{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<div class=\"contentcontainer med left\" style=\"margin-left: -50px;\">\n",
    "<dl class=\"dl-horizontal\">\n",
    "  <dt>Title</dt> <dd> Curve Element</dd>\n",
    "  <dt>Dependencies</dt> <dd>Plotly</dd>\n",
    "  <dt>Backends</dt> <dd><a href='../bokeh/Curve.ipynb'>Bokeh</a></dd> <dd><a href='../matplotlib/Curve.ipynb'>Matplotlib</a></dd> <dd><a href='./Curve.ipynb'>Plotly</a></dd>\n",
    "</dl>\n",
    "</div>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import holoviews as hv\n",
    "hv.extension('plotly')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "``Curve`` Elements are used to display quantitative values over a continuous interval or time span. They accept tabular data with one key dimension representing the samples along the x-axis and one value dimension of the height of the curve at for each sample. See the [Tabular Datasets](../../../user_guide/08-Tabular_Datasets.ipynb) user guide for supported data formats, which include arrays, pandas dataframes and dictionaries of arrays."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Simple Curve\n",
    "\n",
    "A ``Curve`` is a set of values provided for some set of keys from a [continuously indexable 1D coordinate system](../../../user_guide/Continuous_Coordinates.ipynb), where the plotted values will be connected up because they are assumed to be samples from a continuous relation."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "points = [(0.1*i, np.sin(0.1*i)) for i in range(100)]\n",
    "hv.Curve(points)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Interpolation"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The ``Curve`` also supports the ``interpolation`` plot option to determine whether to linearly interpolate the curve values or to draw discrete steps:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "hv.NdOverlay({interp: hv.Curve(points[::8]).opts(interpolation=interp)\n",
    "              for interp in ['linear', 'steps-mid', 'steps-pre', 'steps-post']})"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "For full documentation and the available style and plot options, use ``hv.help(hv.Curve).``"
   ]
  }
 ],
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