{ "cells": [ { "cell_type": "code", "execution_count": null, "metadata": { "collapsed": false, "deletable": true, "editable": true }, "outputs": [], "source": [ "from __future__ import print_function\n", "from bqplot import pyplot as plt\n", "from bqplot import topo_load\n", "from bqplot.interacts import panzoom\n", "import numpy as np\n", "import pandas as pd\n", "import datetime as dt" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "collapsed": false, "deletable": true, "editable": true }, "outputs": [], "source": [ "# initializing data to be plotted\n", "np.random.seed(0)\n", "size = 100\n", "y_data = np.cumsum(np.random.randn(size) * 100.0)\n", "y_data_2 = np.cumsum(np.random.randn(size))\n", "y_data_3 = np.cumsum(np.random.randn(size) * 100.)\n", "\n", "x = np.linspace(0.0, 10.0, size)" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "collapsed": true, "deletable": true, "editable": true }, "outputs": [], "source": [ "price_data = pd.DataFrame(np.cumsum(np.random.randn(150, 2).dot([[0.5, 0.8], [0.8, 1.0]]), axis=0) + 100,\n", " columns=['Security 1', 'Security 2'],\n", " index=pd.date_range(start='01-01-2007', periods=150))\n", "\n", "symbol = 'Security 1'\n", "dates_all = price_data.index.values\n", "final_prices = price_data[symbol].values.flatten()" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "collapsed": true, "deletable": true, "editable": true }, "outputs": [], "source": [ "price_data.index.names = ['date']" ] }, { "cell_type": "markdown", "metadata": { "deletable": true, "editable": true }, "source": [ "## Simple Plots" ] }, { "cell_type": "markdown", "metadata": { "deletable": true, "editable": true }, "source": [ "### Line Chart" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "collapsed": false, "deletable": true, "editable": true }, "outputs": [], "source": [ "plt.figure()\n", "plt.plot(x, y_data)\n", "plt.xlabel('Time')\n", "plt.show()" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "collapsed": true, "deletable": true, "editable": true }, "outputs": [], "source": [ "_ = plt.ylabel('Stock Price')" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "collapsed": true, "deletable": true, "editable": true }, "outputs": [], "source": [ "# Setting the title for the current figure\n", "plt.title('Brownian Increments')" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "collapsed": false, "deletable": true, "editable": true }, "outputs": [], "source": [ "plt.figure()\n", "plt.plot('Security 1', data=price_data)\n", "plt.show()" ] }, { "cell_type": "markdown", "metadata": { "deletable": true, "editable": true }, "source": [ "### Scatter Plot" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "collapsed": false, "deletable": true, "editable": true }, "outputs": [], "source": [ "plt.figure(title='Scatter Plot with colors')\n", "plt.scatter(y_data_2, y_data_3, color=y_data)\n", "plt.show()" ] }, { "cell_type": "markdown", "metadata": { "deletable": true, "editable": true }, "source": [ "### Horizontal and Vertical Lines" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "collapsed": false, "deletable": true, "editable": true }, "outputs": [], "source": [ "## adding a horizontal line at y=0\n", "plt.hline(0)\n", "plt.show()" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "collapsed": false, "deletable": true, "editable": true }, "outputs": [], "source": [ "## adding a vertical line at x=4 with stroke_width and colors being passed.\n", "plt.vline(4., stroke_width=2, colors=['orangered'])\n", "plt.show()" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "collapsed": false, "deletable": true, "editable": true }, "outputs": [], "source": [ "plt.figure()\n", "plt.scatter('Security 1', 'Security 2', color='date', data=price_data.reset_index(), stroke='Black')\n", "plt.show()" ] }, { "cell_type": "markdown", "metadata": { "deletable": true, "editable": true }, "source": [ "### Histogram" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "collapsed": false, "deletable": true, "editable": true }, "outputs": [], "source": [ "plt.figure()\n", "plt.hist(y_data, colors=['OrangeRed'])\n", "plt.show()" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "collapsed": false, "deletable": true, "editable": true }, "outputs": [], "source": [ "plt.figure()\n", "plt.hist('Security 1', data=price_data, colors=['MediumSeaGreen'])\n", "plt.xlabel('Hello')\n", "plt.show()" ] }, { "cell_type": "markdown", "metadata": { "deletable": true, "editable": true }, "source": [ "### Bar Chart" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "collapsed": false, "deletable": true, "editable": true }, "outputs": [], "source": [ "plt.figure()\n", "bar_x=['A', 'B', 'C', 'D', 'E', 'F', 'G', 'H', 'I', 'J', 'K', 'L', 'M', 'N', 'P', 'Q', 'R', 'S', 'T', 'U']\n", "plt.bar(bar_x, y_data_3)\n", "plt.show()" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "collapsed": false, "deletable": true, "editable": true }, "outputs": [], "source": [ "plt.figure()\n", "plt.bar('date', 'Security 2', data=price_data.reset_index()[:10])\n", "plt.show()" ] }, { "cell_type": "markdown", "metadata": { "deletable": true, "editable": true }, "source": [ "### Pie Chart" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "collapsed": false, "deletable": true, "editable": true }, "outputs": [], "source": [ "plt.figure()\n", "d = abs(y_data_2[:5])\n", "plt.pie(d)\n", "plt.show()" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "collapsed": false, "deletable": true, "editable": true }, "outputs": [], "source": [ "plt.figure()\n", "plt.pie('Security 2', color='Security 1', data=price_data[:4])\n", "plt.show()" ] }, { "cell_type": "markdown", "metadata": { "deletable": true, "editable": true }, "source": [ "### OHLC" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "collapsed": false, "deletable": true, "editable": true }, "outputs": [], "source": [ "dates = np.arange(dt.datetime(2014, 1, 2), dt.datetime(2014, 1, 30), dt.timedelta(days=1))\n", "\n", "prices = np.array([[ 187.21 , 187.4 , 185.2 , 185.53 ],\n", " [ 185.83 , 187.35 , 185.3 , 186.64 ],\n", " [ 187.15 , 187.355 , 185.3 , 186. ],\n", " [ 186.39 , 190.35 , 186.38 , 189.71 ],\n", " [ 189.33 , 189.4175, 187.26 , 187.97 ],\n", " [ 189.02 , 189.5 , 186.55 , 187.38 ],\n", " [ 188.31 , 188.57 , 186.28 , 187.26 ],\n", " [ 186.26 , 186.95 , 183.86 , 184.16 ],\n", " [ 185.06 , 186.428 , 183.8818, 185.92 ],\n", " [ 185.82 , 188.65 , 185.49 , 187.74 ],\n", " [ 187.53 , 188.99 , 186.8 , 188.76 ],\n", " [ 188.04 , 190.81 , 187.86 , 190.09 ],\n", " [ 190.23 , 190.39 , 186.79 , 188.43 ],\n", " [ 181.28 , 183.5 , 179.67 , 182.25 ],\n", " [ 181.43 , 183.72 , 180.71 , 182.73 ],\n", " [ 181.25 , 182.8141, 179.64 , 179.64 ],\n", " [ 179.605 , 179.65 , 177.66 , 177.9 ],\n", " [ 178.05 , 178.45 , 176.16 , 176.85 ],\n", " [ 175.98 , 178.53 , 175.89 , 176.4 ],\n", " [ 177.17 , 177.86 , 176.36 , 177.36 ]])\n", "\n", "plt.figure()\n", "plt.ohlc(dates, prices)\n", "plt.show()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Boxplot" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "collapsed": false }, "outputs": [], "source": [ "plt.figure()\n", "plt.boxplot(np.arange(10), np.random.randn(10, 100))\n", "plt.show()" ] }, { "cell_type": "markdown", "metadata": { "deletable": true, "editable": true }, "source": [ "### Map" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "collapsed": false, "deletable": true, "editable": true }, "outputs": [], "source": [ "plt.figure()\n", "plt.geo(map_data='WorldMap')\n", "plt.show()" ] }, { "cell_type": "markdown", "metadata": { "deletable": true, "editable": true }, "source": [ "### Heatmap" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "collapsed": false, "deletable": true, "editable": true }, "outputs": [], "source": [ "plt.figure(padding_y=0)\n", "plt.heatmap(x * x[:, np.newaxis])\n", "plt.show()" ] }, { "cell_type": "markdown", "metadata": { "deletable": true, "editable": true }, "source": [ "### GridHeatMap" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "collapsed": false, "deletable": true, "editable": true }, "outputs": [], "source": [ "plt.figure(padding_y=0)\n", "plt.gridheatmap(x[:10] * x[:10, np.newaxis])\n", "plt.show()" ] }, { "cell_type": "markdown", "metadata": { "deletable": true, "editable": true }, "source": [ "### Plotting Dates" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "collapsed": false, "deletable": true, "editable": true }, "outputs": [], "source": [ "plt.figure()\n", "plt.plot(dates_all, final_prices)\n", "plt.show()" ] }, { "cell_type": "markdown", "metadata": { "deletable": true, "editable": true }, "source": [ "### Editing existing axes properties" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "collapsed": false, "deletable": true, "editable": true }, "outputs": [], "source": [ "## adding grid lines and changing the side of the axis in the figure above\n", "plt.axes(options={'x': {'grid_lines': 'solid'}, 'y': {'side': 'right', 'grid_lines': 'dashed'}})" ] }, { "cell_type": "markdown", "metadata": { "deletable": true, "editable": true }, "source": [ "## Advanced Usage" ] }, { "cell_type": "markdown", "metadata": { "deletable": true, "editable": true }, "source": [ "### Multiple Marks on the same Figure" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "collapsed": false, "deletable": true, "editable": true }, "outputs": [], "source": [ "plt.figure()\n", "plt.plot(x, y_data_3, colors=['orange'])\n", "plt.scatter(x, y_data, stroke='black')\n", "plt.show()" ] }, { "cell_type": "markdown", "metadata": { "deletable": true, "editable": true }, "source": [ "### Using marker strings in Line Chart" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "collapsed": false, "deletable": true, "editable": true }, "outputs": [], "source": [ "mark_x = np.arange(10)\n", "plt.figure(title='Using Marker Strings')\n", "plt.plot(mark_x, 3 * mark_x + 5, 'y-.s') # color=yellow, line_style=dash_dotted, marker=square\n", "plt.plot(mark_x ** 2, 'm:d') # color=magenta, line_style=None, marker=diamond\n", "plt.show()" ] }, { "cell_type": "markdown", "metadata": { "collapsed": true, "deletable": true, "editable": true }, "source": [ "### Partially changing the scales" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "collapsed": false, "deletable": true, "editable": true }, "outputs": [], "source": [ "plt.figure()\n", "plt.plot(x, y_data)\n", "\n", "## preserving the x scale and changing the y scale\n", "plt.scales(scales={'x': plt.Keep})\n", "plt.plot(x, y_data_2, colors=['orange'], axes_options={'y': {'side': 'right', 'color': 'orange',\n", " 'grid_lines': 'none'}})\n", "plt.show()" ] }, { "cell_type": "markdown", "metadata": { "deletable": true, "editable": true }, "source": [ "### Adding a label to the chart" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "collapsed": false, "deletable": true, "editable": true }, "outputs": [], "source": [ "plt.figure()\n", "line = plt.plot(dates_all, final_prices)\n", "plt.show()" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "collapsed": false, "deletable": true, "editable": true }, "outputs": [], "source": [ "## adds the label to the figure created above\n", "plt.label(['Pie Day'], x=[np.datetime64('2007-03-14')], y=[final_prices.mean()], scales=line.scales,\n", " colors=['orange'])" ] }, { "cell_type": "markdown", "metadata": { "deletable": true, "editable": true }, "source": [ "### Changing context figure" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "collapsed": false, "deletable": true, "editable": true }, "outputs": [], "source": [ "plt.figure(1)\n", "plt.plot(x,y_data_3)\n", "plt.show()" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "collapsed": false, "deletable": true, "editable": true }, "outputs": [], "source": [ "plt.figure(2)\n", "plt.plot(x[:20],y_data_3[:20])\n", "plt.show()" ] }, { "cell_type": "markdown", "metadata": { "deletable": true, "editable": true }, "source": [ "### Re-editing first figure" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "collapsed": false, "deletable": true, "editable": true }, "outputs": [], "source": [ "## adds the new line to the first figure\n", "plt.figure(1, title='New title')\n", "plt.plot(x,y_data, colors=['orange'])" ] }, { "cell_type": "markdown", "metadata": { "deletable": true, "editable": true }, "source": [ "### Viewing the properties of the figure" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "collapsed": false, "deletable": true, "editable": true }, "outputs": [], "source": [ "marks = plt.current_figure().marks\n", "marks[0].get_state()" ] }, { "cell_type": "markdown", "metadata": { "deletable": true, "editable": true }, "source": [ "### Showing a second view of the first figure" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "collapsed": false, "deletable": true, "editable": true }, "outputs": [], "source": [ "plt.show()" ] }, { "cell_type": "markdown", "metadata": { "deletable": true, "editable": true }, "source": [ "### Clearing the figure" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "collapsed": true, "deletable": true, "editable": true }, "outputs": [], "source": [ "### Clearing the figure above\n", "plt.clear()" ] }, { "cell_type": "markdown", "metadata": { "deletable": true, "editable": true }, "source": [ "### Deleting a figure and all its views. " ] }, { "cell_type": "code", "execution_count": null, "metadata": { "collapsed": false, "deletable": true, "editable": true }, "outputs": [], "source": [ "plt.show(2)" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "collapsed": true, "deletable": true, "editable": true }, "outputs": [], "source": [ "plt.close(2)" ] }, { "cell_type": "markdown", "metadata": { "deletable": true, "editable": true }, "source": [ "## Interactions in Pyplot" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "collapsed": true, "deletable": true, "editable": true }, "outputs": [], "source": [ "def call_back(name, value):\n", " print(value)" ] }, { "cell_type": "markdown", "metadata": { "deletable": true, "editable": true }, "source": [ "### Brush Selector" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "collapsed": false, "deletable": true, "editable": true }, "outputs": [], "source": [ "plt.figure()\n", "plt.scatter(y_data_2, y_data_3, colors=['orange'], stroke='black')\n", "\n", "## click and drag on the figure to see the selector\n", "plt.brush_selector(call_back)\n", "plt.show(display_toolbar=False)" ] }, { "cell_type": "markdown", "metadata": { "deletable": true, "editable": true }, "source": [ "### Fast Interval Selector" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "collapsed": false, "deletable": true, "editable": true }, "outputs": [], "source": [ "plt.figure()\n", "n= 100\n", "plt.plot(np.arange(n), y_data_3)\n", "## click on the figure to activate the selector\n", "plt.int_selector(call_back)\n", "plt.show(display_toolbar=False)" ] }, { "cell_type": "markdown", "metadata": { "deletable": true, "editable": true }, "source": [ "### Brush Interval Selector with call back on brushing" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "collapsed": false, "deletable": true, "editable": true }, "outputs": [], "source": [ "# click and drag on chart to make a selection\n", "plt.brush_int_selector(call_back, 'brushing')" ] } ], "metadata": { "anaconda-cloud": {}, "kernelspec": { "display_name": "Python [default]", "language": "python", "name": "python3" }, "language_info": { "codemirror_mode": { "name": "ipython", "version": 3 }, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", "version": "3.5.2" } }, "nbformat": 4, "nbformat_minor": 1 }