Introduction to Python

# Print out the weight of the first ten baseball players.
print(baseball_weights[:10])

# What is the median weight of all baseball players in the data?
print(np.median(baseball_weights * 0.453592))

# Who is taller on average? Baseball players or soccer players? Keep in mind that baseball heights are stored in inches!
avg_height_baseball = np.round(np.mean(baseball_heights * 2.54), 2)
avg_height_soccer = np.round(np.mean(soccer_heights), 2)

print(f'Average height of a baseball player: {avg_height_baseball}')
print(f'Average height of a soccer player: {avg_height_soccer}')

# The values in soccer_shooting are decimals. Convert them to whole numbers (e.g., 0.98 becomes 98).
soccer_shooting = soccer_shooting * 10
soccer_shooting

# Do taller players get higher ratings? Calculate the correlation between soccer_ratings and soccer_heights to find out!
x = soccer_ratings
y = soccer_heights

print(np.corrcoef(soccer_ratings, soccer_heights))

# Две переменные могут быть связаны таким образом, что при возрастании значений одной из них значения другой убывают. 
# Это и показывает отрицательный коэффициент корреляции.
# Про такие переменные говорят, что они отрицательно коррелированы.

# What is the average rating for attacking players ('A')?
average_rating_A_players = np.mean(soccer_ratings[soccer_positions == 'A'])
print(average_rating_A_players)