随笔分类 - matplotlib
摘要：import matplotlib.pyplot as plt import numpy as np x=["q","w","e","r","t","y"]#不变的依然是x表示标签值 y=[4,6,7,6,3,9] plt.barh(x,y,align="center",color="green",
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摘要：#画图的基本命令import matplotlib.pyplot as pltimport numpy as npx=np.linspace(0.05,10,1000)y=np.sin(x)plt.plot(x,y,ls='--',lw=2,c='red',label='sin(x)')plt.le
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摘要：import matplotlib as mplimport matplotlib.pyplot as pltx=["a","b","c","d","e","f"]y=[2,3,6,7,9,5,]y1=[5,8,9,3,4,6,]plt.xlim(0,20)plt.barh(x,y,align="c
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摘要：#绘制柱状图import matplotlib.pyplot as pltimport numpy as npx=[1,2,3,4,5,6]y=[3,4,5,6,7,8]c=np.mean(y)plt.bar(x,y,color="red",hatch="/",tick_label=["q","er
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摘要：import matplotlib.pyplot as pltimport matplotlib as mpl#下面的两行是解决中文乱码的问题，sans-serif就是无衬线字体，是一种通用字体族mpl.rcParams['font.sans-serif']=['SimHei']#指定默认字体是Si
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摘要：import matplotlib.pyplot as pltimport numpy as npfig=plt.figure()ax1=fig.add_subplot(121)t=np.arange(0.0,5,0.01)s=np.cos(2*np.pi*t)line,=ax1.plot(t,s,
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摘要：import numpy as np import matplotlib.pyplot as plt def f(t): return np.exp(-t) * np.cos(2*np.pi*t) t1 = np.arange(0.0, 3.0, 0.01) ax1 = plt.subplot(21
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摘要：import matplotlib.pyplot as pltimport numpy as npx=np.linspace(0.05,10,1000)y=np.sin(x)plt.plot(x,y,ls="-.",lw=2.3,color="black",label="sin()")plt.ann
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摘要：import numpy as npimport matplotlib.pyplot as pltfrom scipy.optimize import curve_fit#用python拟合函数最主要模块就是cure_fit#准备数据x=[一组数据]y=[一组数据]#定义你自己想要拟合的函数def
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摘要：import matplotlib.pyplot as pltimport numpy as npimport matplotlib as mpl #解决中文乱码和正负号问题mpl.rcParams["font.sans-serif"]=["SimHei"]mpl.rcParams["axes.un
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摘要：#在图形中添加指示import matplotlib.pyplot as pltimport numpy as npx=np.linspace(0.05,10,1000)y=np.sin(x)plt.plot(x,y,label="plot figure",ls=":",c="red",lw=2)p
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