Bringing it all together: Pokémon z-scores

A list of 720 Pokémon has been loaded into your session as names. Each Pokémon's corresponding Health Points is stored in a NumPy array called hps. You want to analyze the Health Points using the z-score to see how many standard deviations each Pokémon's HP is from the mean of all HPs.

The below code was written to calculate the HP z-score for each Pokémon and gather the Pokémon with the highest HPs based on their z-scores:

poke_zscores = []

for name,hp in zip(names, hps):
    hp_avg = hps.mean()
    hp_std = hps.std()
    z_score = (hp - hp_avg)/hp_std
    poke_zscores.append((name, hp, z_score))

highest_hp_pokemon = []

for name,hp,zscore in poke_zscores:
    if zscore > 2:
        highest_hp_pokemon.append((name, hp, zscore))

This exercise is part of the course

Writing Efficient Python Code

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Hands-on interactive exercise

Have a go at this exercise by completing this sample code.

# Calculate the total HP avg and total HP standard deviation
hp_avg = ____.____
hp_std = ____.____

# Use NumPy to eliminate the previous for loop
z_scores = (____ - ____)/____

# Combine names, hps, and z_scores
poke_zscores2 = [*____(names, hps, z_scores)]
print(*poke_zscores2[:3], sep='\n')

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