US_Crime_Rates.ipynb

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      "name": "US Crime Rates.ipynb",
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      "source": [
        "#**EX1 - United States - Crime Rates - 1960 - 2014**\n",
        "##**Assignment 1**\n",
        "> **By - Aditi Chatterjee**\n"
      ],
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      "cell_type": "markdown",
      "source": [
        "##Introduction:\n",
        "This time you will create a data\n",
        "\n",
        "Special thanks to: https://github.com/justmarkham for sharing the dataset and materials."
      ],
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      "cell_type": "markdown",
      "source": [
        "##Step 1. Import the necessary libraries"
      ],
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      "source": [
        "import pandas as pd\n",
        "import numpy as np"
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "##Step 2. Import the dataset from this [address.](https://raw.githubusercontent.com/a-forty-two/COG_GN22CDBDS001_MARCH_22/main/US_Crime_Rates_1960_2014.csv)\n"
      ],
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      "source": [
        "##Step 3. Assign it to a variable called crime."
      ],
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      }
    },
    {
      "cell_type": "code",
      "source": [
        "crime = pd.read_csv('https://raw.githubusercontent.com/a-forty-two/COG_GN22CDBDS001_MARCH_22/main/US_Crime_Rates_1960_2014.csv', low_memory=False)\n",
        "crime.head()"
      ],
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              "   Year  Population    Total  Violent  Property  Murder  Forcible_Rape  \\\n",
              "0  1960   179323175  3384200   288460   3095700    9110          17190   \n",
              "1  1961   182992000  3488000   289390   3198600    8740          17220   \n",
              "2  1962   185771000  3752200   301510   3450700    8530          17550   \n",
              "3  1963   188483000  4109500   316970   3792500    8640          17650   \n",
              "4  1964   191141000  4564600   364220   4200400    9360          21420   \n",
              "\n",
              "   Robbery  Aggravated_assault  Burglary  Larceny_Theft  Vehicle_Theft  \n",
              "0   107840              154320    912100        1855400         328200  \n",
              "1   106670              156760    949600        1913000         336000  \n",
              "2   110860              164570    994300        2089600         366800  \n",
              "3   116470              174210   1086400        2297800         408300  \n",
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              "      <td>185771000</td>\n",
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              "      <td>3450700</td>\n",
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              "      <th>3</th>\n",
              "      <td>1963</td>\n",
              "      <td>188483000</td>\n",
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              "      <td>316970</td>\n",
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              "      <th>4</th>\n",
              "      <td>1964</td>\n",
              "      <td>191141000</td>\n",
              "      <td>4564600</td>\n",
              "      <td>364220</td>\n",
              "      <td>4200400</td>\n",
              "      <td>9360</td>\n",
              "      <td>21420</td>\n",
              "      <td>130390</td>\n",
              "      <td>203050</td>\n",
              "      <td>1213200</td>\n",
              "      <td>2514400</td>\n",
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      "source": [
        "##Step 4. What is the type of the columns?"
      ],
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    },
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      "cell_type": "code",
      "source": [
        "crime.dtypes"
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        "id": "psXusufkP2gG",
        "outputId": "68a177c5-20b3-4c3c-c95b-e8012e927530"
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            "text/plain": [
              "Year                  int64\n",
              "Population            int64\n",
              "Total                 int64\n",
              "Violent               int64\n",
              "Property              int64\n",
              "Murder                int64\n",
              "Forcible_Rape         int64\n",
              "Robbery               int64\n",
              "Aggravated_assault    int64\n",
              "Burglary              int64\n",
              "Larceny_Theft         int64\n",
              "Vehicle_Theft         int64\n",
              "dtype: object"
            ]
          },
          "metadata": {},
          "execution_count": 16
        }
      ]
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      "cell_type": "markdown",
      "source": [
        "##Step 5. Convert the type of the column Year to datetime64\n"
      ],
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        "id": "bwT-2k-SQOcH"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "crime['Year'] = pd.to_datetime(crime['Year'], format=('%Y'))\n",
        "crime.head()"
      ],
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              "        Year  Population    Total  Violent  Property  Murder  Forcible_Rape  \\\n",
              "0 1960-01-01   179323175  3384200   288460   3095700    9110          17190   \n",
              "1 1961-01-01   182992000  3488000   289390   3198600    8740          17220   \n",
              "2 1962-01-01   185771000  3752200   301510   3450700    8530          17550   \n",
              "3 1963-01-01   188483000  4109500   316970   3792500    8640          17650   \n",
              "4 1964-01-01   191141000  4564600   364220   4200400    9360          21420   \n",
              "\n",
              "   Robbery  Aggravated_assault  Burglary  Larceny_Theft  Vehicle_Theft  \n",
              "0   107840              154320    912100        1855400         328200  \n",
              "1   106670              156760    949600        1913000         336000  \n",
              "2   110860              164570    994300        2089600         366800  \n",
              "3   116470              174210   1086400        2297800         408300  \n",
              "4   130390              203050   1213200        2514400         472800  "
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              "      <td>1964-01-01</td>\n",
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    },
    {
      "cell_type": "code",
      "source": [
        "crime.tail()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 206
        },
        "id": "dCbojxCuZzf5",
        "outputId": "e8f76681-41df-42c3-fdcc-91fadb57d558"
      },
      "execution_count": 18,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "         Year  Population     Total  Violent  Property  Murder  Forcible_Rape  \\\n",
              "50 2010-01-01   309330219  10363873  1251248   9112625   14772          85593   \n",
              "51 2011-01-01   311587816  10258774  1206031   9052743   14661          84175   \n",
              "52 2012-01-01   313873685  10219059  1217067   9001992   14866          85141   \n",
              "53 2013-01-01   316497531   9850445  1199684   8650761   14319          82109   \n",
              "54 2014-01-01   318857056   9475816  1197987   8277829   14249          84041   \n",
              "\n",
              "    Robbery  Aggravated_assault  Burglary  Larceny_Theft  Vehicle_Theft  \n",
              "50   369089              781844   2168457        6204601         739565  \n",
              "51   354772              752423   2185140        6151095         716508  \n",
              "52   355051              762009   2109932        6168874         723186  \n",
              "53   345095              726575   1931835        6018632         700294  \n",
              "54   325802              741291   1729806        5858496         689527  "
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    {
      "cell_type": "code",
      "source": [
        "crime['Year'].dtypes"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "ZgIvXG9TWV9b",
        "outputId": "1fc9d800-6b79-4740-afc8-99da4ef047c4"
      },
      "execution_count": 19,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "dtype('<M8[ns]')"
            ]
          },
          "metadata": {},
          "execution_count": 19
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "##Step 6. Set the Year column as the index of the dataframe"
      ],
      "metadata": {
        "id": "Tkqo6igmSPeY"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "crime.set_index('Year', drop=True, inplace=True)"
      ],
      "metadata": {
        "id": "LufrCv5dQgmw"
      },
      "execution_count": 20,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "crime.head()"
      ],
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        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 238
        },
        "id": "6q_JMKddYXDB",
        "outputId": "10f37272-c8db-4228-e5c7-5f6450c58120"
      },
      "execution_count": 21,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "            Population    Total  Violent  Property  Murder  Forcible_Rape  \\\n",
              "Year                                                                        \n",
              "1960-01-01   179323175  3384200   288460   3095700    9110          17190   \n",
              "1961-01-01   182992000  3488000   289390   3198600    8740          17220   \n",
              "1962-01-01   185771000  3752200   301510   3450700    8530          17550   \n",
              "1963-01-01   188483000  4109500   316970   3792500    8640          17650   \n",
              "1964-01-01   191141000  4564600   364220   4200400    9360          21420   \n",
              "\n",
              "            Robbery  Aggravated_assault  Burglary  Larceny_Theft  \\\n",
              "Year                                                               \n",
              "1960-01-01   107840              154320    912100        1855400   \n",
              "1961-01-01   106670              156760    949600        1913000   \n",
              "1962-01-01   110860              164570    994300        2089600   \n",
              "1963-01-01   116470              174210   1086400        2297800   \n",
              "1964-01-01   130390              203050   1213200        2514400   \n",
              "\n",
              "            Vehicle_Theft  \n",
              "Year                       \n",
              "1960-01-01         328200  \n",
              "1961-01-01         336000  \n",
              "1962-01-01         366800  \n",
              "1963-01-01         408300  \n",
              "1964-01-01         472800  "
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              "\n",
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              "                                                     [key], {});\n",
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              "\n",
              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "            + ' to learn more about interactive tables.';\n",
              "          element.innerHTML = '';\n",
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              "          await google.colab.output.renderOutput(dataTable, element);\n",
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              "  </div>\n",
              "  "
            ]
          },
          "metadata": {},
          "execution_count": 21
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "crime.index"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "YhlTlxJxZ5nx",
        "outputId": "7054ce96-2322-4c35-f0e1-ebd2f7664a8a"
      },
      "execution_count": 22,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "DatetimeIndex(['1960-01-01', '1961-01-01', '1962-01-01', '1963-01-01',\n",
              "               '1964-01-01', '1965-01-01', '1966-01-01', '1967-01-01',\n",
              "               '1968-01-01', '1969-01-01', '1970-01-01', '1971-01-01',\n",
              "               '1972-01-01', '1973-01-01', '1974-01-01', '1975-01-01',\n",
              "               '1976-01-01', '1977-01-01', '1978-01-01', '1979-01-01',\n",
              "               '1980-01-01', '1981-01-01', '1982-01-01', '1983-01-01',\n",
              "               '1984-01-01', '1985-01-01', '1986-01-01', '1987-01-01',\n",
              "               '1988-01-01', '1989-01-01', '1990-01-01', '1991-01-01',\n",
              "               '1992-01-01', '1993-01-01', '1994-01-01', '1995-01-01',\n",
              "               '1996-01-01', '1997-01-01', '1998-01-01', '1999-01-01',\n",
              "               '2000-01-01', '2001-01-01', '2002-01-01', '2003-01-01',\n",
              "               '2004-01-01', '2005-01-01', '2006-01-01', '2007-01-01',\n",
              "               '2008-01-01', '2009-01-01', '2010-01-01', '2011-01-01',\n",
              "               '2012-01-01', '2013-01-01', '2014-01-01'],\n",
              "              dtype='datetime64[ns]', name='Year', freq=None)"
            ]
          },
          "metadata": {},
          "execution_count": 22
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "##Step 7. Delete the Total column"
      ],
      "metadata": {
        "id": "PyvsyqAwSY2B"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "del crime['Total']\n",
        "crime.head()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 238
        },
        "id": "_H1_sgKASML0",
        "outputId": "a0683d0b-d28c-49c7-fd98-ea56e5db34a8"
      },
      "execution_count": 23,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "            Population  Violent  Property  Murder  Forcible_Rape  Robbery  \\\n",
              "Year                                                                        \n",
              "1960-01-01   179323175   288460   3095700    9110          17190   107840   \n",
              "1961-01-01   182992000   289390   3198600    8740          17220   106670   \n",
              "1962-01-01   185771000   301510   3450700    8530          17550   110860   \n",
              "1963-01-01   188483000   316970   3792500    8640          17650   116470   \n",
              "1964-01-01   191141000   364220   4200400    9360          21420   130390   \n",
              "\n",
              "            Aggravated_assault  Burglary  Larceny_Theft  Vehicle_Theft  \n",
              "Year                                                                    \n",
              "1960-01-01              154320    912100        1855400         328200  \n",
              "1961-01-01              156760    949600        1913000         336000  \n",
              "1962-01-01              164570    994300        2089600         366800  \n",
              "1963-01-01              174210   1086400        2297800         408300  \n",
              "1964-01-01              203050   1213200        2514400         472800  "
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              "      <td>9360</td>\n",
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              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                     [key], {});\n",
              "          if (!dataTable) return;\n",
              "\n",
              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "            + ' to learn more about interactive tables.';\n",
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              "  "
            ]
          },
          "metadata": {},
          "execution_count": 23
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "##Step 8. Group the year by decades and sum the values\n",
        "Pay attention to the Population column number, summing this column is a mistake"
      ],
      "metadata": {
        "id": "ZO-8Xh8dSff7"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "type(crime.index)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "onk0HEs1aHGP",
        "outputId": "02fd3d25-806b-4c88-d21f-9005cebe34b4"
      },
      "execution_count": 24,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "pandas.core.indexes.datetimes.DatetimeIndex"
            ]
          },
          "metadata": {},
          "execution_count": 24
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "## resampling this time-series data based on groups of 10 years (DECADES)\n",
        "\n",
        "# 10AS -> 10 years (A), from starting date i.e. 1960-01-01 (S)\n",
        "crimes_decade = crime.resample('10AS').sum()\n",
        "\n",
        "# Use resample to get the maximum value of the \"Population\" column, \n",
        "#i.e., the population at the end of every decade serves as the population for that decade\n",
        "crimes_decade['Population'] = crime['Population'].resample('10AS').max()\n",
        "crimes_decade"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 269
        },
        "id": "1TxZXSyYScmA",
        "outputId": "12fb8b87-3ba2-4d94-e10e-c4e639f96b38"
      },
      "execution_count": 25,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "            Population   Violent   Property  Murder  Forcible_Rape  Robbery  \\\n",
              "Year                                                                          \n",
              "1960-01-01   201385000   4134930   45160900  106180         236720  1633510   \n",
              "1970-01-01   220099000   9607930   91383800  192230         554570  4159020   \n",
              "1980-01-01   248239000  14074328  117048900  206439         865639  5383109   \n",
              "1990-01-01   272690813  17527048  119053499  211664         998827  5748930   \n",
              "2000-01-01   307006550  13968056  100944369  163068         922499  4230366   \n",
              "2010-01-01   318857056   6072017   44095950   72867         421059  1749809   \n",
              "\n",
              "            Aggravated_assault  Burglary  Larceny_Theft  Vehicle_Theft  \n",
              "Year                                                                    \n",
              "1960-01-01             2158520  13321100       26547700        5292100  \n",
              "1970-01-01             4702120  28486000       53157800        9739900  \n",
              "1980-01-01             7619130  33073494       72040253       11935411  \n",
              "1990-01-01            10568963  26750015       77679366       14624418  \n",
              "2000-01-01             8652124  21565176       67970291       11412834  \n",
              "2010-01-01             3764142  10125170       30401698        3569080  "
            ],
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              "      <td>119053499</td>\n",
              "      <td>211664</td>\n",
              "      <td>998827</td>\n",
              "      <td>5748930</td>\n",
              "      <td>10568963</td>\n",
              "      <td>26750015</td>\n",
              "      <td>77679366</td>\n",
              "      <td>14624418</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2000-01-01</th>\n",
              "      <td>307006550</td>\n",
              "      <td>13968056</td>\n",
              "      <td>100944369</td>\n",
              "      <td>163068</td>\n",
              "      <td>922499</td>\n",
              "      <td>4230366</td>\n",
              "      <td>8652124</td>\n",
              "      <td>21565176</td>\n",
              "      <td>67970291</td>\n",
              "      <td>11412834</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2010-01-01</th>\n",
              "      <td>318857056</td>\n",
              "      <td>6072017</td>\n",
              "      <td>44095950</td>\n",
              "      <td>72867</td>\n",
              "      <td>421059</td>\n",
              "      <td>1749809</td>\n",
              "      <td>3764142</td>\n",
              "      <td>10125170</td>\n",
              "      <td>30401698</td>\n",
              "      <td>3569080</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>\n",
              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-c785e429-7244-4db1-9d30-deca3131fc76')\"\n",
              "              title=\"Convert this dataframe to an interactive table.\"\n",
              "              style=\"display:none;\">\n",
              "        \n",
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              "  </svg>\n",
              "      </button>\n",
              "      \n",
              "  <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\n",
              "      flex-wrap:wrap;\n",
              "      gap: 12px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert {\n",
              "      background-color: #E8F0FE;\n",
              "      border: none;\n",
              "      border-radius: 50%;\n",
              "      cursor: pointer;\n",
              "      display: none;\n",
              "      fill: #1967D2;\n",
              "      height: 32px;\n",
              "      padding: 0 0 0 0;\n",
              "      width: 32px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert:hover {\n",
              "      background-color: #E2EBFA;\n",
              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "      fill: #174EA6;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
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              "          document.querySelector('#df-c785e429-7244-4db1-9d30-deca3131fc76 button.colab-df-convert');\n",
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              "          google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "        async function convertToInteractive(key) {\n",
              "          const element = document.querySelector('#df-c785e429-7244-4db1-9d30-deca3131fc76');\n",
              "          const dataTable =\n",
              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                     [key], {});\n",
              "          if (!dataTable) return;\n",
              "\n",
              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "            + ' to learn more about interactive tables.';\n",
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              "  </div>\n",
              "  "
            ]
          },
          "metadata": {},
          "execution_count": 25
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "##Step 9. What is the most dangerous decade to live in the US?"
      ],
      "metadata": {
        "id": "a26VZQctT8hY"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "crimes_decade.idxmax(axis=0)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "jKC8hr5QS4ce",
        "outputId": "17545e96-2579-4611-e11e-d7abf3e5e6ba"
      },
      "execution_count": 26,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Population           2010-01-01\n",
              "Violent              1990-01-01\n",
              "Property             1990-01-01\n",
              "Murder               1990-01-01\n",
              "Forcible_Rape        1990-01-01\n",
              "Robbery              1990-01-01\n",
              "Aggravated_assault   1990-01-01\n",
              "Burglary             1980-01-01\n",
              "Larceny_Theft        1990-01-01\n",
              "Vehicle_Theft        1990-01-01\n",
              "dtype: datetime64[ns]"
            ]
          },
          "metadata": {},
          "execution_count": 26
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "*OBSERVATION: Based on this, we can conclude that the 90's was the most dangerous decade to live in the US.*"
      ],
      "metadata": {
        "id": "dfdl2LFigFM5"
      }
    },
    {
      "cell_type": "code",
      "source": [
        ""
      ],
      "metadata": {
        "id": "Jxrvvfazl4gW"
      },
      "execution_count": null,
      "outputs": []
    }
  ]
}