Numpy는 확실히 R의 문법과 유사한 점이 많은 것 같습니다. 통계를 다루다보니 그런 유사점이 생기지 않았나 싶네요. 기본적인 문법을 정리해보았습니다.
평균, 중위값
# np_baseball is available
# Import numpy
import numpy as np
# Create np_height from np_baseball
np_height = np_baseball[:,0]
# Print out the mean of np_height
print(np.mean(np_height))
# Print out the median of np_height
print(np.median(np_height))
표준편차, 상관계수
# np_baseball is available
# Import numpy
import numpy as np
# Print mean height (first column)
avg = np.mean(np_baseball[:,0])
print("Average: " + str(avg))
# Print median height. Replace 'None'
med = np.median(np_baseball[:,0])
print("Median: " + str(med))
# Print out the standard deviation on height. Replace 'None'
stddev = np.std(np_baseball[:,0])
print("Standard Deviation: " + str(stddev))
# Print out correlation between first and second column. Replace 'None'
corr = np.corrcoef(np_baseball[:,0],np_baseball[:,1])
print("Correlation: " + str(corr))
조건을 만족하는 index 추출하기
# heights and positions are available as lists
# Import numpy
import numpy as np
# Convert positions and heights to numpy arrays: np_positions, np_heights
np_positions = np.array(positions)
np_heights = np.array(heights)
# Heights of the goalkeepers: gk_heights
gk_heights = np_heights[np_positions=='GK']
# Heights of the other players: other_heights
other_heights = np_heights[np_positions!='GK']
# Print out the median height of goalkeepers. Replace 'None'
print("Median height of goalkeepers: " + str(np.median(gk_heights)))
# Print out the median height of other players. Replace 'None'
print("Median height of other players: " + str(np.median(other_heights)))