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‎404.html‎

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<li class="md-nav__item">
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<a href="/xarray_plotly/examples/datasets/" class="md-nav__link">
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<span class="md-ellipsis">
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Dataset Plotting
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</span>
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</a>
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</li>
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<a href="/xarray_plotly/examples/dimensions/" class="md-nav__link">
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‎api/index.html‎

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‎examples/datasets/datasets.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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"metadata": {},
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"source": [
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"# Dataset Plotting\n",
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"\n",
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"Plot multiple variables from an xarray Dataset with automatic or custom slot assignment."
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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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"metadata": {},
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"outputs": [],
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"source": [
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"import numpy as np\n",
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"import xarray as xr\n",
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"\n",
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"from xarray_plotly import config, xpx\n",
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"\n",
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"config.notebook()"
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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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"metadata": {},
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"outputs": [],
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"source": [
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"# Create a Dataset with multiple variables\n",
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"time = np.arange(50)\n",
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"cities = [\"NYC\", \"LA\", \"Chicago\"]\n",
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"\n",
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"ds = xr.Dataset(\n",
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" {\n",
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" \"temperature\": ([\"time\", \"city\"], 20 + 5 * np.random.randn(50, 3).cumsum(axis=0) / 10),\n",
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" \"humidity\": ([\"time\", \"city\"], 50 + 10 * np.random.randn(50, 3).cumsum(axis=0) / 10),\n",
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" \"pressure\": ([\"time\", \"city\"], 1013 + np.random.randn(50, 3).cumsum(axis=0)),\n",
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" },\n",
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" coords={\"time\": time, \"city\": cities},\n",
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")\n",
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"ds"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"## Plot All Variables\n",
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"\n",
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"When you call a plot method on a Dataset without specifying `var`, all variables are combined into a single DataArray with a new `\"variable\"` dimension:"
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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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"metadata": {},
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"outputs": [],
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"source": [
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"# All variables: time -> x, variable -> color, city -> line_dash\n",
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"xpx(ds).line()"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"## Control Where \"variable\" Goes\n",
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"\n",
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"The `\"variable\"` dimension can be assigned to any slot:"
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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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"metadata": {},
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"outputs": [],
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"source": [
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"# Variables as facet columns\n",
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"xpx(ds).line(facet_col=\"variable\")"
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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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"metadata": {},
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"outputs": [],
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"source": [
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"# Variables as rows, cities as columns\n",
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"xpx(ds).line(facet_row=\"variable\", facet_col=\"city\")"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"## Configure Default \"variable\" Position\n",
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"\n",
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"By default, `\"variable\"` is placed as the **second** dimension so it maps to `color`. This keeps your first dimension (e.g., time) on the x-axis.\n",
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"\n",
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"You can change this globally with `config.set_options()`:"
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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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"metadata": {},
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"outputs": [],
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"source": [
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"# Default: position=1 (second) -> variable goes to color\n",
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"# Note: to_array() puts \"variable\" first, but xpx() reorders it to position 1\n",
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"print(\"Raw to_array() dims:\", ds.to_array().dims) # (variable, time, city)\n",
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"print(\"After xpx reorder: (time, variable, city)\") # time->x, variable->color\n",
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"xpx(ds).line(title=\"Default: variable as color (position=1)\")"
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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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"metadata": {},
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"outputs": [],
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"source": [
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"# Position 0: variable goes first (x-axis) - usually not what you want!\n",
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"with config.set_options(dataset_variable_position=0):\n",
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" fig = xpx(ds).line(title=\"position=0: variable on x-axis (probably not desired)\")\n",
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"fig"
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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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"metadata": {},
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"outputs": [],
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"source": [
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"# Position -1: variable goes last -> city gets color, variable gets line_dash\n",
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"with config.set_options(dataset_variable_position=-1):\n",
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" fig = xpx(ds).line(title=\"position=-1: variable as line_dash\")\n",
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"fig"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"## Plot a Single Variable\n",
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"\n",
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"Use `var=\"name\"` to plot just one variable:"
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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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"metadata": {},
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"outputs": [],
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"source": [
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"xpx(ds).line(var=\"temperature\", title=\"Temperature Only\")"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"## Different Plot Types"
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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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"metadata": {},
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"outputs": [],
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"source": [
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"# Bar chart - latest values by city\n",
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"xpx(ds.isel(time=-1)).bar(x=\"city\", color=\"variable\", barmode=\"group\")"
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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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"metadata": {},
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"outputs": [],
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"source": [
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"# Box plot - distribution by variable\n",
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"xpx(ds).box(x=\"variable\", color=\"city\")"
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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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"metadata": {},
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"outputs": [],
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"source": [
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"# Area chart\n",
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"xpx(ds).area(var=\"humidity\", title=\"Humidity Over Time\")"
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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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"metadata": {},
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"outputs": [],
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"source": [
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"# Scatter\n",
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"xpx(ds).scatter(var=\"temperature\", title=\"Temperature Scatter\")"
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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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"metadata": {},
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"outputs": [],
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"source": [
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"# Pie chart - snapshot at one time\n",
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"xpx(ds.isel(time=-1)).pie(var=\"temperature\", names=\"city\", title=\"Temperature Distribution\")"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"## Combining Slot Assignments\n",
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"\n",
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"Mix explicit assignments with auto-assignment:"
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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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"metadata": {},
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"outputs": [],
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"source": [
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"# Explicit: variable -> facet_col, let city auto-assign to color\n",
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"xpx(ds).line(facet_col=\"variable\", color=\"city\")"
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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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"metadata": {},
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"outputs": [],
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"source": [
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"# Skip color slot with None\n",
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"xpx(ds).line(var=\"temperature\", color=None)"
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]
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}
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],
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"metadata": {
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"kernelspec": {
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"display_name": "Python 3",
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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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"name": "python",
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"version": "3.12.0"
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}
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},
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"nbformat": 4,
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"nbformat_minor": 4
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}

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