Merge pull request #7 from dataquestio/fix/josh/improve-solutions

Fix/josh/improve solutions

.gitignore

@@ -3,3 +3,4 @@
 .ipynb_checkpoints
 __pycache__
 temp.py
+*.db

Mission216Solutions.ipynb

@@ -9,11 +9,34 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 1,
    "metadata": {
-    "collapsed": true
+    "collapsed": false
    },
-   "outputs": [],
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "(0, 'Year', 'INTEGER', 0, None, 0)\n",
+      "(1, 'Category', 'TEXT', 0, None, 0)\n",
+      "(2, 'Nominee', 'TEXT', 0, None, 0)\n",
+      "(3, 'Won', 'INTEGER', 0, None, 0)\n",
+      "(4, 'Movie', 'TEXT', 0, None, 0)\n",
+      "(5, 'Character', 'TEXT', 0, None, 0)\n",
+      "(2010, 'Actor -- Leading Role', 'Javier Bardem', 0, 'Biutiful', 'Uxbal')\n",
+      "(2010, 'Actor -- Leading Role', 'Jeff Bridges', 0, 'True Grit', 'Rooster Cogburn')\n",
+      "(2010, 'Actor -- Leading Role', 'Jesse Eisenberg', 0, 'The Social Network', 'Mark Zuckerberg')\n",
+      "(2010, 'Actor -- Leading Role', 'Colin Firth', 1, \"The King's Speech\", 'King George VI')\n",
+      "(2010, 'Actor -- Leading Role', 'James Franco', 0, '127 Hours', 'Aron Ralston')\n",
+      "(2010, 'Actor -- Supporting Role', 'Christian Bale', 1, 'The Fighter', 'Dicky Eklund')\n",
+      "(2010, 'Actor -- Supporting Role', 'John Hawkes', 0, \"Winter's Bone\", 'Teardrop')\n",
+      "(2010, 'Actor -- Supporting Role', 'Jeremy Renner', 0, 'The Town', 'James Coughlin')\n",
+      "(2010, 'Actor -- Supporting Role', 'Mark Ruffalo', 0, 'The Kids Are All Right', 'Paul')\n",
+      "(2010, 'Actor -- Supporting Role', 'Geoffrey Rush', 0, \"The King's Speech\", 'Lionel Logue')\n"
+     ]
+    }
+   ],
    "source": [
     "import sqlite3\n",
     "conn = sqlite3.connect(\"nominations.db\")\n",
@@ -36,11 +59,20 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 2,
    "metadata": {
-    "collapsed": true
+    "collapsed": false
    },
-   "outputs": [],
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "[(1, 2010, 'Steve Martin'), (2, 2009, 'Hugh Jackman'), (3, 2008, 'Jon Stewart'), (4, 2007, 'Ellen DeGeneres'), (5, 2006, 'Jon Stewart'), (6, 2005, 'Chris Rock'), (7, 2004, 'Billy Crystal'), (8, 2003, 'Steve Martin'), (9, 2002, 'Whoopi Goldberg'), (10, 2001, 'Steve Martin')]\n",
+      "[(0, 'id', 'integer', 0, None, 1), (1, 'year', 'integer', 0, None, 0), (2, 'host', 'text', 0, None, 0)]\n"
+     ]
+    }
+   ],
    "source": [
     "years_hosts = [(2010, \"Steve Martin\"),\n",
     "               (2009, \"Hugh Jackman\"),\n",
@@ -72,11 +104,22 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 3,
    "metadata": {
-    "collapsed": true
+    "collapsed": false
    },
-   "outputs": [],
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<sqlite3.Cursor at 0x10675e3b0>"
+      ]
+     },
+     "execution_count": 3,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
    "source": [
     "conn.execute(\"PRAGMA foreign_keys = ON;\")"
    ]
@@ -90,11 +133,19 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 4,
    "metadata": {
-    "collapsed": true
+    "collapsed": false
    },
-   "outputs": [],
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "[(1, 'Actor -- Leading Role', 'Javier Bardem', 'Biutiful', 'Uxbal', '0', 1), (2, 'Actor -- Leading Role', 'Jeff Bridges', 'True Grit', 'Rooster Cogburn', '0', 1), (3, 'Actor -- Leading Role', 'Jesse Eisenberg', 'The Social Network', 'Mark Zuckerberg', '0', 1), (4, 'Actor -- Leading Role', 'Colin Firth', \"The King's Speech\", 'King George VI', '1', 1), (5, 'Actor -- Leading Role', 'James Franco', '127 Hours', 'Aron Ralston', '0', 1)]\n"
+     ]
+    }
+   ],
    "source": [
     "create_nominations_two = '''create table nominations_two \n",
     "(id integer primary key, \n",
@@ -102,7 +153,8 @@
     "nominee text, \n",
     "movie text, \n",
     "character text, \n",
-    "won text, \n",
+    "won text,\n",
+    "ceremony_id integer,\n",
     "foreign key(ceremony_id) references ceremonies(id));\n",
     "'''\n",
     "\n",
@@ -136,14 +188,25 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 5,
    "metadata": {
-    "collapsed": true
+    "collapsed": false
    },
-   "outputs": [],
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<sqlite3.Cursor at 0x10675e6c0>"
+      ]
+     },
+     "execution_count": 5,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
    "source": [
-    "drop_nomimations = \"drop table nominations;\"\n",
-    "conn.execute(drop_nominations_two)\n",
+    "drop_nominations = \"drop table nominations;\"\n",
+    "conn.execute(drop_nominations)\n",
     "\n",
     "rename_nominations_two = \"alter table nominations_two rename to nominations;\"\n",
     "conn.execute(rename_nominations_two)"
@@ -158,11 +221,22 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 6,
    "metadata": {
-    "collapsed": true
+    "collapsed": false
    },
-   "outputs": [],
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<sqlite3.Cursor at 0x10675e960>"
+      ]
+     },
+     "execution_count": 6,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
    "source": [
     "create_movies = \"create table movies (id integer primary key,movie text);\"\n",
     "create_actors = \"create table actors (id integer primary key,actor text);\"\n",
@@ -183,11 +257,20 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 7,
    "metadata": {
-    "collapsed": true
+    "collapsed": false
    },
-   "outputs": [],
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "[(1, 'Biutiful'), (2, 'True Grit'), (3, 'The Social Network'), (4, \"The King's Speech\"), (5, '127 Hours')]\n",
+      "[(1, 'Javier Bardem'), (2, 'Jeff Bridges'), (3, 'Jesse Eisenberg'), (4, 'Colin Firth'), (5, 'James Franco')]\n"
+     ]
+    }
+   ],
    "source": [
     "insert_movies = \"insert into movies (movie) select distinct movie from nominations;\"\n",
     "insert_actors = \"insert into actors (actor) select distinct nominee from nominations;\"\n",
@@ -207,11 +290,19 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 8,
    "metadata": {
-    "collapsed": true
+    "collapsed": false
    },
-   "outputs": [],
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "[(1, 1, 1), (2, 2, 2), (3, 3, 3), (4, 4, 4), (5, 5, 5)]\n"
+     ]
+    }
+   ],
    "source": [
     "pairs_query = \"select movie,nominee from nominations;\"\n",
     "movie_actor_pairs = conn.execute(pairs_query).fetchall()\n",
@@ -221,6 +312,15 @@
     "\n",
     "print(conn.execute(\"select * from movies_actors limit 5;\").fetchall())"
    ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "collapsed": true
+   },
+   "outputs": [],
+   "source": []
   }
  ],
  "metadata": {
@@ -239,7 +339,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.5.0"
+   "version": "3.5.1"
   }
  },
  "nbformat": 4,

README.md

@@ -0,0 +1,16 @@
+# Dataquest Project Solutions
+
+This repository is a series of notebooks that show solutions for the [projects](https://www.dataquest.io/apply) at [Dataquest.io](https://www.dataquest.io/).
+
+Of course, there are always going to be multiple ways to solve any one problem, so these notebooks just show one possible solution.
+
+- [Guided Project: Customizing Data Visualizations](https://github.com/dataquestio/solutions/blob/master/Mission103Solutions.ipynb)
+- [Guided Project: Star Wars survey](https://github.com/dataquestio/solutions/blob/master/Mission201Solutions.ipynb)
+- [Guided Project: Police killings](https://github.com/dataquestio/solutions/blob/master/Mission202Solutions.ipynb)
+- [Guided Project: Visualizing Pixar's Roller Coaster](https://github.com/dataquestio/solutions/blob/master/Mission205Solutions.ipynb)
+- [Guided Project: Analyzing movie reviews](https://github.com/dataquestio/solutions/blob/master/Mission209Solutions.ipynb)
+- [Guided Project: Winning Jeopardy](https://github.com/dataquestio/solutions/blob/master/Mission210Solutions.ipynb)
+- [Guided Project: Predicting board game reviews](https://github.com/dataquestio/solutions/blob/master/Mission211Solutions.ipynb)
+- [Guided Project: Predicting bike rentals](https://github.com/dataquestio/solutions/blob/master/Mission213Solutions.ipynb)
+- [Guided Project: Preparing data for SQLite](https://github.com/dataquestio/solutions/blob/master/Mission215Solutions.ipynb)
+- [Guided Project: Creating relations in SQLite](https://github.com/dataquestio/solutions/blob/master/Mission216Solutions.ipynb)