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fix whitespace issues
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‎python/2D-Histogram.md

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### 2D Histogram of a Bivariate Normal Distribution ###

‎python/2d-histogram-contour.md

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#### Basic 2D Histogram Contour

‎python/3d-axes.md

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‎python/3d-bubble-charts.md

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### 3d Bubble chart with Plotly Express

‎python/3d-camera-controls.md

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### How camera controls work
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The camera position and direction is determined by three vectors: *up*, *center*, *eye*. Their coordinates refer to the 3-d domain, i.e., `(0, 0, 0)` is always the center of the domain, no matter data values.
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The `eye` vector determines the position of the camera. The default is $(x=1.25, y=1.25, z=1.25)$.
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The camera position and direction is determined by three vectors: *up*, *center*, *eye*. Their coordinates refer to the 3-d domain, i.e., `(0, 0, 0)` is always the center of the domain, no matter data values.
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The `eye` vector determines the position of the camera. The default is $(x=1.25, y=1.25, z=1.25)$.
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The `up` vector determines the `up` direction on the page. The default is $(x=0, y=0, z=1)$, that is, the z-axis points up.
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‎python/3d-isosurface-plots.md

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With ``go.Isosurface``, you can plot [isosurface contours](https://en.wikipedia.org/wiki/Isosurface) of a scalar field ``value``, which is defined on ``x``, ``y`` and ``z`` coordinates.
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X, Y, Z = np.mgrid[-5:5:40j, -5:5:40j, -5:5:40j]
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# ellipsoid
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# ellipsoid
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values = X * X * 0.5 + Y * Y + Z * Z * 2
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fig = go.Figure(data=go.Isosurface(
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X, Y, Z = np.mgrid[-5:5:40j, -5:5:40j, -5:5:40j]
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# ellipsoid
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# ellipsoid
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values = X * X * 0.5 + Y * Y + Z * Z * 2
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fig = go.Figure(data=go.Isosurface(
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X, Y, Z = np.mgrid[-5:5:40j, -5:5:40j, -5:5:40j]
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# ellipsoid
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# ellipsoid
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values = X * X * 0.5 + Y * Y + Z * Z * 2
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fig = go.Figure(data=go.Isosurface(
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#### Isosurface with Addtional Slices
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Here we visualize slices parallel to the axes on top of isosurfaces. For a clearer visualization, the `fill` ratio of isosurfaces is decreased below 1 (completely filled).
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Here we visualize slices parallel to the axes on top of isosurfaces. For a clearer visualization, the `fill` ratio of isosurfaces is decreased below 1 (completely filled).
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```python
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import plotly.graph_objects as go
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import numpy as np
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X, Y, Z = np.mgrid[-5:5:40j, -5:5:40j, -5:5:40j]
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# ellipsoid
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# ellipsoid
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values = X * X * 0.5 + Y * Y + Z * Z * 2
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fig = go.Figure(data=go.Isosurface(
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X, Y, Z = np.mgrid[-5:5:40j, -5:5:40j, -5:5:40j]
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# ellipsoid
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# ellipsoid
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values = X * X * 0.5 + Y * Y + Z * Z * 2
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fig = go.Figure(data=go.Isosurface(

‎python/3d-line-plots.md

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### 3D Line plot with Plotly Express

‎python/3d-mesh.md

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colorbar_title='z',
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colorscale=[[0, 'gold'],
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colorscale=[[0, 'gold'],
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[0.5, 'mediumturquoise'],
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# Intensity of each vertex, which will be interpolated and color-coded
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intensity=[0, 0.33, 0.66, 1],
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# Intensity of each vertex, which will be interpolated and color-coded
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intensity = np.linspace(0, 1, 8, endpoint=True),

‎python/3d-scatter-plots.md

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‎python/3d-subplots.md

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‎python/3d-surface-coloring.md

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```python

‎python/3d-surface-plots.md

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‎python/3d-volume.md

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A volume plot with `go.Volume` shows several partially transparent isosurfaces for volume rendering. The API of `go.Volume` is close to the one of `go.Isosurface`. However, whereas [isosurface plots](/python/3d-isosurface-plots/) show all surfaces with the same opacity, tweaking the `opacityscale` parameter of `go.Volume` results in a depth effect and better volume rendering.

‎python/aggregations.md

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‎python/animations.md

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‎python/annotated_heatmap.md

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‎python/axes.md

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‎python/bar-charts.md

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‎python/box-plots.md

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‎python/bubble-charts.md

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‎python/bubble-maps.md

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‎python/bullet-charts.md

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‎python/candlestick-charts.md

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‎python/carpet-contour.md

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### Basic Carpet Plot

‎python/carpet-plot.md

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<!-- #region -->

‎python/carpet-scatter.md

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‎python/choropleth-maps.md

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‎python/click-events.md

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‎python/colorscales.md

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‎python/compare-webgl-svg.md

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‎python/cone-plot.md

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A cone plot is the 3D equivalent of a 2D [quiver plot](/python/quiver-plots/), i.e., it represents a 3D vector field using cones to represent the direction and norm of the vectors. 3-D coordinates are given by `x`, `y` and `z`, and the coordinates of the vector field by `u`, `v` and `w`.

‎python/configuration-options.md

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