复制代码 import altair as alt from vega_datasets import data # 准备数据 source = data.cars() # 绘制散点图 chart = alt.Chart(source).mark_circle(size=60).encode( x="Horsepower", y="Miles_per_Gallon", color="Origin", tooltip=["Name", "Origin"] ).interactive() chart.show()小贴士：...
import altair as altimport pandas as pdimport numpy as npdata = np.random.normal(100, 20, 200)df = pd.DataFrame(data, columns=['data'])alt.Chart(df).mark_boxplot().encode( y='data:Q').properties( width=400, height=300).interactive()ggplot 优点：流行的 R 库 ggplot2 的 ...
# 使用 Plotly Express 创建交互式线图 fig = px.line(df, x='time', y='Value', title='Interactive Line Chart') # 显示图形 fig.show() 交互散点图 # 使用 Plotly Express 创建交互式散点图 fig = px.scatter(X, x='AST', y='ALB', title='Interactive Line Chart') # 显示图形 fig.show(...
When I first began looking at interactive plotting tools in Python, most of the resources I found treated Matplotlib as only a static plotting tool, which is incorrect. Instead, the availble resources mainly focused on writing web applications in Plotly and Dash. Though I may revisit them in ...
# run ansys with interactive plotting enabled ansys = pyansys.Mapdl() # create a square area using keypoints ansys.prep7() ansys.k(1, 0, 0, 0) ansys.k(2, 1, 0, 0) ansys.k(3, 1, 1, 0) ansys.k(4, 0, 1, 0) ansys.l(1, 2) ...
The Matplotlib Object Hierarchy Stateful Versus Stateless Approaches Understanding plt.subplots() Notation The “Figures” Behind The Scenes A Burst of Color: imshow() and matshow() Plotting in Pandas Wrapping Up More Resources Appendix A: Configuration and Styling Appendix B: Interactive ModeRemove...
Use Matplotlibto add interactive plots to your apps Or take a look at PyQtGraph forhigh performance graphs and other visualizations If you're using Qt Designer to create your applications, take a look athow to use PyQtGraph & Matplotlib widgets inside Qt Designer. ...
matplotlib is a desktop plotting package designed for creating plots and figures suitable for publication. The project was started by John Hunter in 2002 to enable a MATLAB-like plotting interface in Python. The matplotlib and IPython communities have collaborated to simplify interactive plotting from ...
Matplotlib is aPythonplotting library that produces publication-quality figures. Matplotlib是一个Python绘图库,用于生成出版物质量的图形。 It can be used both in Python scripts and when using Python’s interactive mode. 它既可以在Python脚本中使用,也可以在使用Python的交互模式时使用。 Matplotlib is a ...
frombokeh.plottingimportfigure, showfrombokeh.modelsimportColumnDataSource# 创建数据x = [1,2,3,4,5] y = [2,4,6,8,10]# 创建Bokeh图表source = ColumnDataSource(data=dict(x=x, y=y)) p = figure(title='Interactive Line Chart', x_axis_label='X-axis', y_axis_label='Y-axis')# 添...