From df6449b55fe4e57038c019f79e5c95e960393c69 Mon Sep 17 00:00:00 2001
From: cif <cif2cif@gmail.com>
Date: Mon, 7 Mar 2022 12:57:17 +0100
Subject: [PATCH] Updated to last version of seaborn

---
 ml2/3_4_Visualisation_Pandas.ipynb | 28 +++++++++-------------------
 1 file changed, 9 insertions(+), 19 deletions(-)

diff --git a/ml2/3_4_Visualisation_Pandas.ipynb b/ml2/3_4_Visualisation_Pandas.ipynb
index e802a5d..846dc34 100644
--- a/ml2/3_4_Visualisation_Pandas.ipynb
+++ b/ml2/3_4_Visualisation_Pandas.ipynb
@@ -367,7 +367,7 @@
    "outputs": [],
    "source": [
     "# Now we visualise age and survived to see if there is some relationship\n",
-    "sns.FacetGrid(df, hue=\"Survived\", size=5).map(sns.kdeplot, \"Age\").add_legend()"
+    "sns.FacetGrid(df, hue=\"Survived\", height=5).map(sns.kdeplot, \"Age\").add_legend()"
    ]
   },
   {
@@ -567,7 +567,7 @@
    "outputs": [],
    "source": [
     "# Plot with seaborn\n",
-    "sns.countplot('Sex', data=df)"
+    "sns.countplot(x='Sex', data=df)"
    ]
   },
   {
@@ -683,16 +683,6 @@
     "df.groupby('Pclass').size()"
    ]
   },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "# Distribution\n",
-    "sns.countplot('Pclass', data=df)"
-   ]
-  },
   {
    "cell_type": "markdown",
    "metadata": {},
@@ -725,7 +715,7 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "sns.factorplot('Pclass',data=df,hue='Sex',kind='count')"
+    "sns.catplot(x='Pclass',data=df,hue='Sex',kind='count')"
    ]
   },
   {
@@ -906,7 +896,7 @@
    "outputs": [],
    "source": [
     "# Distribution\n",
-    "sns.countplot('Embarked', data=df)"
+    "sns.countplot(x='Embarked', data=df)"
    ]
   },
   {
@@ -997,7 +987,7 @@
    "outputs": [],
    "source": [
     "# Distribution\n",
-    "sns.countplot('SibSp', data=df)"
+    "sns.countplot(x='SibSp', data=df)"
    ]
   },
   {
@@ -1180,7 +1170,7 @@
    "outputs": [],
    "source": [
     "# Distribution\n",
-    "sns.countplot('Parch', data=df)"
+    "sns.countplot(x='Parch', data=df)"
    ]
   },
   {
@@ -1233,7 +1223,7 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "df.groupby(['Pclass', 'Sex', 'Parch'])['Parch', 'SibSp', 'Survived'].agg({'Parch': np.size, 'SibSp': np.mean, 'Survived': np.mean})"
+    "df.groupby(['Pclass', 'Sex', 'Parch'])[['Parch', 'SibSp', 'Survived']].agg({'Parch': np.size, 'SibSp': np.mean, 'Survived': np.mean})"
    ]
   },
   {
@@ -1576,7 +1566,7 @@
  ],
  "metadata": {
   "kernelspec": {
-   "display_name": "Python 3",
+   "display_name": "Python 3 (ipykernel)",
    "language": "python",
    "name": "python3"
   },
@@ -1590,7 +1580,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.7.1"
+   "version": "3.8.12"
   },
   "latex_envs": {
    "LaTeX_envs_menu_present": true,