{
"cells": [
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# Introduction to IPython Notebook"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"###Why do I use IPython notebook:\n",
"* Interactive like a REPL\n",
"* Durrable artifacts in cells\n",
"* Shareable like a document...with built-in annotations!\n",
"\n",
"A motivating example..."
]
},
{
"cell_type": "code",
"execution_count": 7,
"metadata": {
"collapsed": false
},
"outputs": [],
"source": [
"from __future__ import division, print_function\n",
"import numpy as np\n",
"import pandas as pd"
]
},
{
"cell_type": "code",
"execution_count": 8,
"metadata": {
"collapsed": false
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"881.png Section3_bokeh.ipynb heat_3-2.png\r\n",
"AAPL.hdf5 Section4_vtk.ipynb interestingBugs.jpg\r\n",
"GOOG.hdf5 Section4_vtk.py iris.csv\r\n",
"README.md Untitled0.ipynb python.png\r\n",
"SaintHelens.vtk goog_fit.png selection.png\r\n",
"Section0_intro.ipynb heat_1-1.png smooth_kernel.png\r\n",
"Section1-1_ipython.ipynb heat_1-2.png smooth_power.png\r\n",
"Section1-2_matplotlib-Live.ipynb heat_2-1.png smooth_signal.png\r\n",
"Section1-2_matplotlib.ipynb heat_2-2.png\r\n",
"Section2_numpy_scipy_pandas.ipynb heat_3-1.png\r\n"
]
}
],
"source": [
"!ls"
]
},
{
"cell_type": "code",
"execution_count": 9,
"metadata": {
"collapsed": false
},
"outputs": [
{
"data": {
"text/plain": [
"Index([u'Unnamed: 0', u'SepalLength', u'SepalWidth', u'PetalLength', u'PetalWidth', u'Species'], dtype='object')"
]
},
"execution_count": 9,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"iris = pd.read_csv(\"iris.csv\")\n",
"iris.columns"
]
},
{
"cell_type": "code",
"execution_count": 10,
"metadata": {
"collapsed": false
},
"outputs": [
{
"data": {
"text/plain": [
"0 5.1\n",
"1 4.9\n",
"2 4.7\n",
"3 4.6\n",
"4 5.0\n",
"Name: SepalLength, dtype: float64"
]
},
"execution_count": 10,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"#iris['SepalLength'].head()\n",
"iris.SepalLength.head()"
]
},
{
"cell_type": "code",
"execution_count": 11,
"metadata": {
"collapsed": false
},
"outputs": [
{
"data": {
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