diff --git a/ipynb/SpellingBee.ipynb b/ipynb/SpellingBee.ipynb
index bc7fd35..015d807 100644
--- a/ipynb/SpellingBee.ipynb
+++ b/ipynb/SpellingBee.ipynb
@@ -594,7 +594,7 @@
     "Here's my idea:\n",
     "\n",
     "1. Try every pangram letterset, but do some precomputation to make `game_score` much faster:\n",
-    "  - Compute the `letterset` and `word_score` for each word in the word list.\n",
+    "  - Compute the `letterset` and `word_score` for each word in the word list. \n",
     "  - Make a table of `{letterset: total_points}` giving the total points of all words with a given letterset. \n",
     "  - I call this a **points table**.\n",
     "  - These calculations are independent of the honeycomb, so are done once, not 55,902  times. \n",
@@ -721,7 +721,7 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "The letterset `'AGLM'` gets 8 points (7 for AMALGAM and 1 for GLAM).  `'ACEIORT'` gets 31 points (17 for CACCIATORE and 14 for EROTICA). `'AEGM'` gets 1 for GAME and `'AEGLMPX'` gets 15 for MEGAPLEX. The other 59 lettersets have no words, no points.\n",
+    "The letterset `'AGLM'` gets 8 points (7 for AMALGAM and 1 for GLAM).  `'ACEIORT'` gets 31 points (17 for CACCIATORE and 14 for EROTICA). `'AEGM'` gets 1 for GAME and `'AEGLMPX'` gets 15 for MEGAPLEX. \n",
     "\n",
     "Let's make sure the new  `top_honeycomb2` function works as well as the old one:"
    ]
@@ -945,11 +945,11 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "This says that `top_honeycomb3`  examined 8,084 honeycombs; an almost 7-fold improvement over the 55,902 examined by `top_honeycomb2`.\n",
+    "`top_honeycomb3`  examined 8,084 honeycombs; an almost 7-fold reduction from the 55,902 examined by `top_honeycomb2`.\n",
     "\n",
     "# 9: Fancy Report\n",
     "\n",
-    "I'd like to see the actual words that each honeycomb can make, and I'm curious about how the words are divided up by letterset. Here's a function to provide such a report. I remembered that there is a `fill` function in Python (it is in the `textwrap` module) but this report turned out to be a lot more complicated than I anticipated. I guess it is difficult to create a practical extraction and reporting tool. I feel you, [Larry Wall](http://www.wall.org/~larry/)."
+    "I'd like to see the actual words that each honeycomb can make, and I'm curious about how the words are divided up by letterset. Here's a function to provide such a report. This report turned out to be a lot more complicated than I anticipated. I guess it is difficult to create a practical extraction and reporting tool. I feel you, [Larry Wall](http://www.wall.org/~larry/)."
    ]
   },
   {
@@ -1352,7 +1352,7 @@
     "   537 words                         1,179 words \n",
     "    <br>50 pangrams  &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; 86 pangrams\n",
     "    <br>3,898 points &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; 8,681 points\n",
-    "    <br> &nbsp; RETAINING &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; ENTERTAINERS\n",
+    "    <br> &nbsp;  &nbsp; RETAINING &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; ENTERTAINERS\n",
     "</center>"
    ]
   },