Update loading-looking.ipynb

content/03-pandas/loading-looking.ipynb

@@ -22,7 +22,7 @@
     "Throughout this chapter, we will use `pandas` to explore a dataset on beer sales across 50 continental states in the US. \n",
     "Above, we have already imported in `pandas` as `pd`, a common nickname for `pandas` (similar to how `numpy` is often abbreviated to `np`).\n",
     "\n",
-    "The dataset we're using is sourced from [_Salience and Taxation: Theory and Evidence_](https://www.aeaweb.org/articles?id=10.1257/aer.99.4.1145) by Chetty, Looney, and Kroft (AER 2009). The original data can be found at the paper's [replication package](https://www.openicpsr.org/openicpsr/project/113312/version/V1/view), and we have modified it for education use. The dataset includes 7 columns:\n",
+    "The dataset we're using is sourced from [_Salience and Taxation: Theory and Evidence_](https://www.aeaweb.org/articles?id=10.1257/aer.99.4.1145) by Chetty, Looney, and Kroft (AER 2009). The original data can be found at the paper's [replication package](https://www.openicpsr.org/openicpsr/project/113312/version/V1/view), and we have modified it for educational use. The dataset includes 7 columns:\n",
     "- `st_name`: the state abbreviation\n",
     "- `year`: the year the data was recorded\n",
     "- `c_beer`: the quantity of beer consumed, in thousands of gallons\n",