.4,0.24], [113.... s expérimentales (T, Cv) : liste_data=[ [12.9,0.00053], [16.1,0.00081], [19.8,0.00138], [24.1,0.00257]... [41.3,0.0133], [47.7,0.02], [57.2,0.0365], [67,0.0595], [76.1,0.092], [87,0.147], [100.4,0.24], [113.
- lennard-jones
- tion du potentiel de Lennard-Jones Argon : σ = 3.405 Å, ε/kB = 118.2 K kB = 1.3806488(13)×10−23 --> ε... J """ from pylab import * def f(r): sigma=3.405 #angstrom ! epsilon=1.632 # 10**-21 J s =... * Ar : 340.1 pm * Kr : 360.1 pm * Xe : 405.5 pm * Données cristaux (cubic close packed ou
- openbabel_jmol
- b bonds = 5 12.0107 6 C x= 0.956 y= -0.086 z= -0.056 15.9994 8 O x= 0.488 y= -1.374 z= 0.299 1.00794 ... 0.64 z= 0.672 1.00794 1 H x= 0.584 y= 0.177 z= -1.05 1.00794 1 H x= 2.049 y= -0.08 z= -0.052 1.00794 1 H x= 0.831 y= -1.996 z= -0.365 partial charges = (
- pandas
- sdatascience.com/40-examples-to-master-pandas-c69d058f434e|40 Examples to Master Pandas - A comprehens... o a NumPy array]] Giorgos Myrianthous, Medium, 06/05/2022 * [[https://towardsdatascience.com/20-of-p... rk on the Pandas library]] Avi Chawla, Medium, 16/05/2022 - Reading a CSV file - Saving a Data
- plot_sinus_cosinus
- oir que ces valeurs intéressantes : <code python 05-setting_ticks.py> ... plt.xticks([-np.pi, -np.pi/