a LOT of MCU work

Author: zsbrown97

Lung Cancer/Lung_Cancer.ipynb

@@ -0,0 +1,123 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 21,
+   "outputs": [],
+   "source": [
+    "from matplotlib import pyplot as plt\n",
+    "\n",
+    "import numpy as np\n",
+    "import pandas as pd"
+   ],
+   "metadata": {
+    "collapsed": false,
+    "pycharm": {
+     "name": "#%%\n"
+    }
+   }
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 22,
+   "outputs": [],
+   "source": [
+    "lc = pd.DataFrame(pd.read_csv('./survey lung cancer.csv'))"
+   ],
+   "metadata": {
+    "collapsed": false,
+    "pycharm": {
+     "name": "#%%\n"
+    }
+   }
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 23,
+   "outputs": [
+    {
+     "data": {
+      "text/plain": "    GENDER  AGE  SMOKING  YELLOW_FINGERS  ANXIETY  PEER_PRESSURE  \\\n0        M   69        1               2        2              1   \n1        M   74        2               1        1              1   \n2        F   59        1               1        1              2   \n3        M   63        2               2        2              1   \n4        F   63        1               2        1              1   \n..     ...  ...      ...             ...      ...            ...   \n304      F   56        1               1        1              2   \n305      M   70        2               1        1              1   \n306      M   58        2               1        1              1   \n307      M   67        2               1        2              1   \n308      M   62        1               1        1              2   \n\n     CHRONIC DISEASE  FATIGUE   ALLERGY   WHEEZING  ALCOHOL CONSUMING  \\\n0                  1         2         1         2                  2   \n1                  2         2         2         1                  1   \n2                  1         2         1         2                  1   \n3                  1         1         1         1                  2   \n4                  1         1         1         2                  1   \n..               ...       ...       ...       ...                ...   \n304                2         2         1         1                  2   \n305                1         2         2         2                  2   \n306                1         1         2         2                  2   \n307                1         2         2         1                  2   \n308                1         2         2         2                  2   \n\n     COUGHING  SHORTNESS OF BREATH  SWALLOWING DIFFICULTY  CHEST PAIN  \\\n0           2                    2                      2           2   \n1           1                    2                      2           2   \n2           2                    2                      1           2   \n3           1                    1                      2           2   \n4           2                    2                      1           1   \n..        ...                  ...                    ...         ...   \n304         2                    2                      2           1   \n305         2                    2                      1           2   \n306         2                    1                      1           2   \n307         2                    2                      1           2   \n308         1                    1                      2           1   \n\n    LUNG_CANCER  \n0           YES  \n1           YES  \n2            NO  \n3            NO  \n4            NO  \n..          ...  \n304         YES  \n305         YES  \n306         YES  \n307         YES  \n308         YES  \n\n[309 rows x 16 columns]",
+      "text/html": "<div>\n<style scoped>\n    .dataframe tbody tr th:only-of-type {\n        vertical-align: middle;\n    }\n\n    .dataframe tbody tr th {\n        vertical-align: top;\n    }\n\n    .dataframe thead th {\n        text-align: right;\n    }\n</style>\n<table border=\"1\" class=\"dataframe\">\n  <thead>\n    <tr style=\"text-align: right;\">\n      <th></th>\n      <th>GENDER</th>\n      <th>AGE</th>\n      <th>SMOKING</th>\n      <th>YELLOW_FINGERS</th>\n      <th>ANXIETY</th>\n      <th>PEER_PRESSURE</th>\n      <th>CHRONIC DISEASE</th>\n      <th>FATIGUE</th>\n      <th>ALLERGY</th>\n      <th>WHEEZING</th>\n      <th>ALCOHOL CONSUMING</th>\n      <th>COUGHING</th>\n      <th>SHORTNESS OF BREATH</th>\n      <th>SWALLOWING DIFFICULTY</th>\n      <th>CHEST PAIN</th>\n      <th>LUNG_CANCER</th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th>0</th>\n      <td>M</td>\n      <td>69</td>\n      <td>1</td>\n      <td>2</td>\n      <td>2</td>\n      <td>1</td>\n      <td>1</td>\n      <td>2</td>\n      <td>1</td>\n      <td>2</td>\n      <td>2</td>\n      <td>2</td>\n      <td>2</td>\n      <td>2</td>\n      <td>2</td>\n      <td>YES</td>\n    </tr>\n    <tr>\n      <th>1</th>\n      <td>M</td>\n      <td>74</td>\n      <td>2</td>\n      <td>1</td>\n      <td>1</td>\n      <td>1</td>\n      <td>2</td>\n      <td>2</td>\n      <td>2</td>\n      <td>1</td>\n      <td>1</td>\n      <td>1</td>\n      <td>2</td>\n      <td>2</td>\n      <td>2</td>\n      <td>YES</td>\n    </tr>\n    <tr>\n      <th>2</th>\n      <td>F</td>\n      <td>59</td>\n      <td>1</td>\n      <td>1</td>\n      <td>1</td>\n      <td>2</td>\n      <td>1</td>\n      <td>2</td>\n      <td>1</td>\n      <td>2</td>\n      <td>1</td>\n      <td>2</td>\n      <td>2</td>\n      <td>1</td>\n      <td>2</td>\n      <td>NO</td>\n    </tr>\n    <tr>\n      <th>3</th>\n      <td>M</td>\n      <td>63</td>\n      <td>2</td>\n      <td>2</td>\n      <td>2</td>\n      <td>1</td>\n      <td>1</td>\n      <td>1</td>\n      <td>1</td>\n      <td>1</td>\n      <td>2</td>\n      <td>1</td>\n      <td>1</td>\n      <td>2</td>\n      <td>2</td>\n      <td>NO</td>\n    </tr>\n    <tr>\n      <th>4</th>\n      <td>F</td>\n      <td>63</td>\n      <td>1</td>\n      <td>2</td>\n      <td>1</td>\n      <td>1</td>\n      <td>1</td>\n      <td>1</td>\n      <td>1</td>\n      <td>2</td>\n      <td>1</td>\n      <td>2</td>\n      <td>2</td>\n      <td>1</td>\n      <td>1</td>\n      <td>NO</td>\n    </tr>\n    <tr>\n      <th>...</th>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n    </tr>\n    <tr>\n      <th>304</th>\n      <td>F</td>\n      <td>56</td>\n      <td>1</td>\n      <td>1</td>\n      <td>1</td>\n      <td>2</td>\n      <td>2</td>\n      <td>2</td>\n      <td>1</td>\n      <td>1</td>\n      <td>2</td>\n      <td>2</td>\n      <td>2</td>\n      <td>2</td>\n      <td>1</td>\n      <td>YES</td>\n    </tr>\n    <tr>\n      <th>305</th>\n      <td>M</td>\n      <td>70</td>\n      <td>2</td>\n      <td>1</td>\n      <td>1</td>\n      <td>1</td>\n      <td>1</td>\n      <td>2</td>\n      <td>2</td>\n      <td>2</td>\n      <td>2</td>\n      <td>2</td>\n      <td>2</td>\n      <td>1</td>\n      <td>2</td>\n      <td>YES</td>\n    </tr>\n    <tr>\n      <th>306</th>\n      <td>M</td>\n      <td>58</td>\n      <td>2</td>\n      <td>1</td>\n      <td>1</td>\n      <td>1</td>\n      <td>1</td>\n      <td>1</td>\n      <td>2</td>\n      <td>2</td>\n      <td>2</td>\n      <td>2</td>\n      <td>1</td>\n      <td>1</td>\n      <td>2</td>\n      <td>YES</td>\n    </tr>\n    <tr>\n      <th>307</th>\n      <td>M</td>\n      <td>67</td>\n      <td>2</td>\n      <td>1</td>\n      <td>2</td>\n      <td>1</td>\n      <td>1</td>\n      <td>2</td>\n      <td>2</td>\n      <td>1</td>\n      <td>2</td>\n      <td>2</td>\n      <td>2</td>\n      <td>1</td>\n      <td>2</td>\n      <td>YES</td>\n    </tr>\n    <tr>\n      <th>308</th>\n      <td>M</td>\n      <td>62</td>\n      <td>1</td>\n      <td>1</td>\n      <td>1</td>\n      <td>2</td>\n      <td>1</td>\n      <td>2</td>\n      <td>2</td>\n      <td>2</td>\n      <td>2</td>\n      <td>1</td>\n      <td>1</td>\n      <td>2</td>\n      <td>1</td>\n      <td>YES</td>\n    </tr>\n  </tbody>\n</table>\n<p>309 rows × 16 columns</p>\n</div>"
+     },
+     "execution_count": 23,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "lc"
+   ],
+   "metadata": {
+    "collapsed": false,
+    "pycharm": {
+     "name": "#%%\n"
+    }
+   }
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 24,
+   "outputs": [
+    {
+     "data": {
+      "text/plain": "<matplotlib.collections.PathCollection at 0x7fd7c05ac5e0>"
+     },
+     "execution_count": 24,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "text/plain": "<Figure size 432x288 with 1 Axes>",
+      "image/png": "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\n"
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "plt.scatter(lc['ANXIETY'], lc['LUNG_CANCER'])\n"
+   ],
+   "metadata": {
+    "collapsed": false,
+    "pycharm": {
+     "name": "#%%\n"
+    }
+   }
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "outputs": [],
+   "source": [],
+   "metadata": {
+    "collapsed": false,
+    "pycharm": {
+     "name": "#%%\n"
+    }
+   }
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 2
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython2",
+   "version": "2.7.6"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 0
+}