数据可视化基础专题（二十六）：numpy80题（五）NumPy进阶修炼第三期｜41-60

import numpy as np
import pandas as pd
import warnings
warnings.filterwarnings("ignore")

data = np.random.randint(1,100, [6,6])
data

np.amax(data, axis=0)

np.amin(data, axis=1)

np.unique(data,return_counts=True)

data.argsort()

np.repeat(data, 2, axis=0)

np.unique(data,axis = 0)

np.random.choice(data[0:1][0], 3, replace=False)

a = data[1:2]
b = data[2:3]
index=np.isin(a,b)
array=a[~index]
array

(~data.any(axis=1)).any()

data.sort(axis = 1)
data

data1 = data.astype(float)

data1[data1 < 5] = np.nan
data1

data1 = data1[~np.isnan(data1).any(axis=1), :]

data1

vals, counts = np.unique(data1[0,:], return_counts=True)
print(vals[np.argmax(counts)])

a = 100
data1.flat[np.abs(data1 - a).argmin()]

data1 - data1.mean(axis=1, keepdims=True)

a = np.max(data1) - np.min(data1)
(data1 - np.min(data1)) / a

mu = np.mean(data1, axis=0)
sigma = np.std(data1, axis=0)
(data1 - mu) / sigma

np.savetxt(‘test.txt‘,data1)