Minor updates.

Author: jtkiley

notebooks/1b_handling.ipynb

@@ -376,7 +376,10 @@
    "source": [
     "# Merging\n",
     "\n",
-    "Like other software, `pandas` is great and merging data, and it as some conveniences not found in most other software.\n",
+    "Like other software, `pandas` is great at merging data, and it as some conveniences not found in most other software.\n",
+    "\n",
+    "If you would like another visual example of the types of merges or joins, [this Atlassian document](https://www.atlassian.com/data/sql/sql-join-types-explained-visually) does a nice job of showing and explaining them.\n",
+    "Pandas, like most dataframe packages, uses the same terminology from SQL (which we will see later) to name different join types.\n",
     "\n",
     "Let's work through a simple example to see it in action."
    ]
@@ -608,6 +611,16 @@
     "1. **SQL.** If you are working with a database directly (including the ones we will see later), the SQL support in pandas is really convenient. That said, if you are using a service with its own package (e.g., WRDS), you probably want the more specific package."
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "263aed1a",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# firmyear.to_parquet(\"firmyear.parquet\")"
+   ]
+  },
   {
    "attachments": {},
    "cell_type": "markdown",