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Grade 9 · Unit 4: First steps in Python

Track: B (code: Python) · Tools: Python in the browser (JupyterLite) or Colab · Lessons: 3 Datasets: class-survey-synthetic

Big idea. Python lets us tell a computer what to do with data step by step: store values, repeat actions and reuse ideas in functions.

What you will be able to do

  • I can store values in variables and lists, and read items by position.
  • I can use a for loop and an if statement to process a list.
  • I can write and test a small function.

Words to know: program, variable (चर), value, list, index, loop, condition, function, argument, return value, error message. Full list: curriculum/framework/glossary.md.

Notebook: notebooks/first_python.ipynb (open in JupyterLite, Colab or Jupyter; runs offline on the synthetic table).

Before you start

You need no programming experience. You do need Grade 8's mean, median and range, because we will teach the computer to calculate them. Open the notebook: a notebook is a page of cells; click a code cell and press Shift + Enter to run it. The result appears underneath.

Lesson 1: Variables and lists

Hook (5 min). Where does a computer keep the number 25 so it can use it again later? How would it keep the travel times of 36 students?

Explanation

A program is a list of instructions the computer follows in order, top to bottom. Python is a programming language that is popular in data science because it reads almost like English and has excellent tools for tables (pandas, Unit 5) and charts (Unit 6).

Variables. A variable is a name attached to a value. The = sign means "make this name refer to this value" (assignment), not "is equal to".

age = 14
name = "Sita"
sleep_hours = 8.2
print(name, "is", age, "years old and slept", sleep_hours, "hours")

Output: Sita is 14 years old and slept 8.2 hours

Values have types: 14 is an integer (int), 8.2 a decimal number (float), "Sita" text (a string, str), True/False a Boolean (bool). Text always goes in quotes.

Python does arithmetic with + - * /, powers with **, and whole-number division with // and remainder with %:

minutes = 135
hours = minutes // 60       # 2
left_over = minutes % 60    # 15
print(hours, "hours and", left_over, "minutes")

Anything after # is a comment for humans; Python ignores it.

Lists. A list stores many values in order, inside square brackets:

travel = [53, 27, 40, 23, 11, 48, 21, 7, 12, 52]   # minutes, first 10 students
print(len(travel))      # how many items: 10
print(travel[0])        # first item: 53
print(travel[-1])       # last item: 52
print(travel[0:3])      # items 0, 1, 2: [53, 27, 40]

Positions (indexes) start at 0, not 1. travel[0] is the first item; travel[9] is the tenth (and last). travel[10] gives an IndexError because there is no eleventh item. Negative indexes count from the end.

Lists can change:

travel[1] = 30          # correct the second value
travel.append(19)       # add a value at the end
print(travel)
print(sum(travel), min(travel), max(travel), sorted(travel))

sum, min, max, sorted and len are built-in functions: Python's tools that work on lists.

Error messages are friends. When something is wrong, Python stops and prints an error. Read the last line first: NameError: name 'travl' is not defined means you spelled a name wrong; SyntaxError means the grammar is wrong (a missing bracket or quote); TypeError usually means you mixed types ("5" + 3).

Activity (20 min) — PRIMM

  1. Predict what each cell in section 1 of the notebook prints, write your prediction, then run it.
  2. Investigate: what does travel[2:5] give? travel[-2]? What happens with travel[20]?
  3. Modify: make a list heights of 8 classmates' heights (cm). Print its length, first and last item, the smallest and largest.
  4. Make: compute the range of heights (largest − smallest) and print it in a sentence with the unit.

Common mistakes

  • Forgetting that indexes start at 0.
  • Writing print(travel[1, 2]) instead of travel[1:3].
  • Mismatched quotes or brackets ("Sita', [1, 2).
  • Using a variable before giving it a value.

Check (5 min). 1. minutes = [5, 20, 35]; minutes[0]? 2. len(minutes)? 3. = or ==: which assigns?

Reflect (2 min). What surprised me? Who or what is missing from this data?

Lesson 2: Loops and conditions

Hook (5 min). Adding 36 numbers by hand takes a few minutes. Adding 3 million (one per person in a province) would take years. How do we make the computer do the same step again and again?

Explanation

A for loop repeats some lines once for each item in a list:

travel = [53, 27, 40, 23, 11, 48, 21, 7, 12, 52]
total = 0
for m in travel:
    total = total + m
print("Total minutes:", total)

Read it as: "start with total = 0; for each value m in the list, add m to total". After the loop, total is 294. The variable m takes each value in turn: 53, then 27, then 40…

Indentation matters. The lines that belong inside the loop are indented (4 spaces). The print is not indented, so it runs once, after the loop finishes. Indent it and it runs 10 times. In Python, indentation is part of the grammar, not decoration.

An if statement runs lines only when a condition is True:

long_trips = 0
for m in travel:
    if m > 30:
        long_trips = long_trips + 1
print(long_trips, "students travel more than 30 minutes")

Conditions use comparison operators: == (equal — two signs!), != (not equal), <, >, <=, >=, and combine with and, or, not. Add other cases with elif ("else if") and else:

for m in travel[:4]:
    if m <= 15:
        label = "short"
    elif m <= 40:
        label = "medium"
    else:
        label = "long"
    print(m, label)

A pattern you will use forever: start a variable (a counter, a total or an empty list), loop over the data, update the variable inside the loop, use the result after the loop.

Activity (20 min) — PRIMM

  1. Predict the total and the count of long trips, then run section 2 of the notebook.
  2. Investigate: move print inside the loop (indent it). What changes? Why?
  3. Modify: count trips of 15 minutes or less.
  4. Make: loop over the list and build a new list of the trips longer than 30 minutes (start with long_list = [] and use long_list.append(m)).

Common mistakes

  • if m = 30: (one = assigns; comparisons need ==).
  • Forgetting the colon : at the end of for and if lines.
  • Mixing tabs and spaces, or indenting by different amounts.
  • Resetting the counter inside the loop.

Check (5 min). 1. What does 'for m in minutes' do? 2. Why is indentation important? 3. Count of values > 30 uses…

Reflect (2 min). What surprised me? Who or what is missing from this data?

Lesson 3: Functions

Hook (5 min). You have now calculated a mean four times this year. How could you write the steps once and use them for any list?

Explanation

A function packages steps under a name. You define it once with def, then call it as often as you like:

def my_mean(values):
    """Return the mean (average) of a list of numbers."""
    total = 0
    for v in values:
        total = total + v
    return total / len(values)

print(my_mean([20, 20, 30, 40, 90]))   # 40.0
  • values is a parameter: a name for whatever list you pass in (the argument).
  • return sends the result back to where the function was called. Without return the function gives back None.
  • The text in triple quotes is a docstring: it explains what the function does.

The median needs the list sorted, then the middle value (or the mean of the two middle values):

def my_median(values):
    """Return the median of a list of numbers."""
    s = sorted(values)
    n = len(s)
    middle = n // 2
    if n % 2 == 1:            # odd count: one middle value
        return s[middle]
    else:                     # even count: mean of the two middle values
        return (s[middle - 1] + s[middle]) / 2

print(my_median([20, 20, 30, 40, 90]))   # 30
print(my_median([1, 2, 3, 4]))           # 2.5

For n = 4, middle = 2, so the two middle values are s[1] and s[2], the 2nd and 3rd items. Tracing through a small example by hand like this is how programmers check their thinking.

Test with small lists whose answers you know. assert stops the program with an error if a statement is false, and does nothing if it is true:

assert my_mean([2, 4, 6]) == 4
assert my_median([5, 1, 3]) == 3
assert my_median([1, 2, 3, 4]) == 2.5
print("All tests passed")

Why functions? Write once, use many times; fix a mistake in one place; give a name to an idea, so the program reads like a description of the analysis. Python already has many functions for data (the statistics module has mean and median; pandas in Unit 5 has hundreds). Writing your own once helps you understand what they do.

Activity (20 min) — PRIMM

  1. Predict my_mean([20, 20, 30, 40, 90]) and my_median([1, 2, 3, 4]), then run section 3.
  2. Investigate: what happens with my_mean([])? Why? (Read the error message.)
  3. Modify: write my_range(values) that returns max − min. Test it with assert.
  4. Make: write count_above(values, limit) that returns how many values are above limit. Use it to count students sleeping more than 8 hours in the class list from the notebook.

Common mistakes

  • Printing inside the function instead of returning (you can't then use the result).
  • Forgetting to call the function (my_mean without brackets is the function itself, not its answer).
  • Sorting the original list by accident (values.sort() changes it); sorted(values) makes a copy.

Check (5 min). 1. What does return do? 2. my_median([1, 2, 3, 4])? 3. Why test with small lists?

Reflect (2 min). What surprised me? Who or what is missing from this data?

Unit summary

  • A program runs top to bottom. = assigns a value to a name. Types: int, float, str, bool.
  • Lists hold values in order; indexes start at 0; len, sum, min, max, sorted work on lists.
  • for x in list: repeats indented lines once per item; if / elif / else choose; == compares.
  • Counter/total pattern: start, loop and update, use after the loop.
  • def name(parameters): … return result; test with assert on small examples.
  • Read error messages from the last line up.

Practice exercises

  1. ★ What does this print? x = 7 then x = x + 3 then print(x * 2).
  2. ★ days = ["Sun", "Mon", "Tue", "Wed"]. What are days[1], days[-1], len(days), days[1:3]?
  3. ★ What is wrong? if age = 14: print("Grade 9").
  4. ★★ Write a loop that prints each value of [5, 12, 30, 45] converted to hours (÷ 60), rounded to 2 decimals (round(x, 2)).
  5. ★★ Write a loop that counts how many items in ["walk", "bus", "walk", "bicycle", "walk"] are "walk".
  6. ★★ Write percent(part, whole) returning part ÷ whole × 100. Test: percent(26, 36) ≈ 72.2.
  7. ★★ Trace by hand: what does my_median([9, 1, 5, 7]) return? Show s, n and middle.
  8. ★★★ Write my_mode(values) returning the most frequent value. (Hint: loop, and use values.count(v).)
  9. ★★★ Write fahrenheit_to_celsius(f) using C = (F − 32) × 5 ÷ 9 and convert a list of temperatures [59, 68, 86, 104] with a loop.
  10. ★★★ This function has a bug. Find and fix it, then write an assert that would have caught it.
def count_long(values, limit):
    count = 0
    for v in values:
        count = 0
        if v > limit:
            count = count + 1
    return count

Exercises with real data

R1. A week of real weather (RD-06). Look up yesterday's and the past week's maximum temperature for your town on Open-Meteo or a weather app. Type the 7 values into a Python list. Use your functions to compute the mean, median and range, and print one sentence with units. Offline fallback: the first 7 values of mean_temp_c from climate_monthly_synthetic.csv, typed in by hand.

R2. Earthquake list (RD-05). Copy the magnitudes of the 15 strongest 2015 earthquakes from the USGS list (or your Unit 3 SQL result) into a Python list. Count how many are 6.0 or more, compute the mean, and write a loop that labels each as "moderate" (< 5), "strong" (5–5.9) or "major" (≥ 6).

R3. Prices (RD-08). Make a list of 10 daily tomato prices (Rs/kg) from the Kalimati data or today's market page. Write a function percent_change(old, new) and use it in a loop to print the day-to-day change.

Unit project: My first data script

Follow Problem · Plan · Data · Analysis · Conclusion. Write a short script (in the notebook) that stores one variable from your class data in a list, uses your own my_mean, my_median and my_range functions (with assert tests), counts values above a threshold with a loop, and prints a three-sentence summary. Full brief and rubric: project.md.

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