From 91571fb520dd76ab4f86e4fbf77d60a1a6d0e8cd Mon Sep 17 00:00:00 2001
From: LinlyBoi <libkyy@e.email>
Date: Tue, 28 Mar 2023 11:23:05 +0200
Subject: [PATCH] Integrating the data in the note book YIPPEEEE

---
 jupyter-notes/Panda Bamboo.ipynb | 65 ++++++++++++++++++++------------
 1 file changed, 41 insertions(+), 24 deletions(-)

diff --git a/jupyter-notes/Panda Bamboo.ipynb b/jupyter-notes/Panda Bamboo.ipynb
index 4ee8038..8b3f2db 100644
--- a/jupyter-notes/Panda Bamboo.ipynb	
+++ b/jupyter-notes/Panda Bamboo.ipynb	
@@ -36,9 +36,9 @@
    "outputs": [],
    "source": [
     "import pandas as pd\n",
+    "from tkinter.filedialog import askopenfilename\n",
     "filename = askopenfilename()\n",
-    "df1= pd.read_csv(filename)\n",
-    "from tkinter.filedialog import askopenfilename"
+    "df1= pd.read_csv(filename)"
    ]
   },
   {
@@ -64,27 +64,9 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 23,
+   "execution_count": null,
    "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "                                       Name\n",
-      "0             Baldur's Gate 3 Early Access \n",
-      "1  Control: Ultimate Edition Cloud Version \n",
-      "2    Doom Eternal: The Ancient Gods Part 1 \n",
-      "3                       Watch Dogs: Legion \n",
-      "4                             Ring Of Pain \n",
-      "5                          Pikmin 3 Deluxe \n",
-      "6                              Ghostrunner \n",
-      "7                                Disc Room \n",
-      "8                                   NHL 21 \n",
-      "9                                    Noita \n"
-     ]
-    }
-   ],
+   "outputs": [],
    "source": [
     "# CLeaning\n",
     "nuke=df1['GameName'].to_list()\n",
@@ -121,7 +103,7 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "# Integrating Game Sales with the previous cleaned data set"
+    "# Integrating Game Datasets together"
    ]
   },
   {
@@ -129,7 +111,42 @@
    "execution_count": null,
    "metadata": {},
    "outputs": [],
-   "source": []
+   "source": [
+    "\n",
+    "filename = askopenfilename()\n",
+    "df2 = pd.read_csv(filename)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# merged = pd.merge(df1,df2, how='inner', sort=True) DOES NOT WORK\n",
+    "# print(merged.head(10))\n",
+    "merged = df2.join(df1, lsuffix='merged') #Good\n",
+    "print(merged.head(10))"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "merged2.to_csv('merged_games.csv')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "print(df1[['Name']].head(100))\n",
+    "print(df2[['Name']].head(100))"
+   ]
   }
  ],
  "metadata": {