Index A | B | C | D | E | F | G | H | I | J | K | L | M | N | O | P | Q | R | S | T | U | V | W | Z A alias altair Anaconda software installer anonymous function arguments argv arrays augmented assignment average B balancing chemical equations Balmer series baseline correction Beer's law using optimization with matricies bioinformatics blackbody radiation boolean logic broadcasting C cheminformatics command line comments compound assignment comprehensions conditions confidence intervals confusion matrix constants constrained optimization curve fitting D DataFrame concatenation create drop columns insert columns merge statistics datetime data descriptors dictionaries E eigenvalues eigenvectors encoding numbers enumeration, [1] equilibrium ICE table kinetic simulation solving double equilibra solving with polynomials error handling except F factorial fancy indexing features file input/output Excel files FASTA mmCIF multiple files PDB reading NMR data with NumPy with pandas with Python fitting data floats Fourier transform basics NMR functions arguments calling functions defining functions docstring recursive scope variable arguments vectorization G gas chromatography gas law GC content generator H Hamming distance Hess's law I images blob detection color contrast eccentricity encoding entropy false color grayscale loading saving immutable InChI indexing inflection points integer division integers interactivity pan and zoom rotate molecules selection widgets interpolation island of stability isomers isotopic decay kinetics J Jupyter notebooks K k-fold cross validation kinetics determine rate constants simulations stochastic simulations L label plotting axes lambda function least squares legend linear equation solving with optimization with SymPy lists local min/max loops break continue for pass while M machine learning blind signal (or source) seperation classification clustering dimensionality reduction k-means random forest supervised unsupervised masking, [1] math algebra calculus differentiation factoring polynomials integration linear algebra matricies ordinary differential equations (ODEs) simplification solve equations symbolic matrix determinant dot product eigenvalues eigenvectors inverse pseudoinverse singular matrix maximization maximum median meshgrid, [1] method minimization minimum missing values with NumPy with pandas mode modules modulo modulus moving average N nan NGLView NMR dynamic Fourier transform integration nmrglue nmrsim plot COSY processing second-order simulation of stochastic simulation widgets simulation nonlinear regression or curve fitting nuclide stability NumPy O ODE optimization orbitals 3D plotting angular wavefunctions graphical integration integration radial wavefunctions scatter plot visualization of P pandas peak identification peak prominence percentile pesudorandom numbers Plank's law plotting 2D NMR spectrum 3D 3D on 2D surface 3D surface plot bar plot box categorical plots colors contour count figure size heat map histogram kde plot markers multifigure overlaying pie plot polar polar plot regression plot saving plots scatter plot stem plot step plot surface plot violin plot polymers block polymers copolymers random flight PubChem Q quartile R radial wavefunction raising exceptions Ramachandran plots random numbers in simulations with NumPy with Python RDKit regression curve fitting linear machine learning multivariable nonlinear normal equation regression plot remote requests residuals root finding optimization with SymPy S saving images saving plots Savitzky-Golay scikit-image scikit-learn SciPy Fourier transform introduced optimization signal processing smoothing data scope sequence alignment sequences Series sets sinle: functions basic arguments slicing slope SMILES smoothing signal data sort lists NumPy arrays Spyder standard deviation standing wave stereochemistry strings structural patterns SymPy syntactic sugar T title on plot transpose try tuples U user input V van der Waals equation variable naming rules variable scope variables vectorization visualize chemical structures W wavefunction weighted average widgets writing files with NumPy with Pandas with Python Z zipping, [1]
