mirror of
https://github.com/vale981/emacs-ipython-notebook
synced 2025-03-09 11:56:38 -04:00
523 lines
256 KiB
Text
523 lines
256 KiB
Text
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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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"# Third Party Libraries With Rich Output"
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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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"A number of third party libraries defined their own custom display logic. This gives their objcts rich output by default when used in the 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": 7,
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"metadata": {
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"collapsed": false
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},
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"outputs": [],
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"source": [
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"from IPython.display import display"
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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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"## Pandas"
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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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"[Pandas](http://pandas.pydata.org/) is a data analysis library for Python. Its `DataFrame` objects have an HTML table representation in the 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": 9,
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"metadata": {
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"collapsed": false
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},
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"outputs": [],
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"source": [
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"import pandas"
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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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"Here is a small amount of stock data for APPL:"
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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": 10,
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"metadata": {
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"collapsed": false
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},
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"Writing data.csv\n"
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]
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}
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],
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"source": [
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"%%writefile data.csv\n",
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"Date,Open,High,Low,Close,Volume,Adj Close\n",
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"2012-06-01,569.16,590.00,548.50,584.00,14077000,581.50\n",
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"2012-05-01,584.90,596.76,522.18,577.73,18827900,575.26\n",
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"2012-04-02,601.83,644.00,555.00,583.98,28759100,581.48\n",
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"2012-03-01,548.17,621.45,516.22,599.55,26486000,596.99\n",
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"2012-02-01,458.41,547.61,453.98,542.44,22001000,540.12\n",
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"2012-01-03,409.40,458.24,409.00,456.48,12949100,454.53"
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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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"Read this as into a `DataFrame`:"
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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": 11,
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"metadata": {
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"collapsed": false
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},
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"outputs": [],
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"source": [
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"df = pandas.read_csv('data.csv')"
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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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"And view the HTML representation:"
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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": 12,
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"metadata": {
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"collapsed": false
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},
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"outputs": [
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{
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"data": {
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"text/html": [
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"<div style=\"max-height:1000px;max-width:1500px;overflow:auto;\">\n",
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"<table border=\"1\" class=\"dataframe\">\n",
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" <thead>\n",
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" <tr style=\"text-align: right;\">\n",
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" <th></th>\n",
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" <th>Date</th>\n",
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" <th>Open</th>\n",
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" <th>High</th>\n",
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" <th>Low</th>\n",
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" <th>Close</th>\n",
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" <th>Volume</th>\n",
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" <th>Adj Close</th>\n",
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" </tr>\n",
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" </thead>\n",
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" <tbody>\n",
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" <tr>\n",
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" <th>0</th>\n",
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" <td> 2012-06-01</td>\n",
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" <td> 569.16</td>\n",
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" <td> 590.00</td>\n",
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" <td> 548.50</td>\n",
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" <td> 584.00</td>\n",
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" <td> 14077000</td>\n",
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" <td> 581.50</td>\n",
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" </tr>\n",
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" <tr>\n",
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" <th>1</th>\n",
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" <td> 2012-05-01</td>\n",
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" <td> 584.90</td>\n",
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" <td> 596.76</td>\n",
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" <td> 522.18</td>\n",
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" <td> 577.73</td>\n",
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" <td> 18827900</td>\n",
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" <td> 575.26</td>\n",
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" </tr>\n",
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" <tr>\n",
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" <th>2</th>\n",
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" <td> 2012-04-02</td>\n",
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" <td> 601.83</td>\n",
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" <td> 644.00</td>\n",
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" <td> 555.00</td>\n",
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" <td> 583.98</td>\n",
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" <td> 28759100</td>\n",
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" <td> 581.48</td>\n",
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" </tr>\n",
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" <tr>\n",
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" <th>3</th>\n",
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" <td> 2012-03-01</td>\n",
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" <td> 548.17</td>\n",
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" <td> 621.45</td>\n",
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" <td> 516.22</td>\n",
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" <td> 599.55</td>\n",
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" <td> 26486000</td>\n",
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" <td> 596.99</td>\n",
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" </tr>\n",
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" <tr>\n",
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" <th>4</th>\n",
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" <td> 2012-02-01</td>\n",
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" <td> 458.41</td>\n",
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" <td> 547.61</td>\n",
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" <td> 453.98</td>\n",
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" <td> 542.44</td>\n",
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" <td> 22001000</td>\n",
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" <td> 540.12</td>\n",
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" </tr>\n",
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" <tr>\n",
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" <th>5</th>\n",
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" <td> 2012-01-03</td>\n",
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" <td> 409.40</td>\n",
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" <td> 458.24</td>\n",
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" <td> 409.00</td>\n",
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" <td> 456.48</td>\n",
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" <td> 12949100</td>\n",
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" <td> 454.53</td>\n",
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" </tr>\n",
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" </tbody>\n",
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"</table>\n",
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"<p>6 rows \u00d7 7 columns</p>\n",
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"</div>"
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],
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"text/plain": [
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" Date Open High Low Close Volume Adj Close\n",
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"0 2012-06-01 569.16 590.00 548.50 584.00 14077000 581.50\n",
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"1 2012-05-01 584.90 596.76 522.18 577.73 18827900 575.26\n",
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"2 2012-04-02 601.83 644.00 555.00 583.98 28759100 581.48\n",
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"3 2012-03-01 548.17 621.45 516.22 599.55 26486000 596.99\n",
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"4 2012-02-01 458.41 547.61 453.98 542.44 22001000 540.12\n",
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"5 2012-01-03 409.40 458.24 409.00 456.48 12949100 454.53\n",
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"\n",
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"[6 rows x 7 columns]"
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]
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},
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"execution_count": 12,
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"metadata": {},
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"output_type": "execute_result"
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}
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],
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"source": [
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"df"
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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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"## SymPy"
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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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"[SymPy](http://sympy.org/) is a symbolic computing library for Python. Its equation objects have LaTeX representations that are rendered in the 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": 13,
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"metadata": {
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"collapsed": false
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},
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"outputs": [],
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"source": [
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"from sympy.interactive.printing import init_printing\n",
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"init_printing(use_latex='mathjax')"
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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": 14,
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"metadata": {
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"collapsed": false
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},
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"outputs": [],
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"source": [
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"from __future__ import division\n",
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"import sympy as sym\n",
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"from sympy import *\n",
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"x, y, z = symbols(\"x y z\")\n",
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"k, m, n = symbols(\"k m n\", integer=True)\n",
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"f, g, h = map(Function, 'fgh')"
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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": 15,
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"metadata": {
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"collapsed": false
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},
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"outputs": [
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{
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"data": {
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"text/latex": [
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"$$\\frac{3 \\pi}{2} + \\frac{e^{i x}}{x^{2} + y}$$"
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],
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"text/plain": [
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" \u2148\u22c5x \n",
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"3\u22c5\u03c0 \u212f \n",
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"\u2500\u2500\u2500 + \u2500\u2500\u2500\u2500\u2500\u2500\n",
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" 2 2 \n",
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" x + y"
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]
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},
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"execution_count": 15,
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"metadata": {},
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"output_type": "execute_result"
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}
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],
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"source": [
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"Rational(3,2)*pi + exp(I*x) / (x**2 + y)"
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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": 16,
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"metadata": {
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"collapsed": false
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},
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"outputs": [
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{
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"data": {
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"text/latex": [
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"$$\\frac{1}{x} \\left(x \\sin{\\left (x \\right )} - 1\\right) + \\frac{1}{x}$$"
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],
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"text/plain": [
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"x\u22c5sin(x) - 1 1\n",
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"\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500 + \u2500\n",
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" x x"
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]
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},
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"execution_count": 16,
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"metadata": {},
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"output_type": "execute_result"
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}
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],
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"source": [
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"a = 1/x + (x*sin(x) - 1)/x\n",
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"a"
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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": 17,
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"metadata": {
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"collapsed": false
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},
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"outputs": [
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{
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"data": {
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"text/latex": [
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"$$1 + \\frac{x^{2}}{2} + \\frac{5 x^{4}}{24} + \\mathcal{O}\\left(x^{6}\\right)$$"
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],
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"text/plain": [
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" 2 4 \n",
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" x 5\u22c5x \u239b 6\u239e\n",
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"1 + \u2500\u2500 + \u2500\u2500\u2500\u2500 + O\u239dx \u23a0\n",
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" 2 24 "
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]
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},
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"execution_count": 17,
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"metadata": {},
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"output_type": "execute_result"
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}
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],
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"source": [
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"(1/cos(x)).series(x, 0, 6)"
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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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"## Vincent"
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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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"[Vincent](https://vincent.readthedocs.org/en/latest/) is a visualization library that uses the [Vega](http://trifacta.github.io/vega/) visualization grammar to build [d3.js](http://d3js.org/) based visualizations in the Notebook and on http://nbviewer.ipython.org. `Visualization` objects in Vincetn have rich HTML and JavaSrcript representations."
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||
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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": 1,
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"metadata": {
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||
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"collapsed": false
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||
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},
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"outputs": [],
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||
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"source": [
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"import vincent\n",
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"import pandas as pd"
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]
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},
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"cell_type": "code",
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"execution_count": 5,
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},
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"outputs": [],
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"source": [
|
||
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"import pandas.io.data as web\n",
|
||
|
|
"import datetime\n",
|
||
|
|
"all_data = {}\n",
|
||
|
|
"date_start = datetime.datetime(2010, 1, 1)\n",
|
||
|
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"date_end = datetime.datetime(2014, 1, 1)\n",
|
||
|
|
"for ticker in ['AAPL', 'IBM', 'YHOO', 'MSFT']:\n",
|
||
|
|
" all_data[ticker] = web.DataReader(ticker, 'yahoo', date_start, date_end)\n",
|
||
|
|
"price = pd.DataFrame({tic: data['Adj Close']\n",
|
||
|
|
" for tic, data in all_data.items()})"
|
||
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]
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},
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" chart({el: \"#vis47fdfca404f24684b44753131b44ed27\"}).update();\n",
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" };\n",
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" _do_plot();\n",
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" })();\n",
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"</script>\n",
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|
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"<style>.vega canvas {width: 100%;}</style>\n",
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" "
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],
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"text/plain": [
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"<vincent.charts.Line at 0x10290f710>"
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]
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}
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],
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"source": [
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||
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"line = vincent.Line(price[['AAPL', 'IBM', 'YHOO', 'MSFT']], width=600, height=300)\n",
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||
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|
"line.axis_titles(x='Date', y='Price')\n",
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||
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|
"line.legend(title='Ticker')\n",
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"display(line)"
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]
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}
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