python一些科學計算基礎

import matplotlib.pyplot as plt import numpy as np import pandas as pd from mpl_toolkits.mplot3d import Axes3D

t = np.arange(0,5,0.2)

plt.plot(t,t**2,'g^')

plt.ylabel('nubers')

plt.xlabel('seed')

plt.title('title')

plt.grid(True)

plt.yscale('log')

plt.show()

#sinx的函數圖

t = np.arange(0,2.0,0.01)

s= np.sin(2 * np.pi*t)

fig,ax = plt.subplots()

ax.set_ylabel('sin')

ax.set_xlabel('df')

ax.plot(t,s)

plt.grid(True)

plt.show()

#餅狀圖

labels ='frogs','hogs','dogs','logs'

sizes =[15,45,10,30]

explode=(0,0.1,0,0)

fig,ax = plt.subplots()

ax.pie(sizes,explode=explode,labels=labels,autopct='%1.lf%%',

shadow=True,startangle=90)

plt.show()

#ax.scatter表示散點圖

#化三維圖形

fig,ax = plt.subplots()

fig = plt.figure()

ax = fig.add_subplot(111,projection ='3d')

x,y=np.random.rand(2,100)*4

ax.bar3d(x,y,x,x,y,x**y)

plt.show()

df=pd.DataFrame(np.random.randn(1000,4), index=pd.date_range('1/1/2000',periods=1000),columns=list('abcd'))

df =df.cumsum()

plt.show()

df = pd.DataFrame(np.random.randn(5,4),index=['A','B','C','D','E'],columns=pd.Index([1,2,3,4])) df.plot(kind='bar') plt.show()

import numpy as np data = np.array([[1,2,3],[3,4,5]]) data = np.zeros((2,3)) data1 = np.empty((2,3)) data2 = np.arange(3,6,2) data3 = np.random.rand(2,3,) data4 = np.arange(100) data5 = np.arange(0,20,2) data5[1:4:2]=1 data6 = np.array([[1,2,3],[4,5,6],[7,8,9]]) data6.sum(axis=1) data6.min(1) print(data6.std())#計算標準差 print(data6.var())#計算方差