# 左下(0.5,-0.5),# 右下(0,0.5),# 顶部(-0.5,-0.5),# 回到起点,闭合路径]plt.figure(figsize=(8,6))plt.scatter(x,y,marker=custom_marker,s=500)plt.title('Scatter Plot with Custom Marker Shape - how2matplotlib.com')plt.xlabel('
's','D']# 三种不同的形状colors=['r','g','b']# 三种不同的颜色for(x,y),label,marker,colorinzip(data,labels,markers,colors):plt.scatter(x,y,marker=marker,color=color,label=label)# 添加图例plt.title('Multi-Scatter Plot with Different Shapes')plt.xlabel('X-axis')plt.ylabel('Y-axi...
1.1 使用scatter函数绘制大点 scatter函数是绘制散点图的主要方法,它允许我们轻松地控制每个点的大小。 importmatplotlib.pyplotaspltimportnumpyasnp x=np.linspace(0,10,10)y=np.sin(x)plt.figure(figsize=(10,6))plt.scatter(x,y,s=100,label='how2matplotlib.com')plt.title('Scatter Plot with Bigger D...
1.plot(x, y, marker='D')表示绘制折线图,marker设置样式菱形。 2.scatter(x, y, marker='s', color='r')绘制散点图,红色正方形。 3.bar(x, y, 0.5, color='c')绘制柱状图,间距为0.5,原色。 4.hist(data,40,normed=1,histtype='bar',facecolor='yellowgreen',alpha=0.75)直方图。 5.设置x轴...
['o','s','^','d','p','*','h','H','+','x']# 形状的集合# 创建散点图plt.figure(figsize=(10,6))fori,shapeinenumerate(shapes):plt.scatter(x[i],y[i],s=sizes[i],marker=shape,alpha=0.5,label=f'Shape:{shape}')plt.title('Scatter Plot with Different Shapes and Sizes')plt...
在Matplotlib中,要添加连接相关散点的线,可以使用plot()函数。具体步骤如下: 导入Matplotlib库: 代码语言:txt 复制 import matplotlib.pyplot as plt 创建散点图: 代码语言:txt 复制 x = [1, 2, 3, 4, 5] y = [2, 4, 6, 8, 10] plt.scatter(x, y) ...
(0,10,11))ax.plot(np.linspace(0,10,100),np.linspace(0,10,100),label='1:1',color='k',linestyle='--')ax.scatter(np.linspace(0,10,20),np.sin(np.linspace(0,10,20)+1),label='1:2',color='g',marker='o')ax.legend(loc='upper left',fontsize=10,frameon=False)ax.grid('...
How to add an img into a matplotlib chart A clean stacked area chart with images in the caption Use an image inside each scatterplot circle Evolution + Line chart + Area chart + Stacked Area + Streamgraph + Candlestick + Timeseries
import matplotlib.pyplot as plt#prepare some datax = [2011, 2012, 2013, 2014, 2015, 2016, 2017, 2018, 2019, 2010]y = [54, 55, 45, 47, 52, 56, 34, 39, 51, 63]area=500plt.scatter(x, y, marker='.', c='red', s=area)plt.show() ...
(5,5)),alpha=0.8,zorder=0)# Add scatterplot ---# Loop through species, colors, and markers.# Each species receives a different combination of color and marker.forspecies,color,markerinzip(SPECIES,COLORS,MARKERS):data=penguins[penguins["species"]==species]ax.scatter("flipper_length_mm","bi...