Data acquisition

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Quick Questions

Shade in the A or B circle for each question.

1. Which describes data acquisition?

A Capturing data from a source and bringing it into a solution in a usable form

B Deleting old data from a database to free up space

2. A student is building a school canteen app. Which is the better first step in data acquisition?

A Design the app's colour scheme

B Choose a suitable source, such as the canteen's sales records

3. Which choice of source fits this need: the current temperature at a weather station?

A A sensor or API that gives live readings

B A survey of students done last year

4. Which approach captures data more accurately?

A Reading values directly from a sensor or form field as they are produced

B Retyping the values from memory later

5. A survey form lets students type their year level as free text. What is the likely problem?

A The data will always be perfectly consistent

B Entries like 'Yr 11', 'eleven' and '11' will be inconsistent

Match the Pairs

Draw a line connecting each item on the left to its match on the right.

Left column		Right column
1data = read_csv("sensor_log.csv")		AThe data is stored straight away without being checked on arrival, so errors and missing values go into the solution.
2if reading >= 0 and reading <= 50 then		BBrings data from a chosen file source into the solution so it can be used
3Choosing a source: the solution gets its weather data from an open data portal through an API		CThe input is used without confirming it is a number. Typed input is text, so the data was not captured in a usable form.
4Capturing accurately: typed survey answers are entered twice and compared		Dif entry1 = entry2 then accept(entry1)
5data <- read_file("survey.csv") store(data)		EChecks the data on arrival to see if it is reasonable before accepting it
6age <- input() age <- age + 1		Fsource <- "https://data.example.gov.au/weather"

Definitions

data acquisition

Fill in the Blanks

Complete each line of code by filling in the missing parts.

print "Enter the temperature" _____ temp

line ← readLine(file) fields ← _____(line, ",")

if temp < -10 __ temp > 50 then print "Reading rejected" end if

if name _ "" then print "Missing value" end if

repeat input score _____ score >= 0 and score <= 100

Spot the Error

Shade in the letter of the line that contains an error.

Question 1

A f = open("temps.csv")

B lines = f.readlines()

C f.close

D print(len(lines))

Question 2

A data = []

B for line in open("a.csv")

C data.append(line.strip())

Question 3

A age = int(input("Age: "))

B if age < 0 and age > 120:

C print("Invalid age")

Question 4

A line = "Ava,7,Red"

B parts = line.split(",")

C year = int(parts[3])

D print(year)

Question 5

A import csv

B f = open("marks.csv", "w")

C reader = csv.reader(f)

D rows = list(reader)

Answer Key

Data acquisition

Section A: Quick Questions

A — Capturing data from a source and bringing it into a solution in a usable form

B — Choose a suitable source, such as the canteen's sales records

A — A sensor or API that gives live readings

A — Reading values directly from a sensor or form field as they are produced

B — Entries like 'Yr 11', 'eleven' and '11' will be inconsistent

Section B: Match the Pairs

data = read_csv("sensor_log.csv") → Brings data from a chosen file source into the solution so it can be used

if reading >= 0 and reading <= 50 then → Checks the data on arrival to see if it is reasonable before accepting it

Choosing a source: the solution gets its weather data from an open data portal through an API → source <- "https://data.example.gov.au/weather"

Capturing accurately: typed survey answers are entered twice and compared → if entry1 = entry2 then accept(entry1)

data <- read_file("survey.csv") store(data) → The data is stored straight away without being checked on arrival, so errors and missing values go into the solution.

age <- input() age <- age + 1 → The input is used without confirming it is a number. Typed input is text, so the data was not captured in a usable form.

Section C: Definitions

data acquisition — Capturing data from a source and bringing it into a solution in a usable form: choose the source, capture it accurately, then check it on arrival.

Section D: Fill in the Blanks

print "Enter the temperature"
input temp

line ← readLine(file)
fields ← split(line, ",")

if temp < -10 or temp > 50 then
  print "Reading rejected"
end if

if name = "" then
  print "Missing value"
end if

repeat
  input score
until score >= 0 and score <= 100

Section E: Spot the Error

C — Without brackets, f.close only names the method and never calls it, so the file stays open. It should be f.close().

B — A for loop header must end with a colon. It should be for line in open("a.csv"):

B — No age can be below 0 and above 120 at the same time, so 'and' never catches bad data. The reasonableness check needs 'or'.

C — The line splits into 3 fields, indexes 0 to 2, so parts[3] is out of range. The year level is in parts[1].

B — Mode "w" opens the file for writing and wipes the existing data. To read the source data, open it normally or with "r".