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Data Science Applied
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Module 1 · Python for Data: pandas, numpy
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DataFrame.melt — wide to long
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📝 **Question:** Why prefer long ('tidy') format for downstream analysis? 📋 Pick the right answer. 💡 **Hint:** Re-read the theory above if unsure.
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📝 **Question:** Why prefer long ('tidy') format for downstream analysis? 📋 Pick the right answer. 💡 **Hint:** Re-read the theory above if unsure.
A
Wide is always better — fewer rows means faster operations across every pandas method you might ever call on the frame later
B
Long format has one observation per row with explicit identifier columns
C
Long uses less memory because every value is stored once in a flat layout instead of being aligned into a sparse wide grid with empty cells
D
Long is the only shape pandas accepts as input to its groupby and pivot_table primitives; wide tables raise TypeError at runtime
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