03 Apr 2026

Data Structures: Arrays and Strings

Lists, strings, tuples, dictionaries, indexing, slicing, and simple array-like thinking in Python.

msc semester-i computational-techniques data-structures python

A data structure stores many related values together. In computational physics, this may be a list of positions, times, velocities, measurements, or labels.

Arrays

An array is an ordered collection of elements of the same general kind, usually stored so that each element can be accessed by its position or index. In numerical work, an array commonly represents a table of values such as time readings, measured temperatures, position coordinates, or sampled values of a function.

For example, the values

\[x_0,\;x_1,\;x_2,\;\ldots,\;x_n\]

may be stored as one array-like object and processed one element at a time.

positions = [0.0, 0.5, 1.0, 1.5, 2.0]
print(positions[0])
print(positions[3])

In plain Python, a list is often used for introductory array-like work. For larger numerical calculations, NumPy arrays are preferred because they are faster and support mathematical operations directly.

Lists

A list is an ordered collection. Its elements can be accessed by index.

temperatures = [298, 300, 303, 305]

print(temperatures[0])
print(temperatures[2])

Python indexing starts from 0. Therefore temperatures[0] is the first element.

Updating a list

temperatures[1] = 301
temperatures.append(307)

The method append() adds a new element at the end.

Slicing

Slicing extracts part of a list.

data = [2, 4, 6, 8, 10]
print(data[1:4])

The slice data[1:4] gives elements with indices 1, 2, and 3.

Strings

A string is a sequence of characters.

name = "Hydrogen"
print(name[0])
print(name[0:5])

Strings support indexing and slicing, but individual characters cannot be changed directly.

Tuples

A tuple is like a list, but it is immutable.

point = (2.0, 3.0)
x = point[0]
y = point[1]

Tuples are useful when the grouped values should remain fixed.

Dictionaries

A dictionary stores values using keys.

constants = {
    "c": 3.0e8,
    "h": 6.626e-34
}

print(constants["c"])

Array-like work

For basic programming, lists are enough. For serious numerical arrays, one usually uses NumPy, but the idea is the same: store many related values and process them systematically.