Mikumiku339的博客

文件下载targetA.csvtargetB.csv要求文件格式及说明处理结果代码import numpy as npimport pandas as pdfrom pandas import read_csvimport matplotlibimport matplotlib.pyplot as plt from matplotlib.pyplot import MultipleLocatormatplotlib.rcParams['axes.unicode_minu

HP滤波图文介绍目标原理python实现代码结果目标我们希望去除信号中的趋势，使信号看起来是直的原理python实现代码import numpy as npimport matplotlib.pyplot as plt%matplotlib inlinedef hp(y, lamb=10): def D_matrix(N): #(N-1,N) 元素全为0 D = np.zeros((N-1,N)) #后(N-1,N-1)对角

python绘制阿里巴巴股票k线图准备流程效果准备安装几个库pip install datetimepip install matplotlibpip install pandas_datareaderpip install mpl_finance流程获取数据数据处理交给mpl_finance绘图#代码import datetime as dtimport matplotlib.dates as mdatesimport matplotlib.pyplot as plti

Numpy学习:分割import numpy as npa = np.arange(12).reshape(3,4)print(np.split(a,2,axis=1))print(np.split(a,3,axis=0))#不等量分割print(np.array_split(a,3,axis=1))

Numpy学习:合并import numpy as npa = np.array([1,2,3])b = np.array([4,5,6])#上下合并 注意参数为tupleprint(np.vstack((b,a)))#左右合并print(np.hstack((a,b)))#增加维度print(a[:,np.newaxis])print(a[:,np.newaxis].shape)print(a[np.newaxis,:])print(a[np.newaxis,:].shap

Numpy学习:索引import numpy as npa = np.arange(3,15).reshape(3,4)print(a)#切片print(a[0:2,1:2])#逐行for row in a: print(row)#逐列for column in a.T: print(column)#压缩到一维print(a.flatten())for item in a.flat: print(item)...

Numpy学习:基本运算import numpy as npa = np.arange(2,14).reshape((3,4))#返回元素下标print(np.argmax(a))print(np.argmin(a))#均值print(a.mean())print(np.mean(a))print(np.average(a))#中位数print(np.median(a))#累加print(np.cumsum(a))#累差print(np.diff(a))#取得所

import numpy as npa = np.array([10,20,30,40])b = np.ones(4)#加减乘除乘方print(a+b)print(a-b)print(a*b)print(a/b)print(b**2)#三角函数print(10*np.sin(a))#蒙版print(a <= 20)#二维a = np.array([[1,1],[0,1]])b = np.arange(4).reshape((2,2))#两者等价c_dot =

Numpy学习：属性与创建import numpy as np#列表转化为矩阵array = np.array([[1,2,3],[4,5,6]])#维度print(array.ndim)#行列数print(array.shape)#元素个数print(array.size)#数据格式#int64a = np.array([1,2,3],dtype=np.int)#int32a = np.array([1,2,3],dtype=np.int32)#float64a = n