update notebook

gboeing · Jan 31, 2024 · 37d0549 · 37d0549
1 parent 4acca05
commit 37d0549
Showing 1 changed file with 2 additions and 2 deletions.
diff --git a/modules/04-data-cleaning-exploration/lecture.ipynb b/modules/04-data-cleaning-exploration/lecture.ipynb
@@ -10,7 +10,7 @@
     "  - Data cleaning and feature engineering with real world data sets\n",
     "  - Exploring data sets with descriptive stats and visualization\n",
     "  \n",
-    "To set this lecture up, I downloaded the most popular data sets from 1) LA's covid dashboard, 2) the LA city data portal, and 3) the LA county data portal. This gives us a variety of real-world data sets that are relatively messy and require some cleaning and transformation prior to analysis."
+    "To set this lecture up, I downloaded the most popular data sets a couple years ago from 1) LA's covid dashboard, 2) the LA city data portal, and 3) the LA county data portal. This gives us a variety of real-world data sets that are relatively messy and require some cleaning and transformation prior to analysis."
    ]
   },
   {
@@ -842,7 +842,7 @@
    "source": [
     "# count plot: like a histogram counting observations across categorical instead of continuous data\n",
     "order = sectors.value_counts().index\n",
-    "ax = sns.countplot(x=sectors, order=order, alpha=0.9, palette=\"plasma\")\n",
+    "ax = sns.countplot(x=sectors, order=order, alpha=0.9)\n",
     "ax.set_xlabel(\"NAICS Sector\")\n",
     "ax.set_ylabel(\"Number of businesses\")\n",
     "ax.get_figure().savefig(\"countplot-naics.png\", dpi=300, bbox_inches=\"tight\")"