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"## 3D scatter plots with Plotly & Python\n",
"\n",
"(copied FROM https://plotly.com/python/3d-scatter-plots/ Wednesday, March 27, 2020)\n",
"\n",
"**All of these cells will display plots in current JupyterLab (versions 3.1.1 & 3.4.8 tested) even without using `%matplotlib inline`.** This was not the case with JupyterLab 2.1.3, where even using `%matplotlib inline` didn't help enable displaying these plots.\n",
"\n",
"\n",
"### 3D scatter plot with Plotly Express\n",
"\n",
"\n",
"[Plotly Express](https://plotly.com/python/plotly-express/) is the easy-to-use, high-level interface to Plotly, which [operates on a variety of types of data](https://plotly.com/python/px-arguments/) and produces [easy-to-style figures](https://plotly.com/python/styling-plotly-express/).\n",
"\n",
"Like the [2D scatter plot](https://plotly.com/python/line-and-scatter/) `px.scatter`, the 3D function `px.scatter_3d` plots individual data in three-dimensional space.\n",
"\n",
"\n"
]
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"linecolor": "white",
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}
},
"scene": {
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"gridcolor": "white",
"gridwidth": 2,
"linecolor": "white",
"showbackground": true,
"ticks": "",
"zerolinecolor": "white"
},
"yaxis": {
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"gridcolor": "white",
"gridwidth": 2,
"linecolor": "white",
"showbackground": true,
"ticks": "",
"zerolinecolor": "white"
},
"zaxis": {
"backgroundcolor": "#E5ECF6",
"gridcolor": "white",
"gridwidth": 2,
"linecolor": "white",
"showbackground": true,
"ticks": "",
"zerolinecolor": "white"
}
},
"shapedefaults": {
"line": {
"color": "#2a3f5f"
}
},
"ternary": {
"aaxis": {
"gridcolor": "white",
"linecolor": "white",
"ticks": ""
},
"baxis": {
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"linecolor": "white",
"ticks": ""
},
"bgcolor": "#E5ECF6",
"caxis": {
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"linecolor": "white",
"ticks": ""
}
},
"title": {
"x": 0.05
},
"xaxis": {
"automargin": true,
"gridcolor": "white",
"linecolor": "white",
"ticks": "",
"title": {
"standoff": 15
},
"zerolinecolor": "white",
"zerolinewidth": 2
},
"yaxis": {
"automargin": true,
"gridcolor": "white",
"linecolor": "white",
"ticks": "",
"title": {
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"zerolinecolor": "white",
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}
}
}
}
},
"text/html": [
""
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"import plotly.express as px\n",
"df = px.data.iris()\n",
"fig = px.scatter_3d(df, x='sepal_length', y='sepal_width', z='petal_width',\n",
" color='species')\n",
"fig.show()"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"A 4th dimension of the data can be represented thanks to the color of the markers. Also, values from the `species` column are used below to assign symbols to markers."
]
},
{
"cell_type": "code",
"execution_count": 2,
"metadata": {},
"outputs": [
{
"data": {
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"config": {
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sepal_width=%{y}
petal_width=%{z}
petal_length=%{marker.color}",
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},
"text/html": [
""
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"metadata": {},
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],
"source": [
"import plotly.express as px\n",
"df = px.data.iris()\n",
"fig = px.scatter_3d(df, x='sepal_length', y='sepal_width', z='petal_width',\n",
" color='petal_length', symbol='species')\n",
"fig.show()"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"#### Style 3d scatter plot\n",
"\n",
"It is possible to customize the style of the figure through the parameters of `px.scatter_3d` for some options, or by updating the traces or the layout of the figure through `fig.update`."
]
},
{
"cell_type": "code",
"execution_count": 3,
"metadata": {},
"outputs": [
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"source": [
"import plotly.express as px\n",
"df = px.data.iris()\n",
"fig = px.scatter_3d(df, x='sepal_length', y='sepal_width', z='petal_width',\n",
" color='petal_length', size='petal_length', size_max=18,\n",
" symbol='species', opacity=0.7)\n",
"\n",
"# tight layout\n",
"fig.update_layout(margin=dict(l=0, r=0, b=0, t=0))"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### 3D Scatter Plot with go.Scatter3d\n",
"\n",
"#### Basic 3D Scatter Plot\n",
"\n",
"If Plotly Express does not provide a good starting point, it is also possible to use the more generic `go.Scatter3D` from `plotly.graph_objs`.\n",
"Like the [2D scatter plot](https://plotly.com/python/line-and-scatter/) `go.Scatter`, `go.Scatter3d` plots individual data in three-dimensional space."
]
},
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"source": [
"import plotly.graph_objects as go\n",
"import numpy as np\n",
"\n",
"# Helix equation\n",
"t = np.linspace(0, 10, 50)\n",
"x, y, z = np.cos(t), np.sin(t), t\n",
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]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"#### 3D Scatter Plot with Colorscaling and Marker Styling"
]
},
{
"cell_type": "code",
"execution_count": 5,
"metadata": {},
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"source": [
"import plotly.graph_objects as go\n",
"import numpy as np\n",
"\n",
"# Helix equation\n",
"t = np.linspace(0, 20, 100)\n",
"x, y, z = np.cos(t), np.sin(t), t\n",
"\n",
"fig = go.Figure(data=[go.Scatter3d(\n",
" x=x,\n",
" y=y,\n",
" z=z,\n",
" mode='markers',\n",
" marker=dict(\n",
" size=12,\n",
" color=z, # set color to an array/list of desired values\n",
" colorscale='Viridis', # choose a colorscale\n",
" opacity=0.8\n",
" )\n",
")])\n",
"\n",
"# tight layout\n",
"fig.update_layout(margin=dict(l=0, r=0, b=0, t=0))\n",
"fig.show()"
]
},
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"metadata": {},
"source": [
"#### Reference\n",
"\n",
"See https://plotly.com/python/reference/#scatter3d for more information and chart attribute options!\n",
"\n",
"\n",
"------\n",
"\n",
"### Use widgets to adjust options\n",
"\n",
"See [this notebook](3D_scatter_adjustableVIAwidgets.ipynb) for examples of how `ipywidgets` can be added to allow setting of options from a range of choices or values."
]
}
],
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