OverviewBooleanSwitchColorPickerDarkThemeProviderGaugeGraduatedBarIndicatorJoystickKnobLEDDisplayNumericInputPowerButtonPrecisionInputSliderStopButtonTankThermometerToggleSwitch Dash Image Annotations Overview & Reference Dash Canvas Overview & Reference Dash Slicer ...
Plotly's Python graphing library makes interactive, publication-quality graphs. Examples of how to make line plots, scatter plots, area charts, bar charts, error bars, box plots, histograms, heatmaps, subplots, multiple-axes, polar charts, and bubble charts. ...
Engineers and data scientists using Python, R, Matlab or JavaScript. Dash Dash is ideal for building data visualization apps with highly custom user interfaces in pure Python. Falcon SQL Client SQL Analysts who want to visualize query results and sync data to Chart Studio ...
“auto” tries to position text inside the bar, but if the bar is too small and no bar is stacked on this one the text is moved outside. If “none”, no text appears. textpositionsrc –Sets the source reference on Chart Studio Cloud for textposition. textsrc –Sets the source ...
Progress Bar Chart Graph Theprogressargument to the@dash.callbackdecorator can be used to update arbitrary component properties. This example creates and updates a Plotly bar graph to display the current calculation status. This example also uses theprogress_defaultargument to specify a grouping of ...
Bar chart Waterfall Bar Chart Pie Chart Donut chart Bubble charts Error Bars chart Box Plots, Horizontal Box Plot, Grouped Box Plot Histograms, Stacked Histograms 2d Density Plots Heatmaps Waterfall charts Indicators Funnel Maps Contour Plots 2d Density Plots Ternary Plots Ribbon Plots 3D Surface Pl...
It can be "Chart" or "Widget". Chart descriptionEXPRESSION (string) Description of the chart displayed in the instrument History: This property is only available when Item type is Chart. Chart dataEXPRESSION (blob) A string or blob containing the samples that will be displayed in the chart....
Bar - Bar_base - Document (pyecharts.org)python # STEP 地震震级分布 mags = data.groupby("level") print("震级分组 ", mags.ngroups) mags = mags.size().items() # ^ mags 只可以迭代一次 xaxis, yaxis = [], [] for x in mags: xaxis.append(x[0]) yaxis.append(x[1]) c3 = (...
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一起安装): import plotly.graph_objects as go fig = go.Figure() fig.add_trace(go.Scatter(y=[2, 1, 4, 3])) fig.add_trace(go.Bar(y=[1, 4, 3, 2])) fig.update_layout(title = 'Hello Figure') fig.show() 更多示例请参见Python文档。