Writing Functions

Last updated on 2024-06-17 | Edit this page

Estimated time: 25 minutes



  • How can I create my own functions?
  • How do variables inside and outside of functions work?
  • How can I make my functions easier to understand?


  • Explain and identify the difference between function definition and function call.
  • Write a function that takes a small, fixed number of arguments and produces a single result.
  • Identify local and global variables.

Use functions to make your code easier to understand.

Human beings can only keep a few items in working memory at a time. But we can work with larger and more complicated ideas by breaking content down into pieces. Functions serve a similar purpose in Python. We can create our own functions to encapsulate complexity and treat specific actions or ideas as a single “thing”. Functions also enable us to re-use code so we can write code one time, but use it many times.

Define a function using def with a name, parameters, and a block of code.

Begin each definition of a new function with the keyword def (for “define”), followed by the name of the function. Function names follow the same rules as variable names. Next, add your parameters in parentheses. You should still use empty parentheses if the function doesn’t take any inputs. Finally, like in conditionals and loops, you’ll add a colon and an indented block of code that will contain the body of your function.


def print_greeting():

Defining a function does not run it.

Note that we don’t have any output when we run code to define a function. This is similar to assigning a value to a variable. The function definition is sort of like a recipe in a cookbook - the recipe doesn’t create a meal until we use it. So we need to “call” a function to execute the code it contains. This means that Python won’t show you errors in your function until you call it. So when a definition of a function runs without error it doesn’t mean that there won’t be errors when it executes later.





Arguments in call are matched to parameters in definition.

Functions are highly useful when they use parameters to pull in data. You can specify parameters when you define a function which become variables when the function is executed.


def print_date(year, month, day):
    joined = f'{year}/{month}/{day}'

print_date(1871, 3, 19)



To expand on the recipe metaphor above, the arguments you add to the () contain the ingredients for the function, while the body contains the recipe.

Functions with defined parameters will result in an error if they are called without passing an argument:




TypeError                                 Traceback (most recent call last)
Cell In[15], line 1
----> 1 print_date()

TypeError: print_date() missing 3 required positional arguments: 'year', 'month', and 'day'

Use return to pass values back from a function.

In the date example above, we printed the results of the function code to output, but there are better way to handle data and objects created within a function. We can use the keyword return ... to send a value back to the “global” environment. (We’ll learn about local and global variables below). A return command can occur anywhere in the function, but is often placed at the very end of a function with the final result.


def calc_fine(days_overdue):
    if days_overdue <= 10:
        fine =  days_overdue * 0.25
        fine = (days_overdue * 0.25) + (days_overdue * .50)
    return fine
fine = calc_fine(12)
f'Fine owed: ${fine}'


'Fine owed: $9.0'

Specify the number of float decimals to display

In the example above, the fine value is displayed as 9.0, though ideally it would print as $9.00. We can use the f-string format specifier of .2f to display two decimal points: {fine:.2f}. If you wanted to display a float with three decimal points you would change the format specifier to {fine:.3f}. Here’s a cheat sheet of other f-string number formats.


fine = calc_fine(12)
f'Fine owed: ${fine:.2f}'


'Fine owed: $9.00'

A function that doesn’t explicitly return a value will automatically return None.


result = print_date(1970, 6, 21)
print(f'result of call is: {result}')


result of call is: None

Variable scope

When we define a variable inside of a function in Python, it’s known as a local variable, which means that it’s not visible to – or known by – the rest of the program. Variables that we define outside of functions are global and are therefore visible throughout the program, including from within other functions. The part of a program in which a variable is visible is called its scope.

This is helpful for people using or writing functions, because they don’t need to worry about repeating variable names that have been created elsewhere in the program.


initial_fine = 0.25
late_fine = 0.50

def calc_fine(days_overdue):
    if days_overdue <= 10:
        days_overdue =  days_overdue * initial_fine
        days_overdue = (days_overdue * initial_fine) + (days_overdue * late_fine)
    return days_overdue
  • initial_fine and late_fine are global variables.
  • days_overdue is a local variable in calc_fine. Note that a function parameter is a variable that is automatically assigned a value when the function is called and so acts as a local variable.


fine = calc_fine(12)
print(f'Fine owed: ${fine:.2f}')
print(f'Fine rates: ${initial_fine:.2f}, ${late_fine:.2f}')
print(f'Days overdue: {days_overdue}')


Fine owed: $9.00
Fine rates: $0.25, $0.50


NameError                                 Traceback (most recent call last)
Cell In[22], line 4
      2 print(f'Fine owed: ${fine:.2f}')
      3 print(f'Fine rates: ${initial_fine:.2f}, ${late_fine:.2f}')
----> 4 print(f'Days overdue: {days_overdue}')

NameError: name 'days_overdue' is not defined

Use docstrings to provide online help.

If the first thing in a function is a string that isn’t assigned to a variable, that string is attached to the function as its documentation. This kind of documentation at the beginning of a function is called a docstring.


def fahr_to_celsius(temp):
    "Input a fahrenheit temperature and return the value in celsius"
    return ((temp - 32) * (5/9))

This is helpful because we can now ask Python’s built-in help system to show us the documentation for the function:




Help on function fahr_to_celsius in module __main__:

    Input a fahrenheit temperature and return the value in celsius

We don’t need to use triple quotes when we write a docstring, but if we do, we can break the string across multiple lines:


def fahr_to_celsius(temp):
    """Convert fahrenheit values to celsius
    Input a value in fahrenheit
    Output a value in celsius"""
    return ((temp - 32) * (5/9))

Create a function

Write a function called addition that takes two parameters and returns their sum. After defining the function, call it with several arguments and print out the results.


def addition(x, y):
    return x + y

addition(3, 6)



Conditional statements within functions

Create a function called grade_converter that takes a numerical score (0 - 100) as its parameter and returns a letter grade based on the score:

  • 90 and above returns ‘A’
  • 80 to 89 returns ‘B’
  • 70 to 79 returns ‘C’
  • 60 to 69 returns ‘D’
  • Below 60 returns ‘F’

After defining the function, test it with a variety of scores to test it out.


def grade_converter(score):
    if score > 100 or score < 0:
        return 'Invalid score'
    elif score >= 90:
        return 'A'
    elif score >= 80:
        return 'B'
    elif score >= 70:
        return 'C'
    elif score >= 60:
        return 'D'
    elif score <= 59:
        return 'F'




Local and global variables

List all of the global variables and all of the local variables in the following code.


fine_rate = 0.25

def fine(days_overdue):
    if days_overdue <= 10:
        fine =  days_overdue * fine_rate
        fine = (days_overdue * fine_rate) + (days_overdue * (fine_rate*2))
    return fine
total_fine = calc_fine(20)
f'Fine owed: ${total_fine:.2f}'


'Fine owed: $15.00'

Global variables:

  • fine_rate
  • total_fine

Local variables:

  • days_overdue
  • fine

CSVs to Pandas function

In the Looping Data Sets episode, we learned to use glob to loop through a directory of CSV files and convert them to a Pandas DataFrame.

Write a function that converts a directory of CSV files into a single Pandas DataFrame. The function should accept one parameter: a string that includes the path and glob wildcard expression to point to a set of CSV files (e.g., 'data/*.csv'). We can assume, for these purposes, that all of the DataFrames have the same column names so that you can use pd.concat(dfs, ignore_index=True) at the end of the function to concatenate a list of DataFrames into a single DataFrame.


import glob
import pandas as pd

def concat_csvs(path):
    dfs = [] 

    for csv in sorted(glob.glob(path)):
        data = pd.read_csv(csv)
    df = pd.concat(dfs, ignore_index=True)
    return df

df = concat_csvs('data/*.csv')

Key Points

  • Break programs down into functions to make them easier to understand.
  • Define a function using def with a name, parameters, and a block of code.
  • Defining a function does not run it.
  • Arguments in call are matched to parameters in definition.
  • Functions may return a result to their caller using return.