By now you have cleaned the price " $129.00" once, computed a line’s revenue once, and printed a few numbers. Cartwheel has 3,991 order lines. You do not want to copy the cleaning code to every place it is needed and then fix a bug in seven copies. Functions let you write the logic once, give it a name, and call it wherever you need it.
def line_revenue(quantity, unit_price, discount=0.0):\n \"\"\"Revenue of one order line: quantity x price, minus the discount.\"\"\"\n return round(quantity * unit_price * (1 - discount), 2)\n\nprint(line_revenue(2, 129.0, 0.15)) # 219.3\nprint(line_revenue(1, 39.0)) # discount defaults to 0.0\nprint(line_revenue(quantity=3, unit_price=24.0, discount=0.25))The pieces: def, the function’s name, parameters in parentheses, a colon, and an indented body. discount=0.0 is a default, used when the caller leaves it out. The triple-quoted line under def is a docstring, which documents what the function does; editors show it when you hover over the name.
return sends a value back to the caller, and the call line_revenue(2, 129.0, 0.15) becomes that value. You can store it, add it, pass it to another function. Calling with names, as in the third example, makes long argument lists readable and protects you from swapping two numbers by accident.
Here is the money cleaner from Lesson 1.2, made reusable. It handles the dollar sign, stray spaces and thousands separators:
\ndef parse_money(text):\n \"\"\"Turn strings like ' $1,234.50' into the float 1234.5.\"\"\"\n cleaned = text.strip().replace(\"$\", \"\").replace(\",\", \"\")\n return float(cleaned)\n\nfor raw in [\" $129.00\", \"18.00\", \"$1,234.50\"]:\n print(raw, \"->\", parse_money(raw))Give functions verb names that say what they return (parse_money, line_revenue, clean_country) and keep each one to a single job; small functions are easy to test with a couple of print calls like the loop above. Now every messy total in the export can go through one tested function. If you discover a new format next month (say, a trailing USD), you fix it in one place.
A report that says 146825.4412 makes readers squint. An f-string, a string with f before the opening quote, lets you drop values into text inside {} and format them with a spec after a colon:
revenue = 146825.4412\norders = 642\nshare = 0.4493\n\nprint(f\"Q4 2025 revenue: ${revenue:,.2f}\") # thousands separator, 2 decimals\nprint(f\"Orders: {orders}, average {revenue / orders:.2f} per order\")\nprint(f\"Share of the year: {share:.1%}\") # percent with 1 decimal\nprint(f\"|{'Egypt':<12}|{orders:>6}|\") # left- and right-aligned columnsThe specs you will use most: ,.2f for money, .1% for shares (it multiplies by 100 for you), ,.0f for large whole numbers, and </> with a width for aligned text. Any expression works inside the braces, including arithmetic like revenue / orders.
When Python cannot continue, it raises an exception and prints a traceback. Beginners read it from the top and get lost. Read it from the bottom:
\nTraceback (most recent call last):\n File "report.py", line 9, in <module>\n total = parse_money(row["Total"])\n ~~~^^^^^^^^^\nKeyError: 'Total'The last line is the error type and message: a dictionary was asked for the key 'Total' and does not have it. One line up is the code that failed, with markers under the exact expression, and above that, the file and line number. The fix here is the column’s real name, 'total'.
The errors you will meet most, and what they almost always mean:
\n| Error | \nUsual cause | \n
|---|---|
NameError | \nA typo in a variable name, or using it before assigning it | \n
KeyError | \nA dictionary key or DataFrame column that does not exist (check spelling and case) | \n
TypeError | \nMixing types, such as text plus a number, or calling a function with the wrong arguments | \n
ValueError | \nThe type is right but the content is not, such as float("$65.00") | \n
IndexError | \nA list position past the end | \n
AttributeError | \nCalling a method the value does not have, often on None | \n
Some failures are part of the data, not bugs. A messy total such as "N/A" will never become a number. try / except lets you decide what happens instead:
def parse_money_or_none(text):\n try:\n return float(text.strip().replace(\"$\", \"\").replace(\",\", \"\"))\n except ValueError:\n return None\n\nprint(parse_money_or_none(\"$65.00\"), parse_money_or_none(\"N/A\"))Catch the specific exception you expect (ValueError here) and nothing else. A bare except: would also swallow a typo in your own code, and you would get None everywhere with no clue why.
That completes your Python toolkit. Section 2 puts it to work at scale: pandas, where a single line operates on every row of a table.
\n","toc":[{"id":"sec-1","text":"Defining a function","level":2},{"id":"sec-2","text":"Cleaning functions","level":2},{"id":"sec-3","text":"f-strings: numbers people can read","level":2},{"id":"sec-4","text":"Reading errors without panic","level":2},{"id":"sec-5","text":"Handling an error you expect","level":3}],"takeaways":["A function names a piece of logic; parameters are its inputs andreturn hands back its output.","A function that prints instead of returning gives back None, so its result cannot be used in further calculations.","f-strings format values inline: f"{revenue:,.2f}" gives 1,234.50 and f"{share:.1%}" gives 12.5%.","Read a traceback from the bottom - the last line names the error type and message, the lines above show where it happened.","try / except handles an error you expect, such as text that cannot become a number; never use it to hide errors you do not understand."],"further":[{"title":"Defining Functions","url":"https://docs.python.org/3/tutorial/controlflow.html#defining-functions"},{"title":"Formatted String Literals (f-strings)","url":"https://docs.python.org/3/tutorial/inputoutput.html#formatted-string-literals"},{"title":"Errors and Exceptions","url":"https://docs.python.org/3/tutorial/errors.html"},{"title":"Format Specification Mini-Language","url":"https://docs.python.org/3/library/string.html#format-specification-mini-language"}],"quiz":[{"q":"What is result after this runs?
def add_tax(amount):\n print(amount * 1.2)\n\nresult = add_tax(100)120.0","why":"The function displays 120.0, but displaying is not returning. Without return, the caller gets nothing back."},{"text":"None","why":"Correct. A function without a return statement returns None, whatever it printed along the way."},{"text":"The string "120.0"","why":"print writes text to the output; it does not hand that text back to the caller."}],"answer":1},{"q":"Which f-string prints Revenue: $146,825.44 when revenue = 146825.4412?
f"Revenue: ${revenue:.2f}"","why":"This gives $146825.44, with no thousands separator. The comma in the format spec adds it."},{"text":"f"Revenue: ${revenue:,}"","why":"The comma adds separators but there is no precision, so you get all the decimals of the float."},{"text":"f"Revenue: ${revenue:,.2f}"","why":"Correct. , adds thousands separators and .2f fixes two decimal places, rounding the value for display."},{"text":"f"Revenue: {round(revenue)}"","why":"This drops the cents and the dollar sign entirely."}],"answer":2},{"q":"The last line of a traceback reads:
\nKeyError: 'Total'What is the most likely cause?
\n","options":[{"text":"The code asks a dictionary (or DataFrame) for a key'Total' that does not exist; the real key is probably 'total'.","why":"Correct. KeyError always names the missing key. Keys are case-sensitive, so compare the spelling with the actual keys."},{"text":"The value of total cannot be converted to a number.","why":"A failed conversion raises ValueError, not KeyError."},{"text":"The variable Total was never defined.","why":"An undefined variable raises NameError: name 'Total' is not defined. The quotes in the message point to a key lookup."}],"answer":0},{"q":"When is wrapping code in try / except a good idea?
ValueError when converting user-typed text, and returning None for values that are not numbers."},{"text":"Whenever you see a SyntaxError.","why":"Syntax errors happen before the code runs, so try cannot catch them; you fix the code instead."}],"answer":1}],"exercise":{"kind":"python","files":[],"starter":"def parse_money(text):\n \"\"\"' $1,234.50' -> 1234.5\"\"\"\n pass\n\n\ndef line_revenue(quantity, unit_price, discount=0.0):\n \"\"\"quantity x unit_price x (1 - discount), rounded to 2 decimals\"\"\"\n pass\n\n\ndef format_money(amount):\n \"\"\"1234.5 -> '$1,234.50'\"\"\"\n pass\n\n\nprint(parse_money(\" $1,234.50\"), line_revenue(2, 129.0, 0.15), format_money(1234.5))\n","solution":"def parse_money(text):\n \"\"\"' $1,234.50' -> 1234.5\"\"\"\n return float(text.strip().replace(\"$\", \"\").replace(\",\", \"\"))\n\n\ndef line_revenue(quantity, unit_price, discount=0.0):\n \"\"\"quantity x unit_price x (1 - discount), rounded to 2 decimals\"\"\"\n return round(quantity * unit_price * (1 - discount), 2)\n\n\ndef format_money(amount):\n \"\"\"1234.5 -> '$1,234.50'\"\"\"\n return f\"${amount:,.2f}\"\n\n\nprint(parse_money(\" $1,234.50\"), line_revenue(2, 129.0, 0.15), format_money(1234.5))\n","checks":[{"id":"parse-simple","test":"parse_money('18.00') == 18.0 and parse_money(' $129.00') == 129.0"},{"id":"parse-thousands","test":"parse_money('$1,234.50') == 1234.5"},{"id":"revenue","test":"line_revenue(2, 129.0, 0.15) == 219.3 and line_revenue(3, 24.0, 0.25) == 54.0"},{"id":"revenue-default","test":"line_revenue(1, 39.0) == 39.0"},{"id":"format","test":"format_money(1234.5) == '$1,234.50' and format_money(18) == '$18.00'"}],"title":"Three helper functions for the report","prompt":"Complete three functions. parse_money(text) returns a float from strings like " $1,234.50", "$129.00" or "18.00". line_revenue(quantity, unit_price, discount=0.0) returns quantity × unit price × (1 − discount), rounded to 2 decimals; the discount defaults to 0. format_money(amount) returns a string like "$1,234.50": a dollar sign, thousands separators and exactly two decimals. Each function must return its result, not print it.
pass with a return statement in each function.","For parse_money, chain .strip(), .replace("$", "") and .replace(",", ""), then wrap it all in float().","For format_money, an f-string with the spec ,.2f does all the formatting: f"${amount:,.2f}"."],"explanation":"Each function does one job and returns its result, so they compose: format_money(line_revenue(2, parse_money("$129.00"), 0.15)) gives "$219.30". The default discount=0.0 means callers can leave it out for full-price lines. In format_money, the first $ is literal text and the braces hold the value with the spec ,.2f: comma separators, fixed two decimals. You will reuse exactly this logic on whole pandas columns in Section 3.
parse_money handles "18.00" and " $129.00"","parse-thousands":"parse_money handles thousands separators: "$1,234.50" becomes 1234.5","revenue":"line_revenue applies the discount and rounds to 2 decimals","revenue-default":"line_revenue works without a discount argument","format":"format_money(1234.5) returns "$1,234.50""}},"words":709,"readMinutes":3}