fix

notebooks/live_coding_04_distributions_statistical_measures.ipynb

@@ -445,7 +445,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 28,
+   "execution_count": 40,
    "id": "50694ecb",
    "metadata": {
     "tags": [
@@ -454,7 +454,7 @@
    },
    "outputs": [],
    "source": [
-    "filename = r\"https://github.com/florian-huber/data_science_course/blob/a595bd6b19565cedff0c3917012be6e05223f7fb/datasets/datasaurus.csv\"\n",
+    "filename = r\"https://raw.githubusercontent.com/florian-huber/data_science_course/a595bd6b19565cedff0c3917012be6e05223f7fb/datasets/datasaurus.csv\"\n",
     "\n",
     "# read data\n",
     "data = pd.read_csv(filename)\n",
@@ -553,7 +553,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "ee3ff920",
+   "id": "54eb9aa9",
    "metadata": {},
    "source": [
     "We can use Pandas and its `groupby` method to quickly get several important statistical measures on all 14 subsets:"
@@ -766,7 +766,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "d5dc7497",
+   "id": "6754183f",
    "metadata": {},
    "source": [
     "### Mini-Exercise: What do you think?\n",
@@ -775,7 +775,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "3bfffda4",
+   "id": "fbbf844e",
    "metadata": {},
    "source": [
     "### Solution\n",
@@ -1976,7 +1976,7 @@
    "id": "92bc9773",
    "metadata": {},
    "source": [
-    "This visualization provides an illustrative look at how wealth is dispersed across different segments of society. Through such visual aids, abstract numbers transform into tangible insights. And I bet the help a lot in sparking some discussions on the distribution of wealth..."
+    "This visualization provides an illustrative look at how wealth is dispersed across different segments of society. Through such visual aids, abstract numbers transform into tangible insights. And I bet they help a lot in sparking discussions on the distribution of wealth..."
    ]
   }
  ],