diff --git a/src/01 Preprocessing.ipynb b/src/01 Preprocessing.ipynb
index d62ec51..ab288fb 100644
--- a/src/01 Preprocessing.ipynb	
+++ b/src/01 Preprocessing.ipynb	
@@ -622,7 +622,7 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "# Remove head coach that were appointed after 2023 seasons\n",
+    "# Remove head coach that were appointed after 2023 season\n",
     "head_coach = head_coach[head_coach['Appointed'] <= '2024-01-14']\n",
     "# Keep head coach that were dimissed after 2015 or that are still active\n",
     "head_coach = head_coach[(head_coach['EndDate'] >= '2015-01-01') | (head_coach['EndDate'].isna())]"
@@ -2212,9 +2212,9 @@
  ],
  "metadata": {
   "kernelspec": {
-   "display_name": "Python (TER)",
+   "display_name": "TER",
    "language": "python",
-   "name": "ter"
+   "name": "python3"
   },
   "language_info": {
    "codemirror_mode": {
diff --git a/src/02 Exploratory data analysis.ipynb b/src/02 Exploratory data analysis.ipynb
index 94769da..c355050 100644
--- a/src/02 Exploratory data analysis.ipynb	
+++ b/src/02 Exploratory data analysis.ipynb	
@@ -11,7 +11,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 10,
+   "execution_count": 1,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -24,7 +24,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 11,
+   "execution_count": 2,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -42,7 +42,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 12,
+   "execution_count": 3,
    "metadata": {},
    "outputs": [
     {
@@ -158,7 +158,7 @@
        "4      Alan Pardew      1423.0  "
       ]
      },
-     "execution_count": 12,
+     "execution_count": 3,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -170,7 +170,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 13,
+   "execution_count": 4,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -179,7 +179,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 14,
+   "execution_count": 5,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -312,7 +312,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 15,
+   "execution_count": 6,
    "metadata": {},
    "outputs": [
     {
@@ -407,7 +407,7 @@
        "Serie A        Italy                       1.36  "
       ]
      },
-     "execution_count": 15,
+     "execution_count": 6,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -430,7 +430,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 16,
+   "execution_count": 7,
    "metadata": {},
    "outputs": [
     {
@@ -467,7 +467,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 17,
+   "execution_count": 8,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -566,12 +566,12 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 18,
+   "execution_count": 10,
    "metadata": {},
    "outputs": [
     {
      "data": {
-      "image/png": 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       "text/plain": [
        "<Figure size 1920x1440 with 1 Axes>"
       ]
@@ -584,7 +584,7 @@
     "#| label: venue_effect\n",
     "plt.figure()\n",
     "sns.countplot(data=match_results[match_results['isHome']], x='Result', hue = \"Result\",\n",
-    "               order = ['win', 'draw', 'loss'], stat = 'proportion', palette = ['red', 'gray', 'green'], alpha = 0.75)\n",
+    "               order = ['win', 'draw', 'loss'], stat = 'proportion', palette = ['red', 'green', 'gray'], alpha = 0.75)\n",
     "plt.title('Match Outcome for Team playing at Home')\n",
     "plt.xlabel('')\n",
     "plt.ylabel('Percentage of Matches')\n",
@@ -601,9 +601,9 @@
  ],
  "metadata": {
   "kernelspec": {
-   "display_name": "Python (TER)",
+   "display_name": "TER",
    "language": "python",
-   "name": "ter"
+   "name": "python3"
   },
   "language_info": {
    "codemirror_mode": {