More snippits

Author: chrisalbon

Untitled0.ipynb

@@ -0,0 +1,84 @@
+{
+ "metadata": {
+  "name": "",
+  "signature": "sha256:cde834b4630abeb021db1dc03e98b143f55b68177957a95a558f61eb79bf28a7"
+ },
+ "nbformat": 3,
+ "nbformat_minor": 0,
+ "worksheets": [
+  {
+   "cells": [
+    {
+     "cell_type": "code",
+     "collapsed": false,
+     "input": [
+      "import pandas as pd\n",
+      "\n",
+      "raw_data = {'name': ['Miller', 'Jacobson', 'Ali', 'Milner', 'Cooze', 'Jacon', 'Ryaner', 'Sone', 'Sloan', 'Piger', 'Riani', 'Ali'], \n",
+      "        'score': [25, 94, 57, 62, 70, 25, 94, 57, 62, 70, 62, 70]}\n",
+      "df = pd.DataFrame(raw_data, columns = ['name', 'score'])\n",
+      "\n",
+      "bins = [0, 25, 50, 75, 100]\n",
+      "group_names = ['Low', 'Okay', 'Good', 'Great']\n",
+      "\n",
+      "cat_obj = pd.cut(df['score'], bins, labels=group_names)\n",
+      "df['cat'] = pd.cut(df['score'], bins, labels=group_names)"
+     ],
+     "language": "python",
+     "metadata": {},
+     "outputs": [],
+     "prompt_number": 4
+    },
+    {
+     "cell_type": "code",
+     "collapsed": false,
+     "input": [
+      "type(cat_obj)"
+     ],
+     "language": "python",
+     "metadata": {},
+     "outputs": [
+      {
+       "metadata": {},
+       "output_type": "pyout",
+       "prompt_number": 7,
+       "text": [
+        "pandas.core.categorical.Categorical"
+       ]
+      }
+     ],
+     "prompt_number": 7
+    },
+    {
+     "cell_type": "code",
+     "collapsed": false,
+     "input": [
+      "type(df['cat'])"
+     ],
+     "language": "python",
+     "metadata": {},
+     "outputs": [
+      {
+       "metadata": {},
+       "output_type": "pyout",
+       "prompt_number": 8,
+       "text": [
+        "pandas.core.series.Series"
+       ]
+      }
+     ],
+     "prompt_number": 8
+    },
+    {
+     "cell_type": "code",
+     "collapsed": false,
+     "input": [],
+     "language": "python",
+     "metadata": {},
+     "outputs": []
+    }
+   ],
+   "metadata": {}
+  }
+ ]
+}