LDL-checkpoint.ipynb

{
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   "source": [
    "!pip install umap-learn"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
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   "source": [
    "from __future__ import print_function\n",
    "import time\n",
    "import numpy as np\n",
    "import pandas as pd\n",
    "from sklearn.datasets import fetch_mldata\n",
    "from sklearn.decomposition import PCA\n",
    "from sklearn.manifold import TSNE\n",
    "%matplotlib inline\n",
    "import matplotlib.pyplot as plt\n",
    "from mpl_toolkits.mplot3d import Axes3D\n",
    "import seaborn as sns\n",
    "\n",
    "import umap\n",
    "import matplotlib\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "colab": {
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     "height": 34
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    "colab_type": "code",
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    "outputId": "e0b68bec-b7ac-40e7-e8f6-7166b0b7aefd"
   },
   "outputs": [],
   "source": [
    "from google.colab import drive\n",
    "drive.mount('/data', force_remount=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "colab": {},
    "colab_type": "code",
    "id": "DmWVE_jpRDRJ"
   },
   "outputs": [],
   "source": [
    "p = \"/data/My Drive/clean_exports/wSCORE/Milano_Cleaned_wSCORE.xlsx\"\n",
    "df =  pd.read_excel(p)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "colab": {},
    "colab_type": "code",
    "id": "gu6WhooSRCPH"
   },
   "outputs": [],
   "source": [
    "l = ['int16', 'int32' , 'int64', 'float16', 'float32', 'float64']\n",
    "\n",
    "dfv = df.select_dtypes(include = l)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "colab_type": "text",
    "id": "H9nSzeJ2dl8Z"
   },
   "source": [
    "### del LDL"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "colab": {},
    "colab_type": "code",
    "id": "Z-iD-cqNQ7YD"
   },
   "outputs": [],
   "source": [
    "dfv = dfv.drop(['LDL_calc', 'SCORE'], axis=1)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "colab_type": "text",
    "id": "FNQjDzNzhyu2"
   },
   "source": [
    "**New df**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "colab": {},
    "colab_type": "code",
    "id": "27eauf_bScbA"
   },
   "outputs": [],
   "source": [
    "reducer = umap.UMAP()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 68
    },
    "colab_type": "code",
    "id": "RlBqXJlOiC3R",
    "outputId": "948805cc-7b4b-4592-eef8-ccb855874adc"
   },
   "outputs": [],
   "source": [
    "emb = reducer.fit_transform(dfv)\n",
    "emb.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "colab": {},
    "colab_type": "code",
    "id": "1mh6SQBKiF2e"
   },
   "outputs": [],
   "source": [
    "label = df['LDL_calc']\n",
    "label = list(label)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "colab": {},
    "colab_type": "code",
    "id": "tpH8G24Cjb6N"
   },
   "outputs": [],
   "source": [
    "l = []\n",
    "for x in label:\n",
    "  if x < 200:\n",
    "    l.append(0)\n",
    "  else:\n",
    "    l.append(1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "colab": {},
    "colab_type": "code",
    "id": "aiXok26ajdrW"
   },
   "outputs": [],
   "source": [
    "colors = ['yellow','blue']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 286
    },
    "colab_type": "code",
    "id": "kneWiZfBkyGB",
    "outputId": "d6fd5deb-4eb6-4965-823a-44b6a0d89af0"
   },
   "outputs": [],
   "source": [
    "plt.scatter(emb[:, 0], emb[:, 1],c=l, cmap=matplotlib.colors.ListedColormap(colors), s = 1)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "colab_type": "text",
    "id": "b-RfMPUPmBIR"
   },
   "source": [
    "**Vista 1**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "colab": {},
    "colab_type": "code",
    "id": "1OmGrTF7mm6o"
   },
   "outputs": [],
   "source": [
    "l1 = l [::4]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 54
    },
    "colab_type": "code",
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    "outputId": "345454fe-a398-4ab9-de69-64a4705a2a43"
   },
   "outputs": [],
   "source": [
    "print(l1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 51
    },
    "colab_type": "code",
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    "outputId": "8a2af82c-e2d4-4269-dba8-c715a950b063"
   },
   "outputs": [],
   "source": [
    "df1 = dfv.loc[:len(dfv):4]\n",
    "emb1 = reducer.fit_transform(df1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 286
    },
    "colab_type": "code",
    "id": "akfs9D2bmEqH",
    "outputId": "46187dcb-86df-4e65-8fca-efa87090655d"
   },
   "outputs": [],
   "source": [
    "plt.scatter(emb1[:, 0], emb1[:, 1], c = l1 , cmap=matplotlib.colors.ListedColormap(colors), s = 1)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "colab_type": "text",
    "id": "xHrXrgbNnczQ"
   },
   "source": [
    "**Visita 2**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
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    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 51
    },
    "colab_type": "code",
    "id": "wfnwedmpmfPf",
    "outputId": "5457ecae-bcd2-40fe-d059-2ea52811061d"
   },
   "outputs": [],
   "source": [
    "l2 = l [1::4]\n",
    "df2 = dfv.loc[1:len(dfv):4]\n",
    "emb2 = reducer.fit_transform(df2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 54
    },
    "colab_type": "code",
    "id": "_F-i4dsxoc7U",
    "outputId": "c245da9c-3753-4da0-e45e-1acdd00af480"
   },
   "outputs": [],
   "source": [
    "print(l2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 286
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    "colab_type": "code",
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    "outputId": "267e42d2-8f2e-49a6-d141-1cdd74095333"
   },
   "outputs": [],
   "source": [
    "plt.scatter(emb2[:, 0], emb2[:, 1], c = l2 , cmap=matplotlib.colors.ListedColormap(colors), s = 1)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "colab_type": "text",
    "id": "aYFc1QMQoxS0"
   },
   "source": [
    "**Visita 3**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
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    "colab": {
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    "outputId": "f4fa9cc5-1079-4783-a829-d9976ba5bdb6"
   },
   "outputs": [],
   "source": [
    "l3 = l [2::4]\n",
    "df3 = dfv.loc[2:len(dfv):4]\n",
    "emb3 = reducer.fit_transform(df3)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 286
    },
    "colab_type": "code",
    "id": "UjGN2JLfo4Yz",
    "outputId": "c0af93f2-ee40-4833-cdcb-c2541d73156b"
   },
   "outputs": [],
   "source": [
    "plt.scatter(emb3[:, 0], emb3[:, 1], c = l3 , cmap=matplotlib.colors.ListedColormap(colors), s = 1)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "colab_type": "text",
    "id": "Q51DqcTgpRTM"
   },
   "source": [
    "**Visita 4**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 51
    },
    "colab_type": "code",
    "id": "2-kyXql2o81k",
    "outputId": "1b92b2c6-2f81-4913-9350-8c4b964a45dc"
   },
   "outputs": [],
   "source": [
    "l4 = l [3::4]\n",
    "df4 = dfv.loc[3:len(dfv):4]\n",
    "emb4 = reducer.fit_transform(df4)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 286
    },
    "colab_type": "code",
    "id": "mIhuKs0zpaQ7",
    "outputId": "8afbcd75-04c3-4611-87be-8f73cdb65b8e"
   },
   "outputs": [],
   "source": [
    "plt.scatter(emb4[:, 0], emb4[:, 1], c = l4 , cmap=matplotlib.colors.ListedColormap(colors), s = 1)"
   ]
  },
  {
   "cell_type": "code",
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    "colab": {},
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    "id": "g_7rWgSwpkSS"
   },
   "outputs": [],
   "source": []
  }
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