Upload Copy_of_Assignment_1_EDA_&_Dataset_stiven_324496561.ipynb

Copy_of_Assignment_1_EDA_&_Dataset_stiven_324496561.ipynb

@@ -199,7 +199,7 @@
       "metadata": {
         "id": "OI0MZzohKwfE"
       },
-      "execution_count": 1,
+      "execution_count": 12,
       "outputs": []
     },
     {
@@ -217,7 +217,7 @@
       "metadata": {
         "id": "SWIrnfSLKwnE"
       },
-      "execution_count": 2,
+      "execution_count": 13,
       "outputs": []
     },
     {
@@ -354,7 +354,8 @@
         "print(\"-\" * 100)\n",
         "print(\"\\n>>> filtering date_of_birth wins losses and draws \")\n",
         "print(\"-\" * 100)\n",
-        "\n",
+        "import pandas as pd\n",
+        "from datetime import date\n",
         "df['date_of_birth'] = pd.to_datetime(df['date_of_birth'])\n",
         "today = pd.to_datetime(date.today())\n",
         "df['Age'] = (today - df['date_of_birth']).dt.days / 365.25\n",
@@ -399,9 +400,9 @@
           "height": 1000
         },
         "collapsed": true,
-        "outputId": "b940c794-db0c-4eae-9d1f-a2ebbce6daf2"
+        "outputId": "f72ef831-ee1d-40e1-f06c-a39c32b09c69"
       },
-      "execution_count": 144,
+      "execution_count": 14,
       "outputs": [
         {
           "output_type": "stream",
@@ -559,14 +560,14 @@
           "output_type": "stream",
           "name": "stderr",
           "text": [
-            "/tmp/ipython-input-2477576501.py:79: FutureWarning: A value is trying to be set on a copy of a DataFrame or Series through chained assignment using an inplace method.\n",
+            "/tmp/ipython-input-2870161678.py:79: FutureWarning: A value is trying to be set on a copy of a DataFrame or Series through chained assignment using an inplace method.\n",
             "The behavior will change in pandas 3.0. This inplace method will never work because the intermediate object on which we are setting values always behaves as a copy.\n",
             "\n",
             "For example, when doing 'df[col].method(value, inplace=True)', try using 'df.method({col: value}, inplace=True)' or df[col] = df[col].method(value) instead, to perform the operation inplace on the original object.\n",
             "\n",
             "\n",
             "  df['stance'].fillna('Unknown', inplace=True)\n",
-            "/tmp/ipython-input-2477576501.py:87: FutureWarning: A value is trying to be set on a copy of a DataFrame or Series through chained assignment using an inplace method.\n",
+            "/tmp/ipython-input-2870161678.py:87: FutureWarning: A value is trying to be set on a copy of a DataFrame or Series through chained assignment using an inplace method.\n",
             "The behavior will change in pandas 3.0. This inplace method will never work because the intermediate object on which we are setting values always behaves as a copy.\n",
             "\n",
             "For example, when doing 'df[col].method(value, inplace=True)', try using 'df.method({col: value}, inplace=True)' or df[col] = df[col].method(value) instead, to perform the operation inplace on the original object.\n",
@@ -611,7 +612,7 @@
             ],
             "text/html": [
               "\n",
-              "  <div id=\"df-52bb01bb-ff12-4c96-b834-872440acb2a6\" class=\"colab-df-container\">\n",
+              "  <div id=\"df-2559c298-d062-4c5d-bc38-0afef1514981\" class=\"colab-df-container\">\n",
               "    <div>\n",
               "<style scoped>\n",
               "    .dataframe tbody tr th:only-of-type {\n",
@@ -789,7 +790,7 @@
               "    <div class=\"colab-df-buttons\">\n",
               "\n",
               "  <div class=\"colab-df-container\">\n",
-              "    <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-52bb01bb-ff12-4c96-b834-872440acb2a6')\"\n",
+              "    <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-2559c298-d062-4c5d-bc38-0afef1514981')\"\n",
               "            title=\"Convert this dataframe to an interactive table.\"\n",
               "            style=\"display:none;\">\n",
               "\n",
@@ -841,12 +842,12 @@
               "\n",
               "    <script>\n",
               "      const buttonEl =\n",
-              "        document.querySelector('#df-52bb01bb-ff12-4c96-b834-872440acb2a6 button.colab-df-convert');\n",
+              "        document.querySelector('#df-2559c298-d062-4c5d-bc38-0afef1514981 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-52bb01bb-ff12-4c96-b834-872440acb2a6');\n",
+              "        const element = document.querySelector('#df-2559c298-d062-4c5d-bc38-0afef1514981');\n",
               "        const dataTable =\n",
               "          await google.colab.kernel.invokeFunction('convertToInteractive',\n",
               "                                                    [key], {});\n",
@@ -866,8 +867,8 @@
               "  </div>\n",
               "\n",
               "\n",
-              "    <div id=\"df-27409ab2-be39-4419-80c6-d53fb90c6e24\">\n",
-              "      <button class=\"colab-df-quickchart\" onclick=\"quickchart('df-27409ab2-be39-4419-80c6-d53fb90c6e24')\"\n",
+              "    <div id=\"df-95c00793-eec7-451b-8fc7-8b2ea8e0cfb1\">\n",
+              "      <button class=\"colab-df-quickchart\" onclick=\"quickchart('df-95c00793-eec7-451b-8fc7-8b2ea8e0cfb1')\"\n",
               "                title=\"Suggest charts\"\n",
               "                style=\"display:none;\">\n",
               "\n",
@@ -986,7 +987,7 @@
               "        }\n",
               "        (() => {\n",
               "          let quickchartButtonEl =\n",
-              "            document.querySelector('#df-27409ab2-be39-4419-80c6-d53fb90c6e24 button');\n",
+              "            document.querySelector('#df-95c00793-eec7-451b-8fc7-8b2ea8e0cfb1 button');\n",
               "          quickchartButtonEl.style.display =\n",
               "            google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
               "        })();\n",
@@ -1002,7 +1003,7 @@
             }
           },
           "metadata": {},
-          "execution_count": 144
+          "execution_count": 14
         }
       ]
     },
@@ -1038,6 +1039,7 @@
         "    'Takedowns/Fight', 'TD Accuracy', 'TD Defense', 'Submissions/Fight',\n",
         "     'total_fights'\n",
         "]\n",
+        "corr_data = df[key_cols]\n",
         "correlation_matrix = corr_data.corr()\n",
         "print(\"\\nCorrelations with WIN_RATE:\")\n",
         "print(correlation_matrix['win_rate'].sort_values(ascending=False).round(3))\n",
@@ -1132,11 +1134,10 @@
           "base_uri": "https://localhost:8080/",
           "height": 1000
         },
-        "collapsed": true,
         "id": "0xO35jtB_arm",
-        "outputId": "638c1f4b-bf3c-4d29-b245-3f33f331749b"
+        "outputId": "6fcc09f8-f4d0-4f7d-c938-23aaadd72ee1"
       },
-      "execution_count": 163,
+      "execution_count": 15,
       "outputs": [
         {
           "output_type": "stream",
@@ -1166,25 +1167,15 @@
             "75%       4.480000       58.000000         2.110000    50.000000    71.000000   \n",
             "max      52.500000      100.000000        24.110000   100.000000   100.000000   \n",
             "\n",
-            "       Submissions/Fight          Age  total_fights     win_rate  \\\n",
-            "count        2973.000000  2973.000000   2973.000000  2973.000000   \n",
-            "mean            0.649479    39.488732     20.389506    70.194717   \n",
-            "std             1.330835     7.780529     13.634073    14.459033   \n",
-            "min             0.000000    21.000000      1.000000     0.000000   \n",
-            "25%             0.000000    34.000000     12.000000    63.636364   \n",
-            "50%             0.200000    39.000000     18.000000    70.833333   \n",
-            "75%             0.800000    44.000000     26.000000    78.571429   \n",
-            "max            21.900000    82.000000    316.000000   100.000000   \n",
-            "\n",
-            "       Aggressiveness_Index  \n",
-            "count           2973.000000  \n",
-            "mean               0.218714  \n",
-            "std                0.077512  \n",
-            "min                0.000000  \n",
-            "25%                0.182538  \n",
-            "50%                0.223961  \n",
-            "75%                0.263198  \n",
-            "max                0.590243  \n",
+            "       Submissions/Fight          Age  total_fights     win_rate  \n",
+            "count        2973.000000  2973.000000   2973.000000  2973.000000  \n",
+            "mean            0.649479    39.488732     20.389506    70.194717  \n",
+            "std             1.330835     7.780529     13.634073    14.459033  \n",
+            "min             0.000000    21.000000      1.000000     0.000000  \n",
+            "25%             0.000000    34.000000     12.000000    63.636364  \n",
+            "50%             0.200000    39.000000     18.000000    70.833333  \n",
+            "75%             0.800000    44.000000     26.000000    78.571429  \n",
+            "max            21.900000    82.000000    316.000000   100.000000  \n",
             "\n",
             "====================================================================================================\n",
             "CORRELATION ANALYSIS\n",
@@ -1202,6 +1193,7 @@
             "reach_in_cm          0.033\n",
             "Absorb/Min           0.001\n",
             "height_cm           -0.057\n",
+            "total_fights        -0.091\n",
             "Name: win_rate, dtype: float64\n"
           ]
         },
@@ -1209,7 +1201,7 @@
           "output_type": "stream",
           "name": "stderr",
           "text": [
-            "/tmp/ipython-input-316548456.py:66: FutureWarning: \n",
+            "/tmp/ipython-input-753851434.py:67: FutureWarning: \n",
             "\n",
             "Passing `palette` without assigning `hue` is deprecated and will be removed in v0.14.0. Assign the `x` variable to `hue` and set `legend=False` for the same effect.\n",
             "\n",
@@ -1290,12 +1282,12 @@
     {
       "cell_type": "code",
       "source": [
-        "\"Among UFC fighters, do in-cage behavioral metrics (represented by the Composite Aggressiveness Index) predict the Win Rate more effectively than static physical metrics (Height, Reach, and Age)?\""
+        "#\"Among UFC fighters, do in-cage behavioral metrics (represented by the Composite Aggressiveness Index) predict the Win Rate more effectively than static physical metrics (Height, Reach, and Age)?\""
       ],
       "metadata": {
         "id": "0ch5l8tIK1Dt"
       },
-      "execution_count": 31,
+      "execution_count": 16,
       "outputs": []
     },
     {
@@ -1326,7 +1318,7 @@
       "metadata": {
         "id": "uLxQ5tJQK6xG"
       },
-      "execution_count": 31,
+      "execution_count": 16,
       "outputs": []
     },
     {
@@ -1342,7 +1334,7 @@
       "metadata": {
         "id": "euWXtGKHK65d"
       },
-      "execution_count": 31,
+      "execution_count": 16,
       "outputs": []
     },
     {
@@ -1394,7 +1386,7 @@
       "metadata": {
         "id": "asKyjjGDK-GJ"
       },
-      "execution_count": 31,
+      "execution_count": 16,
       "outputs": []
     },
     {
@@ -1442,7 +1434,7 @@
       "metadata": {
         "id": "WZcWV_6KbE9s"
       },
-      "execution_count": 31,
+      "execution_count": 16,
       "outputs": []
     },
     {
@@ -1472,7 +1464,7 @@
       "metadata": {
         "id": "r-8LRIrecw9d"
       },
-      "execution_count": 31,
+      "execution_count": 16,
       "outputs": []
     }
   ]