NY_mental_health.ipynb

{
  "nbformat": 4,
  "nbformat_minor": 0,
  "metadata": {
    "colab": {
      "name": "Hospital_dataset.ipynb",
      "provenance": [],
      "collapsed_sections": [
        "rdYFMy4Crs3-"
      ]
    },
    "kernelspec": {
      "name": "python3",
      "display_name": "Python 3"
    }
  },
  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "_JkWhU_29P0g",
        "colab_type": "text"
      },
      "source": [
        "## Hospital Inpatient Discharges 2017 New York State\n",
        "- Instances of hospitalization\n",
        "- 34 columns, 2.9 million rows"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "Ir5-3cZo9Fd2",
        "colab_type": "text"
      },
      "source": [
        "Dataset sourced from New York State Health Department\n",
        "\n",
        "https://health.data.ny.gov/dataset/Hospital-Inpatient-Discharges-SPARCS-De-Identified/22g3-z7e7"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "rdYFMy4Crs3-",
        "colab_type": "text"
      },
      "source": [
        "## Import original Dataset and save to smaller dataset keeping only pertinent data"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab_type": "code",
        "id": "iCWEc3DT2_3K",
        "colab": {}
      },
      "source": [
        "from google.colab import files\n",
        "uploaded = files.upload()"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "ZDlWMaOCIUNm",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "# Imports\n",
        "\n",
        "import pandas as pd\n",
        "import matplotlib.pyplot as plt"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "8KxHeKZ2JNNj",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "# Read in data\n",
        "\n",
        "df = pd.read_csv('Hospital_Inpatient_Discharges__SPARCS_De-Identified___2017.csv')\n",
        "df.head()"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "oAT-vO5hwZp5",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "# Only keep relevent columns\n",
        "\n",
        "age_gender_race_DRG_MDC = df[['Age Group', 'Gender', 'Race', 'APR DRG Code', 'APR DRG Description', 'APR MDC Code', 'APR MDC Description']]\n",
        "age_gender_race_DRG_MDC.head()"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "HoPNEPl2jkir",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "# Save smaller dataset\n",
        "\n",
        "from google.colab import drive\n",
        "drive.mount('drive')"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "7GdC5rzGhStt",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "# Save to Google Drive\n",
        "\n",
        "age_gender_race_DRG_MDC.to_csv('age_gender_race_DRG_MDC.csv')\n",
        "!cp age_gender_race_DRG_MDC.csv \"drive/My Drive/\""
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "JI5T1AHMpd55",
        "colab_type": "text"
      },
      "source": [
        "## Smaller subset of original dataframe keeping: Age, Race, Gender, APR DRG and APR MDC"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "j4JnG_p0o28i",
        "colab_type": "code",
        "outputId": "e2a3053b-561e-488c-a459-7aeb0566c190",
        "colab": {
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            }
          },
          "base_uri": "https://localhost:8080/",
          "height": 72
        }
      },
      "source": [
        "# Open new CSV\n",
        "from google.colab import files\n",
        "uploaded = files.upload()"
      ],
      "execution_count": 0,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
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              "      Upload widget is only available when the cell has been executed in the\n",
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          "metadata": {
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        },
        {
          "output_type": "stream",
          "text": [
            "Saving age_gender_race_DRG_MDC.csv to age_gender_race_DRG_MDC.csv\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "FfpXGx5MpBY-",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "# Imports \n",
        "import pandas as pd\n",
        "import matplotlib.pyplot as plt\n",
        "import numpy as np"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "cP0QIhuCpF6a",
        "colab_type": "code",
        "outputId": "93a0d9b6-234e-4f6c-bdc3-be8174fc2ed6",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 281
        }
      },
      "source": [
        "# Read in CSV\n",
        "age_gender_race_DRG_MDC = pd.read_csv('age_gender_race_DRG_MDC.csv')\n",
        "age_gender_race_DRG_MDC.head()"
      ],
      "execution_count": 0,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
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              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>Unnamed: 0</th>\n",
              "      <th>Age Group</th>\n",
              "      <th>Gender</th>\n",
              "      <th>Race</th>\n",
              "      <th>APR DRG Code</th>\n",
              "      <th>APR DRG Description</th>\n",
              "      <th>APR MDC Code</th>\n",
              "      <th>APR MDC Description</th>\n",
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              "      <td>30 to 49</td>\n",
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              "      <td>750</td>\n",
              "      <td>Schizophrenia</td>\n",
              "      <td>19</td>\n",
              "      <td>Mental Diseases and Disorders</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>1</td>\n",
              "      <td>50 to 69</td>\n",
              "      <td>M</td>\n",
              "      <td>White</td>\n",
              "      <td>194</td>\n",
              "      <td>Heart failure</td>\n",
              "      <td>5</td>\n",
              "      <td>Diseases and Disorders of the Circulatory System</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>2</td>\n",
              "      <td>30 to 49</td>\n",
              "      <td>F</td>\n",
              "      <td>White</td>\n",
              "      <td>465</td>\n",
              "      <td>Urinary stones &amp; acquired upper urinary tract ...</td>\n",
              "      <td>11</td>\n",
              "      <td>Diseases and Disorders of the Kidney and Urina...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>3</td>\n",
              "      <td>50 to 69</td>\n",
              "      <td>F</td>\n",
              "      <td>White</td>\n",
              "      <td>721</td>\n",
              "      <td>Post-operative, post-traumatic, other device i...</td>\n",
              "      <td>18</td>\n",
              "      <td>Infectious and Parasitic Diseases, Systemic or...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>4</td>\n",
              "      <td>18 to 29</td>\n",
              "      <td>F</td>\n",
              "      <td>White</td>\n",
              "      <td>720</td>\n",
              "      <td>Septicemia &amp; disseminated infections</td>\n",
              "      <td>18</td>\n",
              "      <td>Infectious and Parasitic Diseases, Systemic or...</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "   Unnamed: 0  ...                                APR MDC Description\n",
              "0           0  ...                      Mental Diseases and Disorders\n",
              "1           1  ...   Diseases and Disorders of the Circulatory System\n",
              "2           2  ...  Diseases and Disorders of the Kidney and Urina...\n",
              "3           3  ...  Infectious and Parasitic Diseases, Systemic or...\n",
              "4           4  ...  Infectious and Parasitic Diseases, Systemic or...\n",
              "\n",
              "[5 rows x 8 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 3
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "5CmshM7RrJyQ",
        "colab_type": "text"
      },
      "source": [
        "## First Visual: Bar graph comparing top 7 APR Major Diagnosis Categories between age groups"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "_UwI-tDwfK4p",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "# Drop APR MDC Description: \"Newborns and Other Neonates with Conditions Originating in the Perinatal Period\"\n",
        "# as it only applies to newborns\n",
        "\n",
        "age_gender_race_DRG_MDC = age_gender_race_DRG_MDC[age_gender_race_DRG_MDC['APR MDC Description'] != 'Newborns and Other Neonates with Conditions Originating in the Perinatal Period']"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "O2aJyqxIajy2",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "# Drop APR MDC Description: \"Pregnancy, Childbirth and the Puerperium\" as it is \n",
        "# only relevent for females under the age of 50.\n",
        "\n",
        "age_gender_race_DRG_MDC = age_gender_race_DRG_MDC[age_gender_race_DRG_MDC['APR MDC Description'] != 'Pregnancy, Childbirth and the Puerperium']"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "3VmXi32BRZGA",
        "colab_type": "code",
        "outputId": "c94f7277-f9de-45ba-91e1-9cd9d6f4dbfb",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 461
        }
      },
      "source": [
        "# Look at the most common APD MDC Descriptions Overall\n",
        "\n",
        "age_gender_race_DRG_MDC['APR MDC Description'].value_counts()"
      ],
      "execution_count": 0,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Diseases and Disorders of the Circulatory System                                                        300490\n",
              "Diseases and Disorders of the Musculoskeletal System and Conn Tissue                                    211381\n",
              "Diseases and Disorders of the Respiratory System                                                        191532\n",
              "Diseases and Disorders of the Digestive System                                                          189873\n",
              "Diseases and Disorders of the Nervous System                                                            150977\n",
              "Infectious and Parasitic Diseases, Systemic or Unspecified Sites                                        139365\n",
              "Mental Diseases and Disorders                                                                           114924\n",
              "Diseases and Disorders of the Kidney and Urinary Tract                                                   99583\n",
              "Endocrine, Nutritional and Metabolic Diseases and Disorders                                              79913\n",
              "Alcohol/Drug Use and Alcohol/Drug Induced Organic Mental Disorders                                       76025\n",
              "Diseases and Disorders of the Hepatobiliary System and Pancreas                                          64032\n",
              "Diseases and Disorders of the Skin, Subcutaneous Tissue and Breast                                       59554\n",
              "Diseases and Disorders of Blood, Blood Forming Organs and Immunological Disorders                        33711\n",
              "Ear, Nose, Mouth, Throat and Craniofacial Diseases and Disorders                                         32013\n",
              "Rehabilitation, Aftercare, Other Factors Influencing Health Status and Other Health Service Contacts     29666\n",
              "Poisonings, Toxic Effects, Other Injuries and Other Complications of Treatment                           27144\n",
              "Diseases and Disorders of the Female Reproductive System                                                 23618\n",
              "Lymphatic, Hematopoietic, Other Malignancies, Chemotherapy and Radiotherapy                              22601\n",
              "Diseases and Disorders of the Male Reproductive System                                                   10508\n",
              "Human Immunodeficiency Virus Infections                                                                   6579\n",
              "Multiple Significant Trauma                                                                               3961\n",
              "Diseases and Disorders of the Eye                                                                         3635\n",
              "Burns                                                                                                     2141\n",
              "Pre-MDC or Ungroupable                                                                                     197\n",
              "Name: APR MDC Description, dtype: int64"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 6
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "tWIWzfXZJbJ-",
        "colab_type": "code",
        "outputId": "42a78d1f-8acc-4daf-a5f7-10e3be85ba61",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 364
        }
      },
      "source": [
        "# Create a crosstab between APR MDC Description and Age Group\n",
        "# Normalize by age group\n",
        "# Transpose so it is indexed by age group, easier to read\n",
        "\n",
        "MDC_age_norm = pd.crosstab(age_gender_race_DRG_MDC['APR MDC Description'], age_gender_race_DRG_MDC['Age Group'], normalize= 'columns').T\n",
        "MDC_age_norm"
      ],
      "execution_count": 0,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
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              "\n",
              "    .dataframe tbody tr th {\n",
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              "    }\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>APR MDC Description</th>\n",
              "      <th>Alcohol/Drug Use and Alcohol/Drug Induced Organic Mental Disorders</th>\n",
              "      <th>Burns</th>\n",
              "      <th>Diseases and Disorders of Blood, Blood Forming Organs and Immunological Disorders</th>\n",
              "      <th>Diseases and Disorders of the Circulatory System</th>\n",
              "      <th>Diseases and Disorders of the Digestive System</th>\n",
              "      <th>Diseases and Disorders of the Eye</th>\n",
              "      <th>Diseases and Disorders of the Female Reproductive System</th>\n",
              "      <th>Diseases and Disorders of the Hepatobiliary System and Pancreas</th>\n",
              "      <th>Diseases and Disorders of the Kidney and Urinary Tract</th>\n",
              "      <th>Diseases and Disorders of the Male Reproductive System</th>\n",
              "      <th>Diseases and Disorders of the Musculoskeletal System and Conn Tissue</th>\n",
              "      <th>Diseases and Disorders of the Nervous System</th>\n",
              "      <th>Diseases and Disorders of the Respiratory System</th>\n",
              "      <th>Diseases and Disorders of the Skin, Subcutaneous Tissue and Breast</th>\n",
              "      <th>Ear, Nose, Mouth, Throat and Craniofacial Diseases and Disorders</th>\n",
              "      <th>Endocrine, Nutritional and Metabolic Diseases and Disorders</th>\n",
              "      <th>Human Immunodeficiency Virus Infections</th>\n",
              "      <th>Infectious and Parasitic Diseases, Systemic or Unspecified Sites</th>\n",
              "      <th>Lymphatic, Hematopoietic, Other Malignancies, Chemotherapy and Radiotherapy</th>\n",
              "      <th>Mental Diseases and Disorders</th>\n",
              "      <th>Multiple Significant Trauma</th>\n",
              "      <th>Poisonings, Toxic Effects, Other Injuries and Other Complications of Treatment</th>\n",
              "      <th>Pre-MDC or Ungroupable</th>\n",
              "      <th>Rehabilitation, Aftercare, Other Factors Influencing Health Status and Other Health Service Contacts</th>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Age Group</th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0 to 17</th>\n",
              "      <td>0.001463</td>\n",
              "      <td>0.006237</td>\n",
              "      <td>0.039220</td>\n",
              "      <td>0.026574</td>\n",
              "      <td>0.121275</td>\n",
              "      <td>0.004936</td>\n",
              "      <td>0.005663</td>\n",
              "      <td>0.009513</td>\n",
              "      <td>0.032417</td>\n",
              "      <td>0.003249</td>\n",
              "      <td>0.057232</td>\n",
              "      <td>0.112785</td>\n",
              "      <td>0.221308</td>\n",
              "      <td>0.039920</td>\n",
              "      <td>0.067104</td>\n",
              "      <td>0.047566</td>\n",
              "      <td>0.000045</td>\n",
              "      <td>0.048508</td>\n",
              "      <td>0.019098</td>\n",
              "      <td>0.097537</td>\n",
              "      <td>0.001885</td>\n",
              "      <td>0.021629</td>\n",
              "      <td>0.001580</td>\n",
              "      <td>0.013256</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>18 to 29</th>\n",
              "      <td>0.098357</td>\n",
              "      <td>0.002109</td>\n",
              "      <td>0.040677</td>\n",
              "      <td>0.032689</td>\n",
              "      <td>0.096552</td>\n",
              "      <td>0.002462</td>\n",
              "      <td>0.013979</td>\n",
              "      <td>0.037934</td>\n",
              "      <td>0.031599</td>\n",
              "      <td>0.002695</td>\n",
              "      <td>0.053309</td>\n",
              "      <td>0.069894</td>\n",
              "      <td>0.046203</td>\n",
              "      <td>0.036788</td>\n",
              "      <td>0.022881</td>\n",
              "      <td>0.062820</td>\n",
              "      <td>0.004098</td>\n",
              "      <td>0.046572</td>\n",
              "      <td>0.011340</td>\n",
              "      <td>0.241208</td>\n",
              "      <td>0.005991</td>\n",
              "      <td>0.029802</td>\n",
              "      <td>0.000032</td>\n",
              "      <td>0.010009</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>30 to 49</th>\n",
              "      <td>0.109778</td>\n",
              "      <td>0.001515</td>\n",
              "      <td>0.023281</td>\n",
              "      <td>0.085703</td>\n",
              "      <td>0.105575</td>\n",
              "      <td>0.002315</td>\n",
              "      <td>0.035133</td>\n",
              "      <td>0.050919</td>\n",
              "      <td>0.037372</td>\n",
              "      <td>0.002533</td>\n",
              "      <td>0.080552</td>\n",
              "      <td>0.066284</td>\n",
              "      <td>0.053572</td>\n",
              "      <td>0.041900</td>\n",
              "      <td>0.013829</td>\n",
              "      <td>0.063821</td>\n",
              "      <td>0.007251</td>\n",
              "      <td>0.053265</td>\n",
              "      <td>0.010179</td>\n",
              "      <td>0.120147</td>\n",
              "      <td>0.002577</td>\n",
              "      <td>0.020839</td>\n",
              "      <td>0.000025</td>\n",
              "      <td>0.011637</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>50 to 69</th>\n",
              "      <td>0.041841</td>\n",
              "      <td>0.000757</td>\n",
              "      <td>0.011783</td>\n",
              "      <td>0.175531</td>\n",
              "      <td>0.099589</td>\n",
              "      <td>0.001644</td>\n",
              "      <td>0.011028</td>\n",
              "      <td>0.040574</td>\n",
              "      <td>0.048408</td>\n",
              "      <td>0.008516</td>\n",
              "      <td>0.138949</td>\n",
              "      <td>0.075996</td>\n",
              "      <td>0.098476</td>\n",
              "      <td>0.031781</td>\n",
              "      <td>0.012645</td>\n",
              "      <td>0.039095</td>\n",
              "      <td>0.005272</td>\n",
              "      <td>0.068877</td>\n",
              "      <td>0.014364</td>\n",
              "      <td>0.042377</td>\n",
              "      <td>0.001489</td>\n",
              "      <td>0.014768</td>\n",
              "      <td>0.000014</td>\n",
              "      <td>0.016227</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>70 or Older</th>\n",
              "      <td>0.002141</td>\n",
              "      <td>0.000311</td>\n",
              "      <td>0.013800</td>\n",
              "      <td>0.227368</td>\n",
              "      <td>0.098642</td>\n",
              "      <td>0.001455</td>\n",
              "      <td>0.004356</td>\n",
              "      <td>0.023333</td>\n",
              "      <td>0.072871</td>\n",
              "      <td>0.005145</td>\n",
              "      <td>0.122886</td>\n",
              "      <td>0.088538</td>\n",
              "      <td>0.119650</td>\n",
              "      <td>0.024686</td>\n",
              "      <td>0.013555</td>\n",
              "      <td>0.031499</td>\n",
              "      <td>0.000466</td>\n",
              "      <td>0.099439</td>\n",
              "      <td>0.009647</td>\n",
              "      <td>0.012296</td>\n",
              "      <td>0.001823</td>\n",
              "      <td>0.007124</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.018970</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "APR MDC Description  Alcohol/Drug Use and Alcohol/Drug Induced Organic Mental Disorders  ...  Rehabilitation, Aftercare, Other Factors Influencing Health Status and Other Health Service Contacts\n",
              "Age Group                                                                                ...                                                                                                      \n",
              "0 to 17                                                       0.001463                   ...                                           0.013256                                                   \n",
              "18 to 29                                                      0.098357                   ...                                           0.010009                                                   \n",
              "30 to 49                                                      0.109778                   ...                                           0.011637                                                   \n",
              "50 to 69                                                      0.041841                   ...                                           0.016227                                                   \n",
              "70 or Older                                                   0.002141                   ...                                           0.018970                                                   \n",
              "\n",
              "[5 rows x 24 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 7
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "HNGMEWMnJbqf",
        "colab_type": "code",
        "outputId": "190e0369-e5eb-46d5-e0b6-37662741f17a",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 294
        }
      },
      "source": [
        "# Keep the top 7 most common APR MDC Descriptions overall\n",
        "\n",
        "keep = ['Diseases and Disorders of the Circulatory System',\n",
        "        'Diseases and Disorders of the Musculoskeletal System and Conn Tissue',\n",
        "        'Diseases and Disorders of the Respiratory System',\n",
        "        'Diseases and Disorders of the Digestive System',\n",
        "        'Diseases and Disorders of the Nervous System',\n",
        "        'Infectious and Parasitic Diseases, Systemic or Unspecified Sites',\n",
        "        'Mental Diseases and Disorders'\n",
        "        ]\n",
        "\n",
        "MDC_age_processed = MDC_age_norm[keep]\n",
        "MDC_age_processed"
      ],
      "execution_count": 0,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
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              "<style scoped>\n",
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              "\n",
              "    .dataframe tbody tr th {\n",
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              "    }\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>APR MDC Description</th>\n",
              "      <th>Diseases and Disorders of the Circulatory System</th>\n",
              "      <th>Diseases and Disorders of the Musculoskeletal System and Conn Tissue</th>\n",
              "      <th>Diseases and Disorders of the Respiratory System</th>\n",
              "      <th>Diseases and Disorders of the Digestive System</th>\n",
              "      <th>Diseases and Disorders of the Nervous System</th>\n",
              "      <th>Infectious and Parasitic Diseases, Systemic or Unspecified Sites</th>\n",
              "      <th>Mental Diseases and Disorders</th>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Age Group</th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0 to 17</th>\n",
              "      <td>0.026574</td>\n",
              "      <td>0.057232</td>\n",
              "      <td>0.221308</td>\n",
              "      <td>0.121275</td>\n",
              "      <td>0.112785</td>\n",
              "      <td>0.048508</td>\n",
              "      <td>0.097537</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>18 to 29</th>\n",
              "      <td>0.032689</td>\n",
              "      <td>0.053309</td>\n",
              "      <td>0.046203</td>\n",
              "      <td>0.096552</td>\n",
              "      <td>0.069894</td>\n",
              "      <td>0.046572</td>\n",
              "      <td>0.241208</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>30 to 49</th>\n",
              "      <td>0.085703</td>\n",
              "      <td>0.080552</td>\n",
              "      <td>0.053572</td>\n",
              "      <td>0.105575</td>\n",
              "      <td>0.066284</td>\n",
              "      <td>0.053265</td>\n",
              "      <td>0.120147</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>50 to 69</th>\n",
              "      <td>0.175531</td>\n",
              "      <td>0.138949</td>\n",
              "      <td>0.098476</td>\n",
              "      <td>0.099589</td>\n",
              "      <td>0.075996</td>\n",
              "      <td>0.068877</td>\n",
              "      <td>0.042377</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>70 or Older</th>\n",
              "      <td>0.227368</td>\n",
              "      <td>0.122886</td>\n",
              "      <td>0.119650</td>\n",
              "      <td>0.098642</td>\n",
              "      <td>0.088538</td>\n",
              "      <td>0.099439</td>\n",
              "      <td>0.012296</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "APR MDC Description  Diseases and Disorders of the Circulatory System  ...  Mental Diseases and Disorders\n",
              "Age Group                                                              ...                               \n",
              "0 to 17                                                      0.026574  ...                       0.097537\n",
              "18 to 29                                                     0.032689  ...                       0.241208\n",
              "30 to 49                                                     0.085703  ...                       0.120147\n",
              "50 to 69                                                     0.175531  ...                       0.042377\n",
              "70 or Older                                                  0.227368  ...                       0.012296\n",
              "\n",
              "[5 rows x 7 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 8
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "mZSNULsosk3t",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "# Return each column as a list\n",
        "# This will be the y-values for the graph\n",
        "\n",
        "circulatory = MDC_age_processed.loc[:, 'Diseases and Disorders of the Circulatory System'].values.tolist()\n",
        "musculoskeletal = MDC_age_processed.loc[:, 'Diseases and Disorders of the Musculoskeletal System and Conn Tissue'].values.tolist() \n",
        "respiratory = MDC_age_processed.loc[:, 'Diseases and Disorders of the Respiratory System'].values.tolist()\n",
        "digestive = MDC_age_processed.loc[:, 'Diseases and Disorders of the Digestive System'].values.tolist()\n",
        "nervous = MDC_age_processed.loc[:, 'Diseases and Disorders of the Nervous System'].values.tolist()\n",
        "infection = MDC_age_processed.loc[:, 'Infectious and Parasitic Diseases, Systemic or Unspecified Sites'].values.tolist()\n",
        "mental = MDC_age_processed.loc[:, 'Mental Diseases and Disorders'].values.tolist()"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "BFHfssv3JbE_",
        "colab_type": "code",
        "outputId": "4551e7f7-acf8-4910-8245-6697d5c68f22",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 326
        }
      },
      "source": [
        "# Basic exploratory graph\n",
        "\n",
        "MDC_age_processed.plot.bar()\n",
        "plt.show()"
      ],
      "execution_count": 0,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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ouLiYJBIJXbhwgUaPHk1ERMuXL6f169dz6S0tLSklJYUOHTpEM2bM4Lbn5ORQ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\nGVIAAAAASUVORK5CYII=\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "RcDFAND3qAfz",
        "colab_type": "code",
        "outputId": "0c60a22e-5360-43e7-cbe2-7e403c0a1b7f",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 680
        }
      },
      "source": [
        "# Graph\n",
        "\n",
        "# Define some plotting variables\n",
        "x_values = np.array([10,20,30,40,50])\n",
        "width = np.array(0.8)\n",
        "\n",
        "# Create seperate figure and axes variables \n",
        "fig, ax = plt.subplots(figsize = (12,10))\n",
        "\n",
        "# Style\n",
        "plt.style.use('fivethirtyeight')\n",
        "\n",
        "# Add bars\n",
        "# Add descriptive labels and different colors for each APR MDC Description\n",
        "\n",
        "ax.bar(x_values- (3*width), circulatory, width, label= 'Circulatory Disorder',\n",
        "       color= '#FE2712')\n",
        "ax.bar(x_values- (2*width), musculoskeletal, width, label= 'Muscloskeletal Disorder',\n",
        "       color= '#FB9902')\n",
        "ax.bar(x_values- width, infection, width, label= 'Infectious Disease', \n",
        "       color= '#FEFE33')\n",
        "ax.bar(x_values, nervous, width, label= 'Nervous System Disorder', \n",
        "       color= '#347C98')\n",
        "ax.bar(x_values+ width, digestive, width, label= 'Digestive Disorder', \n",
        "       color= '#0247FE')\n",
        "ax.bar(x_values+ (2*width), respiratory, width, label= 'Respiratory Disorder', \n",
        "       color= '#B2D732')\n",
        "ax.bar(x_values+ (3*width), mental, width, label= 'Mental Disorder', \n",
        "       color= '#8601AF')\n",
        "\n",
        "# Set Title\n",
        "ax.set_title(\"How Your Health Concerns Change As You Age\", x=.305, y=1.15, fontsize= 18,\n",
        "             fontweight= 'bold')\n",
        "\n",
        "# Set Subtitle\n",
        "ax.text(s= \"The top seven major diagnosis categories in New York State in 2017 as a percent of total* hospital admissions per age group\",\n",
        "        x= 4.6, y=0.28, fontsize= 12)\n",
        "\n",
        "# Set X-tick and X-tick labels\n",
        "ax.set_xticks(x_values)\n",
        "ax.set_xticklabels(('0 to 17','18 to 29','30 to 49','50 to 69','70 or Older'))\n",
        "\n",
        "# Set Y-tick labels\n",
        "ax.set_yticklabels(['0','10','20','30','40', '50%'])\n",
        "\n",
        "# Set X label\n",
        "ax.set_xlabel('Age Group', color= 'black', fontsize= 14, fontweight= 'bold')\n",
        "\n",
        "# Set figure background color\n",
        "fig.set_facecolor(color='None')\n",
        "\n",
        "# Set the Axes background color\n",
        "ax.set_facecolor(color='None')\n",
        "\n",
        "# Turn off the spine\n",
        "ax.spines['left'].set_visible(False)\n",
        "ax.spines['right'].set_visible(False)\n",
        "ax.spines['top'].set_visible(False)\n",
        "\n",
        "# Color of grid\n",
        "ax.grid(color= '#000000', b= True)\n",
        "\n",
        "# Asterisk text underneath graph\n",
        "ax.text(s= \"* Admissions for the following major diagnosis categories were not included towards the total hospital admissions as they are not applicable to all ages\",\n",
        "        x= 4.5, y= -.13, fontsize= 10, color= '#BDBDBD')\n",
        "ax.text(s= \"   and genders:  - Newborns and Other Neonates with Conditions Originating in the Perinatal Period\",\n",
        "        x= 4.5, y= -.14, fontsize= 10, color= '#BDBDBD')\n",
        "ax.text(s= \"                          - Pregnancy, Childbirth and the Puerperium\",\n",
        "        x= 4.5, y= -.15, fontsize= 10, color= '#BDBDBD')\n",
        "\n",
        "# Show legend, set location, add title\n",
        "ax.legend(bbox_to_anchor=(0.71, -0.155), ncol = 3, title= 'Major Diagnostic Category',\n",
        "          fontsize= 11)\n",
        "\n",
        "fig.subplots_adjust(bottom=0.38)\n",
        "\n",
        "plt.show()\n"
      ],
      "execution_count": 0,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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B1izr37sDcwTjy/DQY4C+GwDki+srO67zEcBRg46hYeWz67ZomefOZds0L8Sv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\n6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ULiH4kl+gOBfwDRbvamQFcRuSqy/g9hH+Mi2wBoBfTCMrzBqlpbVVsDfYBDwnGXY4XV\naHgeBsYD14pIX6xg1wEryBwJ3BEifCq/B94N4b8ReDR8Pw04BGgDfIxVfsAqIXGtnnHhL8YKAe2x\nzCxdt22jsO0rw/GMCPtup6odwjI3iUhn4ECskHFgdANZXO83Qlx5lQ09AlwarnkqC4BDRaQjdv0S\nLckXActFpBC4BSvgJ6SKY6niTNq4h1VkLg5x4VDs5hA9/jZYxUbCNi4PP70K/DqE/V/YDe1TrHA9\nIsTDqdhNZISIJK7bw2H9wYCKSBvgSUKFKBR0zgYOwtLtIFXtGNbZH7hfRNqIyGeRMKaK0x2AvUSk\nrYi0w67Jj8LN530sL+kGvAMcqqo7AM1C4femEM4uwOFY3E/cAIuAU0TksAzLRXXEWvUKsULTIapa\nF8ur+oRwJm4g92AVrsOTKzsxUsWLe4BXwveJQkFGIUwPYTfHTlihJSHVsV4IfC8irbHr24kkyceU\nJn1NpSp/OBRYpqp7hb+nhO/vFZHikE/Xwyp7CXVEpLOI/IXUaTEu/4+G9Qaq8uVEHrk/dtNvA6zA\n4jTAX8M+OmFp6v6kbX3KxmljozQbClSJvLdDuP89HY6zPTAfq4hn0gSL08diBRZInY+fAUwM56E9\nVrgFi1Nvh2N9Bbum0WOKi59p89MYqa5huvyzbTiWYuCPWJzriDWc9I8uqKq7YmWGNuE8/yH8lClf\nTHUPg5j7EhnKDUGq65gpLDcAU0N8SFQEOmB5Xjugj6o2UxtKdTNwpIgUYb1VV2EF8lahkQksf/07\nG8uYnrD8ZCSW7yUqpX+M2RZULw7GHWNCCdA7HNPhwF+06jGIA7B7QmusgnVRZL2VIT+9F2u4iaXW\nYDwOa1RJhGsd8C1wVNhvHzYsh3XBGi0KsUrnSUnbzKaclW1emCzddcokXXo7PxLWhIHYeSzG0tsg\nVd2H1HlGrF90hQf4p4jcAZSIyJ+wXplkp2MFKcL/p4e/u4f1y8WGp2nSeuPD/3OwwuhqEVkClOrG\n4/1fA25U1euB5iKyLqx3lKoOV9VDRWRl0jrFwGQRWSLWtfuPECaw3qbE2M4ZWDctWEF/dGjhyUt1\nUiIOpqpr9zEs00h4QrIc9oa1EJSKyFIs8e6OtVx0At4KrSlHUNX6m0o3qs75YuzmV5xh+ccARESB\nXVV1Z6wQ0z38ewCreOyFFe7XZhn+Q4BnRaRErCfiv2nC8V+xlo85wGIRmSPWCjOXqmtzqqq+A7yL\n/pCc1QAAH7FJREFUVYaSx86nu97lwFPJOw3xLF9EEgWzx1KEryHwhNr49ERlDOz8/QtARN4DZkfW\nSRXHUsWZTHFvGnBnaG3Kl42HKwgW55aG8HwXvm8KTFTrtbs2EvZkRwL3hrg2HmsZa5B0jC9grZaJ\nY39GRNaKyBrgaaoKvp+JyOsx+0gVpz8G9lXVkaG3YlXMutE4eXvYfzHWywLWun1D2O5krDcu0Vv1\nUuR8pFsu6k0R+SLEw5nY9TsAa9xZGJYZQ1Ucy1aqeCFYWiOk3+T8LJVWIUwfhDQUHdqa6li7J5YT\nkdlsGG9TiU1fIvIN0EBVdwKaYXG7OxYXEi2Jh6vqGyEOChvGwXGQMS3G5f+ZfCIiiZv7DKAgxOeu\nWFqeifX6pmsQSkiXz0e1VdWp4Tj7kjqtRf1HRCpEZB6Wb0LqfPwt4OzQe9FOqnp4KwjnEbuuqcIX\nlSk/TbbRNcwi/5wUua+vpOoeMIeqeJ+wEisw/01VT6Jq6FCmfDHVPQzi70uZyg2Q+jpWt3wA8LKI\nrBSREmzoY3OsgagQmBbi4VlYvK4Mx3JmOLcHA/8Xs82M6QnLq9oCL4V93IzdC+JUJw6mkwP8r6rO\nBv4fsFdke4tEZFr4OzmO/jPy/8Fptn8A8LWIvAUgIqtCXlQbeCicjyfYMC6/KSIfh7LYP9k4bWxK\nOStdWSMq3XXKJFV620lEXgvLRIcV9gT6h2N4A+v12p/UeUasX/qQtsrw/5Do54TQjXYycIKq3oRF\n+F3DzS+T0vB/ReTvxOcNzruIPK6qb2C9RxNU9XwRUVUtAo4B/qCqL4vI0CwPrSxyLOWJ/YnIBap6\nUNjPDFXtJCLLstxmsriKQSrR40+EJwdrVfzdJu5/c0zBhn7tjbUS98Z64FJ1hcaFvzrSxoXQUnEN\nUCwiy0MXd91qbL+kGpXPOLdhN+/eoXt+chbrxMaxVOLiXtLvw0LX/DHYjbKXRIbipDESuFNExmvV\nUK04uVhPUEn0S9XkdoqspIr7KeO0qrbHWmMvwIZpnpO0yBSsZ2JPrKX1Wqz7PhEnc7ChTu8nbfeg\npPDELhdjc+N0KtWKFxHr2bABLpv4n+qcZLnLrE3HWqPfx67HOVjB5erQA3U/NqRxUbjxRsOeMZ9M\nlf9nWC35+tXDzt+K0Nq5NYwGThSRWWpDunpksU40nLEvBUoQG8LZHTsPo1X1ThF5NGbRtMNmqpuf\nZnENU0nOy6P5fPI9fr3a0OEjsHvNJfZ1+nyxGvsvB2qJyMIsyg2jibmOm1g+SHVvf0lETo9Z/hGs\nYliCNWBt0LBVjfSUA8wVkXQViLgwpo2DGfTFhop2EpEyteFqibAlx8nKLP7O1pXAYqwHIxc7d6m2\nl/x5q5SzNiPNbOq6OVhP68SY7WWTZwD84nt4MjkCe1agmYgUiEhzrCW9N1ZA6aOqeaErNNNQj5TU\nxoN/LNa1+CxwYOhW/F7sYf07sGEgUW9iXfWNQ8XsdKyVIt1+WojIG2IPyS3BWizTmQ6cFv7uS+oK\nQdRqIJsK4cvAKaq6WwjbLqraPMM6U6k657/CWh3ezLB837D9HsDS0GqyCBuvvr+IfIwNi7qGqiEq\n2ZgGHKeqdUPLanW6c5PtjGXkK9WedfhNzDLVvt4isgJYofY8FSR1ZUc0xJ4DABgQ+X4aVjhH7W1N\n7TIfSnycyRT3wu9zRGQ41mrTKmm7CvxWbWhI4vms5LCfFVk+OR6+iHX9J/aXKBRGj7EnNvyQEO4T\nVXVHtWFSvckc/2PjtNoQj1wReQpriUxOy2DXtytQESplM7FnZxJxciJwqVa9WbJjzDaqs1yc97Ge\ngv3C535UxbFs03UqL2MVOkL6bZj0+2fYs347hJa+I8L3C0KYWoTP0UJUqmOdgg11QFXbYsOa4kSP\nKV36mkpV/vAulteXhtbzxI16acgHYl9Eky4txuX/MZsoUxuylJKIrAI+UXsWA1XNCRXtdMcNqfP5\n5OV2Ar4O4UiVl2QjNh8P+f9iEXkIG3KaSCe5VJ3XM4g8x5XimLLJT6Nir2E18s+MwnYbisgErADb\nPnyf6Z4cew9Ls59M5QZIcR2zCEu2ecDr2BDZ/cJ266tqS/jxZU1fYfngIzHrZpWesLzqV6p6cNhH\nbbVhz9lKVZZId4wNgW9DZedwrDcrYe9EWNg4jvaJ/P8aqb0PNFEbLo+q7qSqtcJ+vxbrje/Hhr1v\nXVR1H1XNDdtPThvZlrOyzQsTsr1OcdKlt9Wh0g1VeRJYXn9hIg9U1ZYhXqXKM2J5hSe904Fnkr57\nKvL9B1g37qOkj8iZnAq8p9Zd1zZsrx12E5iJjVn+Q3QFsYfzbsDGxc7CHpjf4OHkGHeo6hy1oUvT\nw3rpXIp1F87GEtrlGZYnhKdQ7TXSfVItFLqXbwZeDNt/iczDL57BhqfMwgrA14kNOUllCNApbH8Y\nGxaI3wASQ3emYt3TcTfSVOF/CxsaNRvrlp+DDVuoNhGZhRWkFmDduNOSFqncxOsN1jJ9X4hHqVq3\n/gTcrqrvsmHL5P3YTWUeFv/mkvkYU8WZTHHvClV9L6xXRtJQBxGZi43RfkVVZ2EPq4Jd4ydUdQb2\n4GrCf4HeIR4eij202VlVZ4fjuSAs93ugZwjXb7GHoleLyDtYS+ibWFx5WETeTXfgaeL0XsDkcA3G\nAhu1tolIKfbweGKo3FTsBjQnfL4NG9owW1Xnhs9xsl0uLvwlWHx5Qm2oQQX2vAfYsyEvqOqkbLeX\n5HJsGMMcbAjWBkOMQiPEv4H3wv/vRsJ0HvC82hClbyOrpTrWB7BhaPOxl6jMSBGmH48pQ/qaihX+\npoSe1EWEvCLcpB8K4Z5I1RDEOKnSYlz+HxfW2ar6jzTbByvADgxpZC5wQswyyWkjVZr9F3Ctqr4b\nKpy3YGlhGpZXbapU+XgPYFbIh/pQ9RKTtVjB7j1s+EvcSIfotcyUn24gwzXMJv/Mxk7Ac+Ecv0p4\n0Q+Z88UhpL6HxUlbbghSXcdMYZmNvexilqpemSoAYkP8BmAvFpiNlY2iDVj/wIaAzY9ZN6v0JPa8\n8CnA8BDXZ7Lxc9TppIqD6Y7xH9g9ZA72jFb03L0PXBzynEaE4btBo3AeLscqu7HCMfUBRoZjegmr\nHNwPnBW+a8WGvcZvYc8GzQc+Iam8Wo1yVrZ5YWK71cn3ko8z3boDseF7M7Fn9xLljYexsvY7IX4+\niJVVehCfZ8TKqazclB4255yqNhCRNWpvM5uCvUHnnS28jznA8SLyyZbcbpb7zgNqi72VsAU2bvmA\nkDHXCGovBigPQ04OBh7YikOCnHPVpKprRKTB9g6H2zLU3sD4roj8bXuHZUvQyBt3Y377lPAGz20d\nrp+jRJkq/H0D0EREsmloz8ov+hke5zbTX9WGetXFxslu6crOS8Cc7VHZCXbEXlVZG2vdvKgmVXaC\nvYF/hyEBP1D1VjHnnHNbUOiJXwtcvb3D4n6S/kdVf4fVTT5jwyH2m817eJxzzjnnnHM1lj/D45xz\nzjnnnKuxvMLjnHPOOeecq7G8wuOcc84555yrsfylBduA2sRnz4nIk9tofz2Aa0Rkc+aG2VJhGQ0c\nBewrIqVqc5K8LSIFm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d93APYUkQnh8xBSnJss9zMZe2VvCbAGOCd5kt3tRVUfxiZynLe9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\n",
            "text/plain": [
              "<Figure size 864x720 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "PRIdxThjwFQu",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "# Save figure\n",
        "# Download figure to local computer\n",
        "\n",
        "fig.savefig('Health_Age_Final.png')\n",
        "files.download('Health_Age_Final.png')"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "Cqkoh936sNHz",
        "colab_type": "text"
      },
      "source": [
        "## Second Visual"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "ntm6E4ggsZw2",
        "colab_type": "code",
        "outputId": "85710860-07d8-49f5-e253-89204bedf763",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 573
        }
      },
      "source": [
        "# Starting Data\n",
        "\n",
        "age_gender_race_DRG_MDC"
      ],
      "execution_count": 0,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "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>Unnamed: 0</th>\n",
              "      <th>Age Group</th>\n",
              "      <th>Gender</th>\n",
              "      <th>Race</th>\n",
              "      <th>APR DRG Code</th>\n",
              "      <th>APR DRG Description</th>\n",
              "      <th>APR MDC Code</th>\n",
              "      <th>APR MDC Description</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>0</td>\n",
              "      <td>30 to 49</td>\n",
              "      <td>M</td>\n",
              "      <td>White</td>\n",
              "      <td>750</td>\n",
              "      <td>Schizophrenia</td>\n",
              "      <td>19</td>\n",
              "      <td>Mental Diseases and Disorders</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>1</td>\n",
              "      <td>50 to 69</td>\n",
              "      <td>M</td>\n",
              "      <td>White</td>\n",
              "      <td>194</td>\n",
              "      <td>Heart failure</td>\n",
              "      <td>5</td>\n",
              "      <td>Diseases and Disorders of the Circulatory System</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>2</td>\n",
              "      <td>30 to 49</td>\n",
              "      <td>F</td>\n",
              "      <td>White</td>\n",
              "      <td>465</td>\n",
              "      <td>Urinary stones &amp; acquired upper urinary tract ...</td>\n",
              "      <td>11</td>\n",
              "      <td>Diseases and Disorders of the Kidney and Urina...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>3</td>\n",
              "      <td>50 to 69</td>\n",
              "      <td>F</td>\n",
              "      <td>White</td>\n",
              "      <td>721</td>\n",
              "      <td>Post-operative, post-traumatic, other device i...</td>\n",
              "      <td>18</td>\n",
              "      <td>Infectious and Parasitic Diseases, Systemic or...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>4</td>\n",
              "      <td>18 to 29</td>\n",
              "      <td>F</td>\n",
              "      <td>White</td>\n",
              "      <td>720</td>\n",
              "      <td>Septicemia &amp; disseminated infections</td>\n",
              "      <td>18</td>\n",
              "      <td>Infectious and Parasitic Diseases, Systemic or...</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",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2343564</th>\n",
              "      <td>2343564</td>\n",
              "      <td>50 to 69</td>\n",
              "      <td>F</td>\n",
              "      <td>White</td>\n",
              "      <td>120</td>\n",
              "      <td>Major respiratory &amp; chest procedures</td>\n",
              "      <td>4</td>\n",
              "      <td>Diseases and Disorders of the Respiratory System</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2343565</th>\n",
              "      <td>2343565</td>\n",
              "      <td>50 to 69</td>\n",
              "      <td>F</td>\n",
              "      <td>Other Race</td>\n",
              "      <td>198</td>\n",
              "      <td>Angina pectoris &amp; coronary atherosclerosis</td>\n",
              "      <td>5</td>\n",
              "      <td>Diseases and Disorders of the Circulatory System</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2343566</th>\n",
              "      <td>2343566</td>\n",
              "      <td>30 to 49</td>\n",
              "      <td>M</td>\n",
              "      <td>Other Race</td>\n",
              "      <td>347</td>\n",
              "      <td>Other back &amp; neck disorders, fractures &amp; injuries</td>\n",
              "      <td>8</td>\n",
              "      <td>Diseases and Disorders of the Musculoskeletal ...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2343567</th>\n",
              "      <td>2343567</td>\n",
              "      <td>70 or Older</td>\n",
              "      <td>F</td>\n",
              "      <td>Black/African American</td>\n",
              "      <td>512</td>\n",
              "      <td>Uterine &amp; adnexa procedures for non-ovarian &amp; ...</td>\n",
              "      <td>13</td>\n",
              "      <td>Diseases and Disorders of the Female Reproduct...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2343568</th>\n",
              "      <td>2343568</td>\n",
              "      <td>18 to 29</td>\n",
              "      <td>F</td>\n",
              "      <td>White</td>\n",
              "      <td>775</td>\n",
              "      <td>Alcohol abuse &amp; dependence</td>\n",
              "      <td>20</td>\n",
              "      <td>Alcohol/Drug Use and Alcohol/Drug Induced Orga...</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>1873423 rows × 8 columns</p>\n",
              "</div>"
            ],
            "text/plain": [
              "         Unnamed: 0  ...                                APR MDC Description\n",
              "0                 0  ...                      Mental Diseases and Disorders\n",
              "1                 1  ...   Diseases and Disorders of the Circulatory System\n",
              "2                 2  ...  Diseases and Disorders of the Kidney and Urina...\n",
              "3                 3  ...  Infectious and Parasitic Diseases, Systemic or...\n",
              "4                 4  ...  Infectious and Parasitic Diseases, Systemic or...\n",
              "...             ...  ...                                                ...\n",
              "2343564     2343564  ...   Diseases and Disorders of the Respiratory System\n",
              "2343565     2343565  ...   Diseases and Disorders of the Circulatory System\n",
              "2343566     2343566  ...  Diseases and Disorders of the Musculoskeletal ...\n",
              "2343567     2343567  ...  Diseases and Disorders of the Female Reproduct...\n",
              "2343568     2343568  ...  Alcohol/Drug Use and Alcohol/Drug Induced Orga...\n",
              "\n",
              "[1873423 rows x 8 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 13
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "ciX8FkEfsxOm",
        "colab_type": "code",
        "outputId": "9963d9a7-3b7f-40fd-98d7-72fa28580a30",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 590
        }
      },
      "source": [
        "# Create mental health subset\n",
        "\n",
        "mental = age_gender_race_DRG_MDC[age_gender_race_DRG_MDC['APR MDC Description'] == 'Mental Diseases and Disorders']\n",
        "mental"
      ],
      "execution_count": 0,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
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              "\n",
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              "\n",
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              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>Unnamed: 0</th>\n",
              "      <th>Age Group</th>\n",
              "      <th>Gender</th>\n",
              "      <th>Race</th>\n",
              "      <th>APR DRG Code</th>\n",
              "      <th>APR DRG Description</th>\n",
              "      <th>APR MDC Code</th>\n",
              "      <th>APR MDC Description</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>0</td>\n",
              "      <td>30 to 49</td>\n",
              "      <td>M</td>\n",
              "      <td>White</td>\n",
              "      <td>750</td>\n",
              "      <td>Schizophrenia</td>\n",
              "      <td>19</td>\n",
              "      <td>Mental Diseases and Disorders</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>32</th>\n",
              "      <td>32</td>\n",
              "      <td>50 to 69</td>\n",
              "      <td>M</td>\n",
              "      <td>White</td>\n",
              "      <td>751</td>\n",
              "      <td>Major depressive disorders &amp; other/unspecified...</td>\n",
              "      <td>19</td>\n",
              "      <td>Mental Diseases and Disorders</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>34</th>\n",
              "      <td>34</td>\n",
              "      <td>30 to 49</td>\n",
              "      <td>F</td>\n",
              "      <td>White</td>\n",
              "      <td>750</td>\n",
              "      <td>Schizophrenia</td>\n",
              "      <td>19</td>\n",
              "      <td>Mental Diseases and Disorders</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>37</th>\n",
              "      <td>37</td>\n",
              "      <td>30 to 49</td>\n",
              "      <td>F</td>\n",
              "      <td>Black/African American</td>\n",
              "      <td>751</td>\n",
              "      <td>Major depressive disorders &amp; other/unspecified...</td>\n",
              "      <td>19</td>\n",
              "      <td>Mental Diseases and Disorders</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>40</th>\n",
              "      <td>40</td>\n",
              "      <td>18 to 29</td>\n",
              "      <td>M</td>\n",
              "      <td>Black/African American</td>\n",
              "      <td>750</td>\n",
              "      <td>Schizophrenia</td>\n",
              "      <td>19</td>\n",
              "      <td>Mental Diseases and Disorders</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",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2343468</th>\n",
              "      <td>2343468</td>\n",
              "      <td>50 to 69</td>\n",
              "      <td>M</td>\n",
              "      <td>White</td>\n",
              "      <td>750</td>\n",
              "      <td>Schizophrenia</td>\n",
              "      <td>19</td>\n",
              "      <td>Mental Diseases and Disorders</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2343470</th>\n",
              "      <td>2343470</td>\n",
              "      <td>18 to 29</td>\n",
              "      <td>F</td>\n",
              "      <td>White</td>\n",
              "      <td>759</td>\n",
              "      <td>Eating disorders</td>\n",
              "      <td>19</td>\n",
              "      <td>Mental Diseases and Disorders</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2343473</th>\n",
              "      <td>2343473</td>\n",
              "      <td>50 to 69</td>\n",
              "      <td>M</td>\n",
              "      <td>White</td>\n",
              "      <td>750</td>\n",
              "      <td>Schizophrenia</td>\n",
              "      <td>19</td>\n",
              "      <td>Mental Diseases and Disorders</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2343476</th>\n",
              "      <td>2343476</td>\n",
              "      <td>18 to 29</td>\n",
              "      <td>M</td>\n",
              "      <td>Black/African American</td>\n",
              "      <td>753</td>\n",
              "      <td>Bipolar disorders</td>\n",
              "      <td>19</td>\n",
              "      <td>Mental Diseases and Disorders</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2343483</th>\n",
              "      <td>2343483</td>\n",
              "      <td>18 to 29</td>\n",
              "      <td>F</td>\n",
              "      <td>Black/African American</td>\n",
              "      <td>750</td>\n",
              "      <td>Schizophrenia</td>\n",
              "      <td>19</td>\n",
              "      <td>Mental Diseases and Disorders</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>114924 rows × 8 columns</p>\n",
              "</div>"
            ],
            "text/plain": [
              "         Unnamed: 0 Age Group  ... APR MDC Code            APR MDC Description\n",
              "0                 0  30 to 49  ...           19  Mental Diseases and Disorders\n",
              "32               32  50 to 69  ...           19  Mental Diseases and Disorders\n",
              "34               34  30 to 49  ...           19  Mental Diseases and Disorders\n",
              "37               37  30 to 49  ...           19  Mental Diseases and Disorders\n",
              "40               40  18 to 29  ...           19  Mental Diseases and Disorders\n",
              "...             ...       ...  ...          ...                            ...\n",
              "2343468     2343468  50 to 69  ...           19  Mental Diseases and Disorders\n",
              "2343470     2343470  18 to 29  ...           19  Mental Diseases and Disorders\n",
              "2343473     2343473  50 to 69  ...           19  Mental Diseases and Disorders\n",
              "2343476     2343476  18 to 29  ...           19  Mental Diseases and Disorders\n",
              "2343483     2343483  18 to 29  ...           19  Mental Diseases and Disorders\n",
              "\n",
              "[114924 rows x 8 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 14
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "UgxoL8C1sxR_",
        "colab_type": "code",
        "outputId": "1fc70aec-9295-4d53-ca12-5a66b79b2898",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 406
        }
      },
      "source": [
        "# Drop unnecessary columns\n",
        "\n",
        "mental = mental[['Age Group', 'Gender', 'Race', 'APR DRG Description']]\n",
        "mental"
      ],
      "execution_count": 0,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "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>Age Group</th>\n",
              "      <th>Gender</th>\n",
              "      <th>Race</th>\n",
              "      <th>APR DRG Description</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>30 to 49</td>\n",
              "      <td>M</td>\n",
              "      <td>White</td>\n",
              "      <td>Schizophrenia</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>32</th>\n",
              "      <td>50 to 69</td>\n",
              "      <td>M</td>\n",
              "      <td>White</td>\n",
              "      <td>Major depressive disorders &amp; other/unspecified...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>34</th>\n",
              "      <td>30 to 49</td>\n",
              "      <td>F</td>\n",
              "      <td>White</td>\n",
              "      <td>Schizophrenia</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>37</th>\n",
              "      <td>30 to 49</td>\n",
              "      <td>F</td>\n",
              "      <td>Black/African American</td>\n",
              "      <td>Major depressive disorders &amp; other/unspecified...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>40</th>\n",
              "      <td>18 to 29</td>\n",
              "      <td>M</td>\n",
              "      <td>Black/African American</td>\n",
              "      <td>Schizophrenia</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>...</th>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2343468</th>\n",
              "      <td>50 to 69</td>\n",
              "      <td>M</td>\n",
              "      <td>White</td>\n",
              "      <td>Schizophrenia</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2343470</th>\n",
              "      <td>18 to 29</td>\n",
              "      <td>F</td>\n",
              "      <td>White</td>\n",
              "      <td>Eating disorders</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2343473</th>\n",
              "      <td>50 to 69</td>\n",
              "      <td>M</td>\n",
              "      <td>White</td>\n",
              "      <td>Schizophrenia</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2343476</th>\n",
              "      <td>18 to 29</td>\n",
              "      <td>M</td>\n",
              "      <td>Black/African American</td>\n",
              "      <td>Bipolar disorders</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2343483</th>\n",
              "      <td>18 to 29</td>\n",
              "      <td>F</td>\n",
              "      <td>Black/African American</td>\n",
              "      <td>Schizophrenia</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>114924 rows × 4 columns</p>\n",
              "</div>"
            ],
            "text/plain": [
              "        Age Group  ...                                APR DRG Description\n",
              "0        30 to 49  ...                                      Schizophrenia\n",
              "32       50 to 69  ...  Major depressive disorders & other/unspecified...\n",
              "34       30 to 49  ...                                      Schizophrenia\n",
              "37       30 to 49  ...  Major depressive disorders & other/unspecified...\n",
              "40       18 to 29  ...                                      Schizophrenia\n",
              "...           ...  ...                                                ...\n",
              "2343468  50 to 69  ...                                      Schizophrenia\n",
              "2343470  18 to 29  ...                                   Eating disorders\n",
              "2343473  50 to 69  ...                                      Schizophrenia\n",
              "2343476  18 to 29  ...                                  Bipolar disorders\n",
              "2343483  18 to 29  ...                                      Schizophrenia\n",
              "\n",
              "[114924 rows x 4 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 15
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "Gw8ghApvsxTl",
        "colab_type": "code",
        "outputId": "97db8d9a-e272-42be-bbca-e3b91917e544",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 283
        }
      },
      "source": [
        "# Value counts of APR DRG Descriptions\n",
        "\n",
        "mental['APR DRG Description'].value_counts()"
      ],
      "execution_count": 0,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Schizophrenia                                                  35607\n",
              "Bipolar disorders                                              25430\n",
              "Major depressive disorders & other/unspecified psychoses       23944\n",
              "Depression except major depressive disorder                    11713\n",
              "Organic mental health disturbances                              4991\n",
              "Adjustment disorders & neuroses except depressive diagnoses     4002\n",
              "Acute anxiety & delirium states                                 3376\n",
              "Behavioral disorders                                            2390\n",
              "Disorders of personality & impulse control                      1584\n",
              "Other mental health disorders                                   1002\n",
              "Mental illness diagnosis w O.R. procedure                        463\n",
              "Eating disorders                                                 419\n",
              "Tracheostomy w MV 96+ hours w extensive procedure or ECMO          2\n",
              "Tracheostomy w MV 96+ hours w/o extensive procedure                1\n",
              "Name: APR DRG Description, dtype: int64"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 16
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "MMlg5phQvaGx",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "# Drop both Tracheostomy categories as they are statistically insignificant\n",
        "\n",
        "mental = mental[mental['APR DRG Description'] != 'Tracheostomy w MV 96+ hours w extensive procedure or ECMO']\n",
        "mental =  mental[mental['APR DRG Description'] != 'Tracheostomy w MV 96+ hours w/o extensive procedure']"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "g753QO8rwps7",
        "colab_type": "code",
        "outputId": "a617bec7-44d2-4655-fb31-87652ea25a31",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 331
        }
      },
      "source": [
        "# Create crosstab to get counts for APR DRG Description per Age Group\n",
        "# Normalize across age group (across row)\n",
        "\n",
        "mental_age = pd.crosstab(mental['Age Group'], mental['APR DRG Description'], normalize= 'index')\n",
        "mental_age"
      ],
      "execution_count": 0,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "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>APR DRG Description</th>\n",
              "      <th>Acute anxiety &amp; delirium states</th>\n",
              "      <th>Adjustment disorders &amp; neuroses except depressive diagnoses</th>\n",
              "      <th>Behavioral disorders</th>\n",
              "      <th>Bipolar disorders</th>\n",
              "      <th>Depression except major depressive disorder</th>\n",
              "      <th>Disorders of personality &amp; impulse control</th>\n",
              "      <th>Eating disorders</th>\n",
              "      <th>Major depressive disorders &amp; other/unspecified psychoses</th>\n",
              "      <th>Mental illness diagnosis w O.R. procedure</th>\n",
              "      <th>Organic mental health disturbances</th>\n",
              "      <th>Other mental health disorders</th>\n",
              "      <th>Schizophrenia</th>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Age Group</th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0 to 17</th>\n",
              "      <td>0.037633</td>\n",
              "      <td>0.058520</td>\n",
              "      <td>0.160011</td>\n",
              "      <td>0.216875</td>\n",
              "      <td>0.161391</td>\n",
              "      <td>0.002852</td>\n",
              "      <td>0.017759</td>\n",
              "      <td>0.280732</td>\n",
              "      <td>0.002760</td>\n",
              "      <td>0.023923</td>\n",
              "      <td>0.014814</td>\n",
              "      <td>0.022727</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>18 to 29</th>\n",
              "      <td>0.024870</td>\n",
              "      <td>0.046615</td>\n",
              "      <td>0.012901</td>\n",
              "      <td>0.246043</td>\n",
              "      <td>0.120528</td>\n",
              "      <td>0.025569</td>\n",
              "      <td>0.004322</td>\n",
              "      <td>0.213858</td>\n",
              "      <td>0.004389</td>\n",
              "      <td>0.008246</td>\n",
              "      <td>0.003957</td>\n",
              "      <td>0.288702</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>30 to 49</th>\n",
              "      <td>0.024899</td>\n",
              "      <td>0.032926</td>\n",
              "      <td>0.005001</td>\n",
              "      <td>0.245960</td>\n",
              "      <td>0.092699</td>\n",
              "      <td>0.015029</td>\n",
              "      <td>0.001737</td>\n",
              "      <td>0.185845</td>\n",
              "      <td>0.004290</td>\n",
              "      <td>0.004580</td>\n",
              "      <td>0.006817</td>\n",
              "      <td>0.380218</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>50 to 69</th>\n",
              "      <td>0.029341</td>\n",
              "      <td>0.021970</td>\n",
              "      <td>0.002337</td>\n",
              "      <td>0.202114</td>\n",
              "      <td>0.085074</td>\n",
              "      <td>0.007155</td>\n",
              "      <td>0.000791</td>\n",
              "      <td>0.213549</td>\n",
              "      <td>0.003308</td>\n",
              "      <td>0.024055</td>\n",
              "      <td>0.010248</td>\n",
              "      <td>0.400058</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>70 or Older</th>\n",
              "      <td>0.055923</td>\n",
              "      <td>0.012482</td>\n",
              "      <td>0.000979</td>\n",
              "      <td>0.086515</td>\n",
              "      <td>0.054577</td>\n",
              "      <td>0.001713</td>\n",
              "      <td>0.000979</td>\n",
              "      <td>0.178781</td>\n",
              "      <td>0.005629</td>\n",
              "      <td>0.445423</td>\n",
              "      <td>0.021782</td>\n",
              "      <td>0.135218</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "APR DRG Description  Acute anxiety & delirium states  ...  Schizophrenia\n",
              "Age Group                                             ...               \n",
              "0 to 17                                     0.037633  ...       0.022727\n",
              "18 to 29                                    0.024870  ...       0.288702\n",
              "30 to 49                                    0.024899  ...       0.380218\n",
              "50 to 69                                    0.029341  ...       0.400058\n",
              "70 or Older                                 0.055923  ...       0.135218\n",
              "\n",
              "[5 rows x 12 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 18
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "fCf5W9OjzSkW",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "# Create Y-Values\n",
        "\n",
        "anxiety = mental_age.loc[:, 'Acute anxiety & delirium states'].values.tolist()\n",
        "adjustment = mental_age.loc[:, 'Adjustment disorders & neuroses except depressive diagnoses'].values.tolist()\n",
        "behavioral = mental_age.loc[:, 'Behavioral disorders'].values.tolist()\n",
        "bipolar = mental_age.loc[:, 'Bipolar disorders'].values.tolist()\n",
        "minor_depressive = mental_age.loc[:, 'Depression except major depressive disorder'].values.tolist()\n",
        "personality = mental_age.loc[:, 'Disorders of personality & impulse control'].values.tolist()\n",
        "eating = mental_age.loc[:, 'Eating disorders'].values.tolist()\n",
        "major_depressive = mental_age.loc[:, 'Major depressive disorders & other/unspecified psychoses'].values.tolist()\n",
        "operation = mental_age.loc[:, 'Mental illness diagnosis w O.R. procedure'].values.tolist()\n",
        "organic = mental_age.loc[:, 'Organic mental health disturbances'].values.tolist()\n",
        "other = mental_age.loc[:, 'Other mental health disorders'].values.tolist()\n",
        "schizophrenia = mental_age.loc[:, 'Schizophrenia'].values.tolist()\n"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "ZqGPcUKS0NrG",
        "colab_type": "code",
        "outputId": "f8fa5021-c69a-4c7f-b27b-86fdef94eebe",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 282
        }
      },
      "source": [
        "# Basic exploratory graph\n",
        "\n",
        "plt.plot(anxiety, color= 'red')\n",
        "plt.plot(adjustment, color= 'blue')\n",
        "plt.plot(behavioral, color= 'orange')\n",
        "plt.plot(bipolar, color= 'green')\n",
        "plt.plot(minor_depressive, color= 'yellow')\n",
        "plt.plot(personality, color= 'pink')\n",
        "plt.plot(eating, color= 'purple')\n",
        "plt.plot(major_depressive, color= 'black')\n",
        "plt.plot(operation, color= 'brown')\n",
        "plt.plot(organic, color= 'teal')\n",
        "plt.plot(other, color= 'gray')\n",
        "plt.plot(schizophrenia, color= 'tan')\n",
        "\n",
        "plt.show()"
      ],
      "execution_count": 0,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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Uw2rSOW1D0ULI4+ciOC5vxi4eJHgP+ZxCDCqbYRoYKQzYX38M4pBY0EKpD3vmnLdH1ey5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\nhBiRyJxGTfMAAAAASUVORK5CYII=\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "t6CrYYgmiJWW",
        "colab_type": "code",
        "outputId": "9cf4f01e-b4a5-495d-d30d-ee041abb028f",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 384
        }
      },
      "source": [
        "# Want to Graph with Plotly, need to convert data in Tidy format\n",
        "\n",
        "# Reset index\n",
        "mental_age_tidy = mental_age.reset_index()\n",
        "mental_age_tidy"
      ],
      "execution_count": 0,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "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>APR DRG Description</th>\n",
              "      <th>Age Group</th>\n",
              "      <th>Acute anxiety &amp; delirium states</th>\n",
              "      <th>Adjustment disorders &amp; neuroses except depressive diagnoses</th>\n",
              "      <th>Behavioral disorders</th>\n",
              "      <th>Bipolar disorders</th>\n",
              "      <th>Depression except major depressive disorder</th>\n",
              "      <th>Disorders of personality &amp; impulse control</th>\n",
              "      <th>Eating disorders</th>\n",
              "      <th>Major depressive disorders &amp; other/unspecified psychoses</th>\n",
              "      <th>Mental illness diagnosis w O.R. procedure</th>\n",
              "      <th>Organic mental health disturbances</th>\n",
              "      <th>Other mental health disorders</th>\n",
              "      <th>Schizophrenia</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>0 to 17</td>\n",
              "      <td>0.037633</td>\n",
              "      <td>0.058520</td>\n",
              "      <td>0.160011</td>\n",
              "      <td>0.216875</td>\n",
              "      <td>0.161391</td>\n",
              "      <td>0.002852</td>\n",
              "      <td>0.017759</td>\n",
              "      <td>0.280732</td>\n",
              "      <td>0.002760</td>\n",
              "      <td>0.023923</td>\n",
              "      <td>0.014814</td>\n",
              "      <td>0.022727</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>18 to 29</td>\n",
              "      <td>0.024870</td>\n",
              "      <td>0.046615</td>\n",
              "      <td>0.012901</td>\n",
              "      <td>0.246043</td>\n",
              "      <td>0.120528</td>\n",
              "      <td>0.025569</td>\n",
              "      <td>0.004322</td>\n",
              "      <td>0.213858</td>\n",
              "      <td>0.004389</td>\n",
              "      <td>0.008246</td>\n",
              "      <td>0.003957</td>\n",
              "      <td>0.288702</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>30 to 49</td>\n",
              "      <td>0.024899</td>\n",
              "      <td>0.032926</td>\n",
              "      <td>0.005001</td>\n",
              "      <td>0.245960</td>\n",
              "      <td>0.092699</td>\n",
              "      <td>0.015029</td>\n",
              "      <td>0.001737</td>\n",
              "      <td>0.185845</td>\n",
              "      <td>0.004290</td>\n",
              "      <td>0.004580</td>\n",
              "      <td>0.006817</td>\n",
              "      <td>0.380218</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>50 to 69</td>\n",
              "      <td>0.029341</td>\n",
              "      <td>0.021970</td>\n",
              "      <td>0.002337</td>\n",
              "      <td>0.202114</td>\n",
              "      <td>0.085074</td>\n",
              "      <td>0.007155</td>\n",
              "      <td>0.000791</td>\n",
              "      <td>0.213549</td>\n",
              "      <td>0.003308</td>\n",
              "      <td>0.024055</td>\n",
              "      <td>0.010248</td>\n",
              "      <td>0.400058</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>70 or Older</td>\n",
              "      <td>0.055923</td>\n",
              "      <td>0.012482</td>\n",
              "      <td>0.000979</td>\n",
              "      <td>0.086515</td>\n",
              "      <td>0.054577</td>\n",
              "      <td>0.001713</td>\n",
              "      <td>0.000979</td>\n",
              "      <td>0.178781</td>\n",
              "      <td>0.005629</td>\n",
              "      <td>0.445423</td>\n",
              "      <td>0.021782</td>\n",
              "      <td>0.135218</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "APR DRG Description    Age Group  ...  Schizophrenia\n",
              "0                        0 to 17  ...       0.022727\n",
              "1                       18 to 29  ...       0.288702\n",
              "2                       30 to 49  ...       0.380218\n",
              "3                       50 to 69  ...       0.400058\n",
              "4                    70 or Older  ...       0.135218\n",
              "\n",
              "[5 rows x 13 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 21
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "Ex6U3p9XjElq",
        "colab_type": "code",
        "outputId": "f6f027b1-6555-4680-fd3b-ac084db87e98",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 230
        }
      },
      "source": [
        "# Column headers to list\n",
        "headers = list(mental_age)\n",
        "headers"
      ],
      "execution_count": 0,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "['Acute anxiety & delirium states',\n",
              " 'Adjustment disorders & neuroses except depressive diagnoses',\n",
              " 'Behavioral disorders',\n",
              " 'Bipolar disorders',\n",
              " 'Depression except major depressive disorder',\n",
              " 'Disorders of personality & impulse control',\n",
              " 'Eating disorders',\n",
              " 'Major depressive disorders & other/unspecified psychoses',\n",
              " 'Mental illness diagnosis w O.R. procedure',\n",
              " 'Organic mental health disturbances',\n",
              " 'Other mental health disorders',\n",
              " 'Schizophrenia']"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 22
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "puaRiKktiJUE",
        "colab_type": "code",
        "outputId": "9eb292ff-4bba-492e-87ad-33734f10fd75",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 1000
        }
      },
      "source": [
        "# Convert to Tidy data format\n",
        "\n",
        "mental_age_tidy = mental_age_tidy.melt(id_vars= 'Age Group', value_vars= headers)\n",
        "mental_age_tidy"
      ],
      "execution_count": 0,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "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>Age Group</th>\n",
              "      <th>APR DRG Description</th>\n",
              "      <th>value</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>0 to 17</td>\n",
              "      <td>Acute anxiety &amp; delirium states</td>\n",
              "      <td>0.037633</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>18 to 29</td>\n",
              "      <td>Acute anxiety &amp; delirium states</td>\n",
              "      <td>0.024870</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>30 to 49</td>\n",
              "      <td>Acute anxiety &amp; delirium states</td>\n",
              "      <td>0.024899</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>50 to 69</td>\n",
              "      <td>Acute anxiety &amp; delirium states</td>\n",
              "      <td>0.029341</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>70 or Older</td>\n",
              "      <td>Acute anxiety &amp; delirium states</td>\n",
              "      <td>0.055923</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>5</th>\n",
              "      <td>0 to 17</td>\n",
              "      <td>Adjustment disorders &amp; neuroses except depress...</td>\n",
              "      <td>0.058520</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>6</th>\n",
              "      <td>18 to 29</td>\n",
              "      <td>Adjustment disorders &amp; neuroses except depress...</td>\n",
              "      <td>0.046615</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>7</th>\n",
              "      <td>30 to 49</td>\n",
              "      <td>Adjustment disorders &amp; neuroses except depress...</td>\n",
              "      <td>0.032926</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>8</th>\n",
              "      <td>50 to 69</td>\n",
              "      <td>Adjustment disorders &amp; neuroses except depress...</td>\n",
              "      <td>0.021970</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>9</th>\n",
              "      <td>70 or Older</td>\n",
              "      <td>Adjustment disorders &amp; neuroses except depress...</td>\n",
              "      <td>0.012482</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>10</th>\n",
              "      <td>0 to 17</td>\n",
              "      <td>Behavioral disorders</td>\n",
              "      <td>0.160011</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>11</th>\n",
              "      <td>18 to 29</td>\n",
              "      <td>Behavioral disorders</td>\n",
              "      <td>0.012901</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>12</th>\n",
              "      <td>30 to 49</td>\n",
              "      <td>Behavioral disorders</td>\n",
              "      <td>0.005001</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>13</th>\n",
              "      <td>50 to 69</td>\n",
              "      <td>Behavioral disorders</td>\n",
              "      <td>0.002337</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>14</th>\n",
              "      <td>70 or Older</td>\n",
              "      <td>Behavioral disorders</td>\n",
              "      <td>0.000979</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>15</th>\n",
              "      <td>0 to 17</td>\n",
              "      <td>Bipolar disorders</td>\n",
              "      <td>0.216875</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>16</th>\n",
              "      <td>18 to 29</td>\n",
              "      <td>Bipolar disorders</td>\n",
              "      <td>0.246043</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>17</th>\n",
              "      <td>30 to 49</td>\n",
              "      <td>Bipolar disorders</td>\n",
              "      <td>0.245960</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>18</th>\n",
              "      <td>50 to 69</td>\n",
              "      <td>Bipolar disorders</td>\n",
              "      <td>0.202114</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>19</th>\n",
              "      <td>70 or Older</td>\n",
              "      <td>Bipolar disorders</td>\n",
              "      <td>0.086515</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>20</th>\n",
              "      <td>0 to 17</td>\n",
              "      <td>Depression except major depressive disorder</td>\n",
              "      <td>0.161391</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>21</th>\n",
              "      <td>18 to 29</td>\n",
              "      <td>Depression except major depressive disorder</td>\n",
              "      <td>0.120528</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>22</th>\n",
              "      <td>30 to 49</td>\n",
              "      <td>Depression except major depressive disorder</td>\n",
              "      <td>0.092699</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>23</th>\n",
              "      <td>50 to 69</td>\n",
              "      <td>Depression except major depressive disorder</td>\n",
              "      <td>0.085074</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>24</th>\n",
              "      <td>70 or Older</td>\n",
              "      <td>Depression except major depressive disorder</td>\n",
              "      <td>0.054577</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>25</th>\n",
              "      <td>0 to 17</td>\n",
              "      <td>Disorders of personality &amp; impulse control</td>\n",
              "      <td>0.002852</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>26</th>\n",
              "      <td>18 to 29</td>\n",
              "      <td>Disorders of personality &amp; impulse control</td>\n",
              "      <td>0.025569</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>27</th>\n",
              "      <td>30 to 49</td>\n",
              "      <td>Disorders of personality &amp; impulse control</td>\n",
              "      <td>0.015029</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>28</th>\n",
              "      <td>50 to 69</td>\n",
              "      <td>Disorders of personality &amp; impulse control</td>\n",
              "      <td>0.007155</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>29</th>\n",
              "      <td>70 or Older</td>\n",
              "      <td>Disorders of personality &amp; impulse control</td>\n",
              "      <td>0.001713</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>30</th>\n",
              "      <td>0 to 17</td>\n",
              "      <td>Eating disorders</td>\n",
              "      <td>0.017759</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>31</th>\n",
              "      <td>18 to 29</td>\n",
              "      <td>Eating disorders</td>\n",
              "      <td>0.004322</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>32</th>\n",
              "      <td>30 to 49</td>\n",
              "      <td>Eating disorders</td>\n",
              "      <td>0.001737</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>33</th>\n",
              "      <td>50 to 69</td>\n",
              "      <td>Eating disorders</td>\n",
              "      <td>0.000791</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>34</th>\n",
              "      <td>70 or Older</td>\n",
              "      <td>Eating disorders</td>\n",
              "      <td>0.000979</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>35</th>\n",
              "      <td>0 to 17</td>\n",
              "      <td>Major depressive disorders &amp; other/unspecified...</td>\n",
              "      <td>0.280732</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>36</th>\n",
              "      <td>18 to 29</td>\n",
              "      <td>Major depressive disorders &amp; other/unspecified...</td>\n",
              "      <td>0.213858</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>37</th>\n",
              "      <td>30 to 49</td>\n",
              "      <td>Major depressive disorders &amp; other/unspecified...</td>\n",
              "      <td>0.185845</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>38</th>\n",
              "      <td>50 to 69</td>\n",
              "      <td>Major depressive disorders &amp; other/unspecified...</td>\n",
              "      <td>0.213549</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>39</th>\n",
              "      <td>70 or Older</td>\n",
              "      <td>Major depressive disorders &amp; other/unspecified...</td>\n",
              "      <td>0.178781</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>40</th>\n",
              "      <td>0 to 17</td>\n",
              "      <td>Mental illness diagnosis w O.R. procedure</td>\n",
              "      <td>0.002760</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>41</th>\n",
              "      <td>18 to 29</td>\n",
              "      <td>Mental illness diagnosis w O.R. procedure</td>\n",
              "      <td>0.004389</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>42</th>\n",
              "      <td>30 to 49</td>\n",
              "      <td>Mental illness diagnosis w O.R. procedure</td>\n",
              "      <td>0.004290</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>43</th>\n",
              "      <td>50 to 69</td>\n",
              "      <td>Mental illness diagnosis w O.R. procedure</td>\n",
              "      <td>0.003308</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>44</th>\n",
              "      <td>70 or Older</td>\n",
              "      <td>Mental illness diagnosis w O.R. procedure</td>\n",
              "      <td>0.005629</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>45</th>\n",
              "      <td>0 to 17</td>\n",
              "      <td>Organic mental health disturbances</td>\n",
              "      <td>0.023923</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>46</th>\n",
              "      <td>18 to 29</td>\n",
              "      <td>Organic mental health disturbances</td>\n",
              "      <td>0.008246</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>47</th>\n",
              "      <td>30 to 49</td>\n",
              "      <td>Organic mental health disturbances</td>\n",
              "      <td>0.004580</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>48</th>\n",
              "      <td>50 to 69</td>\n",
              "      <td>Organic mental health disturbances</td>\n",
              "      <td>0.024055</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>49</th>\n",
              "      <td>70 or Older</td>\n",
              "      <td>Organic mental health disturbances</td>\n",
              "      <td>0.445423</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>50</th>\n",
              "      <td>0 to 17</td>\n",
              "      <td>Other mental health disorders</td>\n",
              "      <td>0.014814</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>51</th>\n",
              "      <td>18 to 29</td>\n",
              "      <td>Other mental health disorders</td>\n",
              "      <td>0.003957</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>52</th>\n",
              "      <td>30 to 49</td>\n",
              "      <td>Other mental health disorders</td>\n",
              "      <td>0.006817</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>53</th>\n",
              "      <td>50 to 69</td>\n",
              "      <td>Other mental health disorders</td>\n",
              "      <td>0.010248</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>54</th>\n",
              "      <td>70 or Older</td>\n",
              "      <td>Other mental health disorders</td>\n",
              "      <td>0.021782</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>55</th>\n",
              "      <td>0 to 17</td>\n",
              "      <td>Schizophrenia</td>\n",
              "      <td>0.022727</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>56</th>\n",
              "      <td>18 to 29</td>\n",
              "      <td>Schizophrenia</td>\n",
              "      <td>0.288702</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>57</th>\n",
              "      <td>30 to 49</td>\n",
              "      <td>Schizophrenia</td>\n",
              "      <td>0.380218</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>58</th>\n",
              "      <td>50 to 69</td>\n",
              "      <td>Schizophrenia</td>\n",
              "      <td>0.400058</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>59</th>\n",
              "      <td>70 or Older</td>\n",
              "      <td>Schizophrenia</td>\n",
              "      <td>0.135218</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "      Age Group                                APR DRG Description     value\n",
              "0       0 to 17                    Acute anxiety & delirium states  0.037633\n",
              "1      18 to 29                    Acute anxiety & delirium states  0.024870\n",
              "2      30 to 49                    Acute anxiety & delirium states  0.024899\n",
              "3      50 to 69                    Acute anxiety & delirium states  0.029341\n",
              "4   70 or Older                    Acute anxiety & delirium states  0.055923\n",
              "5       0 to 17  Adjustment disorders & neuroses except depress...  0.058520\n",
              "6      18 to 29  Adjustment disorders & neuroses except depress...  0.046615\n",
              "7      30 to 49  Adjustment disorders & neuroses except depress...  0.032926\n",
              "8      50 to 69  Adjustment disorders & neuroses except depress...  0.021970\n",
              "9   70 or Older  Adjustment disorders & neuroses except depress...  0.012482\n",
              "10      0 to 17                               Behavioral disorders  0.160011\n",
              "11     18 to 29                               Behavioral disorders  0.012901\n",
              "12     30 to 49                               Behavioral disorders  0.005001\n",
              "13     50 to 69                               Behavioral disorders  0.002337\n",
              "14  70 or Older                               Behavioral disorders  0.000979\n",
              "15      0 to 17                                  Bipolar disorders  0.216875\n",
              "16     18 to 29                                  Bipolar disorders  0.246043\n",
              "17     30 to 49                                  Bipolar disorders  0.245960\n",
              "18     50 to 69                                  Bipolar disorders  0.202114\n",
              "19  70 or Older                                  Bipolar disorders  0.086515\n",
              "20      0 to 17        Depression except major depressive disorder  0.161391\n",
              "21     18 to 29        Depression except major depressive disorder  0.120528\n",
              "22     30 to 49        Depression except major depressive disorder  0.092699\n",
              "23     50 to 69        Depression except major depressive disorder  0.085074\n",
              "24  70 or Older        Depression except major depressive disorder  0.054577\n",
              "25      0 to 17         Disorders of personality & impulse control  0.002852\n",
              "26     18 to 29         Disorders of personality & impulse control  0.025569\n",
              "27     30 to 49         Disorders of personality & impulse control  0.015029\n",
              "28     50 to 69         Disorders of personality & impulse control  0.007155\n",
              "29  70 or Older         Disorders of personality & impulse control  0.001713\n",
              "30      0 to 17                                   Eating disorders  0.017759\n",
              "31     18 to 29                                   Eating disorders  0.004322\n",
              "32     30 to 49                                   Eating disorders  0.001737\n",
              "33     50 to 69                                   Eating disorders  0.000791\n",
              "34  70 or Older                                   Eating disorders  0.000979\n",
              "35      0 to 17  Major depressive disorders & other/unspecified...  0.280732\n",
              "36     18 to 29  Major depressive disorders & other/unspecified...  0.213858\n",
              "37     30 to 49  Major depressive disorders & other/unspecified...  0.185845\n",
              "38     50 to 69  Major depressive disorders & other/unspecified...  0.213549\n",
              "39  70 or Older  Major depressive disorders & other/unspecified...  0.178781\n",
              "40      0 to 17          Mental illness diagnosis w O.R. procedure  0.002760\n",
              "41     18 to 29          Mental illness diagnosis w O.R. procedure  0.004389\n",
              "42     30 to 49          Mental illness diagnosis w O.R. procedure  0.004290\n",
              "43     50 to 69          Mental illness diagnosis w O.R. procedure  0.003308\n",
              "44  70 or Older          Mental illness diagnosis w O.R. procedure  0.005629\n",
              "45      0 to 17                 Organic mental health disturbances  0.023923\n",
              "46     18 to 29                 Organic mental health disturbances  0.008246\n",
              "47     30 to 49                 Organic mental health disturbances  0.004580\n",
              "48     50 to 69                 Organic mental health disturbances  0.024055\n",
              "49  70 or Older                 Organic mental health disturbances  0.445423\n",
              "50      0 to 17                      Other mental health disorders  0.014814\n",
              "51     18 to 29                      Other mental health disorders  0.003957\n",
              "52     30 to 49                      Other mental health disorders  0.006817\n",
              "53     50 to 69                      Other mental health disorders  0.010248\n",
              "54  70 or Older                      Other mental health disorders  0.021782\n",
              "55      0 to 17                                      Schizophrenia  0.022727\n",
              "56     18 to 29                                      Schizophrenia  0.288702\n",
              "57     30 to 49                                      Schizophrenia  0.380218\n",
              "58     50 to 69                                      Schizophrenia  0.400058\n",
              "59  70 or Older                                      Schizophrenia  0.135218"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 23
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "XAQZK7rmM0at",
        "colab_type": "code",
        "outputId": "6760176a-0c7d-485b-d810-5748b5d2465e",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 816
        }
      },
      "source": [
        "# Graph using Plotly\n",
        "\n",
        "import plotly.express as px\n",
        "\n",
        "# Set x and y values, grouped by color\n",
        "# Set title\n",
        "# Set figure size\n",
        "# Set y-axis label\n",
        "# Set template style\n",
        "\n",
        "fig2 = px.line(mental_age_tidy, x= 'Age Group', y= 'value', color= 'APR DRG Description',\n",
        "              title= '<b>How Mental Health Admissions Vary With Age<b>',\n",
        "              width= 830, height= 800,\n",
        "              labels= {'value': 'Percent of Mental Health Admissions By Age Group'},\n",
        "              template= 'plotly_white'\n",
        "              )\n",
        "\n",
        "\n",
        "# Update layout\n",
        "# Update title location\n",
        "# Update font size\n",
        "# Update legend location\n",
        "# Update axis ticks and labels\n",
        "# Update subtitle\n",
        "# Update legend title \n",
        "\n",
        "fig2.update_layout(\n",
        "    title= {'y': .93, 'x': 0.5},\n",
        "    title_font_size= 20,\n",
        "    font= dict(size= 12),\n",
        "    legend= dict(x=0, y= -0.8),\n",
        "    yaxis= dict(\n",
        "        tickvals= [0, 0.05, 0.1, 0.15, 0.2, 0.25, 0.3, 0.35, 0.4, 0.45],\n",
        "        ticktext= ['0','5', '10', '15', '20', '25', '30', '35', '40', '45%']),\n",
        "    annotations= [dict(x= -0.08, y= 1.07, showarrow= False, xref= 'paper', yref= 'paper', \n",
        "                       text= '<i>Mental health disorders as a percent of total mental health hospital admissions by age group in the state of New York in 2017<i>'), \n",
        "                  dict(x= 0.045, y= -.18, showarrow= False, xref= 'paper', yref= 'paper', \n",
        "                       text= '<b>Mental Health Disorders<b>: <i>Click to filter<i>')]\n",
        ")\n",
        "\n",
        "# Change Color\n",
        "# Two of the colors are repeated\n",
        "fig2['data'][11]['line']['color']=\"black\"\n",
        "fig2['data'][10]['line']['color']=\"purple\"\n",
        "\n",
        "#Change legend names\n",
        "fig2.for_each_trace(lambda t: t.update(name=t.name.split(\"=\")[1]))\n",
        "\n",
        "fig2.show()"
      ],
      "execution_count": 0,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/html": [
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              "                        {\"responsive\": true}\n",
              "                    ).then(function(){\n",
              "                            \n",
              "var gd = document.getElementById('253829f0-0fdf-4ac5-bea0-64b531f0f696');\n",
              "var x = new MutationObserver(function (mutations, observer) {{\n",
              "        var display = window.getComputedStyle(gd).display;\n",
              "        if (!display || display === 'none') {{\n",
              "            console.log([gd, 'removed!']);\n",
              "            Plotly.purge(gd);\n",
              "            observer.disconnect();\n",
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              "}});\n",
              "\n",
              "// Listen for the removal of the full notebook cells\n",
              "var notebookContainer = gd.closest('#notebook-container');\n",
              "if (notebookContainer) {{\n",
              "    x.observe(notebookContainer, {childList: true});\n",
              "}}\n",
              "\n",
              "// Listen for the clearing of the current output cell\n",
              "var outputEl = gd.closest('.output');\n",
              "if (outputEl) {{\n",
              "    x.observe(outputEl, {childList: true});\n",
              "}}\n",
              "\n",
              "                        })\n",
              "                };\n",
              "                \n",
              "            </script>\n",
              "        </div>\n",
              "</body>\n",
              "</html>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "FmWyEa1uM0hw",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "# Save interactive Plotly graph as html\n",
        "\n",
        "import plotly.io as pio\n",
        "pio.write_html(fig2, file= 'index.html', auto_open= True)"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "fdQYZrMK2yXU",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "# Download graph to local computer \n",
        "\n",
        "files.download('index.html')"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "zqdas_7n6LHl",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        ""
      ],
      "execution_count": 0,
      "outputs": []
    }
  ]
}