最直接的方式就是多次调用plot方法。 >>> plot(x1, y1, 'bo') >>> plot(x2, y2, 'go') 1. 2. 或者,你的数据本身是一个二维数组,就可以直接传入x,y,数据的每一列都会被绘制成图。例如:数组a的第一列代表x值,其他列代表y值。 >>> plot(a[0], a[1:]) 1. 第三种方法是用多组[x],y,...
importmatplotlib.pyplotasplt# 设置数据x=[1,2,3,4,5]y=[2,3,5,7,10]plt.plot(x,y,linestyle='--',color='gray',label='Line - how2matplotlib.com')# 绘制线plt.scatter([x[2]],[y[2]],color='red',s=100,label='Highlight Point (3,5) - how2matplotlib.com')# 突出显示中间点plt...
font_path = excel.FontPath.CHINESE_SIMPLIFIED # Point the properties to the font path. font_properties = FontProperties(fname=font_path) plt.rcParams['font.family'] = font_properties.get_name() # Make the plot. myplot = pd.DataFrame({'欧文': [1,2,3], '比尔': [1,2,3]}).plot...
graph_objs_toolsheatmap(package)heatmapgl(package)histogram(package)histogram2d(package)histogram2dcontour(package)layout(package)mesh3d(package)ohlc(package)parcoords(package)pie(package)pointcloud(package)sankey(package)scatter(package)scatter3d(package)scattercarpet(package)scattergeo(package)scattergl(pack...
ax.text(-.08,1.1,"Base Charts in Python Exercise 01: Point Charts",transform=ax.transAxes,color='k',ha='left',va='center',size=15,fontweight='extra bold')ax.text(.91,-.1,'\nVisualization by DataCharm',transform=ax.transAxes,ha='center',va='center',fontsize=7,color='black')plt...
barbs(X, Y, U, V) # Arbitrary set of vectors, make them longer and change the pivot point # (point around which they're rotated) to be the middle axs1[0, 1].barbs( data['x'], data['y'], data['u'], data['v'], length=8, pivot='middle') # Showing colormapping with ...
All this does is that it changes the appearance of x and y in your plot. 所有这一切只是改变了绘图中x和y的外观。 Let’s try running the plot up to this point. 让我们试着将绘图运行到这一点。 If you’re not familiar with LaTeX, you can drop the dollar signs and we can re-run ...
plt.plot(x, y, 'ro-',label="xxx") # red+solid-point+line plt.xlabel("...") plt.ylabel("...") matplotlib.pyplot.title("...") plt.xlim(a,b) # limit the x-axis plt.ylim(c,d) # limit the y-axis plt.grid() #show grid ...
from plotnine import ggplot, aes, geom_point # 创建数据帧 df = pd.DataFrame({'x': [1, 2, 3, 4, 5], 'y': [2, 4, 6, 8, 10]}) # 绘制散点图 ggplot(df, aes(x='x', y='y')) + geom_point() + ggtitle("Scatter Plot") 6.Altair:Altair是一个声明性的可视化库,它基于Ve...
首先介绍下bokeh bokeh擅长制作交互式图表，当然在地图展示方面也毫不逊色。Bokeh支持google地图、geojson...