Your thesis codes satisfaction scores on a 1–5 Likert scale. Your methodology says anything below 2.5 is low, 2.5–4.0 is medium, above 4.0 is high. In Excel, how do you implement that rule?
Nested IF: =IF(A1<2.5,"low",IF(A1<4.0,"medium","high")). Works, but it's unreadable and breaks if I change the thresholds.
is_valid_response from yesterday gave you a guard — you only categorise rows that passed validation. Now for the rows that pass, if/elif/else is Python's three-tier branch. It reads like English and the thresholds are named arguments:
score = 3.2
mid = 2.5
high = 4.0
if score < mid:
category = "low"
elif score < high:
category = "medium"
else:
category = "high"
print(category) # medium
If the first if is False, Python checks elif automatically? It doesn't re-evaluate score < mid again?
Exactly right — Python tries conditions top to bottom and stops at the first one that's True. If score < mid is False, it moves to elif score < high. If that's also False, else catches everything remaining. You never check the same condition twice:
def categorize_satisfaction(score: float, mid: float, high: float) -> str:
if score < mid:
result = "low"
elif score < high:
result = "medium"
else:
result = "high"
print(f"Score {score}: {result}")
return result
And because mid and high are parameters, I can adjust the thresholds for different studies without rewriting the function.
Your nested Excel IF just became a readable, reusable function.
Week 1 done — I can format, clean, validate, and categorise any response from my survey. That's my entire pre-analysis pipeline.
The else is not optional. Without it, a score of exactly 4.0 falls through all conditions and returns None instead of "high". Always close the branch with else when categorising numeric ranges — it's the catch-all that makes the logic complete.
Python evaluates conditions top to bottom and stops at the first True:
if score < mid: # checked first
return "low"
elif score < high: # only checked if first is False
return "medium"
else: # catch-all — always runs if nothing matched
return "high"elif not ifTwo separate if statements both evaluate independently. elif short-circuits — Python skips it entirely if the first if already matched. For mutually exclusive categories, always use elif.
< mid excludes the midpoint itself (it falls into elif). < high excludes 4.0 exactly (it falls into else). Design your thresholds intentionally.
Your thesis codes satisfaction scores on a 1–5 Likert scale. Your methodology says anything below 2.5 is low, 2.5–4.0 is medium, above 4.0 is high. In Excel, how do you implement that rule?
Nested IF: =IF(A1<2.5,"low",IF(A1<4.0,"medium","high")). Works, but it's unreadable and breaks if I change the thresholds.
is_valid_response from yesterday gave you a guard — you only categorise rows that passed validation. Now for the rows that pass, if/elif/else is Python's three-tier branch. It reads like English and the thresholds are named arguments:
score = 3.2
mid = 2.5
high = 4.0
if score < mid:
category = "low"
elif score < high:
category = "medium"
else:
category = "high"
print(category) # mediumIf the first if is False, Python checks elif automatically? It doesn't re-evaluate score < mid again?
Exactly right — Python tries conditions top to bottom and stops at the first one that's True. If score < mid is False, it moves to elif score < high. If that's also False, else catches everything remaining. You never check the same condition twice:
def categorize_satisfaction(score: float, mid: float, high: float) -> str:
if score < mid:
result = "low"
elif score < high:
result = "medium"
else:
result = "high"
print(f"Score {score}: {result}")
return resultAnd because mid and high are parameters, I can adjust the thresholds for different studies without rewriting the function.
Your nested Excel IF just became a readable, reusable function.
Week 1 done — I can format, clean, validate, and categorise any response from my survey. That's my entire pre-analysis pipeline.
The else is not optional. Without it, a score of exactly 4.0 falls through all conditions and returns None instead of "high". Always close the branch with else when categorising numeric ranges — it's the catch-all that makes the logic complete.
Python evaluates conditions top to bottom and stops at the first True:
if score < mid: # checked first
return "low"
elif score < high: # only checked if first is False
return "medium"
else: # catch-all — always runs if nothing matched
return "high"elif not ifTwo separate if statements both evaluate independently. elif short-circuits — Python skips it entirely if the first if already matched. For mutually exclusive categories, always use elif.
< mid excludes the midpoint itself (it falls into elif). < high excludes 4.0 exactly (it falls into else). Design your thresholds intentionally.
Lin is coding satisfaction scores from her psychology thesis survey into three tiers for her regression model. Write `categorize_satisfaction(score, mid, high)` that returns `'low'` if `score < mid`, `'medium'` if `score < high`, and `'high'` otherwise. For example, `categorize_satisfaction(3.2, 2.5, 4.0)` should return `'medium'`.
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