然后我们可以创建一个简单的折线图,使用display函数来显示它: importmatplotlib.pyplotasplt# 生成数据x=[1,2,3,4,5]y=[2,3,5,7,11]# 创建折线图plt.plot(x,y,marker='o')plt.title('简单折线图')plt.xlabel('X轴')plt.ylabel('Y轴')# 使用display函数显示图形plt.show() 1. 2. 3. 4. 5....
display import display,HTML import pandas as pd title = 'Team scores' ds = pd.Series({'Alpha' : 67, 'Bravo' : 30, 'Charlie' : 20, 'Delta': 12, 'Echo': 23, 'Foxtrot': 56}) print(sum(ds)) Xlim = 16 Ylim = 13 Xpos = 0 Ypos = 12 ##change to zero for upwards series...
axes[1, 1].plot(df['Mes'], df['deep learning']) 我们可以为每个变量的点绘制具有不同样式的图形: plt.plot(df ['Mes'],df ['data science'],'r-')plt.plot(df ['Mes'],df ['data science'] * 2,'bs')plt .plot(df ['Mes'],df ['data science'] * 3,'g ^') 现在让我们看一些...
添加标签、自定义轴并显示绘图。 importmatplotlib.pyplotaspltimportnumpyasnp# Sample data for demonstrationx=np.linspace(0,10,100)y1=np.sin(x)y2=np.cos(x)# Create a figure and axisfig,ax=plt.subplots()# Plot the two linesax.plot(x,y1,label='Line 1',color='blue')ax.plot(x,y2,lab...
from sqlalchemyimportcreate_engineimportdatetimeasdt defget_info():"""获取大屏第一列信息数据"""headers={'User-Agent':'Mozilla/5.0 (MSIE 10.0; Windows NT 6.1; Trident/5.0)','referer':'https: // passport.csdn.net / login',}# 我的博客地址 ...
()), start=1, end=2) # Make the plot p = figure(x_range=FactorRange(*x), width=1200, title="Election results") p.vbar(x='x', top='y', width=0.9, source=source, fill_color=fill_color, line_color=fill_color) # Customise some display properties p.y_range.start = 0 p.x_...
# Display the plot chord 1. 2. 3. 4. 5. 6. 7. 8. 9. 10. 11. 12. 13. 14. 15. 16. 17. 18. 19. 20. 21. 22. 23. 24. 25. 26. 27. 28. 29. 30. 31. 32. 33. 34. 35. 36. 37. 38. 39. 40. 41. 42. ...
display it san_map = folium.Map(location=[latitude, longitude], zoom_start=12) # Display the...
importmatplotlib.pyplot as plt#%matplotlib inline#Using the different pyplot functions, we can create, customize, and display a plot. For example, we can use 2 functions to :plt.plot() plt.show() 结果如下: 三。插入数据 first_twelve = unrate[0:12] ...
plt.plot(y[:,1]) plt.pause(0.001) # pause a bit so that plots are updated if is_ipython: display.clear_output(wait=True) display.display(plt.gcf()) x = np.linspace(-10,10,500) y = [] for i in range(len(x)): y1 = np.cos(i/(3*3.14)) ...