{
 "cells": [
  {
   "cell_type": "code",
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   "source": [
    "import pandas as pd\n",
    "import numpy as np\n",
    "import plotly.express as px\n",
    "import plotly.graph_objects as go\n",
    "from jupyter_dash import JupyterDash\n",
    "import dash_core_components as dcc\n",
    "import dash_html_components as html\n",
    "from dash.dependencies import Input, Output\n",
    "\n",
    "# code and plot setup\n",
    "# settings\n",
    "pd.options.plotting.backend = \"plotly\"\n",
    "\n",
    "# sample dataframe of a wide format\n",
    "np.random.seed(4); cols = list('abc')\n",
    "X = np.random.randn(50,len(cols))  \n",
    "df=pd.DataFrame(X, columns=cols)\n",
    "df.iloc[0]=0;\n",
    "\n",
    "# plotly figure\n",
    "fig = df.plot()\n",
    "\n",
    "app = JupyterDash(__name__)\n",
    "app.layout = html.Div([\n",
    "    html.H1(\"Random datastream\"),\n",
    "            dcc.Interval(\n",
    "            id='interval-component',\n",
    "            interval=1*1000, # in milliseconds\n",
    "            n_intervals=0\n",
    "        ),\n",
    "    dcc.Graph(id='graph'),\n",
    "])\n",
    "\n",
    "# Define callback to update graph\n",
    "@app.callback(\n",
    "    Output('graph', 'figure'),\n",
    "    [Input('interval-component', \"n_intervals\")]\n",
    ")\n",
    "def streamFig(value):\n",
    "    \n",
    "    global df\n",
    "    \n",
    "    Y = np.random.randn(1,len(cols))  \n",
    "    df2 = pd.DataFrame(Y, columns = cols)\n",
    "    df = df.append(df2, ignore_index=True)#.reset_index()\n",
    "    df.tail()\n",
    "    df3=df.copy()\n",
    "    df3 = df3.cumsum()\n",
    "    fig = df3.plot()\n",
    "    return(fig)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
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    "app.run_server(mode='inline')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
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