Common Functions

Common Functions#

Tools You’ll Use Constantly#

Every time you analyze experimental data, you’ll need to find the minimum, maximum, or average of a list of values. Every time you compute an error, you’ll need an absolute value. Every time you report a result, you’ll want to round it.

Python comes with many built-in functions. No imports needed. These are the ones you’ll reach for most often. Learn them once, use them forever.

Working with Numbers#

abs(): Absolute value#

error = -0.0023
print(abs(error))

difference = 5 - 8
print(abs(difference))

Output:

0.0023
3

round(): Round to decimal places#

pi = 3.14159265359

print(round(pi))
print(round(pi, 2))
print(round(pi, 4))

concentration = 0.123456789
print(f"C = {round(concentration, 3)} mol/L")

Output:

3
3.14
3.1416
C = 0.123 mol/L

min() and max(): Find extreme values#

temps = [300, 350, 280, 420, 390]

print(min(temps))
print(max(temps))
print(max(10, 20, 5))

Output:

280
420
20

They work with both lists and multiple arguments.

sum(): Add up all values#

values = [1, 2, 3, 4, 5]
print(sum(values))

data = [2.3, 2.5, 2.4, 2.6, 2.5]
average = sum(data) / len(data)
print(f"Average: {average}")

Output:

15
Average: 2.46

pow(): Raise to a power#

print(pow(2, 3))
print(pow(10, -2))

Output:

8
0.01

pow(2, 3) is equivalent to 2**3.

Working with Collections#

len(): Count items#

temps = [300, 350, 400, 450]
print(len(temps))

name = "methane"
print(len(name))

properties = {"MW": 18.0, "Tb": 373}
print(len(properties))

Output:

4
7
2

For strings, it counts characters. For dictionaries, it counts key-value pairs.

sorted(): Return a sorted list#

values = [3, 1, 4, 1, 5, 9, 2]
print(sorted(values))
print(values)
print(sorted(values, reverse=True))

Output:

[1, 1, 2, 3, 4, 5, 9]
[3, 1, 4, 1, 5, 9, 2]
[9, 5, 4, 3, 2, 1, 1]

Notice the original list is unchanged. Use reverse=True for descending order.

reversed(): Iterate in reverse#

temps = [300, 350, 400]
for T in reversed(temps):
    print(T)

Output:

400
350
300

Type Checking and Conversion#

type(): Check the type#

x = 3.14
print(type(x))

temps = [300, 350, 400]
print(type(temps))

Output:

<class 'float'>
<class 'list'>

Type conversion functions#

print(int(3.7))
print(int("42"))

print(float(5))
print(float("3.14"))

print(str(273.15))

print(list(range(5)))
print(list("abc"))

print(tuple([1, 2, 3]))

print(set([1, 2, 2, 3]))

Output:

3
42
5.0
3.14
273.15
[0, 1, 2, 3, 4]
['a', 'b', 'c']
(1, 2, 3)
{1, 2, 3}

Note that int() truncates (doesn’t round), and set() removes duplicates.

Useful for Iteration#

range(): Generate sequences#

print(list(range(5)))
print(list(range(2, 7)))
print(list(range(0, 10, 2)))

Output:

[0, 1, 2, 3, 4]
[2, 3, 4, 5, 6]
[0, 2, 4, 6, 8]

enumerate(): Get index and value#

temps = [300, 350, 400]
for i, T in enumerate(temps):
    print(f"Index {i}: {T} K")

zip(): Pair up lists#

x = [1, 2, 3]
y = [10, 20, 30]
for a, b in zip(x, y):
    print(a, b)

Boolean Tests#

all(): Check if all are True#

values = [True, True, True]
print(all(values))

values = [True, False, True]
print(all(values))

temps = [300, 350, 400]
print(all(T > 0 for T in temps))

Output:

True
False
True

Useful for checking if all items in a collection meet some condition.

any(): Check if at least one is True#

values = [False, False, True]
print(any(values))

temps = [300, 350, 500, 400]
print(any(T > 450 for T in temps))

Output:

True
True

Useful for checking if at least one item meets some condition.

Input/Output#

input(): Get user input#

name = input("Enter name: ")
value = float(input("Enter number: "))

Quick Reference Table#

Function

Purpose

Example

abs(x)

Absolute value

abs(-5) → 5

round(x, n)

Round to n decimals

round(3.14159, 2) → 3.14

min(...)

Smallest value

min([3, 1, 2]) → 1

max(...)

Largest value

max([3, 1, 2]) → 3

sum(list)

Sum all values

sum([1, 2, 3]) → 6

len(x)

Number of items

len([1, 2, 3]) → 3

sorted(x)

Sorted copy

sorted([3, 1, 2]) → [1, 2, 3]

type(x)

Check type

type(3.14) → <class 'float'>

int(x)

Convert to int

int("42") → 42

float(x)

Convert to float

float("3.14") → 3.14

str(x)

Convert to string

str(42) → "42"

list(x)

Convert to list

list(range(3)) → [0, 1, 2]

range(n)

Sequence 0 to n-1

list(range(3)) → [0, 1, 2]

all(x)

All True?

all([True, True]) → True

any(x)

Any True?

any([False, True]) → True

Practical Example: Data Analysis#

# Experimental measurements
measurements = [2.31, 2.45, 2.38, 2.52, 2.41, 2.39]

# Basic statistics
n = len(measurements)
total = sum(measurements)
average = total / n
minimum = min(measurements)
maximum = max(measurements)
range_val = maximum - minimum

print(f"n = {n}")
print(f"Sum = {round(total, 2)}")
print(f"Average = {round(average, 3)}")
print(f"Min = {minimum}, Max = {maximum}")
print(f"Range = {round(range_val, 2)}")

# Check data quality
all_positive = all(x > 0 for x in measurements)
any_outliers = any(abs(x - average) > 0.2 for x in measurements)

print(f"All positive: {all_positive}")
print(f"Has outliers: {any_outliers}")

What’s Next?#

You now have a solid foundation in Python basics! Next, you’ll learn about NumPy for numerical computing in NumPy Basics.

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