03_SimpleStockCharts.ipynb

{
  "cells": [
    {
      "cell_type": "markdown",
      "source": [
        "# Simple Stock Charts"
      ],
      "metadata": {}
    },
    {
      "cell_type": "markdown",
      "source": [
        "## Types of Stock Charts"
      ],
      "metadata": {}
    },
    {
      "cell_type": "code",
      "source": [
        "import numpy as np\n",
        "import matplotlib.pyplot as plt\n",
        "import pandas as pd\n",
        "\n",
        "import warnings\n",
        "warnings.filterwarnings(\"ignore\")\n",
        "\n",
        "# fix_yahoo_finance is used to fetch data \n",
        "import fix_yahoo_finance as yf\n",
        "yf.pdr_override()"
      ],
      "outputs": [],
      "execution_count": null,
      "metadata": {
        "collapsed": false,
        "outputHidden": false,
        "inputHidden": false
      }
    },
    {
      "cell_type": "code",
      "source": [
        "# input\n",
        "symbol = 'AAPL'\n",
        "start = '2018-12-01'\n",
        "end = '2019-01-01'\n",
        "\n",
        "# Read data \n",
        "df = yf.download(symbol,start,end)\n",
        "\n",
        "# View Columns\n",
        "df.head()"
      ],
      "outputs": [],
      "execution_count": null,
      "metadata": {
        "collapsed": false,
        "outputHidden": false,
        "inputHidden": false
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "## Line Charts"
      ],
      "metadata": {}
    },
    {
      "cell_type": "code",
      "source": [
        "plt.figure(figsize=(12,8))\n",
        "plt.plot(df['Adj Close'])\n",
        "plt.title(\"Stock Line Chart\")\n",
        "plt.legend(loc='best')\n",
        "plt.xlabel(\"Date\")\n",
        "plt.ylabel(\"Price\")\n",
        "plt.show()"
      ],
      "outputs": [],
      "execution_count": null,
      "metadata": {}
    },
    {
      "cell_type": "markdown",
      "source": [
        "## High Low Close Bar Stock Chart (HLC)"
      ],
      "metadata": {}
    },
    {
      "cell_type": "markdown",
      "source": [
        "https://stackoverflow.com/questions/44810875/how-to-draw-a-classic-stock-chart-with-matplotlib"
      ],
      "metadata": {}
    },
    {
      "cell_type": "markdown",
      "source": [
        "## Open High Low Close Bar Stock Chart (OHLC)"
      ],
      "metadata": {}
    },
    {
      "cell_type": "code",
      "source": [
        "import plotly.plotly as py\n",
        "import plotly.graph_objs as go\n",
        "from plotly.offline import init_notebook_mode, iplot\n",
        "\n",
        "# Plot OHLC Bar Chart\n",
        "trace = go.Ohlc(x=df['12-2018'].index,\n",
        "                open=df['12-2018'].Open,\n",
        "                high=df['12-2018'].High,\n",
        "                low=df['12-2018'].Low,\n",
        "                close=df['12-2018'].Close)\n",
        "data = [trace]\n",
        "iplot(data, filename='simple_ohlc')"
      ],
      "outputs": [],
      "execution_count": null,
      "metadata": {
        "collapsed": false,
        "outputHidden": false,
        "inputHidden": false
      }
    },
    {
      "cell_type": "code",
      "source": [
        "py.iplot(data)"
      ],
      "outputs": [],
      "execution_count": null,
      "metadata": {
        "collapsed": false,
        "outputHidden": false,
        "inputHidden": false
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "## Japanese Candlesticks Charts"
      ],
      "metadata": {}
    },
    {
      "cell_type": "markdown",
      "source": [
        "Learn about candlestick:\n",
        "\n",
        "https://www.quantinsti.com/blog/candlestick-patterns-meaning\n",
        "\nhttps://www.investopedia.com/trading/candlestick-charting-what-is-it/"
      ],
      "metadata": {}
    },
    {
      "cell_type": "code",
      "source": [
        "from mpl_finance import candlestick_ohlc\n",
        "from matplotlib import dates as mdates\n",
        "import datetime as dt"
      ],
      "outputs": [],
      "execution_count": null,
      "metadata": {
        "collapsed": false,
        "outputHidden": false,
        "inputHidden": false
      }
    },
    {
      "cell_type": "code",
      "source": [
        "# Converting date to pandas datetime format\n",
        "dfc = df.copy()\n",
        "dfc = dfc.reset_index()\n",
        "dfc['Date'] = mdates.date2num(dfc['Date'].astype(dt.date))\n",
        "dfc.head()"
      ],
      "outputs": [],
      "execution_count": null,
      "metadata": {
        "collapsed": false,
        "outputHidden": false,
        "inputHidden": false
      }
    },
    {
      "cell_type": "code",
      "source": [
        "fig = plt.figure(figsize=(14,10))\n",
        "ax1 = plt.subplot(2, 1, 1)\n",
        "candlestick_ohlc(ax1,dfc.values, width=0.5, colorup='g', colordown='r', alpha=1.0)\n",
        "ax1.xaxis_date()\n",
        "ax1.xaxis.set_major_formatter(mdates.DateFormatter('%d-%m-%Y'))\n",
        "ax1.set_title('Stock '+ symbol +' Closing Price')\n",
        "ax1.set_ylabel('Price')\n",
        "ax1.legend(loc='best')"
      ],
      "outputs": [],
      "execution_count": null,
      "metadata": {
        "collapsed": false,
        "outputHidden": false,
        "inputHidden": false
      }
    },
    {
      "cell_type": "code",
      "source": [
        "# Plot Candlestick Chart\n",
        "trace = go.Candlestick(x=df['12-2018'].index,\n",
        "                open=df['12-2018'].Open,\n",
        "                high=df['12-2018'].High,\n",
        "                low=df['12-2018'].Low,\n",
        "                close=df['12-2018'].Close)\n",
        "\n",
        "data = [trace]\n",
        "iplot(data, filename='simple_ohlc')"
      ],
      "outputs": [],
      "execution_count": null,
      "metadata": {
        "collapsed": false,
        "outputHidden": false,
        "inputHidden": false
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "## Point and Figure Chart"
      ],
      "metadata": {}
    },
    {
      "cell_type": "markdown",
      "source": [
        "https://github.com/pviglucci/pypf"
      ],
      "metadata": {}
    },
    {
      "cell_type": "code",
      "source": [
        "from pypf.chart import PFChart\n",
        "from pypf.instrument import YahooSecurity\n",
        "i = YahooSecurity(symbol, force_download, force_cache, period, debug)\n",
        "c = PFChart(i, box_size, duration, interval, method, reversal, style, trend_lines, debug)\n",
        "c.create_chart()\n",
        "print(c.chart)"
      ],
      "outputs": [],
      "execution_count": null,
      "metadata": {
        "collapsed": false,
        "outputHidden": false,
        "inputHidden": false
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "## Market Profile Stock Charts"
      ],
      "metadata": {}
    },
    {
      "cell_type": "markdown",
      "source": [
        "https://github.com/bfolkens/py-market-profile"
      ],
      "metadata": {}
    },
    {
      "cell_type": "code",
      "source": [
        "from market_profile import MarketProfile"
      ],
      "outputs": [],
      "execution_count": null,
      "metadata": {
        "collapsed": false,
        "outputHidden": false,
        "inputHidden": false
      }
    },
    {
      "cell_type": "code",
      "source": [
        "mp = MarketProfile(df, tick_size=1)\n",
        "mp_slice = mp[df.index.max() - pd.Timedelta(6.5, 'd'):df.index.max()]"
      ],
      "outputs": [],
      "execution_count": null,
      "metadata": {
        "collapsed": false,
        "outputHidden": false,
        "inputHidden": false
      }
    },
    {
      "cell_type": "code",
      "source": [
        "data = mp_slice.profile\n",
        "data.plot(kind='bar')"
      ],
      "outputs": [],
      "execution_count": null,
      "metadata": {
        "collapsed": false,
        "outputHidden": false,
        "inputHidden": false
      }
    }
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