EDA.ipynb

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  },
  "cells": [
    {
      "cell_type": "code",
      "metadata": {
        "id": "_L0W4TiCa_AP"
      },
      "source": [
        "import numpy as np  \n",
        "import pandas as pd  \n",
        "import seaborn as sns\n",
        "import plotly.express as px\n",
        "import matplotlib.pyplot as plt\n",
        "import plotly.graph_objects as go\n",
        "import ipywidgets as widgets\n",
        "from ipywidgets import interact, interact_manual"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "mdBE2zgXbUaP",
        "outputId": "d65850b3-f424-4e06-f423-b8ea4f906125"
      },
      "source": [
        "from google.colab import drive\n",
        "drive.mount('/content/drive')"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Mounted at /content/drive\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 916
        },
        "id": "vgjHjbBBbeKj",
        "outputId": "1211b8bd-fd25-4ffd-ed43-c9e4ab7f5ec2"
      },
      "source": [
        "data=pd.read_csv('/content/drive/MyDrive/BigData/crime1-p.csv')\n",
        "data.info()\n",
        "data.head()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "<class 'pandas.core.frame.DataFrame'>\n",
            "RangeIndex: 7355291 entries, 0 to 7355290\n",
            "Data columns (total 22 columns):\n",
            " #   Column                Dtype  \n",
            "---  ------                -----  \n",
            " 0   ID                    int64  \n",
            " 1   Case Number           object \n",
            " 2   Date                  object \n",
            " 3   Block                 object \n",
            " 4   IUCR                  object \n",
            " 5   Primary Type          object \n",
            " 6   Description           object \n",
            " 7   Location Description  object \n",
            " 8   Arrest                bool   \n",
            " 9   Domestic              bool   \n",
            " 10  Beat                  int64  \n",
            " 11  District              float64\n",
            " 12  Ward                  float64\n",
            " 13  Community Area        float64\n",
            " 14  FBI Code              object \n",
            " 15  X Coordinate          float64\n",
            " 16  Y Coordinate          float64\n",
            " 17  Year                  int64  \n",
            " 18  Updated On            object \n",
            " 19  Latitude              float64\n",
            " 20  Longitude             float64\n",
            " 21  Location              object \n",
            "dtypes: bool(2), float64(7), int64(3), object(10)\n",
            "memory usage: 1.1+ GB\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
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              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>ID</th>\n",
              "      <th>Case Number</th>\n",
              "      <th>Date</th>\n",
              "      <th>Block</th>\n",
              "      <th>IUCR</th>\n",
              "      <th>Primary Type</th>\n",
              "      <th>Description</th>\n",
              "      <th>Location Description</th>\n",
              "      <th>Arrest</th>\n",
              "      <th>Domestic</th>\n",
              "      <th>Beat</th>\n",
              "      <th>District</th>\n",
              "      <th>Ward</th>\n",
              "      <th>Community Area</th>\n",
              "      <th>FBI Code</th>\n",
              "      <th>X Coordinate</th>\n",
              "      <th>Y Coordinate</th>\n",
              "      <th>Year</th>\n",
              "      <th>Updated On</th>\n",
              "      <th>Latitude</th>\n",
              "      <th>Longitude</th>\n",
              "      <th>Location</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>10224738</td>\n",
              "      <td>HY411648</td>\n",
              "      <td>09/05/2015 01:30:00 PM</td>\n",
              "      <td>043XX S WOOD ST</td>\n",
              "      <td>0486</td>\n",
              "      <td>BATTERY</td>\n",
              "      <td>DOMESTIC BATTERY SIMPLE</td>\n",
              "      <td>RESIDENCE</td>\n",
              "      <td>False</td>\n",
              "      <td>True</td>\n",
              "      <td>924</td>\n",
              "      <td>9.0</td>\n",
              "      <td>12.0</td>\n",
              "      <td>61.0</td>\n",
              "      <td>08B</td>\n",
              "      <td>1165074.0</td>\n",
              "      <td>1875917.0</td>\n",
              "      <td>2015</td>\n",
              "      <td>02/10/2018 03:50:01 PM</td>\n",
              "      <td>41.815117</td>\n",
              "      <td>-87.670000</td>\n",
              "      <td>(41.815117282, -87.669999562)</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>10224739</td>\n",
              "      <td>HY411615</td>\n",
              "      <td>09/04/2015 11:30:00 AM</td>\n",
              "      <td>008XX N CENTRAL AVE</td>\n",
              "      <td>0870</td>\n",
              "      <td>THEFT</td>\n",
              "      <td>POCKET-PICKING</td>\n",
              "      <td>CTA BUS</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>1511</td>\n",
              "      <td>15.0</td>\n",
              "      <td>29.0</td>\n",
              "      <td>25.0</td>\n",
              "      <td>06</td>\n",
              "      <td>1138875.0</td>\n",
              "      <td>1904869.0</td>\n",
              "      <td>2015</td>\n",
              "      <td>02/10/2018 03:50:01 PM</td>\n",
              "      <td>41.895080</td>\n",
              "      <td>-87.765400</td>\n",
              "      <td>(41.895080471, -87.765400451)</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>11646166</td>\n",
              "      <td>JC213529</td>\n",
              "      <td>09/01/2018 12:01:00 AM</td>\n",
              "      <td>082XX S INGLESIDE AVE</td>\n",
              "      <td>0810</td>\n",
              "      <td>THEFT</td>\n",
              "      <td>OVER $500</td>\n",
              "      <td>RESIDENCE</td>\n",
              "      <td>False</td>\n",
              "      <td>True</td>\n",
              "      <td>631</td>\n",
              "      <td>6.0</td>\n",
              "      <td>8.0</td>\n",
              "      <td>44.0</td>\n",
              "      <td>06</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>2018</td>\n",
              "      <td>04/06/2019 04:04:43 PM</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>10224740</td>\n",
              "      <td>HY411595</td>\n",
              "      <td>09/05/2015 12:45:00 PM</td>\n",
              "      <td>035XX W BARRY AVE</td>\n",
              "      <td>2023</td>\n",
              "      <td>NARCOTICS</td>\n",
              "      <td>POSS: HEROIN(BRN/TAN)</td>\n",
              "      <td>SIDEWALK</td>\n",
              "      <td>True</td>\n",
              "      <td>False</td>\n",
              "      <td>1412</td>\n",
              "      <td>14.0</td>\n",
              "      <td>35.0</td>\n",
              "      <td>21.0</td>\n",
              "      <td>18</td>\n",
              "      <td>1152037.0</td>\n",
              "      <td>1920384.0</td>\n",
              "      <td>2015</td>\n",
              "      <td>02/10/2018 03:50:01 PM</td>\n",
              "      <td>41.937406</td>\n",
              "      <td>-87.716650</td>\n",
              "      <td>(41.937405765, -87.716649687)</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>10224741</td>\n",
              "      <td>HY411610</td>\n",
              "      <td>09/05/2015 01:00:00 PM</td>\n",
              "      <td>0000X N LARAMIE AVE</td>\n",
              "      <td>0560</td>\n",
              "      <td>ASSAULT</td>\n",
              "      <td>SIMPLE</td>\n",
              "      <td>APARTMENT</td>\n",
              "      <td>False</td>\n",
              "      <td>True</td>\n",
              "      <td>1522</td>\n",
              "      <td>15.0</td>\n",
              "      <td>28.0</td>\n",
              "      <td>25.0</td>\n",
              "      <td>08A</td>\n",
              "      <td>1141706.0</td>\n",
              "      <td>1900086.0</td>\n",
              "      <td>2015</td>\n",
              "      <td>02/10/2018 03:50:01 PM</td>\n",
              "      <td>41.881903</td>\n",
              "      <td>-87.755121</td>\n",
              "      <td>(41.881903443, -87.755121152)</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "         ID Case Number  ...  Longitude                       Location\n",
              "0  10224738    HY411648  ... -87.670000  (41.815117282, -87.669999562)\n",
              "1  10224739    HY411615  ... -87.765400  (41.895080471, -87.765400451)\n",
              "2  11646166    JC213529  ...        NaN                            NaN\n",
              "3  10224740    HY411595  ... -87.716650  (41.937405765, -87.716649687)\n",
              "4  10224741    HY411610  ... -87.755121  (41.881903443, -87.755121152)\n",
              "\n",
              "[5 rows x 22 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 3
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "VPWSUtd3yoBY",
        "outputId": "40e859d5-d15a-45cc-e273-6ba28f5cd796"
      },
      "source": [
        "data.isnull().sum()/ len(data) * 100"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "ID                      0.000000\n",
              "Case Number             0.000054\n",
              "Date                    0.000000\n",
              "Block                   0.000000\n",
              "IUCR                    0.000000\n",
              "Primary Type            0.000000\n",
              "Description             0.000000\n",
              "Location Description    0.113578\n",
              "Arrest                  0.000000\n",
              "Domestic                0.000000\n",
              "Beat                    0.000000\n",
              "District                0.000639\n",
              "Ward                    8.359125\n",
              "Community Area          8.340703\n",
              "FBI Code                0.000000\n",
              "X Coordinate            0.995433\n",
              "Y Coordinate            0.995433\n",
              "Year                    0.000000\n",
              "Updated On              0.000000\n",
              "Latitude                0.995433\n",
              "Longitude               0.995433\n",
              "Location                0.995433\n",
              "dtype: float64"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 6
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "DI8pOHTzvkbw"
      },
      "source": [
        "#plt.figure(figsize=(10,7))\n",
        "#sns.heatmap(data.isnull(),cbar =False, cmap = 'viridis')"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "LhiwuAMxdMso"
      },
      "source": [
        "data=data.dropna()"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "jBZJ9SWA5WjB"
      },
      "source": [
        "# =====================================================================\n",
        "# =====================================================================\n",
        "# ====================================================================="
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "eZ-w9upD-2yq"
      },
      "source": [
        "# Defining plot_counts"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "cWEi22yj5-NX"
      },
      "source": [
        "def plot_counts(serie, title):\n",
        "    df = pd.DataFrame(serie.value_counts()[:15])\n",
        "    df.columns = [\"Freq\"]\n",
        "    df[\"Type\"] = df.index\n",
        "    fig = px.bar(df, y=\"Freq\", x=\"Type\", text=\"Freq\", color=\"Freq\", color_continuous_scale=px.colors.sequential.OrRd)\n",
        "    fig.update_traces(texttemplate=\"%{text:.2s}\", textposition=\"outside\")\n",
        "    #fig.update_layout(uniformtext_minsize=8, uniformtext_mode=\"hide\")\n",
        "    fig.update_layout(title_text=title)\n",
        "    fig.show()\n"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "uJzgn5Jo4h7R"
      },
      "source": [
        "#Frequency by Primary Type"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 542
        },
        "id": "bbmHJRmLfK6k",
        "outputId": "4db89432-d01a-41ef-9e58-54d876aba4bf"
      },
      "source": [
        "plot_counts(data[\"Primary Type\"], \"Kind of Crimes\")"
      ],
      "execution_count": null,
      "outputs": [
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        "# Frequency by Location"
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        "outputId": "4dd39627-f428-441f-f637-a227adf2b9f7"
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        "# Frequency by Description of Crimes\n",
        "\n",
        "---\n",
        "\n"
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{\"anchor\": \"x\", \"domain\": [0.0, 1.0], \"title\": {\"text\": \"Freq\"}}},\n",
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          },
          "metadata": {
            "tags": []
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      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "MrMG-wXX-ugE"
      },
      "source": [
        "# =====================================================================\n",
        "# =====================================================================\n",
        "# ====================================================================="
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "dFQBdSziC-56"
      },
      "source": [
        "# Chances of someone getting arrested crimewise "
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 816
        },
        "id": "gq4xt-IW_s2B",
        "outputId": "fcc015c4-fc69-46ca-fde5-0bd9fc12d1fa"
      },
      "source": [
        "aux = data.groupby('Primary Type')['Arrest'].mean().reset_index()\n",
        "aux['Arrest (%)'] = aux['Arrest'].round(4)*100\n",
        "aux.sort_values('Arrest', inplace=True)\n",
        "fig = px.bar(\n",
        "    aux,\n",
        "    orientation='h',\n",
        "    x=\"Arrest (%)\",\n",
        "    y=\"Primary Type\",\n",
        "    color=\"Arrest (%)\",\n",
        "    text=\"Arrest (%)\",\n",
        "    height=800,\n",
        "    width=1200,\n",
        "    color_continuous_scale=px.colors.sequential.OrRd\n",
        "\n",
        ")\n",
        "fig.update_traces(texttemplate=\"%{text:.4s}\", textposition=\"outside\")\n",
        "fig.update_layout(title_text=\"Arrested Rate in % per Type Crime in Chicago.\")\n",
        "\n",
        "fig.show()\n"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
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\"gridcolor\": \"white\", \"gridwidth\": 2, \"linecolor\": \"white\", \"showbackground\": true, \"ticks\": \"\", \"zerolinecolor\": \"white\"}}, \"shapedefaults\": {\"line\": {\"color\": \"#2a3f5f\"}}, \"ternary\": {\"aaxis\": {\"gridcolor\": \"white\", \"linecolor\": \"white\", \"ticks\": \"\"}, \"baxis\": {\"gridcolor\": \"white\", \"linecolor\": \"white\", \"ticks\": \"\"}, \"bgcolor\": \"#E5ECF6\", \"caxis\": {\"gridcolor\": \"white\", \"linecolor\": \"white\", \"ticks\": \"\"}}, \"title\": {\"x\": 0.05}, \"xaxis\": {\"automargin\": true, \"gridcolor\": \"white\", \"linecolor\": \"white\", \"ticks\": \"\", \"title\": {\"standoff\": 15}, \"zerolinecolor\": \"white\", \"zerolinewidth\": 2}, \"yaxis\": {\"automargin\": true, \"gridcolor\": \"white\", \"linecolor\": \"white\", \"ticks\": \"\", \"title\": {\"standoff\": 15}, \"zerolinecolor\": \"white\", \"zerolinewidth\": 2}}}, \"title\": {\"text\": \"Arrested Rate in % per Type Crime in Chicago.\"}, \"width\": 1200, \"xaxis\": {\"anchor\": \"y\", \"domain\": [0.0, 1.0], \"title\": {\"text\": \"Arrest (%)\"}}, \"yaxis\": {\"anchor\": \"x\", \"domain\": [0.0, 1.0], \"title\": {\"text\": \"Primary Type\"}}},\n",
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            ]
          },
          "metadata": {
            "tags": []
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        }
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    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
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        },
        "id": "d_DvgpLMQ_J5",
        "outputId": "67913ddb-a069-42da-905f-158952fb7c64"
      },
      "source": [
        "aux = data.groupby('Primary Type')['Arrest'].mean()#.reset_index()\n",
        "aux"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Primary Type\n",
              "ARSON                                0.121374\n",
              "ASSAULT                              0.221471\n",
              "BATTERY                              0.224510\n",
              "BURGLARY                             0.056791\n",
              "CONCEALED CARRY LICENSE VIOLATION    0.969374\n",
              "CRIM SEXUAL ASSAULT                  0.149830\n",
              "CRIMINAL DAMAGE                      0.068112\n",
              "CRIMINAL SEXUAL ASSAULT              0.075084\n",
              "CRIMINAL TRESPASS                    0.710820\n",
              "DECEPTIVE PRACTICE                   0.141961\n",
              "GAMBLING                             0.993203\n",
              "HOMICIDE                             0.466407\n",
              "HUMAN TRAFFICKING                    0.088235\n",
              "INTERFERENCE WITH PUBLIC OFFICER     0.926385\n",
              "INTIMIDATION                         0.155989\n",
              "KIDNAPPING                           0.104260\n",
              "LIQUOR LAW VIOLATION                 0.990734\n",
              "MOTOR VEHICLE THEFT                  0.083870\n",
              "NARCOTICS                            0.994178\n",
              "NON - CRIMINAL                       0.157895\n",
              "NON-CRIMINAL                         0.060606\n",
              "NON-CRIMINAL (SUBJECT SPECIFIED)     0.333333\n",
              "OBSCENITY                            0.804412\n",
              "OFFENSE INVOLVING CHILDREN           0.195854\n",
              "OTHER NARCOTIC VIOLATION             0.687500\n",
              "OTHER OFFENSE                        0.178639\n",
              "PROSTITUTION                         0.995732\n",
              "PUBLIC INDECENCY                     0.994286\n",
              "PUBLIC PEACE VIOLATION               0.657742\n",
              "RITUALISM                            0.133333\n",
              "ROBBERY                              0.095383\n",
              "SEX OFFENSE                          0.284358\n",
              "STALKING                             0.146083\n",
              "THEFT                                0.113519\n",
              "WEAPONS VIOLATION                    0.762068\n",
              "Name: Arrest, dtype: float64"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 26
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "Ac3g3OwARAFC"
      },
      "source": [
        ""
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
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          "referenced_widgets": [
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      "source": [
        "@interact\n",
        "def describe(DISTRICT=list(sorted(data['District'].unique()))):\n",
        "    p2=data[data['District']==DISTRICT]['Block']\n",
        "    global t1\n",
        "    t1=DISTRICT\n",
        "    plt.figure(figsize=(10,10))\n",
        "\n",
        "    sns.countplot(y=p2,data=data,order = p2.value_counts().iloc[:30].index,palette='autumn')\n",
        "    plt.title('Total crimes in District  ')\n",
        "    plt.show()\n",
        "   "
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "application/vnd.jupyter.widget-view+json": {
              "model_id": "abc4868c90b34ff9860db97b5300c636",
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              "interactive(children=(Dropdown(description='DISTRICT', options=(1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0, 1…"
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        "outputId": "4ef9fd1b-f3aa-4d9f-8cde-fad725605681"
      },
      "source": [
        "@interact\n",
        "def describe(column=list(sorted(data[data['District']==t1]['Block'].unique()))):\n",
        "    p3=data[data['Block']==column]['Location Description']\n",
        "    plt.figure(figsize=(10,10))\n",
        "    sns.countplot(y=p3,data=data,order = p3.value_counts().iloc[:30].index,palette='autumn')\n",
        "    plt.title('total crimes')\n",
        "    plt.show()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "application/vnd.jupyter.widget-view+json": {
              "model_id": "21f9d14b8ec3418890f6dc51b3237957",
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              "interactive(children=(Dropdown(description='column', options=('0000X E 11TH ST', '0000X E 13TH ST', '0000X E 1…"
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}