From ebcbc58cc7e080888929aea6e19177b158cc5df3 Mon Sep 17 00:00:00 2001
From: Ahmed Nasser <ahmednasser1601@gmail.com>
Date: Mon, 26 Sep 2022 22:54:54 +0200
Subject: [PATCH] Created using Colaboratory

---
 Stock_Analysis_Netflix.ipynb | 247 ++++++++++++++++++-----------------
 1 file changed, 124 insertions(+), 123 deletions(-)

diff --git a/Stock_Analysis_Netflix.ipynb b/Stock_Analysis_Netflix.ipynb
index aae92b8..9fa67b3 100644
--- a/Stock_Analysis_Netflix.ipynb
+++ b/Stock_Analysis_Netflix.ipynb
@@ -5,8 +5,7 @@
     "colab": {
       "provenance": [],
       "collapsed_sections": [],
-      "toc_visible": true,
-      "authorship_tag": "ABX9TyPEU1N1rqEFDb/+wLASqbLn",
+      "authorship_tag": "ABX9TyN9YaO1JTFIyCR0ieNNGmpk",
       "include_colab_link": true
     },
     "kernelspec": {
@@ -88,62 +87,64 @@
     {
       "cell_type": "markdown",
       "source": [
-        ">> #### |> ***Connect Kaggle with API_Token***\n",
+        ">> #### |> ***Download Dataset with API_Token***\n",
         ">> \"username\":\"ahmednasser1601\""
       ],
       "metadata": {
-        "id": "PFVlqxtJhA3S"
+        "id": "cbFIl_HVuUWJ"
       }
     },
     {
       "cell_type": "code",
       "source": [
-        "!mkdir ~/.kaggle\n",
-        "!touch ~/.kaggle/kaggle.json\n",
-        "\n",
-        "api_token = {\"username\":\"ahmednasser1601\",\"key\":\"fd950b67a38861322900a50fdc9f6881\"}\n",
+        "!pip install jovian opendatasets --upgrade --quiet\n",
+        "!pip install -q kaggle\n",
         "\n",
-        "with open('/root/.kaggle/kaggle.json', 'w') as file:\n",
-        "    json.dump(api_token, file)\n",
+        "import urllib.request\n",
+        "import opendatasets as od\n",
         "\n",
-        "!chmod 600 ~/.kaggle/kaggle.json"
-      ],
-      "metadata": {
-        "id": "a6C0xmzSKaS3"
-      },
-      "execution_count": 2,
-      "outputs": []
-    },
-    {
-      "cell_type": "markdown",
-      "source": [
-        ">> #### |> ***Download Dataset***"
-      ],
-      "metadata": {
-        "id": "cbFIl_HVuUWJ"
-      }
-    },
-    {
-      "cell_type": "code",
-      "source": [
-        "!kaggle datasets download pritsheta/netflix-stock-data-from-2002-to-2021 -f NFLX.csv"
+        "od.download(\"https://www.kaggle.com/datasets/pritsheta/netflix-stock-data-from-2002-to-2021\")"
       ],
       "metadata": {
         "colab": {
           "base_uri": "https://localhost:8080/"
         },
         "id": "qJ78InyzNSmF",
-        "outputId": "f09ca838-94d5-4152-ba56-06baf9d4e808"
+        "outputId": "92862f06-7e74-4b13-8ad7-b44b22add43e"
       },
-      "execution_count": 3,
+      "execution_count": 2,
       "outputs": [
         {
           "output_type": "stream",
           "name": "stdout",
           "text": [
-            "Downloading NFLX.csv to /content\n",
-            "\r  0% 0.00/328k [00:00<?, ?B/s]\n",
-            "\r100% 328k/328k [00:00<00:00, 86.5MB/s]\n"
+            "\u001b[?25l\r\u001b[K     |████▊                           | 10 kB 31.3 MB/s eta 0:00:01\r\u001b[K     |█████████▌                      | 20 kB 11.1 MB/s eta 0:00:01\r\u001b[K     |██████████████▎                 | 30 kB 14.7 MB/s eta 0:00:01\r\u001b[K     |███████████████████             | 40 kB 13.6 MB/s eta 0:00:01\r\u001b[K     |███████████████████████▉        | 51 kB 12.5 MB/s eta 0:00:01\r\u001b[K     |████████████████████████████▋   | 61 kB 14.5 MB/s eta 0:00:01\r\u001b[K     |████████████████████████████████| 68 kB 5.7 MB/s \n",
+            "\u001b[?25h  Building wheel for uuid (setup.py) ... \u001b[?25l\u001b[?25hdone\n",
+            "Please provide your Kaggle credentials to download this dataset. Learn more: http://bit.ly/kaggle-creds\n",
+            "Your Kaggle username: ahmednasser1601\n",
+            "Your Kaggle Key: ··········\n",
+            "Downloading netflix-stock-data-from-2002-to-2021.zip to ./netflix-stock-data-from-2002-to-2021\n"
+          ]
+        },
+        {
+          "output_type": "stream",
+          "name": "stderr",
+          "text": [
+            "100%|██████████| 92.7k/92.7k [00:00<00:00, 26.9MB/s]"
+          ]
+        },
+        {
+          "output_type": "stream",
+          "name": "stdout",
+          "text": [
+            "\n"
+          ]
+        },
+        {
+          "output_type": "stream",
+          "name": "stderr",
+          "text": [
+            "\n"
           ]
         }
       ]
@@ -151,7 +152,7 @@
     {
       "cell_type": "code",
       "source": [
-        "df = pd.read_csv('NFLX.csv')\n",
+        "df = pd.read_csv('netflix-stock-data-from-2002-to-2021/NFLX.csv')\n",
         "df['Date'] = pd.to_datetime(df['Date'])\n",
         "df = df.set_index('Date')\n",
         "df"
@@ -162,9 +163,9 @@
           "height": 455
         },
         "id": "bZCx1uF7pa2k",
-        "outputId": "d7d70693-e839-440c-afdc-711de1ec2c98"
+        "outputId": "40a8a426-8586-47a7-f75d-c2e983296b19"
       },
-      "execution_count": 4,
+      "execution_count": 3,
       "outputs": [
         {
           "output_type": "execute_result",
@@ -202,7 +203,7 @@
             ],
             "text/html": [
               "\n",
-              "  <div id=\"df-a9f722f5-a76b-4be4-a5fd-b79d0817364b\">\n",
+              "  <div id=\"df-b20041e9-5a41-4990-9f68-2a7e02d8e5aa\">\n",
               "    <div class=\"colab-df-container\">\n",
               "      <div>\n",
               "<style scoped>\n",
@@ -343,7 +344,7 @@
               "</table>\n",
               "<p>4874 rows × 6 columns</p>\n",
               "</div>\n",
-              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-a9f722f5-a76b-4be4-a5fd-b79d0817364b')\"\n",
+              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-b20041e9-5a41-4990-9f68-2a7e02d8e5aa')\"\n",
               "              title=\"Convert this dataframe to an interactive table.\"\n",
               "              style=\"display:none;\">\n",
               "        \n",
@@ -394,12 +395,12 @@
               "\n",
               "      <script>\n",
               "        const buttonEl =\n",
-              "          document.querySelector('#df-a9f722f5-a76b-4be4-a5fd-b79d0817364b button.colab-df-convert');\n",
+              "          document.querySelector('#df-b20041e9-5a41-4990-9f68-2a7e02d8e5aa button.colab-df-convert');\n",
               "        buttonEl.style.display =\n",
               "          google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
               "\n",
               "        async function convertToInteractive(key) {\n",
-              "          const element = document.querySelector('#df-a9f722f5-a76b-4be4-a5fd-b79d0817364b');\n",
+              "          const element = document.querySelector('#df-b20041e9-5a41-4990-9f68-2a7e02d8e5aa');\n",
               "          const dataTable =\n",
               "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
               "                                                     [key], {});\n",
@@ -422,7 +423,7 @@
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+          "execution_count": 3
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@@ -461,9 +462,9 @@
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       "outputs": [
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@@ -473,7 +474,7 @@
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@@ -498,19 +499,19 @@
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       "outputs": [
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           "data": {
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-              "<matplotlib.axes._subplots.AxesSubplot at 0x7f89b0054850>"
+              "<matplotlib.axes._subplots.AxesSubplot at 0x7f0ab15f7750>"
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           "data": {
             "text/plain": [
-              "<matplotlib.axes._subplots.AxesSubplot at 0x7f89afdbc290>"
+              "<matplotlib.axes._subplots.AxesSubplot at 0x7f0aafadd910>"
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@@ -639,7 +640,7 @@
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@@ -680,9 +681,9 @@
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@@ -721,9 +722,9 @@
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       "outputs": [
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@@ -733,7 +734,7 @@
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@@ -760,9 +761,9 @@
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         "id": "_UXhzfEB8sSB",
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+        "outputId": "c00f4dda-90d3-4048-875c-b127c64dc653"
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       "outputs": [
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@@ -772,7 +773,7 @@
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+          "execution_count": 12
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@@ -809,9 +810,9 @@
           "height": 725
         },
         "id": "dLVOexWZ92TU",
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+        "outputId": "1ee13333-cad6-4a5a-bd6c-68546faed2ec"
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       "outputs": [
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@@ -836,9 +837,9 @@
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         "id": "6U5Mrz5U-H9C",
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       "outputs": [
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@@ -895,9 +896,9 @@
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         "id": "pgT0IbbSHCvR",
-        "outputId": "40272b8e-3e89-4e56-eaf6-b5eb8c1eaf90"
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@@ -913,7 +914,7 @@
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               "\n",
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+              "  <div id=\"df-b38e17c8-f760-4cf4-a4c1-7e1a65aafcc8\">\n",
               "    <div class=\"colab-df-container\">\n",
               "      <div>\n",
               "<style scoped>\n",
@@ -964,7 +965,7 @@
               "  </tbody>\n",
               "</table>\n",
               "</div>\n",
-              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-a53ebe07-1273-4db9-a2a8-6fbcf835bcd2')\"\n",
+              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-b38e17c8-f760-4cf4-a4c1-7e1a65aafcc8')\"\n",
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@@ -1015,12 +1016,12 @@
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               "        const buttonEl =\n",
-              "          document.querySelector('#df-a53ebe07-1273-4db9-a2a8-6fbcf835bcd2 button.colab-df-convert');\n",
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               "        buttonEl.style.display =\n",
               "          google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
               "\n",
               "        async function convertToInteractive(key) {\n",
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               "          const dataTable =\n",
               "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
               "                                                     [key], {});\n",
@@ -1043,7 +1044,7 @@
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+          "execution_count": 15
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@@ -1059,9 +1060,9 @@
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         "id": "QwKIzR-FQKv9",
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@@ -1078,7 +1079,7 @@
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@@ -1099,9 +1100,9 @@
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@@ -1134,7 +1135,7 @@
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             "text/plain": [
-              "[<matplotlib.lines.Line2D at 0x7f89aff34190>]"
+              "[<matplotlib.lines.Line2D at 0x7f0aafc47b10>]"
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+              "<matplotlib.legend.Legend at 0x7f0aacdc7750>"
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@@ -1251,19 +1252,19 @@
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@@ -1306,7 +1307,7 @@
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@@ -1375,9 +1376,9 @@
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@@ -1411,7 +1412,7 @@
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         "id": "lR3Idw10aCly"
       },
-      "execution_count": 27,
+      "execution_count": 26,
       "outputs": []
     },
     {
@@ -1440,19 +1441,19 @@
           "height": 611
         },
         "id": "APq0qoiUbWW-",
-        "outputId": "46faf9b6-052e-49d3-dbfa-3b3ff4d1d4bf"
+        "outputId": "87af7402-88da-494c-94df-db7121b3d2f5"
       },
-      "execution_count": 28,
+      "execution_count": 27,
       "outputs": [
         {
           "output_type": "execute_result",
           "data": {
             "text/plain": [
-              "<matplotlib.axes._subplots.AxesSubplot at 0x7f89ad21d710>"
+              "<matplotlib.axes._subplots.AxesSubplot at 0x7f0aacf5ba90>"
             ]
           },
           "metadata": {},
-          "execution_count": 28
+          "execution_count": 27
         },
         {
           "output_type": "display_data",
@@ -1504,9 +1505,9 @@
           "height": 679
         },
         "id": "17wh4llUbi8e",
-        "outputId": "062bf10b-e9f7-4b4d-b4b0-c0e61379b710"
+        "outputId": "4b819345-b4f9-4542-ab43-7c12ca00d80b"
       },
-      "execution_count": 29,
+      "execution_count": 28,
       "outputs": [
         {
           "output_type": "stream",
@@ -1520,11 +1521,11 @@
           "output_type": "execute_result",
           "data": {
             "text/plain": [
-              "<matplotlib.axes._subplots.AxesSubplot at 0x7f89acfcc190>"
+              "<matplotlib.axes._subplots.AxesSubplot at 0x7f0aacda5a50>"
             ]
           },
           "metadata": {},
-          "execution_count": 29
+          "execution_count": 28
         },
         {
           "output_type": "display_data",
@@ -1551,19 +1552,19 @@
           "height": 656
         },
         "id": "AeQQzXvGccmk",
-        "outputId": "f224c997-6829-468c-a15f-41d53fb0f119"
+        "outputId": "029ace51-1bda-48b1-fd9c-3f320f02b79e"
       },
-      "execution_count": 30,
+      "execution_count": 29,
       "outputs": [
         {
           "output_type": "execute_result",
           "data": {
             "text/plain": [
-              "<matplotlib.axes._subplots.AxesSubplot at 0x7f89ace02610>"
+              "<matplotlib.axes._subplots.AxesSubplot at 0x7f0aacafd110>"
             ]
           },
           "metadata": {},
-          "execution_count": 30
+          "execution_count": 29
         },
         {
           "output_type": "display_data",
@@ -1621,7 +1622,7 @@
       "metadata": {
         "id": "92wS7VbFeadK"
       },
-      "execution_count": 31,
+      "execution_count": 30,
       "outputs": []
     },
     {
@@ -1637,9 +1638,9 @@
           "height": 1000
         },
         "id": "x-IgQUQjesHH",
-        "outputId": "87047c83-f4b7-404f-eb96-e84cb87a5c8d"
+        "outputId": "72dbcf3a-b36f-46ce-8de2-bedcd508bb3f"
       },
-      "execution_count": 32,
+      "execution_count": 31,
       "outputs": [
         {
           "output_type": "stream",