data_analysis19

笔记

import numpy as np

np.random.seed(10)
t = np.random.randint(0,20,(3,4))
print(t)

t2 = np.array([[3,3,3,3,3,3],[3,3,3,3,10,11],[12,13,14,15,16,17],[18,19,20,20,20,20]]).astype("float")
t2[3,3] = np.nan
print(t2)
t2[:,0] = 0
print(t2)
np.count_nonzero(t2)
print(t2!=t2)
print(np.count_nonzero(t2!=t2))
print(np.isnan(t2))
print(np.count_nonzero(np.isnan(t2)))
print(np.sum(t2))

t3 = np.arange(12).reshape((3,4))
print(t3)
print(np.sum(t3))
print(np.sum(t3,axis=0))
print(np.sum(t3,axis=1))
print("*"*66)
print(np.sum(t2,axis=0))
# 和
print(t2.sum(axis=0))
# 均值
print(t2.mean(axis=0))
# 中值
# print(t2.median(axis=0)) # 有nan
# 最大值
print(t2.max(axis=0))
# 最小值
print(t2.min(axis=0))
# 极值
print(np.ptp(t2,axis=0))
# 标准差
print(t2.std(axis=0))