diff --git a/groupby.ipynb b/groupby.ipynb
index bcc13ae..f4c124c 100644
--- a/groupby.ipynb
+++ b/groupby.ipynb
@@ -12,6 +12,980 @@
     "import numpy as np"
    ]
   },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## 分组计算\n",
+    "\n",
+    "分组计算三步曲：拆分 -> 应用 -> 合并\n",
+    "\n",
+    "* 拆分：根据什么进行分组？\n",
+    "* 应用：每个分组进行什么样的计算？\n",
+    "* 合并：把每个分组的计算结果合并起来。\n",
+    "\n",
+    "\n",
+    "![groupby](groupby.png)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 8,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>data1</th>\n",
+       "      <th>data2</th>\n",
+       "      <th>key1</th>\n",
+       "      <th>key2</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>6</td>\n",
+       "      <td>1</td>\n",
+       "      <td>a</td>\n",
+       "      <td>one</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>2</td>\n",
+       "      <td>8</td>\n",
+       "      <td>a</td>\n",
+       "      <td>two</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>4</td>\n",
+       "      <td>7</td>\n",
+       "      <td>b</td>\n",
+       "      <td>one</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>4</td>\n",
+       "      <td>6</td>\n",
+       "      <td>b</td>\n",
+       "      <td>two</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>1</td>\n",
+       "      <td>7</td>\n",
+       "      <td>a</td>\n",
+       "      <td>one</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "   data1  data2 key1 key2\n",
+       "0      6      1    a  one\n",
+       "1      2      8    a  two\n",
+       "2      4      7    b  one\n",
+       "3      4      6    b  two\n",
+       "4      1      7    a  one"
+      ]
+     },
+     "execution_count": 8,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "df = pd.DataFrame({'key1': ['a', 'a', 'b', 'b', 'a'],\n",
+    "                  'key2': ['one', 'two', 'one', 'two', 'one'],\n",
+    "                  'data1': np.random.randint(1, 10, 5),\n",
+    "                  'data2': np.random.randint(1, 10, 5)})\n",
+    "df"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### 对 Series 进行分组\n",
+    "\n",
+    "通过索引对齐关联起来"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 9,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [],
+   "source": [
+    "grouped = df['data1'].groupby(df['key1'])"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 10,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "key1\n",
+       "a    3\n",
+       "b    4\n",
+       "Name: data1, dtype: int32"
+      ]
+     },
+     "execution_count": 10,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "grouped.mean()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 13,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "key1  key2\n",
+       "a     one     3.5\n",
+       "      two     2.0\n",
+       "b     one     4.0\n",
+       "      two     4.0\n",
+       "Name: data1, dtype: float64"
+      ]
+     },
+     "execution_count": 13,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "df['data1'].groupby([df['key1'], df['key2']]).mean()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### 对 DataFrame 进行分组"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 25,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>data1</th>\n",
+       "      <th>data2</th>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>key1</th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>a</th>\n",
+       "      <td>3</td>\n",
+       "      <td>5.333333</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>b</th>\n",
+       "      <td>4</td>\n",
+       "      <td>6.500000</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "      data1     data2\n",
+       "key1                 \n",
+       "a         3  5.333333\n",
+       "b         4  6.500000"
+      ]
+     },
+     "execution_count": 25,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "df.groupby('key1').mean()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 26,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "key1  key2\n",
+       "a     one     3.5\n",
+       "      two     2.0\n",
+       "b     one     4.0\n",
+       "      two     4.0\n",
+       "Name: data1, dtype: float64"
+      ]
+     },
+     "execution_count": 26,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "means = df.groupby(['key1', 'key2']).mean()['data1']\n",
+    "means"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 27,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th>key2</th>\n",
+       "      <th>one</th>\n",
+       "      <th>two</th>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>key1</th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>a</th>\n",
+       "      <td>3.5</td>\n",
+       "      <td>2</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>b</th>\n",
+       "      <td>4.0</td>\n",
+       "      <td>4</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "key2  one  two\n",
+       "key1          \n",
+       "a     3.5    2\n",
+       "b     4.0    4"
+      ]
+     },
+     "execution_count": 27,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "means.unstack()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 64,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "key1  key2\n",
+       "a     one     3.5\n",
+       "      two     2.0\n",
+       "b     one     4.0\n",
+       "      two     4.0\n",
+       "Name: data1, dtype: float64"
+      ]
+     },
+     "execution_count": 64,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "df.groupby(['key1', 'key2'])['data1'].mean()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### 每个分组的元素个数"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 29,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "key1  key2\n",
+       "a     one     2\n",
+       "      two     1\n",
+       "b     one     1\n",
+       "      two     1\n",
+       "dtype: int64"
+      ]
+     },
+     "execution_count": 29,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "df.groupby(['key1', 'key2']).size()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### 对分组进行迭代"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 35,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "a\n",
+      "   data1  data2 key1 key2\n",
+      "0      6      1    a  one\n",
+      "1      2      8    a  two\n",
+      "4      1      7    a  one\n",
+      "b\n",
+      "   data1  data2 key1 key2\n",
+      "2      4      7    b  one\n",
+      "3      4      6    b  two\n"
+     ]
+    }
+   ],
+   "source": [
+    "for name, group in df.groupby('key1'):\n",
+    "    print name\n",
+    "    print group\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 37,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "('a', 'one')\n",
+      "   data1  data2 key1 key2\n",
+      "0      6      1    a  one\n",
+      "4      1      7    a  one\n",
+      "('a', 'two')\n",
+      "   data1  data2 key1 key2\n",
+      "1      2      8    a  two\n",
+      "('b', 'one')\n",
+      "   data1  data2 key1 key2\n",
+      "2      4      7    b  one\n",
+      "('b', 'two')\n",
+      "   data1  data2 key1 key2\n",
+      "3      4      6    b  two\n"
+     ]
+    }
+   ],
+   "source": [
+    "for name, group in df.groupby(['key1', 'key2']):\n",
+    "    print name\n",
+    "    print group"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### 转化为字典"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 40,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "{'a':    data1  data2 key1 key2\n",
+       " 0      6      1    a  one\n",
+       " 1      2      8    a  two\n",
+       " 4      1      7    a  one, 'b':    data1  data2 key1 key2\n",
+       " 2      4      7    b  one\n",
+       " 3      4      6    b  two}"
+      ]
+     },
+     "execution_count": 40,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "d = dict(list(df.groupby('key1')))\n",
+    "d"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 41,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>data1</th>\n",
+       "      <th>data2</th>\n",
+       "      <th>key1</th>\n",
+       "      <th>key2</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>6</td>\n",
+       "      <td>1</td>\n",
+       "      <td>a</td>\n",
+       "      <td>one</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>2</td>\n",
+       "      <td>8</td>\n",
+       "      <td>a</td>\n",
+       "      <td>two</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>1</td>\n",
+       "      <td>7</td>\n",
+       "      <td>a</td>\n",
+       "      <td>one</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "   data1  data2 key1 key2\n",
+       "0      6      1    a  one\n",
+       "1      2      8    a  two\n",
+       "4      1      7    a  one"
+      ]
+     },
+     "execution_count": 41,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "d['a']"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### 按列分组"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 55,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "data1     int32\n",
+       "data2     int32\n",
+       "key1     object\n",
+       "key2     object\n",
+       "dtype: object"
+      ]
+     },
+     "execution_count": 55,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "df.dtypes"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 63,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "{dtype('int32'):    data1  data2\n",
+       " 0      6      1\n",
+       " 1      2      8\n",
+       " 2      4      7\n",
+       " 3      4      6\n",
+       " 4      1      7, dtype('O'):   key1 key2\n",
+       " 0    a  one\n",
+       " 1    a  two\n",
+       " 2    b  one\n",
+       " 3    b  two\n",
+       " 4    a  one}"
+      ]
+     },
+     "execution_count": 63,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "grouped = df.groupby(df.dtypes, axis=1)\n",
+    "dict(list(grouped))"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### 通过字典进行分组"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 83,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>a</th>\n",
+       "      <th>b</th>\n",
+       "      <th>c</th>\n",
+       "      <th>d</th>\n",
+       "      <th>e</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>Alice</th>\n",
+       "      <td>8</td>\n",
+       "      <td>5</td>\n",
+       "      <td>3</td>\n",
+       "      <td>7</td>\n",
+       "      <td>3</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>Bob</th>\n",
+       "      <td>2</td>\n",
+       "      <td>3</td>\n",
+       "      <td>3</td>\n",
+       "      <td>6</td>\n",
+       "      <td>9</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>Candy</th>\n",
+       "      <td>3</td>\n",
+       "      <td>9</td>\n",
+       "      <td>7</td>\n",
+       "      <td>9</td>\n",
+       "      <td>1</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>Dark</th>\n",
+       "      <td>1</td>\n",
+       "      <td>8</td>\n",
+       "      <td>3</td>\n",
+       "      <td>6</td>\n",
+       "      <td>4</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>Emily</th>\n",
+       "      <td>2</td>\n",
+       "      <td>3</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "      <td>3</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "       a  b  c  d  e\n",
+       "Alice  8  5  3  7  3\n",
+       "Bob    2  3  3  6  9\n",
+       "Candy  3  9  7  9  1\n",
+       "Dark   1  8  3  6  4\n",
+       "Emily  2  3  1  1  3"
+      ]
+     },
+     "execution_count": 83,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "df = pd.DataFrame(np.random.randint(1, 10, (5, 5)), \n",
+    "                  columns=['a', 'b', 'c', 'd', 'e'], \n",
+    "                  index=['Alice', 'Bob', 'Candy', 'Dark', 'Emily'])\n",
+    "df"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 84,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>a</th>\n",
+       "      <th>b</th>\n",
+       "      <th>c</th>\n",
+       "      <th>d</th>\n",
+       "      <th>e</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>Alice</th>\n",
+       "      <td>8</td>\n",
+       "      <td>5</td>\n",
+       "      <td>3</td>\n",
+       "      <td>7</td>\n",
+       "      <td>3</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>Bob</th>\n",
+       "      <td>2</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>6</td>\n",
+       "      <td>9</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>Candy</th>\n",
+       "      <td>3</td>\n",
+       "      <td>9</td>\n",
+       "      <td>7</td>\n",
+       "      <td>9</td>\n",
+       "      <td>1</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>Dark</th>\n",
+       "      <td>1</td>\n",
+       "      <td>8</td>\n",
+       "      <td>3</td>\n",
+       "      <td>6</td>\n",
+       "      <td>4</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>Emily</th>\n",
+       "      <td>2</td>\n",
+       "      <td>3</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "      <td>3</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "       a   b   c  d  e\n",
+       "Alice  8   5   3  7  3\n",
+       "Bob    2 NaN NaN  6  9\n",
+       "Candy  3   9   7  9  1\n",
+       "Dark   1   8   3  6  4\n",
+       "Emily  2   3   1  1  3"
+      ]
+     },
+     "execution_count": 84,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "df.ix[1, 1:3] = np.NaN\n",
+    "df"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 87,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [],
+   "source": [
+    "mapping = {'a': 'red', 'b': 'red', 'c': 'blue', 'd': 'orange', 'e': 'blue'}\n",
+    "grouped = df.groupby(mapping, axis=1)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 88,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>blue</th>\n",
+       "      <th>orange</th>\n",
+       "      <th>red</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>Alice</th>\n",
+       "      <td>6</td>\n",
+       "      <td>7</td>\n",
+       "      <td>13</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>Bob</th>\n",
+       "      <td>9</td>\n",
+       "      <td>6</td>\n",
+       "      <td>2</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>Candy</th>\n",
+       "      <td>8</td>\n",
+       "      <td>9</td>\n",
+       "      <td>12</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>Dark</th>\n",
+       "      <td>7</td>\n",
+       "      <td>6</td>\n",
+       "      <td>9</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>Emily</th>\n",
+       "      <td>4</td>\n",
+       "      <td>1</td>\n",
+       "      <td>5</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "       blue  orange  red\n",
+       "Alice     6       7   13\n",
+       "Bob       9       6    2\n",
+       "Candy     8       9   12\n",
+       "Dark      7       6    9\n",
+       "Emily     4       1    5"
+      ]
+     },
+     "execution_count": 88,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "grouped.sum()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 89,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>blue</th>\n",
+       "      <th>orange</th>\n",
+       "      <th>red</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>Alice</th>\n",
+       "      <td>2</td>\n",
+       "      <td>1</td>\n",
+       "      <td>2</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>Bob</th>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>Candy</th>\n",
+       "      <td>2</td>\n",
+       "      <td>1</td>\n",
+       "      <td>2</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>Dark</th>\n",
+       "      <td>2</td>\n",
+       "      <td>1</td>\n",
+       "      <td>2</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>Emily</th>\n",
+       "      <td>2</td>\n",
+       "      <td>1</td>\n",
+       "      <td>2</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "       blue  orange  red\n",
+       "Alice     2       1    2\n",
+       "Bob       1       1    1\n",
+       "Candy     2       1    2\n",
+       "Dark      2       1    2\n",
+       "Emily     2       1    2"
+      ]
+     },
+     "execution_count": 89,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "grouped.count()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 90,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "blue      2\n",
+       "orange    1\n",
+       "red       2\n",
+       "dtype: int64"
+      ]
+     },
+     "execution_count": 90,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "grouped.size()"
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": null,