Importing_And_Reading_CSV_Files_With_Python.ipynb

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      "source": [
        "#import data\n",
        "import pandas as pd\n",
        "df = pd.read_csv(\"cities.csv\")\n",
        "df.head()"
      ],
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              "   LatD   \"LatM\"   \"LatS\"  \"NS\"   \"LonD\"   \"LonM\"   \"LonS\"  \"EW\"  \\\n",
              "0    41        5       59   \"N\"       80       39        0   \"W\"   \n",
              "1    42       52       48   \"N\"       97       23       23   \"W\"   \n",
              "2    46       35       59   \"N\"      120       30       36   \"W\"   \n",
              "3    42       16       12   \"N\"       71       48        0   \"W\"   \n",
              "4    43       37       48   \"N\"       89       46       11   \"W\"   \n",
              "\n",
              "               \"City\"  \"State\"  \n",
              "0        \"Youngstown\"       OH  \n",
              "1           \"Yankton\"       SD  \n",
              "2            \"Yakima\"       WA  \n",
              "3         \"Worcester\"       MA  \n",
              "4   \"Wisconsin Dells\"       WI  "
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          },
          "metadata": {},
          "execution_count": 9
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    {
      "cell_type": "code",
      "source": [
        "#Add a column\n",
        "df[\"City_Number\"] = 5\n",
        "print(df)"
      ],
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        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "XYluLR2N1WPJ",
        "outputId": "ba849dcb-1d5b-4af8-95dc-2af5a1b2554b"
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      "outputs": [
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          "text": [
            "     LatD   \"LatM\"   \"LatS\"  \"NS\"   \"LonD\"   \"LonM\"   \"LonS\"  \"EW\"  \\\n",
            "0      41        5       59   \"N\"       80       39        0   \"W\"   \n",
            "1      42       52       48   \"N\"       97       23       23   \"W\"   \n",
            "2      46       35       59   \"N\"      120       30       36   \"W\"   \n",
            "3      42       16       12   \"N\"       71       48        0   \"W\"   \n",
            "4      43       37       48   \"N\"       89       46       11   \"W\"   \n",
            "..    ...      ...      ...   ...      ...      ...      ...   ...   \n",
            "123    39       31       12   \"N\"      119       48       35   \"W\"   \n",
            "124    50       25       11   \"N\"      104       39        0   \"W\"   \n",
            "125    40       10       48   \"N\"      122       14       23   \"W\"   \n",
            "126    40       19       48   \"N\"       75       55       48   \"W\"   \n",
            "127    41        9       35   \"N\"       81       14       23   \"W\"   \n",
            "\n",
            "                 \"City\"  \"State\"  City_Number  \n",
            "0          \"Youngstown\"       OH            5  \n",
            "1             \"Yankton\"       SD            5  \n",
            "2              \"Yakima\"       WA            5  \n",
            "3           \"Worcester\"       MA            5  \n",
            "4     \"Wisconsin Dells\"       WI            5  \n",
            "..                  ...      ...          ...  \n",
            "123              \"Reno\"       NV            5  \n",
            "124            \"Regina\"       SA            5  \n",
            "125         \"Red Bluff\"       CA            5  \n",
            "126           \"Reading\"       PA            5  \n",
            "127           \"Ravenna\"      OH             5  \n",
            "\n",
            "[128 rows x 11 columns]\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#describe columns\n",
        "df.describe()"
      ],
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          "height": 300
        },
        "id": "C3R4VXNz2J8i",
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              "             LatD      \"LatM\"      \"LatS\"      \"LonD\"      \"LonM\"      \"LonS\"  \\\n",
              "count  128.000000  128.000000  128.000000  128.000000  128.000000  128.000000   \n",
              "mean    38.820312   30.765625   27.492188   93.250000   27.742188   26.960938   \n",
              "std      5.200596   16.426158   18.977814   15.466499   16.927937   18.727807   \n",
              "min     26.000000    1.000000    0.000000   71.000000    0.000000    0.000000   \n",
              "25%     35.000000   16.000000   11.000000   80.000000   14.000000   11.000000   \n",
              "50%     39.000000   31.000000   24.000000   89.500000   26.500000   23.500000   \n",
              "75%     42.250000   45.000000   47.000000  103.250000   40.250000   47.000000   \n",
              "max     50.000000   59.000000   59.000000  123.000000   58.000000   59.000000   \n",
              "\n",
              "       City_Number  \n",
              "count        128.0  \n",
              "mean           5.0  \n",
              "std            0.0  \n",
              "min            5.0  \n",
              "25%            5.0  \n",
              "50%            5.0  \n",
              "75%            5.0  \n",
              "max            5.0  "
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              "      <th></th>\n",
              "      <th>LatD</th>\n",
              "      <th>\"LatM\"</th>\n",
              "      <th>\"LatS\"</th>\n",
              "      <th>\"LonD\"</th>\n",
              "      <th>\"LonM\"</th>\n",
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              "      <th>count</th>\n",
              "      <td>128.000000</td>\n",
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              "      <td>128.000000</td>\n",
              "      <td>128.000000</td>\n",
              "      <td>128.000000</td>\n",
              "      <td>128.000000</td>\n",
              "      <td>128.0</td>\n",
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              "      <th>mean</th>\n",
              "      <td>38.820312</td>\n",
              "      <td>30.765625</td>\n",
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              "      <td>93.250000</td>\n",
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              "      <td>26.960938</td>\n",
              "      <td>5.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>std</th>\n",
              "      <td>5.200596</td>\n",
              "      <td>16.426158</td>\n",
              "      <td>18.977814</td>\n",
              "      <td>15.466499</td>\n",
              "      <td>16.927937</td>\n",
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              "      <td>0.0</td>\n",
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              "      <th>min</th>\n",
              "      <td>26.000000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>71.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>5.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>25%</th>\n",
              "      <td>35.000000</td>\n",
              "      <td>16.000000</td>\n",
              "      <td>11.000000</td>\n",
              "      <td>80.000000</td>\n",
              "      <td>14.000000</td>\n",
              "      <td>11.000000</td>\n",
              "      <td>5.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>50%</th>\n",
              "      <td>39.000000</td>\n",
              "      <td>31.000000</td>\n",
              "      <td>24.000000</td>\n",
              "      <td>89.500000</td>\n",
              "      <td>26.500000</td>\n",
              "      <td>23.500000</td>\n",
              "      <td>5.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>75%</th>\n",
              "      <td>42.250000</td>\n",
              "      <td>45.000000</td>\n",
              "      <td>47.000000</td>\n",
              "      <td>103.250000</td>\n",
              "      <td>40.250000</td>\n",
              "      <td>47.000000</td>\n",
              "      <td>5.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>max</th>\n",
              "      <td>50.000000</td>\n",
              "      <td>59.000000</td>\n",
              "      <td>59.000000</td>\n",
              "      <td>123.000000</td>\n",
              "      <td>58.000000</td>\n",
              "      <td>59.000000</td>\n",
              "      <td>5.0</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>\n",
              "    <div class=\"colab-df-buttons\">\n",
              "\n",
              "  <div class=\"colab-df-container\">\n",
              "    <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-27eb6e39-58e1-47cf-9d38-e42546d26a40')\"\n",
              "            title=\"Convert this dataframe to an interactive table.\"\n",
              "            style=\"display:none;\">\n",
              "\n",
              "  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\" viewBox=\"0 -960 960 960\">\n",
              "    <path d=\"M120-120v-720h720v720H120Zm60-500h600v-160H180v160Zm220 220h160v-160H400v160Zm0 220h160v-160H400v160ZM180-400h160v-160H180v160Zm440 0h160v-160H620v160ZM180-180h160v-160H180v160Zm440 0h160v-160H620v160Z\"/>\n",
              "  </svg>\n",
              "    </button>\n",
              "\n",
              "  <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\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",
              "    .colab-df-buttons div {\n",
              "      margin-bottom: 4px;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
              "      fill: #D2E3FC;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "      fill: #FFFFFF;\n",
              "    }\n",
              "  </style>\n",
              "\n",
              "    <script>\n",
              "      const buttonEl =\n",
              "        document.querySelector('#df-27eb6e39-58e1-47cf-9d38-e42546d26a40 button.colab-df-convert');\n",
              "      buttonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "      async function convertToInteractive(key) {\n",
              "        const element = document.querySelector('#df-27eb6e39-58e1-47cf-9d38-e42546d26a40');\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",
              "        element.innerHTML = '';\n",
              "        dataTable['output_type'] = 'display_data';\n",
              "        await google.colab.output.renderOutput(dataTable, element);\n",
              "        const docLink = document.createElement('div');\n",
              "        docLink.innerHTML = docLinkHtml;\n",
              "        element.appendChild(docLink);\n",
              "      }\n",
              "    </script>\n",
              "  </div>\n",
              "\n",
              "\n",
              "<div id=\"df-7cc99cb3-c998-405a-ac67-8e45c871923d\">\n",
              "  <button class=\"colab-df-quickchart\" onclick=\"quickchart('df-7cc99cb3-c998-405a-ac67-8e45c871923d')\"\n",
              "            title=\"Suggest charts.\"\n",
              "            style=\"display:none;\">\n",
              "\n",
              "<svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
              "     width=\"24px\">\n",
              "    <g>\n",
              "        <path d=\"M19 3H5c-1.1 0-2 .9-2 2v14c0 1.1.9 2 2 2h14c1.1 0 2-.9 2-2V5c0-1.1-.9-2-2-2zM9 17H7v-7h2v7zm4 0h-2V7h2v10zm4 0h-2v-4h2v4z\"/>\n",
              "    </g>\n",
              "</svg>\n",
              "  </button>\n",
              "\n",
              "<style>\n",
              "  .colab-df-quickchart {\n",
              "      --bg-color: #E8F0FE;\n",
              "      --fill-color: #1967D2;\n",
              "      --hover-bg-color: #E2EBFA;\n",
              "      --hover-fill-color: #174EA6;\n",
              "      --disabled-fill-color: #AAA;\n",
              "      --disabled-bg-color: #DDD;\n",
              "  }\n",
              "\n",
              "  [theme=dark] .colab-df-quickchart {\n",
              "      --bg-color: #3B4455;\n",
              "      --fill-color: #D2E3FC;\n",
              "      --hover-bg-color: #434B5C;\n",
              "      --hover-fill-color: #FFFFFF;\n",
              "      --disabled-bg-color: #3B4455;\n",
              "      --disabled-fill-color: #666;\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart {\n",
              "    background-color: var(--bg-color);\n",
              "    border: none;\n",
              "    border-radius: 50%;\n",
              "    cursor: pointer;\n",
              "    display: none;\n",
              "    fill: var(--fill-color);\n",
              "    height: 32px;\n",
              "    padding: 0;\n",
              "    width: 32px;\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart:hover {\n",
              "    background-color: var(--hover-bg-color);\n",
              "    box-shadow: 0 1px 2px rgba(60, 64, 67, 0.3), 0 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "    fill: var(--button-hover-fill-color);\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart-complete:disabled,\n",
              "  .colab-df-quickchart-complete:disabled:hover {\n",
              "    background-color: var(--disabled-bg-color);\n",
              "    fill: var(--disabled-fill-color);\n",
              "    box-shadow: none;\n",
              "  }\n",
              "\n",
              "  .colab-df-spinner {\n",
              "    border: 2px solid var(--fill-color);\n",
              "    border-color: transparent;\n",
              "    border-bottom-color: var(--fill-color);\n",
              "    animation:\n",
              "      spin 1s steps(1) infinite;\n",
              "  }\n",
              "\n",
              "  @keyframes spin {\n",
              "    0% {\n",
              "      border-color: transparent;\n",
              "      border-bottom-color: var(--fill-color);\n",
              "      border-left-color: var(--fill-color);\n",
              "    }\n",
              "    20% {\n",
              "      border-color: transparent;\n",
              "      border-left-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "    }\n",
              "    30% {\n",
              "      border-color: transparent;\n",
              "      border-left-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "      border-right-color: var(--fill-color);\n",
              "    }\n",
              "    40% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "    }\n",
              "    60% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "    }\n",
              "    80% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "      border-bottom-color: var(--fill-color);\n",
              "    }\n",
              "    90% {\n",
              "      border-color: transparent;\n",
              "      border-bottom-color: var(--fill-color);\n",
              "    }\n",
              "  }\n",
              "</style>\n",
              "\n",
              "  <script>\n",
              "    async function quickchart(key) {\n",
              "      const quickchartButtonEl =\n",
              "        document.querySelector('#' + key + ' button');\n",
              "      quickchartButtonEl.disabled = true;  // To prevent multiple clicks.\n",
              "      quickchartButtonEl.classList.add('colab-df-spinner');\n",
              "      try {\n",
              "        const charts = await google.colab.kernel.invokeFunction(\n",
              "            'suggestCharts', [key], {});\n",
              "      } catch (error) {\n",
              "        console.error('Error during call to suggestCharts:', error);\n",
              "      }\n",
              "      quickchartButtonEl.classList.remove('colab-df-spinner');\n",
              "      quickchartButtonEl.classList.add('colab-df-quickchart-complete');\n",
              "    }\n",
              "    (() => {\n",
              "      let quickchartButtonEl =\n",
              "        document.querySelector('#df-7cc99cb3-c998-405a-ac67-8e45c871923d button');\n",
              "      quickchartButtonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "    })();\n",
              "  </script>\n",
              "</div>\n",
              "    </div>\n",
              "  </div>\n"
            ]
          },
          "metadata": {},
          "execution_count": 13
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#dataframe info\n",
        "df.info()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "v9fsGlkY2OB9",
        "outputId": "b3a7779a-9381-44a9-e267-5334a8724475"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "<class 'pandas.core.frame.DataFrame'>\n",
            "RangeIndex: 128 entries, 0 to 127\n",
            "Data columns (total 11 columns):\n",
            " #   Column       Non-Null Count  Dtype \n",
            "---  ------       --------------  ----- \n",
            " 0   LatD         128 non-null    int64 \n",
            " 1    \"LatM\"      128 non-null    int64 \n",
            " 2    \"LatS\"      128 non-null    int64 \n",
            " 3    \"NS\"        128 non-null    object\n",
            " 4    \"LonD\"      128 non-null    int64 \n",
            " 5    \"LonM\"      128 non-null    int64 \n",
            " 6    \"LonS\"      128 non-null    int64 \n",
            " 7    \"EW\"        128 non-null    object\n",
            " 8    \"City\"      128 non-null    object\n",
            " 9    \"State\"     128 non-null    object\n",
            " 10  City_Number  128 non-null    int64 \n",
            "dtypes: int64(7), object(4)\n",
            "memory usage: 11.1+ KB\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#export data\n",
        "df.to_csv(\"cities1.csv\")"
      ],
      "metadata": {
        "id": "qm0CIyXL2Q_l"
      },
      "execution_count": null,
      "outputs": []
    }
  ]
}