Python for Chemists: 50 Solved Practical Problems

Use python as a calculator in google colab, performing basic arithmetic with +, -, *, /, and mastering order of operations, integer division //, exponentiation **, and modulus %.

Explore Python basics by distinguishing integers and floats, using type to check values, and applying arithmetic rules, then practice abs, length, and round with banker's rounding, and print with variables.

Explore common math module functions and constants, including pi, e, sqrt, exp, log, sin, and cos, and learn to convert between radians and degrees while computing the hypotenuse and norm.

Learn how variables represent values you can change, with clear names like boltzmann_constant and avogadro_number. Follow naming rules (letters, digits, underscore), never start with a digit, and avoid reserved keywords.

Learn to calculate energy using Einstein equation e=mc^2 with mass and the speed of light in Google Colab, including a Python example that prints the energy.

Calculate moles from mass using molar mass with a Python example in Google Colab. Find moles of water in a 25 g sample with molar mass 18.01528 g/mol.

Estimate the atmospheric pressure on Mars using 6.5 millibars as the average, then convert Earth's sea-level pressure of 1013 millibars to torr by multiplying by 760, yielding about 4.88 torr.

Convert enthalpy of evaporation of water from kilojoules per mole to joules per mole by multiplying 40.67 by 1000. Print the computed joules per mole.

Compute the number of water molecules from 200 ml by calculating mass from density, then moles from mass, and finally molecules using Avogadro's number in Python.

Calculate the root mean square velocity of oxygen at 27°C (c rms) using c rms = sqrt(3RT/m) and implement in Python with math.sqrt and rounding.

Compute the speed of sound in air at 27°C and -50°C using gamma r over m and root-mean-square velocity concepts, with air mass 29 g/mol, and implement the Python calculations.

Explore how numpy, imported as np, handles zero division by returning NaN with a warning, unlike the math module, while calculating the speed of sound in air.

Explore calculating the pH of a weak acid, using benzoic acid as an example, by deriving Ka from pKa and solving x via square root, with Python and NumPy.

Explore solving pH from pKa for a weak acid with Python by building a compact, single-line calculation for benzoic acid, including Ka, C, and the pH formula.

Compute the equilibrium constant from enthalpies and entropies using NumPy, applying standard enthalpies and standard molar entropies for CO2, H2, CO, and H2O at 298 kelvin.

Apply the Arrhenius equation to two temperatures. Use k2/k1 = 10 to calculate activation energy Ea with Ea = R ln(10)/(1/T1 - 1/T2) in kelvin, demonstrated in Python with numpy.

Demonstrate compound assignment by showing how assigning x to y copies the value, so y stays five when x becomes eight, highlighting memory behavior of variables.

Explore how variables can perform complex assignment by mapping chemical names to atomic numbers, and verify by entering hydrogen, helium, lithium, beryllium, and boron in various orders.

Learn how augmented assignment uses the augmented assignment operator in Python as a shorthand to update a variable and assign the result back, with examples like x += 1.

Explore how strings in Python are used to build chemical formulas, like hexane and sodium bromide, by concatenating CH3 and CH2 units, handling multiplication with plus signs, and printing headers.

Explore how strings and integers interact in Python, showing how arithmetic differs from string concatenation, and how to convert strings to int or float with int() and float().

Learn to combine strings with integers and floats in Python to print chemical data, such as carbon's atomic mass 12.0107, and display symbols like delta and angstrom using string methods.

Learn how to index and slice strings in Python using zero-based and negative indices, with examples on gadolinium and ranges like 0:4, 0:5, and 3:5.

Explore string indexing and slicing in Python, reverse strings, step through characters, and combine slices to reconstruct words; extract extensions and transform names by slicing and concatenation.

Explore Python string methods to convert text to upper or lower case and strip characters. Learn to measure length, count occurrences, and locate indices on a hexane molecule example.

Learn Python string methods: capitalize the first letter, upper the entire string, and split by a separator. Explore is alpha numeric, is alpha, and is digit checks on alphanumeric text.

Learn to split strings by spaces and separators like comma or colon, and to join fragments with a delimiter using Python's split and join methods.

Explore converting chemical formulas with Python string methods by removing prefixes and suffixes from hexane, stitching fragments, and replacing groups to form decane, hexanedioic acid, or hexanediol.

Learn to print the second row of the periodic table in python using string methods, tabs, and newlines to display lithium through neon and their atomic numbers 3 to 10.

Learn to format Python strings using the format method and placeholders to present dynamic values like the root mean square velocity of oxygen at 300 Kelvin in a readable sentence.

Explore two string formatting methods in Python by constructing a sentence about benzoic acid’s molecular weight, 122 grams per mole, and transforming its capitalization.

Demonstrate formatting a numeric string in Python to display atmospheric pressure in millibars using f-strings and format specifiers, including exponent form, precision, and field width.

Compute the CO2 yield from metabolizing 500 g of serine by converting mass to moles, applying three CO2 per amino acid, and deriving a CO2 mass of about 742 g.

Discover Python boolean operators, focusing on equality, not equality, and ordering tests. Compare integers and floats, explore identity with is and is not, and understand true or false results.

Analyze complex boolean logic using and, or, and not to determine true or false outcomes for multiple inputs, with examples eight greater than five and eight not less than five.

Explore the behavior of boolean operators and, or, and not with inputs A and B, using truth tables to map true and false to 1 and 0 in Python.

Learn how any and all boolean operators handle multiple inputs. Test element presence in compounds, such as boron and beryllium hydroxide, and check for silicon.

Learn how to perform a boolean inclusion test on a metals list, checking if names or symbols are present and highlighting case-sensitive matching for accurate results.

The lecture introduces lists and indexing, showing how to create a list of ionization potentials for alkaline earth metals with square brackets and to index and slice to retrieve values.

Explore Python list functions, including append, sort, reverse, and insert, and learn the difference between extend and append, copy lists, and handle nested lists.

Learn to manipulate a Python list of ionization potentials using append, extend, insert, pop, remove, and sort; add boron, aluminum, gallium, and indium to build chemistry datasets.

See how sorting a mixed list of alphabets and digits triggers the error not supported between instances of string and float. Remove the string to sort and print IP correctly.

Discover how strings are immutable and how ID reveals memory references when assigning variables. See how lists can share references, remain same after append, and how copying creates new IDs.

Explore tuples in Python, an immutable sequence shown with parentheses. Use tuples to store constant orbital energies, compute differences between elements, and handle rounding errors from floating-point precision.

Introduce a set, represented by curly brackets, which holds unique elements; duplicates like lithium appear only once, as shown by a set containing lithium, potassium, and sodium.

Explore how to use Python sets to add and remove elements, compare metals and nonmetals, and perform union, intersection, difference, and symmetric difference to identify common or unique items.

Explore set operations on hydrocarbon data by combining two sets to form a union, finding their intersection, adding a new item to a set, and computing the symmetric difference.

Explore how dictionaries in Python store ionization potentials as key-value pairs using curly braces, enabling access to keys, values, and items and adding elements like sodium.

Define a Python function with parameters m and n to print a table of a number, call it with arguments, and fix range to start from 1.

Define a function to compute quadratic roots using the discriminant and the quadratic formula, importing math and returning root1 and root2; warn about math domain error for negative discriminants.

Build a python function to calculate root mean square velocity as a function of temperature and mass, using math and the constant r, with unit handling and local scope.

Compute a first order rate in Python by defining rate = k * A0^n with n = 1, and test with A0 and k.

Compute the heat capacity of copper and silicon using the Einstein model in Python with numpy, defining the CV_Einstein function and evaluating at 300 Kelvin.

Define a function to compute the molarity of a solution as moles solute divided by volume solvent, and return the result. Demonstrate with 0.5 moles and 1.5 l, yielding 0.3333.

Calculate a gas's partial pressure from mole fraction and total pressure in a Python example, using p = x × P total, and print the oxygen partial pressure.

Compute the energy levels of a particle in a three-dimensional box with python and numpy, using energy_level to evaluate E = ħ^2/(8m)(nx^2/lx^2+ny^2/ly^2+nz^2/lz^2) and compare with direct math.

Translate 3d coordinates using a four-parameter function that adds x, y, and z shifts to original coordinates, with default zero shifts and index-based axes.

Demonstrate Python translations along x, y, and z axes, with defaults for y and z as zero and the first value applying to x.

Develop a general Python solution to translate coordinates for multiple atoms in Cartesian space by adding increments x_t, y_t, and z_t to x, y, and z for each coordinate set.