《Python数据可视化之matplotlib实践》 源码 第一篇 入门 第四章
图 4.1
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import matplotlib import matplotlib.pyplot as plt import numpy as np # 设置matplotlib正常显示中文和负号 matplotlib.rcParams['font.sans-serif']=['SimHei'] # 用黑体显示中文 matplotlib.rcParams['axes.unicode_minus']=False # 正常显示负号 x=np.linspace(-2*np.pi, 2*np.pi, 200) y=np.sin(x) y1=np.cos(x) plt.plot(x,y, label=r"$\sin(x)$") plt.plot(x,y1,label=r"$\cos(x)$") plt.legend(loc="lower left") plt.title("正弦函数和余弦函数的折线图") plt.show()
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图 4.2
![](https://images.cnblogs.com/OutliningIndicators/ContractedBlock.gif)
import matplotlib import matplotlib.pyplot as plt import numpy as np # 设置matplotlib正常显示中文和负号 matplotlib.rcParams['font.sans-serif']=['SimHei'] # 用黑体显示中文 matplotlib.rcParams['axes.unicode_minus']=False # 正常显示负号 x=np.arange(0, 2.1, 0.1) y=np.power(x, 3) y1=np.power(x,2) y2=np.power(x, 1) plt.plot(x, y, ls='-', lw=2, label='$x^{3}$') plt.plot(x, y1, ls='-', lw=2, label='$x^{2}$', c='r') plt.plot(x, y2, ls='-', lw=2, label='$x^{1}$', c='y') plt.legend(loc='upper left', bbox_to_anchor=(0.05, 0.95), ncol=3, title="power function", shadow=True, fancybox=True) plt.show()
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图 4.3
![](https://images.cnblogs.com/OutliningIndicators/ContractedBlock.gif)
import matplotlib import matplotlib.pyplot as plt import numpy as np # 设置matplotlib正常显示中文和负号 matplotlib.rcParams['font.sans-serif']=['SimHei'] # 用黑体显示中文 matplotlib.rcParams['axes.unicode_minus']=False # 正常显示负号 x=np.linspace(-2, 2, 1000) y=np.exp(x) plt.plot(x, y, ls="-", lw=2, color='g') plt.title("center demo") plt.title("Left Demo", loc="left", fontdict={"size":"xx-large","color":"r", "family":"Times New Roman"}) plt.title("right demo", loc="right", family="Comic Sans MS", size=20, style="oblique", color="c") plt.show()
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图 4.4
![](https://images.cnblogs.com/OutliningIndicators/ContractedBlock.gif)
import matplotlib import matplotlib.pyplot as plt import numpy as np # 设置matplotlib正常显示中文和负号 matplotlib.rcParams['font.sans-serif']=['SimHei'] # 用黑体显示中文 matplotlib.rcParams['axes.unicode_minus']=False # 正常显示负号 elements=["面粉", "砂糖", "奶油", "草莓酱", "坚果"] weight=[40, 15, 20, 10, 15] colors=["#1b9e77", "#d95f02", "#7570b3", "#66a61e", "#e6ab02"] wedges, texts, autotexts=plt.pie(weight, autopct="%3.1f%%", textprops=dict(color="w"), colors=colors) plt.legend(wedges, elements, fontsize=12, title="配料表", loc="center left", bbox_to_anchor=(0.91, 0, 0.3, 1)) #调整百分比字体类型和大小 plt.setp(autotexts, size=15, weight="bold") #调整标签字体类型和大小 # plt.setp(texts, size=32) plt.title("果酱面包配料比例表") plt.show()
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图 4.5
![](https://images.cnblogs.com/OutliningIndicators/ContractedBlock.gif)
import matplotlib import matplotlib.pyplot as plt import numpy as np # 设置matplotlib正常显示中文和负号 matplotlib.rcParams['font.sans-serif']=['SimHei'] # 用黑体显示中文 matplotlib.rcParams['axes.unicode_minus']=False # 正常显示负号 x=np.linspace(-2*np.pi, 2*np.pi, 200) y=np.sin(x) plt.subplot(211) plt.plot(x, y) plt.subplot(212) plt.xlim(-2*np.pi, 2*np.pi) plt.xticks(np.pi*np.arange(-4, 5)/2, [r"$-2\pi$", r"$-3\pi/2$", r"$-2\pi$", r"$-\pi$", r"$0$", r"$\pi/2$", r"$\pi$", r"$3\pi/2$", r"$2\pi$", ]) plt.plot(x, y) plt.show()
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图 4.6
![](https://images.cnblogs.com/OutliningIndicators/ContractedBlock.gif)
import matplotlib import matplotlib.pyplot as plt import numpy as np # 设置matplotlib正常显示中文和负号 matplotlib.rcParams['font.sans-serif']=['SimHei'] # 用黑体显示中文 matplotlib.rcParams['axes.unicode_minus']=False # 正常显示负号 time=np.arange(1, 11, 0.5) machinePower=np.power(time, 2)+0.7 plt.plot(time, machinePower, linestyle="-", linewidth=2, color="r") #逆序设置坐标轴刻度标签 plt.xlim(10, 1) plt.xlabel("使用年限") plt.ylabel("机器功率") plt.title("机器损耗曲线") plt.grid(ls=":", lw=1, color="gray", alpha=0.5) plt.show()
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图 4.7
![](https://images.cnblogs.com/OutliningIndicators/ContractedBlock.gif)
import matplotlib import matplotlib.pyplot as plt import numpy as np # 设置matplotlib正常显示中文和负号 matplotlib.rcParams['font.sans-serif']=['SimHei'] # 用黑体显示中文 matplotlib.rcParams['axes.unicode_minus']=False # 正常显示负号 labels=["A难度水平", "B难度水平", "C难度水平", "D难度水平"] students=[0.35, 0.15, 0.20, 0.30] explode=(0.1, 0.1, 0.1, 0.1) colors=["#377eb8", "#e41a1c", "#4daf4a", "#984ea3"] plt.pie(students, explode=explode, labels=labels, autopct="%1.1f%%", startangle=45, shadow=True, colors=colors) colLabels=["A难度水平", "B难度水平", "C难度水平", "D难度水平"] rowLabels=["学生选择试卷人数"] studentValues=[[350, 150, 200, 300]] colColors=["#377eb8", "#e41a1c", "#4daf4a", "#984ea3"] plt.table(cellText=studentValues, cellLoc="center", colWidths=[0.25]*4, colLabels=colLabels, colColours=colColors, rowLabels=rowLabels, rowLoc="center", colLoc="center", loc="bottom", rowColours='r') plt.title("选择不同难度测试试卷的学生占比") plt.show()
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posted on 2020-05-19 18:20 Angry_Panda 阅读(661) 评论(0) 编辑 收藏 举报