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‎2D-Histogram.ipynb

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‎2d-histogram-contour.ipynb

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‎3d-axes.ipynb

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{
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"cells": [
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{
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"cell_type": "markdown",
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"id": "68bb6fe8",
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"metadata": {},
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"source": [
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"### Range of axes\n",
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"\n",
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"3D figures have an attribute in `layout` called `scene`, which contains\n",
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"attributes such as `xaxis`, `yaxis` and `zaxis` parameters, in order to\n",
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"set the range, title, ticks, color etc. of the axes.\n",
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"\n",
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"For creating 3D charts, see [this page](https://plotly.com/python/3d-charts/).\n",
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"\n",
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"Set `range` on an axis to manually configure a range for that axis. If you don't set `range`, it's automatically calculated. In this example, we set a `range` on `xaxis`, `yaxis`, and `zaxis`."
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "b6f2d4dc",
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"metadata": {},
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"outputs": [],
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"source": [
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"import plotly.graph_objects as go\n",
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"import numpy as np\n",
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"np.random.seed(1)\n",
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"\n",
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"N = 70\n",
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"\n",
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"fig = go.Figure(data=[go.Mesh3d(x=(70*np.random.randn(N)),\n",
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" y=(55*np.random.randn(N)),\n",
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" z=(40*np.random.randn(N)),\n",
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" opacity=0.5,\n",
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" color='rgba(244,22,100,0.6)'\n",
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" )])\n",
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"\n",
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"fig.update_layout(\n",
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" scene = dict(\n",
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" xaxis = dict(nticks=4, range=[-100,100],),\n",
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" yaxis = dict(nticks=4, range=[-50,100],),\n",
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" zaxis = dict(nticks=4, range=[-100,100],),),\n",
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" width=700,\n",
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" margin=dict(r=20, l=10, b=10, t=10))\n",
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"\n",
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"fig.show()"
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]
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},
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{
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"cell_type": "markdown",
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"id": "c9e11629",
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"metadata": {},
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"source": [
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"### Setting only a Lower or Upper Bound for Range\n",
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"\n",
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"*New in 5.17*\n",
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"\n",
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"You can also set just a lower or upper bound for `range`. In this case, autorange is used for the other bound. In this example, we apply autorange to the lower bound of the `yaxis` and the upper bound of `zaxis` by setting them to `None`."
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "1d6c29ba",
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"metadata": {},
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"outputs": [],
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"source": [
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"import plotly.graph_objects as go\n",
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"import numpy as np\n",
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"np.random.seed(1)\n",
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"\n",
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"N = 70\n",
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"\n",
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"fig = go.Figure(data=[go.Mesh3d(x=(70*np.random.randn(N)),\n",
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" y=(55*np.random.randn(N)),\n",
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" z=(40*np.random.randn(N)),\n",
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" opacity=0.5,\n",
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" color='rgba(244,22,100,0.6)'\n",
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" )])\n",
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"\n",
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"fig.update_layout(\n",
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" scene = dict(\n",
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" xaxis = dict(nticks=4, range=[-100,100],),\n",
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" yaxis = dict(nticks=4, range=[None, 100],),\n",
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" zaxis = dict(nticks=4, range=[-100, None],),),\n",
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" width=700,\n",
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" margin=dict(r=20, l=10, b=10, t=10))\n",
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"\n",
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"fig.show()"
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]
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},
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{
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"cell_type": "markdown",
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"id": "fd61d49e",
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"metadata": {},
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"source": [
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"### Fixed Ratio Axes"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "4478ccb7",
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"metadata": {},
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"outputs": [],
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"source": [
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"import plotly.graph_objects as go\n",
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"from plotly.subplots import make_subplots\n",
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"import numpy as np\n",
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"\n",
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"N = 50\n",
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"\n",
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"fig = make_subplots(rows=2, cols=2,\n",
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" specs=[[{'is_3d': True}, {'is_3d': True}],\n",
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" [{'is_3d': True}, {'is_3d': True}]],\n",
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" print_grid=False)\n",
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"for i in [1,2]:\n",
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" for j in [1,2]:\n",
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" fig.add_trace(\n",
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" go.Mesh3d(\n",
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" x=(60*np.random.randn(N)),\n",
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" y=(25*np.random.randn(N)),\n",
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" z=(40*np.random.randn(N)),\n",
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" opacity=0.5,\n",
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" ),\n",
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" row=i, col=j)\n",
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"\n",
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"fig.update_layout(width=700, margin=dict(r=10, l=10, b=10, t=10))\n",
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"# fix the ratio in the top left subplot to be a cube\n",
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"fig.update_layout(scene_aspectmode='cube')\n",
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"# manually force the z-axis to appear twice as big as the other two\n",
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"fig.update_layout(scene2_aspectmode='manual',\n",
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" scene2_aspectratio=dict(x=1, y=1, z=2))\n",
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"# draw axes in proportion to the proportion of their ranges\n",
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"fig.update_layout(scene3_aspectmode='data')\n",
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"# automatically produce something that is well proportioned using 'data' as the default\n",
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"fig.update_layout(scene4_aspectmode='auto')\n",
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"fig.show()"
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]
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},
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{
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"cell_type": "markdown",
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"id": "38f8ca0d",
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"metadata": {},
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"source": [
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"### Set Axes Title"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "a59f6639",
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"metadata": {},
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"outputs": [],
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"source": [
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"import plotly.graph_objects as go\n",
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"import numpy as np\n",
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"\n",
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"# Define random surface\n",
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"N = 50\n",
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"fig = go.Figure()\n",
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"fig.add_trace(go.Mesh3d(x=(60*np.random.randn(N)),\n",
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" y=(25*np.random.randn(N)),\n",
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" z=(40*np.random.randn(N)),\n",
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" opacity=0.5,\n",
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" color='yellow'\n",
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" ))\n",
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"fig.add_trace(go.Mesh3d(x=(70*np.random.randn(N)),\n",
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" y=(55*np.random.randn(N)),\n",
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" z=(30*np.random.randn(N)),\n",
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" opacity=0.5,\n",
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" color='pink'\n",
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" ))\n",
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"\n",
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"fig.update_layout(scene = dict(\n",
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" xaxis=dict(\n",
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" title=dict(\n",
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" text='X AXIS TITLE'\n",
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" )\n",
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" ),\n",
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" yaxis=dict(\n",
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" title=dict(\n",
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" text='Y AXIS TITLE'\n",
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" )\n",
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" ),\n",
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" zaxis=dict(\n",
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" title=dict(\n",
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" text='Z AXIS TITLE'\n",
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" )\n",
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" ),\n",
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" ),\n",
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" width=700,\n",
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" margin=dict(r=20, b=10, l=10, t=10))\n",
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"\n",
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"fig.show()"
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]
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},
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{
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"cell_type": "markdown",
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"id": "315c4538",
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"metadata": {},
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"source": [
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"### Ticks Formatting"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "421cba75",
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"metadata": {},
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"outputs": [],
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"source": [
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"import plotly.graph_objects as go\n",
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"import numpy as np\n",
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"\n",
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"# Define random surface\n",
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"N = 50\n",
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"fig = go.Figure(data=[go.Mesh3d(x=(60*np.random.randn(N)),\n",
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" y=(25*np.random.randn(N)),\n",
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" z=(40*np.random.randn(N)),\n",
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" opacity=0.5,\n",
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" color='rgba(100,22,200,0.5)'\n",
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" )])\n",
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"\n",
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"# Different types of customized ticks\n",
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"fig.update_layout(scene = dict(\n",
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" xaxis = dict(\n",
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" ticktext= ['TICKS','MESH','PLOTLY','PYTHON'],\n",
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" tickvals= [0,50,75,-50]),\n",
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" yaxis = dict(\n",
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" nticks=5, tickfont=dict(\n",
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" color='green',\n",
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" size=12,\n",
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" family='Old Standard TT, serif',),\n",
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" ticksuffix='#'),\n",
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" zaxis = dict(\n",
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" nticks=4, ticks='outside',\n",
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" tick0=0, tickwidth=4),),\n",
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" width=700,\n",
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" margin=dict(r=10, l=10, b=10, t=10)\n",
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" )\n",
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"\n",
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"fig.show()"
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]
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},
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{
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"cell_type": "markdown",
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"id": "88e41734",
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"metadata": {},
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"source": [
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"### Background and Grid Color"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "5fbfaadb",
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"metadata": {},
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"outputs": [],
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"source": [
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"import plotly.graph_objects as go\n",
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"import numpy as np\n",
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"\n",
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"N = 50\n",
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"fig = go.Figure(data=[go.Mesh3d(x=(30*np.random.randn(N)),\n",
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" y=(25*np.random.randn(N)),\n",
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" z=(30*np.random.randn(N)),\n",
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" opacity=0.5,)])\n",
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"\n",
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"\n",
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"# xaxis.backgroundcolor is used to set background color\n",
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"fig.update_layout(scene = dict(\n",
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" xaxis = dict(\n",
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" backgroundcolor=\"rgb(200, 200, 230)\",\n",
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" gridcolor=\"white\",\n",
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" showbackground=True,\n",
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" zerolinecolor=\"white\",),\n",
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" yaxis = dict(\n",
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" backgroundcolor=\"rgb(230, 200,230)\",\n",
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" gridcolor=\"white\",\n",
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" showbackground=True,\n",
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" zerolinecolor=\"white\"),\n",
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" zaxis = dict(\n",
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" backgroundcolor=\"rgb(230, 230,200)\",\n",
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" gridcolor=\"white\",\n",
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" showbackground=True,\n",
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" zerolinecolor=\"white\",),),\n",
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" width=700,\n",
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" margin=dict(\n",
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" r=10, l=10,\n",
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" b=10, t=10)\n",
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" )\n",
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"fig.show()"
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]
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},
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{
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"cell_type": "markdown",
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"id": "29a75416",
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"metadata": {},
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"source": [
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"### Disabling tooltip spikes\n",
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"\n",
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"By default, guidelines originating from the tooltip point are drawn. It is possible to disable this behaviour with the `showspikes` parameter. In this example we only keep the `z` spikes (projection of the tooltip on the `x-y` plane). Hover on the data to show this behaviour."
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "cab2807f",
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"metadata": {
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"lines_to_next_cell": 2
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},
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"outputs": [],
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"source": [
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"import plotly.graph_objects as go\n",
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"import numpy as np\n",
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"\n",
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"N = 50\n",
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"fig = go.Figure(data=[go.Mesh3d(x=(30*np.random.randn(N)),\n",
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" y=(25*np.random.randn(N)),\n",
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" z=(30*np.random.randn(N)),\n",
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" opacity=0.5,)])\n",
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"fig.update_layout(scene=dict(xaxis_showspikes=False,\n",
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" yaxis_showspikes=False))\n",
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"fig.show()"
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]
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},
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{
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"cell_type": "markdown",
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"id": "9bb6ce1d",
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"metadata": {},
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"source": [
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"### What About Dash?\n",
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"\n",
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"[Dash](https://dash.plot.ly/) is an open-source framework for building analytical applications, with no Javascript required, and it is tightly integrated with the Plotly graphing library.\n",
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"\n",
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"Learn about how to install Dash at https://dash.plot.ly/installation.\n",
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"\n",
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"Everywhere in this page that you see `fig.show()`, you can display the same figure in a Dash application by passing it to the `figure` argument of the [`Graph` component](https://dash.plot.ly/dash-core-components/graph) from the built-in `dash_core_components` package like this:\n",
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"\n",
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"```python\n",
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"import plotly.graph_objects as go # or plotly.express as px\n",
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"fig = go.Figure() # or any Plotly Express function e.g. px.bar(...)\n",
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"# fig.add_trace( ... )\n",
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"# fig.update_layout( ... )\n",
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"\n",
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"from dash import Dash, dcc, html\n",
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"\n",
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"app = Dash()\n",
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"app.layout = html.Div([\n",
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" dcc.Graph(figure=fig)\n",
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"])\n",
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"\n",
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"app.run_server(debug=True, use_reloader=False) # Turn off reloader if inside Jupyter\n",
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"```"
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]
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}
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],
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"metadata": {
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"jupytext": {
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"notebook_metadata_filter": "all"
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},
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"kernelspec": {
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"display_name": "Python 3 (ipykernel)",
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"language": "python",
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"name": "python3"
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},
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"language_info": {
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"codemirror_mode": {
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"name": "ipython",
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"version": 3
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},
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"file_extension": ".py",
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"mimetype": "text/x-python",
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"name": "python",
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"nbconvert_exporter": "python",
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"pygments_lexer": "ipython3",
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"version": "3.10.4"
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},
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"plotly": {
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"description": "How to format axes of 3d plots in Python with Plotly.",
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"display_as": "3d_charts",
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"language": "python",
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"layout": "base",
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"name": "3D Axes",
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"order": 1,
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"page_type": "example_index",
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"permalink": "python/3d-axes/",
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"thumbnail": "thumbnail/3d-axes.png"
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}
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},
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"nbformat": 4,
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"nbformat_minor": 5
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}

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