diff --git a/pandas/pandas.ipynb b/pandas/pandas.ipynb
index 7dcd716..ec66649 100644
--- a/pandas/pandas.ipynb
+++ b/pandas/pandas.ipynb
@@ -1,7 +1,7 @@
 {
  "metadata": {
   "name": "",
-  "signature": "sha256:1d166238da27d666eaee4041e79ad7adcc22b6b5ef5d6098ce354d0160c79ba5"
+  "signature": "sha256:59c1808d14cc90fbdffb75e71fc2ec13c01cc1495fab34aa19ab482445ca6801"
  },
  "nbformat": 3,
  "nbformat_minor": 0,
@@ -3972,7 +3972,8 @@
      "cell_type": "code",
      "collapsed": false,
      "input": [
-      "df_10.sub(ser_10, axis=0)"
+      "df_11 = df_10.sub(ser_10, axis=0)\n",
+      "df_11"
      ],
      "language": "python",
      "metadata": {},
@@ -4028,6 +4029,297 @@
       }
      ],
      "prompt_number": 77
+    },
+    {
+     "cell_type": "markdown",
+     "metadata": {},
+     "source": [
+      "NumPy ufuncs (element-wise array methods) operate on pandas objects:"
+     ]
+    },
+    {
+     "cell_type": "code",
+     "collapsed": false,
+     "input": [
+      "df_12 = np.abs(df_11)\n",
+      "df_12"
+     ],
+     "language": "python",
+     "metadata": {},
+     "outputs": [
+      {
+       "html": [
+        "<div style=\"max-height:1000px;max-width:1500px;overflow:auto;\">\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",
+        "    </tr>\n",
+        "  </thead>\n",
+        "  <tbody>\n",
+        "    <tr>\n",
+        "      <th>0</th>\n",
+        "      <td>  99.451186</td>\n",
+        "      <td>  98.867789</td>\n",
+        "      <td>  98.676912</td>\n",
+        "      <td>  99.999886</td>\n",
+        "    </tr>\n",
+        "    <tr>\n",
+        "      <th>1</th>\n",
+        "      <td> 199.455117</td>\n",
+        "      <td> 199.274013</td>\n",
+        "      <td> 199.207350</td>\n",
+        "      <td> 199.907661</td>\n",
+        "    </tr>\n",
+        "    <tr>\n",
+        "      <th>2</th>\n",
+        "      <td> 299.562413</td>\n",
+        "      <td> 298.921967</td>\n",
+        "      <td> 298.690777</td>\n",
+        "      <td> 299.603233</td>\n",
+        "    </tr>\n",
+        "  </tbody>\n",
+        "</table>\n",
+        "</div>"
+       ],
+       "metadata": {},
+       "output_type": "pyout",
+       "prompt_number": 78,
+       "text": [
+        "            a           b           c           d\n",
+        "0   99.451186   98.867789   98.676912   99.999886\n",
+        "1  199.455117  199.274013  199.207350  199.907661\n",
+        "2  299.562413  298.921967  298.690777  299.603233"
+       ]
+      }
+     ],
+     "prompt_number": 78
+    },
+    {
+     "cell_type": "markdown",
+     "metadata": {},
+     "source": [
+      "Apply a function on 1D arrays to each column:"
+     ]
+    },
+    {
+     "cell_type": "code",
+     "collapsed": false,
+     "input": [
+      "func_1 = lambda x: x.max() - x.min()\n",
+      "df_12.apply(func_1)"
+     ],
+     "language": "python",
+     "metadata": {},
+     "outputs": [
+      {
+       "metadata": {},
+       "output_type": "pyout",
+       "prompt_number": 79,
+       "text": [
+        "a    200.111226\n",
+        "b    200.054178\n",
+        "c    200.013864\n",
+        "d    199.603347\n",
+        "dtype: float64"
+       ]
+      }
+     ],
+     "prompt_number": 79
+    },
+    {
+     "cell_type": "markdown",
+     "metadata": {},
+     "source": [
+      "Apply a function on 1D arrays to each row:"
+     ]
+    },
+    {
+     "cell_type": "code",
+     "collapsed": false,
+     "input": [
+      "df_12.apply(func_1, axis=1)"
+     ],
+     "language": "python",
+     "metadata": {},
+     "outputs": [
+      {
+       "metadata": {},
+       "output_type": "pyout",
+       "prompt_number": 80,
+       "text": [
+        "0    1.322973\n",
+        "1    0.700311\n",
+        "2    0.912456\n",
+        "dtype: float64"
+       ]
+      }
+     ],
+     "prompt_number": 80
+    },
+    {
+     "cell_type": "markdown",
+     "metadata": {},
+     "source": [
+      "Apply a function and return a DataFrame:"
+     ]
+    },
+    {
+     "cell_type": "code",
+     "collapsed": false,
+     "input": [
+      "func_2 = lambda x: Series([x.min(), x.max()], index=['min', 'max'])\n",
+      "df_12.apply(func_2)"
+     ],
+     "language": "python",
+     "metadata": {},
+     "outputs": [
+      {
+       "html": [
+        "<div style=\"max-height:1000px;max-width:1500px;overflow:auto;\">\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",
+        "    </tr>\n",
+        "  </thead>\n",
+        "  <tbody>\n",
+        "    <tr>\n",
+        "      <th>min</th>\n",
+        "      <td>  99.451186</td>\n",
+        "      <td>  98.867789</td>\n",
+        "      <td>  98.676912</td>\n",
+        "      <td>  99.999886</td>\n",
+        "    </tr>\n",
+        "    <tr>\n",
+        "      <th>max</th>\n",
+        "      <td> 299.562413</td>\n",
+        "      <td> 298.921967</td>\n",
+        "      <td> 298.690777</td>\n",
+        "      <td> 299.603233</td>\n",
+        "    </tr>\n",
+        "  </tbody>\n",
+        "</table>\n",
+        "</div>"
+       ],
+       "metadata": {},
+       "output_type": "pyout",
+       "prompt_number": 81,
+       "text": [
+        "              a           b           c           d\n",
+        "min   99.451186   98.867789   98.676912   99.999886\n",
+        "max  299.562413  298.921967  298.690777  299.603233"
+       ]
+      }
+     ],
+     "prompt_number": 81
+    },
+    {
+     "cell_type": "markdown",
+     "metadata": {},
+     "source": [
+      "Apply an element-wise Python function to a DataFrame:"
+     ]
+    },
+    {
+     "cell_type": "code",
+     "collapsed": false,
+     "input": [
+      "func_3 = lambda x: '%.2f' %x\n",
+      "df_12.applymap(func_3)"
+     ],
+     "language": "python",
+     "metadata": {},
+     "outputs": [
+      {
+       "html": [
+        "<div style=\"max-height:1000px;max-width:1500px;overflow:auto;\">\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",
+        "    </tr>\n",
+        "  </thead>\n",
+        "  <tbody>\n",
+        "    <tr>\n",
+        "      <th>0</th>\n",
+        "      <td>  99.45</td>\n",
+        "      <td>  98.87</td>\n",
+        "      <td>  98.68</td>\n",
+        "      <td> 100.00</td>\n",
+        "    </tr>\n",
+        "    <tr>\n",
+        "      <th>1</th>\n",
+        "      <td> 199.46</td>\n",
+        "      <td> 199.27</td>\n",
+        "      <td> 199.21</td>\n",
+        "      <td> 199.91</td>\n",
+        "    </tr>\n",
+        "    <tr>\n",
+        "      <th>2</th>\n",
+        "      <td> 299.56</td>\n",
+        "      <td> 298.92</td>\n",
+        "      <td> 298.69</td>\n",
+        "      <td> 299.60</td>\n",
+        "    </tr>\n",
+        "  </tbody>\n",
+        "</table>\n",
+        "</div>"
+       ],
+       "metadata": {},
+       "output_type": "pyout",
+       "prompt_number": 82,
+       "text": [
+        "        a       b       c       d\n",
+        "0   99.45   98.87   98.68  100.00\n",
+        "1  199.46  199.27  199.21  199.91\n",
+        "2  299.56  298.92  298.69  299.60"
+       ]
+      }
+     ],
+     "prompt_number": 82
+    },
+    {
+     "cell_type": "markdown",
+     "metadata": {},
+     "source": [
+      "Apply an element-wise Python function to a Series:"
+     ]
+    },
+    {
+     "cell_type": "code",
+     "collapsed": false,
+     "input": [
+      "df_12['a'].map(func_3)"
+     ],
+     "language": "python",
+     "metadata": {},
+     "outputs": [
+      {
+       "metadata": {},
+       "output_type": "pyout",
+       "prompt_number": 83,
+       "text": [
+        "0     99.45\n",
+        "1    199.46\n",
+        "2    299.56\n",
+        "Name: a, dtype: object"
+       ]
+      }
+     ],
+     "prompt_number": 83
     }
    ],
    "metadata": {}