diff --git a/astropy.ipynb b/astropy.ipynb
index 62d0525..2c0572c 100644
--- a/astropy.ipynb
+++ b/astropy.ipynb
@@ -1913,16 +1913,25 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 169,
+   "execution_count": 212,
    "metadata": {},
    "outputs": [],
    "source": [
-    "lotss_sources = SkyCoord(ra=lotss_table['RA'], dec=lotss_table['DEC'])"
+    "lotss_selection = lotss_table[lotss_table['Total_flux']>20]"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 170,
+   "execution_count": 213,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "lotss_sources = SkyCoord(ra=lotss_selection['RA'], dec=lotss_selection['DEC'])"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 214,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -1931,7 +1940,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 171,
+   "execution_count": 215,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -1940,29 +1949,27 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 172,
+   "execution_count": 216,
    "metadata": {},
    "outputs": [
     {
      "data": {
       "text/plain": [
-       "array([  22,   36,   37,  253,  289,  310,  448,  556, 1091, 1153, 1201,\n",
-       "       1245, 1277, 1309, 1328, 1477, 1787, 1804, 1845, 1855, 1906, 1932,\n",
-       "       1950, 2036, 2069, 2109, 2139, 2226, 2330, 2351, 2404, 2539, 2613,\n",
-       "       2613, 2685, 2706, 2706, 2708, 2748, 2751, 2817, 2860, 2913, 2913,\n",
-       "       2918, 2928, 3006, 3070, 3072, 3202, 3216, 3239, 3283, 3283, 3326,\n",
-       "       3367, 3423, 3436, 3470, 3497, 3523, 3527, 3545, 3549, 3706, 3706,\n",
-       "       3765, 3791, 3853, 3873, 3930, 3951, 3951, 4001, 4073, 4117, 4151,\n",
-       "       4299, 4355, 4367, 4423, 4443, 4456, 4606, 4632, 4662, 4730, 4741,\n",
-       "       4750, 4785, 4855, 4971, 4972, 4972, 4972, 4982, 5125, 5207, 5361,\n",
-       "       5420, 5420, 5444, 5462, 5464, 5552, 5563, 5602, 5640, 5682, 5701,\n",
-       "       5708, 5732, 5736, 5761, 5802, 5821, 5916, 5923, 5959, 6042, 6104,\n",
-       "       6174, 6194, 6199, 6216, 6246, 6255, 6403, 6428, 6455, 6462, 6478,\n",
-       "       6513, 6526, 6617, 6661, 6661, 6762, 6876, 6934, 6936, 7000, 7048,\n",
-       "       7049, 7052, 7052, 7068, 7131, 7135, 7137, 7196])"
+       "array([  1,   2,   3,   6,   7,   8,   9,  10,  18,  22,  23,  24,  25,\n",
+       "        26,  27,  29,  37,  33,  35,  37,  39,  40,  41,  42,  43,  44,\n",
+       "        45,  48,  50,  51,  52,  53,  54,  54,  57,  58,  58,  59,  60,\n",
+       "        61,  63,  65,  67,  67,  68,  69,  71,  72,  73,  76,  77,  78,\n",
+       "        80,  80,  82,  83,  84,  85,  86,  88,  89,  92,  93,  94,  95,\n",
+       "        95,  96,  98,  99, 100, 101, 102, 102, 104, 106, 107, 108, 112,\n",
+       "       114, 116, 117, 118, 119, 123, 125, 127, 128, 129, 130, 132, 133,\n",
+       "       135, 136, 136, 136, 137, 140, 141, 142, 144, 144, 145, 146, 147,\n",
+       "       148, 151, 152, 154, 155, 156, 157, 158, 159, 160, 163, 161, 162,\n",
+       "       163, 166, 168, 169, 171, 172, 173, 174, 176, 177, 182, 183, 184,\n",
+       "       185, 186, 189, 190, 192, 193, 193, 195, 197, 199, 200, 201, 203,\n",
+       "       204, 205, 205, 208, 209, 210, 211, 212])"
       ]
      },
-     "execution_count": 172,
+     "execution_count": 216,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -1973,14 +1980,14 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 176,
+   "execution_count": 224,
    "metadata": {},
    "outputs": [
     {
      "data": {
-      "image/png": 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\n",
+      "image/png": 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\n",
       "text/plain": [
-       "<Figure size 432x288 with 1 Axes>"
+       "<Figure size 576x576 with 1 Axes>"
       ]
      },
      "metadata": {},
@@ -1988,23 +1995,13 @@
     }
    ],
    "source": [
-    "fig, ax = plt.subplots()\n",
-    "ax.plot(lotss_table[lotss_idx][\"Total_flux\"], tgss_table[\"Sint\"], \"k.\");\n",
-    "ax.set_aspect('auto')"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "*TODO* Make this cross-match somewhat more realistic."
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "Note: Barnard's star simbad astroquery example at https://astroquery.readthedocs.io/en/latest/simbad/simbad.html"
+    "fig, ax = plt.subplots(figsize=(8,8))\n",
+    "ax.plot([0,2000],[0,2000])\n",
+    "ax.plot(lotss_selection[lotss_idx][\"Total_flux\"][dist_2d<0.001*u.deg],\n",
+    "        tgss_table[\"Sint\"][dist_2d<0.001*u.deg], \"k.\");\n",
+    "ax.set_xlabel(\"LoTSS flux\")\n",
+    "ax.set_ylabel(\"TGSS flux\")\n",
+    "ax.set_aspect(1)"
    ]
   },
   {
@@ -2016,7 +2013,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 177,
+   "execution_count": 202,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -2025,7 +2022,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 178,
+   "execution_count": 203,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -2034,7 +2031,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 179,
+   "execution_count": 204,
    "metadata": {},
    "outputs": [
     {
@@ -2359,6 +2356,13 @@
     "print(tap_result.to_table())"
    ]
   },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Note: Barnard's star simbad astroquery example at https://astroquery.readthedocs.io/en/latest/simbad/simbad.html"
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": null,