Make more cells markdown instead of raw

Author: wesm

appa.ipynb

@@ -634,19 +634,21 @@
    ]
   },
   {
-   "cell_type": "raw",
+   "cell_type": "markdown",
    "metadata": {
     "deletable": true,
     "editable": true
    },
    "source": [
+    "```python\n",
     "def demean_axis(arr, axis=0):\n",
     "    means = arr.mean(axis)\n",
     "\n",
     "    # This generalizes things like [:, :, np.newaxis] to N dimensions\n",
     "    indexer = [slice(None)] * arr.ndim\n",
     "    indexer[axis] = np.newaxis\n",
-    "    return arr - means[indexer]"
+    "    return arr - means[indexer]\n",
+    "```"
    ]
   },
   {
@@ -1342,12 +1344,13 @@
    ]
   },
   {
-   "cell_type": "raw",
+   "cell_type": "markdown",
    "metadata": {
     "deletable": true,
     "editable": true
    },
    "source": [
+    "```python\n",
     "In [209]: x = np.random.randn(10000000)\n",
     "\n",
     "In [210]: y = np.random.randn(10000000)\n",
@@ -1356,28 +1359,32 @@
     "1 loop, best of 3: 2 s per loop\n",
     "\n",
     "In [212]: %timeit (x - y).mean()\n",
-    "100 loops, best of 3: 14.7 ms per loop"
+    "100 loops, best of 3: 14.7 ms per loop\n",
+    "```"
    ]
   },
   {
-   "cell_type": "raw",
+   "cell_type": "markdown",
    "metadata": {
     "deletable": true,
     "editable": true
    },
    "source": [
+    "```python\n",
     "In [213]: import numba as nb\n",
     "\n",
-    "In [214]: numba_mean_distance = nb.jit(mean_distance)"
+    "In [214]: numba_mean_distance = nb.jit(mean_distance)\n",
+    "```"
    ]
   },
   {
-   "cell_type": "raw",
+   "cell_type": "markdown",
    "metadata": {
     "deletable": true,
     "editable": true
    },
    "source": [
+    "```python\n",
     "@nb.jit\n",
     "def mean_distance(x, y):\n",
     "    nx = len(x)\n",
@@ -1386,32 +1393,37 @@
     "    for i in range(nx):\n",
     "        result += x[i] - y[i]\n",
     "        count += 1\n",
-    "    return result / count"
+    "    return result / count\n",
+    "```"
    ]
   },
   {
-   "cell_type": "raw",
+   "cell_type": "markdown",
    "metadata": {
     "deletable": true,
     "editable": true
    },
    "source": [
+    "```python\n",
     "In [215]: %timeit numba_mean_distance(x, y)\n",
-    "100 loops, best of 3: 10.3 ms per loop"
+    "100 loops, best of 3: 10.3 ms per loop\n",
+    "```"
    ]
   },
   {
-   "cell_type": "raw",
+   "cell_type": "markdown",
    "metadata": {
     "deletable": true,
     "editable": true
    },
    "source": [
+    "```python\n",
     "from numba import float64, njit\n",
     "\n",
     "@njit(float64(float64[:], float64[:]))\n",
     "def mean_distance(x, y):\n",
-    "    return (x - y).mean()"
+    "    return (x - y).mean()\n",
+    "```"
    ]
   },
   {
@@ -1425,33 +1437,37 @@
    ]
   },
   {
-   "cell_type": "raw",
+   "cell_type": "markdown",
    "metadata": {
     "deletable": true,
     "editable": true
    },
    "source": [
+    "```python\n",
     "from numba import vectorize\n",
     "\n",
     "@vectorize\n",
     "def nb_add(x, y):\n",
-    "    return x + y"
+    "    return x + y\n",
+    "```"
    ]
   },
   {
-   "cell_type": "raw",
+   "cell_type": "markdown",
    "metadata": {
     "deletable": true,
     "editable": true
    },
    "source": [
+    "```python\n",
     "In [13]: x = np.arange(10)\n",
     "\n",
     "In [14]: nb_add(x, x)\n",
     "Out[14]: array([  0.,   2.,   4.,   6.,   8.,  10.,  12.,  14.,  16.,  18.])\n",
     "\n",
     "In [15]: nb_add.accumulate(x, 0)\n",
-    "Out[15]: array([  0.,   1.,   3.,   6.,  10.,  15.,  21.,  28.,  36.,  45.])"
+    "Out[15]: array([  0.,   1.,   3.,   6.,  10.,  15.,  21.,  28.,  36.,  45.])\n",
+    "```"
    ]
   },
   {
@@ -1678,7 +1694,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.6.0"
+   "version": "3.5.1"
   }
  },
  "nbformat": 4,