Given a 2D NumPy array data representing daily temperatures for a week (rows = days, columns = cities), how would you find the highest temperature recorded in each city?

hard📝 Application Q15 of 15

NumPy - Aggregation Functions

Given a 2D NumPy array data representing daily temperatures for a week (rows = days, columns = cities), how would you find the highest temperature recorded in each city?

Anp.max(data, axis=1)

Bnp.min(data, axis=1)

Cnp.min(data, axis=0)

Dnp.max(data, axis=0)

Step-by-Step Solution

Solution:

Step 1: Understand data layout
Rows represent days, columns represent cities. To find max per city, we want max down each column.
Step 2: Use axis=0 for column-wise operation
Using np.max(data, axis=0) finds the maximum temperature for each city across all days.
Final Answer:
np.max(data, axis=0) -> Option D
Quick Check:
Max per city = np.max(data, axis=0) [OK]

Quick Trick: axis=0 aggregates down columns (cities) [OK]

Common Mistakes:

Using axis=1 to find max per city
Using np.min() instead of np.max()
Confusing rows and columns

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More NumPy Quizzes

Given a 2D NumPy array data representing daily temperatures for a week (rows = days, columns = cities), how would you find the highest temperature recorded in each city?

Step 1: Understand data layout

Step 2: Use axis=0 for column-wise operation

Final Answer:

Quick Check:

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