Malaysia EDA/Haha/Assignment_Pandas_Haha.ipynb

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        "<a href=\"https://colab.research.google.com/github/drshahizan/Python_EDA/blob/main/Malaysia%20EDA/Haha/Assignment_Pandas_Haha.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
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      "source": [
        "# Foreign Direct Investment In Malaysia <a href=\"https://colab.research.google.com/drive/1vIqufdcKSzCjetkUtgbwsNbVWBRr2Onp?usp=sharing\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>\n",
        "This project aims to investigate the flows of foreign direct investment in Malaysia. The dataset consists of 8 columns and 1535 rows. The dataset is obtained from https://data.gov.my/ which contains many kinds of dataset ranging from agriculture to education. We have selected this dataset because we like to know how the impact of foreign direct investment affects the economy of Malaysia. We will perform a series of steps like data processing, data cleaning and visualization on this dataset. Google Colab and Github will be used in this project.<br><br>\n",
        "**Group Members:**\n",
        "\n",
        "<table>\n",
        "  <tr>\n",
        "    <th>Name</th>\n",
        "    <th>Matric</th>\n",
        "  </tr>\n",
        "  <tr>\n",
        "    <th>Hong Pei Geok</th>\n",
        "    <th>A20EC0044</th>\n",
        "  </tr>\n",
        "  <tr>\n",
        "    <th>Vincent Boo Ee Khai</th>\n",
        "    <th>A20EC0231</th>\n",
        "  </tr>\n",
        "</table>\n",
        "\n",
        "\n",
        "    \n",
        "\n",
        "\n",
        "\n",
        " "
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      "source": [
        "## Downloading the Dataset\n",
        "\n",
        "*   We use flow of foreign direct investment in Malaysia dataset.\n",
        "*   Contains information about investment from different contries in Malaysia.\n",
        "*   There are 1535 samples and 8 feature variables in this dataset.\n",
        "\n",
        "\n",
        "\n",
        "\n",
        "\n"
      ]
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      "source": [
        "#### Attribute Information:\n",
        "| Acronym | Description |\n",
        "| --- | --- |\n",
        "| **Year** |    Year of investment |\n",
        "|**Quarter** |   Quarter of each year |\n",
        "| **Blocks of countries** | Group of countries |\n",
        "| **Category** |  Category of countries |\n",
        "| **Countries** |  Name of countries |\n",
        "| **Credit RM million** |    Flow of funds to Malaysia |\n",
        "| **Debit RM million** |   Flow of funds from Malaysia |\n",
        "| **Net RM million** |  Credit RM million - Debit RM million |"
      ],
      "metadata": {
        "id": "Ax8LihPa2Lsq"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "Let's begin by downloading the data, and listing the files within the dataset.<br>\n",
        "The data can be downloaded from this website https://www.data.gov.my/data/ms_MY/dataset/flows-of-foreign-direct-investment-in-malaysia-by-blocks-of-countriesquarterly. The dataset is in zip file format and there is only one csv file inside this dataset. \n",
        "\n"
      ],
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    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "XXnPmr-JVJJ3"
      },
      "source": [
        "The dataset has been downloaded and extracted."
      ]
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    {
      "cell_type": "markdown",
      "metadata": {
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      "source": [
        "**Next step**<br>\n",
        "The dataset has been uploaded to github and it can be downloaded through this link https://raw.githubusercontent.com/peiyu00/data/main/flows-of-foreign-direct-investment-in-malaysia_blo.csv. "
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "u0vucnGFVJJ5"
      },
      "source": [
        "## Data Preparation and Cleaning\n",
        "\n",
        "Data preparation is the important process to clean and transform the data. This step can help to remove missing data, outlier and duplicate value in order to produce quality data analysis results. \n",
        "\n"
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "First, we import all the required libraries from Python. "
      ],
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    {
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      "execution_count": 1,
      "metadata": {
        "id": "df5R-2s3VJJ5"
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      "outputs": [],
      "source": [
        "import pandas as pd\n",
        "import numpy as np\n",
        "import seaborn as sns\n",
        "import matplotlib.pyplot as plt"
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "The data is loaded into the pandas data frame."
      ],
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              "   Year Quarter Blocks of countries  Category                    Countries  \\\n",
              "0  2008      1Q           East Asia  of which  China, People's Republic of   \n",
              "1  2008      1Q           East Asia  of which               Hong Kong, SAR   \n",
              "2  2008      1Q           East Asia  of which                        Japan   \n",
              "3  2008      1Q           East Asia  of which           Korea, Republic of   \n",
              "4  2008      1Q           East Asia  of which                       Taiwan   \n",
              "\n",
              "   Credit RM million  Debit RM million  Net RM million  \n",
              "0                269               286             -17  \n",
              "1                551              1295            -744  \n",
              "2               1952              1291             661  \n",
              "3                518               269             250  \n",
              "4                122               190             -68  "
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      "source": [
        "df = pd.read_csv('https://raw.githubusercontent.com/peiyu00/data/main/flows-of-foreign-direct-investment-in-malaysia_blo.csv')\n",
        "df.head()"
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      "source": [
        "Before preprocessing the data, we should understand the properties of our dataset."
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            "<class 'pandas.core.frame.DataFrame'>\n",
            "RangeIndex: 1534 entries, 0 to 1533\n",
            "Data columns (total 8 columns):\n",
            " #   Column               Non-Null Count  Dtype \n",
            "---  ------               --------------  ----- \n",
            " 0   Year                 1534 non-null   int64 \n",
            " 1   Quarter              1534 non-null   object\n",
            " 2   Blocks of countries  1534 non-null   object\n",
            " 3   Category             1534 non-null   object\n",
            " 4   Countries            1534 non-null   object\n",
            " 5   Credit RM million    1534 non-null   int64 \n",
            " 6   Debit RM million     1534 non-null   int64 \n",
            " 7   Net RM million       1534 non-null   int64 \n",
            "dtypes: int64(4), object(4)\n",
            "memory usage: 96.0+ KB\n"
          ]
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      "source": [
        "df.info()"
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      "cell_type": "markdown",
      "source": [
        "Describe function is a useful way to know the characteristics of data by getting a summary about the data."
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              "              Year  Credit RM million  Debit RM million  Net RM million\n",
              "count  1534.000000        1534.000000       1534.000000     1534.000000\n",
              "mean   2014.881356        2350.971317       1749.621904      601.335072\n",
              "std       4.260317        3233.098898       2493.099895     1571.238998\n",
              "min    2008.000000       -4059.000000          0.000000    -6834.000000\n",
              "25%    2011.000000         337.250000        235.000000      -45.000000\n",
              "50%    2015.000000         954.000000        659.000000      233.000000\n",
              "75%    2019.000000        3341.500000       2391.250000      959.250000\n",
              "max    2022.000000       34158.000000      24961.000000    12176.000000"
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              "      <th>mean</th>\n",
              "      <td>2014.881356</td>\n",
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              "      <th>75%</th>\n",
              "      <td>2019.000000</td>\n",
              "      <td>3341.500000</td>\n",
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              "      <td>959.250000</td>\n",
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              "      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",
              "      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-fe66eb57-5510-438d-9015-1a0135057c6e 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-fe66eb57-5510-438d-9015-1a0135057c6e');\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",
              "  </div>\n",
              "  "
            ]
          },
          "metadata": {},
          "execution_count": 4
        }
      ],
      "source": [
        "df.describe()"
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "We calculate the number of missing value for each column."
      ],
      "metadata": {
        "id": "nIHoePZsNuzq"
      }
    },
    {
      "cell_type": "code",
      "execution_count": 5,
      "metadata": {
        "id": "h46ilQakVJJ6",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "822545ca-711b-46fc-f103-c25183024cdf"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Year                   0\n",
            "Quarter                0\n",
            "Blocks of countries    0\n",
            "Category               0\n",
            "Countries              0\n",
            "Credit RM million      0\n",
            "Debit RM million       0\n",
            "Net RM million         0\n",
            "dtype: int64\n"
          ]
        }
      ],
      "source": [
        "print(df.isnull().sum())"
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "We can also count the value of not null for each column."
      ],
      "metadata": {
        "id": "xjc5mmHLny1E"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "df.notna().sum()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "Wlrlxgd4oJn7",
        "outputId": "7cc0530d-55c6-428d-90d3-5b0664e1df8b"
      },
      "execution_count": 6,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Year                   1534\n",
              "Quarter                1534\n",
              "Blocks of countries    1534\n",
              "Category               1534\n",
              "Countries              1534\n",
              "Credit RM million      1534\n",
              "Debit RM million       1534\n",
              "Net RM million         1534\n",
              "dtype: int64"
            ]
          },
          "metadata": {},
          "execution_count": 6
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "Since there are no null values in all of the columns, the dropna() will not affect the size of original data. "
      ],
      "metadata": {
        "id": "24r7fi-RouDx"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "df = df.dropna()    # Dropping the missing values.\n",
        "df.count()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "1FBR9D06oi2i",
        "outputId": "ef61bf75-2079-49d8-e977-889327edf81f"
      },
      "execution_count": 7,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Year                   1534\n",
              "Quarter                1534\n",
              "Blocks of countries    1534\n",
              "Category               1534\n",
              "Countries              1534\n",
              "Credit RM million      1534\n",
              "Debit RM million       1534\n",
              "Net RM million         1534\n",
              "dtype: int64"
            ]
          },
          "metadata": {},
          "execution_count": 7
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "We can know the number of duplicated rows for each column and remove them. "
      ],
      "metadata": {
        "id": "Pntox4PepCUg"
      }
    },
    {
      "cell_type": "code",
      "execution_count": 8,
      "metadata": {
        "id": "cfcSY6YSVJJ6",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "03f7f6d2-b9ab-4cff-8fff-99d8a028c67c"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "number of duplicate rows:  (0, 8)\n"
          ]
        }
      ],
      "source": [
        "duplicate_rows_df = df[df.duplicated()]\n",
        "print(\"number of duplicate rows: \", duplicate_rows_df.shape)"
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "df.count()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "JhwkqYfnqv95",
        "outputId": "aadee7e9-da9a-408d-aca0-3c8ebbbd8770"
      },
      "execution_count": 9,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Year                   1534\n",
              "Quarter                1534\n",
              "Blocks of countries    1534\n",
              "Category               1534\n",
              "Countries              1534\n",
              "Credit RM million      1534\n",
              "Debit RM million       1534\n",
              "Net RM million         1534\n",
              "dtype: int64"
            ]
          },
          "metadata": {},
          "execution_count": 9
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "However, there are no duplicate rows in our data. So, removing the duplicate row will not affect the size of original data."
      ],
      "metadata": {
        "id": "zucfNzKAvqdi"
      }
    },
    {
      "cell_type": "code",
      "execution_count": 10,
      "metadata": {
        "id": "HsDyuPIgVJJ6",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "37b49144-79c9-4be3-ce57-4a198c9cdc2a"
      },
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Year                   1534\n",
              "Quarter                1534\n",
              "Blocks of countries    1534\n",
              "Category               1534\n",
              "Countries              1534\n",
              "Credit RM million      1534\n",
              "Debit RM million       1534\n",
              "Net RM million         1534\n",
              "dtype: int64"
            ]
          },
          "metadata": {},
          "execution_count": 10
        }
      ],
      "source": [
        "df = df.drop_duplicates()\n",
        "df.count()"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "_0m5LkbVVJJ6"
      },
      "source": [
        "## Exploratory Analysis and Visualization\n",
        "\n",
        "In this section, we will do some analysis about the data and also represent the data by visualization in order to gain some insight from the data. \n",
        "\n"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "RuPTpsGWVJJ7"
      },
      "source": [
        "Let's begin by importing`matplotlib.pyplot` and `seaborn`."
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 11,
      "metadata": {
        "id": "zOTtwqAMVJJ7"
      },
      "outputs": [],
      "source": [
        "import seaborn as sns\n",
        "import matplotlib\n",
        "import matplotlib.pyplot as plt\n",
        "%matplotlib inline\n",
        "\n",
        "sns.set_style('darkgrid')\n",
        "matplotlib.rcParams['font.size'] = 14\n",
        "matplotlib.rcParams['figure.figsize'] = (9, 5)\n",
        "matplotlib.rcParams['figure.facecolor'] = '#00000000'"
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "**Sum**<br>\n",
        "The built-in function has been used to calculate the sum for numeric data fields. "
      ],
      "metadata": {
        "id": "NnaoVEK_9jAI"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "print(df.sum(axis=0)[['Year','Credit RM million','Debit RM million', \"Net RM million\"]])"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "CiFnzLFx9ILX",
        "outputId": "91c5c424-5c22-497b-899b-064fe7822799"
      },
      "execution_count": 12,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Year                 3090828\n",
            "Credit RM million    3606390\n",
            "Debit RM million     2683920\n",
            "Net RM million        922448\n",
            "dtype: object\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "**Other Measures**<br>\n",
        "The summary of each column like mean, standard deviation, minimum and maximum."
      ],
      "metadata": {
        "id": "gEo02ZtG71LA"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "df.describe().transpose()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 174
        },
        "id": "ZUXLbecE7uqf",
        "outputId": "af6d2ce4-c898-4ea7-c246-26e6c473c6e1"
      },
      "execution_count": 13,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "                    count         mean          std     min      25%     50%  \\\n",
              "Year               1534.0  2014.881356     4.260317  2008.0  2011.00  2015.0   \n",
              "Credit RM million  1534.0  2350.971317  3233.098898 -4059.0   337.25   954.0   \n",
              "Debit RM million   1534.0  1749.621904  2493.099895     0.0   235.00   659.0   \n",
              "Net RM million     1534.0   601.335072  1571.238998 -6834.0   -45.00   233.0   \n",
              "\n",
              "                       75%      max  \n",
              "Year               2019.00   2022.0  \n",
              "Credit RM million  3341.50  34158.0  \n",
              "Debit RM million   2391.25  24961.0  \n",
              "Net RM million      959.25  12176.0  "
            ],
            "text/html": [
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              "    <tr style=\"text-align: right;\">\n",
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              "      <th>min</th>\n",
              "      <th>25%</th>\n",
              "      <th>50%</th>\n",
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              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>Year</th>\n",
              "      <td>1534.0</td>\n",
              "      <td>2014.881356</td>\n",
              "      <td>4.260317</td>\n",
              "      <td>2008.0</td>\n",
              "      <td>2011.00</td>\n",
              "      <td>2015.0</td>\n",
              "      <td>2019.00</td>\n",
              "      <td>2022.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Credit RM million</th>\n",
              "      <td>1534.0</td>\n",
              "      <td>2350.971317</td>\n",
              "      <td>3233.098898</td>\n",
              "      <td>-4059.0</td>\n",
              "      <td>337.25</td>\n",
              "      <td>954.0</td>\n",
              "      <td>3341.50</td>\n",
              "      <td>34158.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Debit RM million</th>\n",
              "      <td>1534.0</td>\n",
              "      <td>1749.621904</td>\n",
              "      <td>2493.099895</td>\n",
              "      <td>0.0</td>\n",
              "      <td>235.00</td>\n",
              "      <td>659.0</td>\n",
              "      <td>2391.25</td>\n",
              "      <td>24961.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Net RM million</th>\n",
              "      <td>1534.0</td>\n",
              "      <td>601.335072</td>\n",
              "      <td>1571.238998</td>\n",
              "      <td>-6834.0</td>\n",
              "      <td>-45.00</td>\n",
              "      <td>233.0</td>\n",
              "      <td>959.25</td>\n",
              "      <td>12176.0</td>\n",
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              "  </tbody>\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",
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              "\n",
              "    .colab-df-convert {\n",
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              "      border-radius: 50%;\n",
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              "    }\n",
              "\n",
              "    .colab-df-convert:hover {\n",
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              "      fill: #174EA6;\n",
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              "\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",
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              "\n",
              "      <script>\n",
              "        const buttonEl =\n",
              "          document.querySelector('#df-59fe1460-87ac-4c59-9167-46c1755259ff button.colab-df-convert');\n",
              "        buttonEl.style.display =\n",
              "          google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
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              "        async function convertToInteractive(key) {\n",
              "          const element = document.querySelector('#df-59fe1460-87ac-4c59-9167-46c1755259ff');\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",
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              "    </div>\n",
              "  </div>\n",
              "  "
            ]
          },
          "metadata": {},
          "execution_count": 13
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "Fv4NPHasVJJ7"
      },
      "source": [
        "**Boxplot**<br>\n",
        "It displays the distribution of data based on minimum, Q1, median, Q3 and maximum. From here, we can know whether the data is skewed or symmetric. Not only that, the outlier can also be observed and removed. "
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 14,
      "metadata": {
        "id": "NKN6RIplVJJ7",
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          "height": 360
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      },
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<matplotlib.axes._subplots.AxesSubplot at 0x7f57e35449d0>"
            ]
          },
          "metadata": {},
          "execution_count": 14
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 648x360 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ],
      "source": [
        "sns.boxplot(x=df['Year'])"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 15,
      "metadata": {
        "id": "-Scf_lKnVJJ7",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 360
        },
        "outputId": "d90e23bd-fe49-453c-ece7-755579c71a1b"
      },
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<matplotlib.axes._subplots.AxesSubplot at 0x7f57e344ff70>"
            ]
          },
          "metadata": {},
          "execution_count": 15
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 648x360 with 1 Axes>"
            ],
            "image/png": "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\n"
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ],
      "source": [
        "sns.boxplot(x=df['Credit RM million'])"
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "sns.boxplot(x=df['Debit RM million'])"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 360
        },
        "id": "e04VRuB8emaU",
        "outputId": "473d100c-c576-476e-a480-f4e277f4bf95"
      },
      "execution_count": 16,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<matplotlib.axes._subplots.AxesSubplot at 0x7f57e2f6df70>"
            ]
          },
          "metadata": {},
          "execution_count": 16
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 648x360 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "sns.boxplot(x=df['Net RM million'])"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 360
        },
        "id": "D-U14yrt2dPu",
        "outputId": "65e700a5-b0f4-435a-85f8-6c97c6f943d9"
      },
      "execution_count": 17,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<matplotlib.axes._subplots.AxesSubplot at 0x7f57e2f49d60>"
            ]
          },
          "metadata": {},
          "execution_count": 17
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 648x360 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "Dn_AW-5uVJJ7"
      },
      "source": [
        "From the above 4 boxplot, it can be noticed that there exist outliers in the data. Therefore, IQR has been calculated and used to remove outliers. The size of data is decreased to 1287."
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 18,
      "metadata": {
        "id": "c7fugjWzVJJ7",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "44bb38d2-a2c4-4c9e-b8cf-1e3022da82c8"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Year                    8.00\n",
            "Credit RM million    3004.25\n",
            "Debit RM million     2156.25\n",
            "Net RM million       1004.25\n",
            "dtype: float64\n"
          ]
        }
      ],
      "source": [
        "Q1 = df.quantile(0.25)\n",
        "Q3 = df.quantile(0.75)\n",
        "IQR = Q3 - Q1\n",
        "print(IQR)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 19,
      "metadata": {
        "id": "pPnlFwy2VJJ7",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "dbfe5586-343f-4cd4-d48e-97f899834025"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "<ipython-input-19-f4e1682787c4>:1: FutureWarning: Automatic reindexing on DataFrame vs Series comparisons is deprecated and will raise ValueError in a future version.  Do `left, right = left.align(right, axis=1, copy=False)` before e.g. `left == right`\n",
            "  df = df[~((df < (Q1 - 1.5 * IQR)) |(df > (Q3 + 1.5 * IQR))).any(axis=1)]\n"
          ]
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "(1287, 8)"
            ]
          },
          "metadata": {},
          "execution_count": 19
        }
      ],
      "source": [
        "df = df[~((df < (Q1 - 1.5 * IQR)) |(df > (Q3 + 1.5 * IQR))).any(axis=1)]\n",
        "df.shape"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "rN1bUu8RVJJ7"
      },
      "source": [
        "**Histogram**<br>\n",
        "It shows the probability distribution of numeric data. There are 4 fields in numeric value, but the year is not a continuous variable. "
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 20,
      "metadata": {
        "id": "Zatc4Si_VJJ8",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 616
        },
        "outputId": "1db21d9e-ee7e-4d07-ef1d-ff3ec49c199b"
      },
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 1080x720 with 4 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ],
      "source": [
        "df.hist(bins=50, figsize=(15,10))\n",
        "plt.show()"
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "**Bar Chart**<br>\n",
        "Bar charts are important to present categorical data. We have used bar charts to get the frequency of investment for each block of countries and also countries."
      ],
      "metadata": {
        "id": "ec1-V1dqA6Lc"
      }
    },
    {
      "cell_type": "code",
      "execution_count": 21,
      "metadata": {
        "id": "kMrm6CiAVJJ8",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 555
        },
        "outputId": "1d2923f9-977f-4444-dd20-21adfda59cea"
      },
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Text(0.5, 0, 'Countries')"
            ]
          },
          "metadata": {},
          "execution_count": 21
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 720x360 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ],
      "source": [
        "df.Countries.value_counts().nlargest(40)[1:].plot(kind='bar', figsize=(10,5))\n",
        "plt.title(\"Investment by Countries\")\n",
        "plt.ylabel('Number of Investment')\n",
        "plt.xlabel('Countries')"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 22,
      "metadata": {
        "id": "RSt7KlcfVJJ8",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 538
        },
        "outputId": "2ecb7809-f7d8-4e2e-c8a8-3a94d02d9c06"
      },
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Text(0.5, 0, 'Blocks of Countries')"
            ]
          },
          "metadata": {},
          "execution_count": 22
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 720x360 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ],
      "source": [
        "df['Blocks of countries'].value_counts().nlargest(40).plot(kind='bar', figsize=(10,5))\n",
        "plt.title(\"Record Over Year\")\n",
        "plt.ylabel('Number of Record')\n",
        "plt.xlabel('Blocks of Countries')"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "tLNLw0EOVJJ8"
      },
      "source": [
        "**Scatterplot**<br>\n",
        "Scatterplot shows the relationship between two variables. By observing the scatterplot, we can know that there is a positive correlation between “Debit RM million” and “Credit RM million”. This means when “Debit RM million” increases, “Credit RM million” will also increase. "
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "for feature_name in df.columns:\n",
        "    plt.figure(figsize=(5, 4));\n",
        "    plt.scatter(df[feature_name], df['Net RM million']);\n",
        "    plt.ylabel('Net RM million', size=12);\n",
        "    plt.xlabel(feature_name, size=12);\n",
        "    plt.xticks(rotation=90)\n",
        "    \n",
        "plt.show();"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 1000
        },
        "id": "-unj03wC5blx",
        "outputId": "60b44a15-a9f1-43ad-db9c-2fe03145644e"
      },
      "execution_count": 23,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 360x288 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {
            "needs_background": "light"
          }
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 360x288 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {
            "needs_background": "light"
          }
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 360x288 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {
            "needs_background": "light"
          }
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 360x288 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {
            "needs_background": "light"
          }
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 360x288 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {
            "needs_background": "light"
          }
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 360x288 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {
            "needs_background": "light"
          }
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 360x288 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {
            "needs_background": "light"
          }
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 360x288 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 24,
      "metadata": {
        "id": "61sgf555VJJ8",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 396
        },
        "outputId": "bcbac736-7246-46c0-f128-a8c25316a931"
      },
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 720x432 with 1 Axes>"
            ],
            "image/png": 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7N4nA5iNXr3pOWWRiYqpw6tTZek9DeLBgwXy0No2L1i97lGfXQvCLPmtr6DV/N7UWLVmvzVfJ+mX93loFrzVctKjrW8AH0hhfFkIhhGhwkryws9btwk3SfsFuan0v1Yx1rLcgU3eR1kCCUAghGpikhYKzmghRab9gN1Hvpd6CKwgVgha1om6C0BjzWeB+4MvW2jtL23LAdmATsBA4CHzSWnvYdd5C4I+B20qbngA+Za095TrmPcBDwArgbeBR4D5rrfzjQoimIqmlr57dLoKotF+wmyj3knXBlWVLrmgu6pJlbIz5pxRF30tlu34H2AJ8CrgBOAHsMcZ0uY55DHgf8JHSn/cBf+kauxvYAwyXxvgt4NPAXdW4FyGEqCdJLX21KPqchDj9gue15TyPhej3EiS4skBWLbmi+ai5IDTG9AD/H/AvgZOu7Tngt4EHrLWPW2tfBj4OdAF3lI5ZRlEEbrLWvmCtfQH4DeDnjDGmNNQvAfOBj1trX7bW/jXw+8BdpWsIIUTT4GcF68q3B55Xr5IvA4PDbNx5kBX9+9i48+Ccbh5xSrj4JUXGuZesCy6/day3JVc0H/WwEO4E/tpa+7dl268C+oBnnA3W2nPAPuDG0qZVwDvA867zDgBnyo7ZXzrX4WngcmBJOrcghBDZYPOaJXNq5gGcm5gObZ22YVkvT25ayYtb1vLkppU1EYNhLd6iWi4f3n9sTns5KIrBOPeS5RqCA4PDnJuYmzjTkaPullzRfNQ0htAY8+vAtcAve+zuK/1d/j/YMHCF65i33LGA1tqCMeaE6/w+4AceYzj7XvebX3t7jgUL5ofdhqgD7e1tWpsGRutXPW5fdRV/+HdHOXl2Ytb2iekCjxx4g9tXXZXKdfzW8IlDx+nfc4Q3R8a4rKeTLeuu47bll3uO8ciBNzzds+553r7qKr77o7P81298n6kCtOfgF953xZz7CLLsxfmsffrDhs997WXGXMKrc14bn/6wqftn9pEDbzDh0Ty46+J5sddVv4ONT7XXsGaCsOTSvR/4oLV2Iuz4ejA1VchUnS1xgazVQBPx0PpVl1Nnvf9LfXNkLLXn7rWG5QkZx0fG+NxXX+bM2XFPC51fP2T3PAcGh/mb//VDpko6aKoAf/O/fsi7/9H8SEklvV35WPe89soFbF23dE6W8dorF9T9M+v3vE6dnZj1vKJkSOt3sPHxqUOY2vi1tBCuAv4RcPhCuB/twFpjzCeA60vbeoHvuc7rBYZK/x4CFhljco6VsBQXuLjsmPLfhl7XPiGEaCrqlTEcNwM2yjyjjplmd5Cs1tkLe15pZUhnueyOqB21jCH8KvAe4Kdcf74J/JfSv49QFGzrnBOMMZ3AGi7EDL4AXEpRXDqsAi4pO2ZN6VyHdcBx4FiaNySEEFmgXhnDcRMyoswzaEx3QsrD+49x6/WL69oHudqEPa80MqSjxHWK1qBmFsJSncBT7m3GmDPA26WMYowxfwRsNcZ8l6JA/DzFJJLHSmMMGmOeAh41xmwqDfMo8HVrrS39/BjFWoZ/boz5AnAd8BngHtUhFEI0I379eKstjuJaJqPM02/Mrnz7HGvYrsMnmk4Eugl7XmlkSKvOoXDIWqeSPwAuBr7MhcLU6621o65j7gD+A8XMYSgWpr7T2WmtHTHGrCuN8U2KpW36gS9VffZCCFEn6uH2TOK2DZun35i5XI6xyalZx1YiXBrFTRr0vNIIFQgTlY3ynETl5PzqOLUiExNTBQXdZhMFRDc2WVk/vdyS47eG1XimXmNu323xe1vde4uJHTPnJTobzdoY5z781m/jzoOeorKv9Nyb4Tk1Cz5JJd8CPpDG+JEthMaYlcDNFBM4ZgU1WGv/dRqTEUKIapH1FmX1olJBl4Zl0msOT25aOeuYh/cf821VF3cd03aT1uuLRhqhAkFWXrmTW4tIgtAYczdFd+6rFJMz3F/UZGIUQmQevdwu4AiYcoEVVySnIYSiCnUv4eIQto7l8/QTlkm6k9T7i0algjxIVG7fbT3PyUoXF5EuUS2EvwX8a2vtQ9WcjBBCVIustyirFV5uRjdRRXJaQiiqUHf+vS2mSPGapx9JyvQ0wxcNP1FZr3JGoj5ELTvTDeyu5kSEEKKaZLlFWS3xEjDlRBHJaZQ8CbqW1/YNy3rp81mvXA7P/shR7heilenx6sPczF806lXOSNSHqILwr4CPVHMiQghRDZyXuJeloxVfblGEShSRnJYQiivUvUQKwHQBzzp6QfOJU8PQr15fd6e3o60ZvmhsWNbL1vVLm7rWo7hAVJfx94F7jDGrgZeAWX2SrLUq6SKEyBxB7tG+JsgyThLDFxRDB9FFclruxLila8pj3nK5ohh043bZ+s2zrys/J3ElCD+LKD6VOlZfvTDy2Fkmq11cRPpEFYS/RrFA9I2lP24KqMafECKD+LkL44qBLJI0hm/zmiXc99QRJspVFNDT2cGWm66JJADSah2XJFPWLVJW9O/zPGZodJyNOw+y+uqF7Dp8ouJ5+lkax6a8BeGBoydjjS9EvYkkCK21V1V7IkIIkTaVujWzXLcwaTLDhmW9PLj3VSbGp+bsu3hee+T7S7M7ShIrlLM2QWUunG4mt16/mANHT1Y0zzDLajnNEEMoWovYnUqMMZcCBWvtmSrMRwghUqMSt2a9y4mEUYnYHfUQg1HPdVOJO7ESsR2WKe1mbHKaA0dPVmwR9rOI5jvaGBmbnHN8M8QQitYialIJxphPGmO+B4wAp40xbxhjNldvakIIURmVZEmmlUVbLSrJmq53xrVfgoY7OziIqJnDDmlY6/wSLLbcdI0ycUVTELUw9Vbgs8CDwN+XNq8BHjDGdFtrH6jS/IQQIjGVuDWzXk6kkhi+oHNr4SavtHZfWpnMcQmyiGY1tECIqER1GX8C2GSt/SvXtr3GmFeA+wEJQiFEJknq1sx6Ud5KxK7fuYCnm/zQD0d44dgp3hwZS0XwVCq2/damp7OD8cnpWCI5qQDOcnypEEmIKggXA9/w2P4ioN8AIUTTEWaBy4IgqCSGz+vcjTsPelruHj80NPNzGrGUlYptvzZ2I2OTdOfbyXd0cHpsMnRdksaJZj2+VIgkRBWER4A7gHvLtt8BePcREkKIBibIAtesgiCqhc7t3k0ijOO6u72usXX9Us9+zKfHp+jsaOOeW0zoPJK6rqvRri4LXzBEaxNVEO4A/psxZi1woLRtNfDPgF+swryEEKLu+Fngsta/1ktMOPNMs2i1m+HR8cTCOI672+8aW9cv5clNKz270ERdi6Su67TjS5v1C4ZoLKLWIfwbY8xK4N8AP1faPAissNb+Q7UmJ4QQWSRLCSdeYuLeAUsul5spPh2naHXUci69XfmKhHFUd3fYNSpZi6Su67TjS7P2BUO0JpHrEFprvwX8chXnIoQQDUGWEk68xMRkgTkt1aIWrXbGdCx3QZ0+tu/2jhgaGh1nRf++miSgVLIWfgLY3XbOy/qaVpeW8nuJul2IauArCI0xP2atfdv5d9AgznFCCNEKpC0IKiGOaIhyrJflbvkVPTxy4I05WcZeMXwO7vqCzrhJCBN8lazFhmW9HPrhyKykGYBdh0+w/IoewDvreuv6pTMxjGnE/GXpC4ZoXYIshG8ZYy6z1p4AfgSeHYJype3t1ZicEEJkkTTbtlVKnLi/pAJjw7Jebl91FadOnZ21PYqLuVLXZ5jgq3QtvHoOuwuQ+7lyn9y0MrX1ztIXDNG6BAnCmwDH8vezNZiLEEI0DJWUfEkTLzHRkWNWDCFUR2CUizG/vsJelsmoWbVRBF8la5HEXZu2KzdLXzBE6+IrCK21/8Pr30II0ew0UgmQoCLTtbgHtxjzyviFuZbJuFm11RTfYe7aWrlys/IFQ7QugTGEUQdRDKEQolloxBIgfmKi1vON6vrMUlZtUGLJ8it65uyb15bj7PlJ36SZRvoyIYSbtoB9PwLeCvnjHCOEEE1BkFgRRcGzcedBVvTvY+POgwwMDs/s27Csl63rl9LXlScH9HXl2bp+6RxBlKWs2g3Lern1+sVztu86fAJg1v30dHZQKBQ4PT41K2nGeQbOl4mhkvu8fL8QWSYohlBxg0KIliNNsZK2taje1qco1tMors+sZdUGJZa4k0c27jzIyNik53FO1nVWLJ9CxCVSDKEQQrQKaYmVtF3PaY6XVFimJXiyllUb9UtA2HFZsnwKERfFEAohWppyceRViLkjB+cmpmIVW05DPD3w7BG+8tIQ0z7pu0nEWCXCMi3Bk7Ws2qhfAsKOy5rlU4g4BLmM/WoPulEdQiFEw+IljnYdPsGt1y/mwNGTDI+O05Vv59zE9IyrMKqA8hNJQ6PjbNx5MFQIPfDskTkFk+Ncx49KhGqagidLWbVRLZZhx2XN8ilEHBRDKIRoWfzE0YGjJ3ly00qgGDd2enx8zjFhAiqoYLSzPUhcfuWlcDHoXCcOlVj5mlXwRLVYhh2XNcunEHFQDKEQomWJIo6CjgmKxYvSxQP8xaWfm9hNEjFWiZWvmQVPVItl2HFZsnwKEQf1MhZCtCxRxJHfMV359sBYPC/x5Gcx9BKdbTl/UZgrzSuJGKvUyhdX8NQ7M1oIEQ31MhZCtCxRxJHfMblcjrHJqVnjlVv7ysVT1E4eAB99b59nDOHHlvfxmQ9d53k/UcRXtax8XtcGGq7ItxCtinoZCyEalkqtT25xNDQ6TltudhFqP0vf5jVL2L7beo4ZlDQSxzrniD4ny7gtVxSJQWLw3gHLZOHCPO4dsLPu033faQoyv8zli9pzqssnRIOQKxQiBKq0CBMTU4VTp87WexrCgwUL5qO1aVySrl+Q4CsXIVAUV16dMaJcJ+5Yfta+csrHqZYL9eaHDnB6fGrO9u58O3vvXD1rW5I5BK1h1GfhkANe3LI28vGicvR/aOPjtYaLFnV9C/hAGuMHWQjnUIolXExZyztr7XfSmIwQQjiE1ctLsytEkrGSJo1UK+nASwx6ba9Gr+a4pW+qWZev1jGLca+nmEqRVSIJQmPMTwN/BryntMmJHVQMoRCiKoSJtDS7QiQZq9KkkVridmGfm5hK3Y0bdO/lVKtMzcDgMA/ufXWWAK52zGJccV0NMS5EWrSFHwLAnwI/pBhXeD2wDPhJ199CCJEqYSLNz8qUxPqUdKwNy3p5ctNKXtyylic3raQvxTnFpafT//v90Og4hdLf5b14HSoRrZvXLKGzI/x10teVT+TSD8MRWl5WUndMaNr4fWnZMWBZ0b+PjTsPMjA4HHp8teYnRByiuoyXAr9orX21mpMRQgiHsJIwaRZJTmusehZu3nLTNdz31BEmohQw9KAS0VqenONFX1d+pth32ngJLTfVstD6jTvtSuxxWwDV61hkmagWwr+naA0UQoia4GV1courDct62bp+KX1deXJUZn0KG+uBZ4+w8kv7uKF/Hyu/tI8Hnj2SaJxqsmFZL7/7ketmXTsqaYhWx1r6seV9VRk/iDBBVS0LbZRx3RbANK3aQqRNVAvhvwL+xBhzNfAyMOHeaa3dl/bEhBCtTZR6eWkmaPiNVd5TeLrAzM9eJWDq2anCfe2BwWF2DFjP4tbd+XbmX9SRemLDwOAwuw6fmLP91usXV/WZBMUwVlOMRk0scgRrs7b+E81BHJfxTwMf9tinpBIhRFWopriKmu3p11P4Ky8N+dYErDdOTJ2XGOzsaOPum6+tynP1c90eOHoy9Wu58RNmPZ0dbLnpmqp9hsq/tOR8uss4FsBmbv0nGp+ogvBR4Fng3wHDeHctEUKIhiBOtqdfSF7CUL2a4CfM2nJU1YVdrxi5egqtcqtsmAVQvY5FVokqCN8F3GKtfa2akxFCiFoQp+6gX0/htlx680m7Np2fACsUqlveJEpv6GqRBaElC6BoZKIKwj3A+4HEgtAY80ngN4AlpU2HgS9Ya3eV9ueA7cAmYCFwEPiktfawa4yFwB8Dt5U2PQF8ylp7ynXMe4CHgBUUW+89Ctxnrc3w93khRC2JY8ny6yn80ffOTZ5IQjVq09VLmClGLhvCVIgkRBWETwH9xpj3At9mblLJ30QY4wfAvwVeoZjd/HHgq8aY91trXwJ+B9gC/ApggW3AHmOMsdaOlr9Eri0AACAASURBVMZ4DPgJ4COln/8E+EtgI4AxppuieN0H3AC8m2JB7TNAf8R7FUI0OX6CqSvfPqcPcdyewnFJs+OKQ72EmSxkQjQukXoZG2OCUqgK1tpESSXGmLeBzwI7gePAQ9ba3yvtuxg4AdxtrX3UGLMM+A7wQWvtgdIxHwT2A++21lpjzG8Cvw/0WmvPlY75PPCbwLvCrITqZZxd1Iezscna+nnFenXkIJfLzarjF9bPOA1X74r+fZ5B2ZX2+03bDV3pGqplW33J2u+giE8mehlba6PWK4yEMaYd+EXgUuB54CqgD3jGdc1zxph9wI0U3b6rgHdKxzscoGj9u5GiVXEVsN8RgyWeBu6j6Kp+Pc37EEI0Fm5R0t3ZwUXtOUbHp2ZaupV38Qiy1KXl6q2WezdLrku1bBMi+0R1GadCKb7vBaCTorj7qLX228aYG0uHDJedMgxcUfp3H/CW28pnrS0YY06U9jnH/MBjDGdfoCBsb8+xYMH8GHckakV7e5vWpoHJwvo9ceg49+95hbGJoigZGZukc14bD/7z93Lb8su57nef8jxveHTcc+6PHHjD09X7yIE3uH3VVZHn9ekPGz73tZdn5gXQOa+NT3/YsGDBfJ44dJz+PUd4c2SMy3o62bLuOm5bfnnk8dOikjVM61mJ5GThd1BURrXXsKaCkKIV76eAHuCfA39hjPmZGs/Bl6mpgkzqGUXujsYmC+v3xaftLNEFMDYxzReftqy9ckGgpc5r7m+OjHle582RsVj3uvbKBWxdt3SOO3XtlQv4qxden2VZOz4yxue++jJnzo7X3LJWyRqm9axEcrLwOygqw8dlnNr4NRWE1trzgNMP+VvGmBuAfwP8XmlbL/A91ym9gJPeNwQsMsbkHCthKTN5cdkx5f9L9rr2CSFalLDM4riJGGm6ev3cu9VIOKkH9SxHI4SIRqqxgQmvn6foyh0C1jk7jDGdwBouxAy+QDHmcJXr/FXAJWXHrCmd67COYsLKsfSnL4RoFML6yMbtQxzWazmIgcFhNu48yIr+fWzceZCBwfJomSL1KvScNl7PCmD11QvrMJvoRF0nIZqBmlkIjTEPALuA7wNdwB3AzwC3lmIB/wjYaoz5LnAE+DzFOMPHAKy1g8aYp4BHjTGbSsM+CnzdWmtLPz9GsZbhnxtjvgBcB3wGuEd1CIVobaJYAOMkYiQtsRInwaKpLGseFS12HT7B8it6Ij/zWmYqKxFGtBq1dBn3Af+59PcI8BKwwVr7dGn/HwAXA1/mQmHq9a4ahFAUkf+BYuYwFAtT3+nstNaOGGPWlcb4JnCSYv3BL1XpnoQQDUI1auQlyeSN4wZuhkLPM8Jqaq4gjOP+rrVAaxZ3vRBRCRSExpiXogxirX1vhGN+JWR/AdhR+uN3zEngl0PG+TaQvHiXEKJpyUIpljhuYLeIHRodpy13QZS492cZv77KDlHd3/3PvVY1geZleWwWd70QUQmzEP4T4A3grym6b4UQQlRAXDewI3Ya1X3pda9uori/BwaH59SIdKhUoPlZHrvy7Zwen0o0XyEakTBB+EngXwKfAP4r8KfW2ueDTxFCCOFHEjdwI7sv23Iw7RPBHdX97VhEvahUoPk923xHB50dbQ3trhciDoGC0Fr7H4H/WCoo/a+AJ0qFoP8M+Atr7YkazFEIITJDpYkNSWIZG9l96ScGgcAsbjdB91mpQPMbe2RskntvMWq3J1qGqK3rvg38tjHmd4CfB34b+IIxZrG1dqSaExRCJEf9Y9MlrcSGKLGM7rXL5TyTdBvCfdnn4yLv68pHfmZ+bvbufPucMeJ+5v3Gdnhy08pIcxSi0Ylbh3ANRUH4UxRr/mX/66kQLYojXoZGxylwQbyollpygly3UQmqbefsu6F/H9t225m187KyNYr7cvOaJcxry83aNq8tF2vufjUf77752lnbknzmg+bx4N5XffcJ0WyEWgiNMT9BMY7w48A84C+A91pr9ZsiRIZp5LizrFKp6zbIwgjMiS0sp61kKUzb2lttS3KhzLxZ/nMYUd3sST7zG5b1sm239dx3enyKgcFh/b6IliCs7Mwe4IMUC0pvBp5SgWchGoNaxZ05YsIpizJdKLoDs+aeTkP0VFooOszCGCQGoSgGX9ySblUtL5G6bbdl226byjo+vP8Yk2VvjckCoV9MvNYrzH2b9DPv59Z25p+lz7EQ1SLMQngzxZZyBvh94PeNMXMOilKHUAhRW2rR5aJcTDiuzayVRUkr9q/SQtGVinRn7dK06AXVCXQ/p9tXXZVo/CT3nHS9kn7mN69Z4mslbITEHSHSICyG8B6K7eH+Gng84I8QImNU0ms3KkFiIm5sXTVJI/YP4vc7Lieon3KYaHHWLu3Y0DDBU+k6hvWQ9iLpeiX9zG9Y1ktPp7d9pBESd4RIg7CyM/fUaiJCiHSpRqu2csLERFasK2m6zyvpdhJmYfSLIXS7bjfuPJhqbGhYli1Uto5JrKpJ16uSz/yWm65p+DaBQlRCRb2MjTEXA79lrX0gpfkIIVKk2q3awsRENa0rcdymtXCfRyGKYAm7p7RjQ70EWzmVPKckIq2S9Ur6ma/FFyghskyULON/BKwEJoC91topY8w8il1MPgu0AxKEQrQgQWKimtaVuDFmlcb+pUmQYIkiZtIQt+Vi+tbrF3Pg6EnPcdN4TnFFWr3WKwu9roWoF4ExhMaYG4FXgCeBAeCAMebdwEvAncB9wE9Ue5JCiGzijqmDYlkUiB9bF5e4MWYblvVy6/WLZ+bXloNbr1/ckC//SmNDvWIQdx0+weY1S/jGlrXce4tJHCOZFpXGagoh4hNmIbwPeBr4AvCrwL8Bvg7cC/ylStAIIephVYnrNh0YHGbX4RMzWdDTBdh1+ATLr+hpOJFRqWszrFZfNdczjptf1johaktYlvFy4D5r7cvA7wIF4LPW2v8kMSiEqBdxM1fTyjJOi6BuJVHYsKyXJzet5J5bimXAtu+2kcepV19kdc4RItuECcIfA94CsNaeBc4C/1DtSQkhRBBx3ab1EkFexBVGfuIxqcBKUgYmDbImyoUQs4mSZbzQGDMJ5ChaCLuNMT/mPsBa+3Y1JieEEF7EdZtmJcsY4rVXC0qeSdqasF4JG1kS5UKIuUQRhN9x/TsHfKPs5wLFTGMhhKgZcWLMkoigavX3jSOMgkSf3zhhNQXrVV4lS6JcCDGXMEH4szWZhRAiM1RLCNUTLxG0+uqFPLz/GNt32zn3mVarOy/iCKMg8RhUA3JgcDhwnvVI2EjTMtmMn1Eh6k2uUFBuiMPExFTh1Kmz9Z6G8GDBgvlobapPuRCC4ku70pIfaa5fGmIg7D437jzoKbb6uvI8uWllxfOP+oyD5hHUfzeNeZaTxhpWa+0c+iQOfdH/oY2P1xouWtT1LeADaYxfUacSIURzkTQurVakZbkLu89qxrvFcdkGWdU2LOv1FYRB86yndS0Ny2RQ/+w0LblCtBoShEKIGeoR+B9HoKQlWP1crc59xo13iyuyogqjMPHYl2Ce5YJ6227Lg3tf5e6br82EiPJ6lnDhGYT5tLL0BUaIRkKCUIg6kcU4qFoH/se1+MURrH7PN6gsi3Ofq69eyOOHhmbt84t3q2a8oTOG3zhx4/L8rGunx6cyYVnzepb3PXWEQqHAZIzoJmUuCxGfsDqEQogqkNUivZW2RYtL3Np0UWvoBT3foLp3m9csmelqUo5fq7t619fLu9arO98eGO8ZJJSyUBPQ61lOTMcTg6DMZSGSEEkQGmO2GWPme2y/2BizLf1pCdEc+BUVrreI8KNWPWSd5xLmui0nqmBNUq4FivfvZ0U7cPRkrLnWqvPHyNjkzLbT41P0P/ea7xeLMKFUb8taGtevRU1FIZqRqC7j7cAjFDuVuJlf2ndvmpMSohkIciVmuUhvtUuSBGWJOvgJl6gJGX5Cc2h03Dfurq90zbhrU6/6en7CdWRs0tf9u3nNEu4dsL4Wt3pb1oJK6QTR15XPVOiFEI1IVJexU4C6nJ8G1KVECA+CrFT1ah+WBYKyRCHcwrNhWS+b1yyhtyQCHt5/bJZFLMztvvrqhYFWxrhrU2s3u0MS9++GZb1ckve3A9TbsrZ5zRLmteVineOU2Hlxy1qe3LRSYlCIhARaCI0xoxSFYAE4aoxxi8J2oJOi5VAIUUaQpemeW0zV2ofVM1klyrWDhEyUOnJhSRxhbvcDR0+ydf1S33nGTdSoRecPr+caZk3ze86nXS7mcqoRGhA3+/rBva8yMT4VaXy5h4VIjzCX8Z0UrYN/CnwOGHHtOw8cs9a+UKW5CdHQBLkSqyUiqp3xmvTat6+6auY4v+cStZhy0hqCDs61/a6VZG2q6Wb3e663Xr+YXYdP+FpbcznvjiVBz78W84bgz+KojxjMAffcYjKXmS9EsxAoCK21fwFgjHkdeN5aO1GTWQnRBIRZmqohIupZWDro2m5BWGkLsyDL68DgMLkchDVgunfA0v/ca5wem/QUFuWi0LE6OmVrwkRJmlZav+fqWDof3Psqpz1E1HQBTwGWZgu5JPMO+yyGfZGSABSiOvgKQmPMj1lrnfjAbwNdxhjPY13HCSFK1MKVWE49k1WiZgyHPZcwMeUnGLry7dz/zCtMRyhRMllgJjvXy3LlZ9069MORWVa5OOe6j/HC776D1tQRSAODw+wYsHPu3UuApf25TDLvIGolWIUQswmyEL5ljLnMWnsC+BHeSSVOskl7NSYnRKNTa4tG2hmvUS1dUYo9u/F7LlHElJ9gyOVyjE1Giz0rp1w4+Vm3vvLSUKjoSmIZC7rvKGu6YVkv22O0sUvrc1npvL2oxxcpIUSwILyJCxnEP1uDuQghKiRN60rQyx5mv7DPnvdPVIhz7Shiyk8w+AmiqLiFk58Vy8/6GOXcIMtY0H17rSkU12PjzoMzYslPgBVg1nG1cGfvGLB89L19c2Ico34W5RoWovb4CkJr7f/w+rcQIrukaV3xe9k/uPdVzk8VZgnFKHOKQlQx5SUYHt5/zHMuPZ0djE9OB5a6gdmWKz9x1ZbzFoVRzg2yjIW5hcH7/twi3U84uo+L4vKOgiMq/dZ+ugC7Dp/g1usXc+DoSVn6hGgAIvcyNsZ0AncAP1na9B3gr6y156oxMSFEMqJaV8IsRb5lSyKWBIH4mauVuLz9rKNbbroGuCCSu/LtnJuYZsKl7MotV35jeWX2Rj03yDIWdt/Omnp1d3EsiU7WtJ9QC3J57xiwM9cJI0phcWfcA0dPRsocF0LUn6it694HvAb0AytKfx6kWJvwfdWbnhAiCn4t8oKOD+ulXGmR7DAR5DXnSoo8l7fd6+nsgEKBbbst23Zbzk1Mcc8thr13rua29/Ti1D9uy83tU+zXwu8zH7outLVfkvZ/Ue87zIK6YVkvT25aiV9pZz+Xt5ORHKWXdlhhcTdDpcxvIUT2yRXC6jMAxphvAkeBX7XWniltu4RifcJrrLUfqOosa8TExFTh1Kny7nwiCyxYMB+tjTdeFpvOjrZAEeLXR9hdC9Bv3HxH26z+uQ49nR1cPK/d0+JYvn5Bc4bKXd4Dg8OeLdrac/DzPrFtlfRsTiMuL8oYUdYN4ENfft5zjfxaTvmN48ZZwxX9+wLHKKfSZyvSQf+HNj5ea7hoUde3gFQ0WFSX8fXA/+OIQQBr7RljzL3AN9OYiBAiGUmyWqPE6vnFIwK+rtmoL/2gOafRfuzh/cc8+/VOFeBvDg3NETSV1GpMqxh4FFd/VHe03xf9fHsOcjlfC1+U8kRx+w3Xqg6mEKIyogrC7wKXU4wbdHMZcCTVGQkhYpEkqzVqrF6QSKnEIhZWXLpSa1uQYPGzbiWt1VjLYuBRk4b8un2MTxX4heW9PH5oyHN/V76djTsPBo4dFF/pN26SZ1vPFoxCtCKBhaldP34e+OOSRfB/lrb909L2z1RvekKIMJIkYlRSniaNF3VYcelKrW1+2cBhc0qCn9gpLwuTFlEsiX7Pt7uzg12HT3ie05GDcxPTnB4vnldeZuiRA2/w5sgYvV153+zhA0dPplIHs54tGIVoVYKSSn4EvFX68wTwbuAxisklr5X+/ZPA16o8RyFEAEkSMZIkPkC0ZJRK5pzzcGc61rY4BInBiztyiRNXvAgSO0mfT6X4Pd9CoeDpLm7LwSX5jlmZ11B89v3Pvcb9z7zC8ZGxmTXfdfgEm9cs4cUta2e5+CtJCnITZHUVQlSHIJexilEL0QAkrT2YpPhvWu7RuMWl47oc+wLi3D67/jrPaye1PAXV/wP/51NNl2jc51sowGmPJBTAMznF757SqoNZzxaMQrQqkQpTp4Ex5rPALwAGGKfoev6stfZl1zE5YDuwCVgIHAQ+aa097DpmIfDHwG2lTU8An7LWnnId8x7gIYrlcd4GHgXus9bGdCIJ0RjUqrNDmi/qOMWl47oc/UTax5b3zel4UilBhaMdyp9PLVyiSZ5vnGQRvzVP47OYdgtGIUQ4keoQQlFkGWMeMsYMGGMuK237eWPMT0cc4meAh4EbKbbFmwSeLYtV/B1gC/Ap4AbgBLDHGNPlOuYx4H3AR0p/3gf8pWue3cAeYLg0xm8BnwbuinqvQghv/F7Iab2oK3U5OrUNt++25DvauLjjQkW+7nw7y6/oSWWe5Tj1//wKcZc/n3q5RIOer9++7rx3q/pqirO0XM9CiOhELUy9HvgGcAVFMXdxadc1FC16oVhrP2yt/TNr7cvW2m8D/wJYBKwuXSMH/DbwgLX28ZLl8ONAF8UOKRhjllEUgZustS9Ya18AfgP4OWOMKV3ql4D5wMdL1/pr4PeBu0rXEEIkpNovaq/YxluvX8zD+4+FFt0uj28cGZvknKv2zOnxqarH86VVYLpaBMWO+u27++Zray7Oksa4CiGSE7XszH3AXdbah40xo67tf0fRopeELoqC9GTp56uAPuAZ5wBr7TljzD6KVsVHgVXAO8DzrnEOAGdKx9jSMfvLWuo9XbqHJcDrfhNqb8+xYMH8hLcjqkl7e5vWpkY8ceg4/XuO8ObIGJf1dLJl3XXctvxyAG5fdRWXzM/77vcjzvrdvuoqbl911cxcPve1lxmbcLlW97zCJfPzc675yIE3IrVTe+TAGzPjRyHoeXjNPcrzuaynk+MjY3POv6ynM/Q5xZmP3xz97t9v3yXz8/Q/e4Q3TyW7ZhKC5inio/9DG59qr2FUQfhPgN0e298GfsxjexT+PfC/gRdKP/eV/i7/+j5M0TLpHPOWOxbQWlswxpxwnd8H/MBjDGefryCcmiqokntGUZX92vDAs0dm1ZI7PjLG5776Ms+/cmKmzEhXvp1crmhsn54ucObseOjaJFm/gcFhdgzYub13J6b54tOWtVcumLX9TQ+B5cWbI2OR51Ie6+c8jzNnx32tVWuvXMDaX1sxa1v59T6x+krPsj+fWH1l4NySzCcOfokua69cAB+6ji8+bXlzZIwvPm1Tu6aoDfo/tPHx6VSS2vhRBeHbFEXZsbLt72Ou+ArFGPMl4IPAB6213hVUhRCpE5TZOjA47FlYeGxyetb2066ix9WqD+cIH7/yMV6u1agdNOLEvlWr6HTSbNxqFsEOSnQBuH/PK7MttaoLKERTEVUQPgZ80Rjzf1Es9N9hjPlnwIPAn8W5oDHmD4H/G/hZa+1R1y7njdMLfM+1vde1bwhYZIzJOVbCUlzg4rJjyv+H6nXtE6IlCctsTZrQkKYgcQRSLqSwtJeoCyv/AvFj36oZ65ckG7ea8wlLdHHEYPk+CUIhmoOoWcafp+hqfQO4lGILu+eAvwd+L+rFjDH/HrgduMla+92y3a9TFGzrXMd3Amu4EDP4Qun6q1znrQIuKTtmTelch3XAceZaOIXIDE6GbFjyRFLCXviViAq/c517uu53n4qVEBIkBv1EnVciwseW91WUmFDtrOq4VHM+QWJTdQGFaH4iWQittRPALxljtgE/TVFI/oO19pXgMy9gjPkyxczinwdOGmOcmL93rLXvlGIB/wjYaoz5LsUeyZ+nmETyWGkeg8aYp4BHjTGbSuc/CnzdWutUXH2MYubznxtjvgBcR7G93j2qQyiySi3q0oW91KO6XL1wBInbytfd2cGZ8UmcRN+ge/ISq1605QgUdXGsblEKQ1fS4i8t3PPsyrczry03q6OI13ySFL0Oqv13bmLKs0C16gIK0TxEdRkDYK112tYlYXPp771l2+8BdpT+/QcUS9p8mQuFqddba92ZzXcA/4Fi5jAUC1Pf6ZrjiDFmXWmMb1LMYu4HvpRw3kJUnWrGhjmEFfuN4nL1whEk5aI2ToeLKJamzo42XzEYVwBFFeDlsX5OQs323Zb+516jUCgwOj4VuyNH1PmWz/P0+BQdOejp7OD02KTnuUm/XPiJ39VXL+RrL82NtpnXllNdQCGaiFBBaIy5mGLB6I8BV1OMITwK/Hegv6y8iy/W2tAagCUL3g4uCESvY04CvxwyzreBtVHmJUQWSOqSiyOEwqxdznkP7n11VuJIGI7IO3t+MpKYTJIQ0hdDNEURQHEEuGN1vHCd4rNxC944Ft048/Wa52QBLp7XzrOfvLHieyu/T+d89+fp4f3HmPTwrVw8r03xg0I0EYGC0BjTQTFW8H3AU8AuIAf8JLAN2GCM+WfWWu8mmEI0KWn3oU3SqiuuEIqS2eoWP0Gt2MqJ42r2SwjZ5tNnNwc8uWml73hJBFAUAV6+xucmpgIF79jkNDsGLNt328DPRJz5+s1zaHScjTsPeq5jJfF+Xi53v/7HozG+NAghsk+YhXATcC3wPnc/YQBjzD8B/hb4deA/Vmd6QtQXL+EHpB7vlyRWLYkQKhd823dbHt5/zFcYbtx5MHFcoRdBCSH9z72WKE4tiQDyE+AFYOPOg6y+eiG7Dp+YtcZRmI4QLxlnvkGWU2d7+bXS7gOsvsJCtAZhWcb/HPi9cjEIUGot9++AX6zGxISoN+WZr86Lt/+511LvQ5ukVVclbmav+/LKAK40i3ReW47ufHuke9py0zWJWqQlybz1ajHnMDQ6zuOHhmLHUpbj/ky4M8hzPsEzfpZTv3n6XSvt9oJ+czg3McXA4HDVs+OFELUhzEJ4PcX+wn48SzGDV4imw88C5ycUKhVPcevSJbXcxLEsxs087uns4OJ57XNcmU6FfUc8+LmsL2rP4RgJezo72HLTNaHPJIl11e0+T9MCWs7w6Pic7i8Fn1oHQ6Pj3NC/j+58O3fffO2sz4PbSu03X+fzl7TotR/OeV/629c4de6CBXdkbJL7njpCoVCIlEkuhMg2YYJwIfBWwP63gAUB+4VoWOIKvFq70JKWRIljWYyTedzZ0RYo4EI7YZRdZzyihS6pAHL2+8UuetGdb2f+RR2RRWR3Z4dn9xcoltDxqrd4enyKewfszBzLvyj4ufHdn78kRa+D2LCsl0cOvDFLEAKzyt84qGC1EI1JmCBsB4ISRqZLxwjRdPhZY7rz7ZyfKsQWYmknoiQVQnEsi0HXiHs/QZZJrwzlOMIiqQCK4+bv7Gibsdyt6N9HWFHTzo42xif8Ey8KhaIb3WstJgv43nu9aiNG7RUNKlgtRCMSJghzwH82xvj9diuqWDQtfi/eu2++FognxKpVeDqJEIorKMqvUe72vecWE2kOQRmzcc9xU4nQDhr/Y8v7OHD0pOe4fqK6LVcUer1deVZfvdDXOgiQyyW797RdwlG5rKeT4xFFoRJOhGg8wgThX0QY4z+lMREhskbYizfOC7gWhaejUomgqETYBokov1Z1YcKiUqHd3dnhmdnc09nBZz50ne95XqK6IweX5IsFowGetT8KvHZQez4Ivve0XcJR2LLuOj731Zdn3fO8ttysGEKofScXIUQ6BApCa+2v1moiQmSRtF68WesFW4mLNamw9bNMBsUnhgmLSuYzMDjMmfG5YnBeW44tN10TeK5XEe/JwoVi1ZUmqnTkwu+91ty2/HLOnB33LMNUa2ulECJ9YrWuE0Iko1lquVVa9Bi8O2F4PZuezo5QYRE0nzBXchodOM5Ppd8e3Z1lnDX8vkhkca5CiHhIEApRxgPPHuErLw0xXSi6Mz/63r5A92EUqpkIkHayShCVCls/QeH1bLysdOX36ufy7e7sCHUl+4nJqB04vKyTlZID9t65OtUxk+D1mbp91VX1npYQooqEVzwVooVwasY58V3TBXj80BAPPHukonGTFJ6OgleR6W27LTdUqUhw2kWPIfqz8brXM+OTzGubXem5s6ONQqHg60p2SFLQ2k0Uq2h3vn3mvno6O0L/w62FxTiskLRf4fInDh2v+tyEEPVDFkIhXHzlJe+s0K+8NBRqJQyz1HlZxyq17gVZqapRJDhpQsoTh45z79e/M2PNK3eLRolp9LrXyQJ0X9TGj1/UMWs+fv133SKuUqttWNFud5kaKK71vQPWN5mkFskYUZJw/OIy+/ccYe2vrajq/IQQ9UOCUIgSA4PDvi/rsIzQJNmuaZSiCbNSVSOTuVwUOla3oPu87+kjTLji7cqLL0cRxkEu3nI3q19cYnnxZvd9xBXkQUW723Jw6/WLI8UsQtEqmtTVH+dLRZQkHL/nHKcOoRCi8ZAgFIIL4syPNp/+sw5Jsl2DeiJHFQZRWsulnckcV8g+vP/YLDHoMFkodgnpf+41zoxPhrY/ixO/GNX6Fyfbulx4rb564axWe26mC7Dr8AmWX9ETKrRywJObVkaag9ec4qxFUC3IjTsPsnnNEt/nfFlPZ6I5CiEaA8UQCkF4gsBH39sXeH7c7NuBwWHPZIigc7zYvGbJnBi6cqLEpYXFlbkJEr9ehN3PyNjkHMuZ13hx4hfTjtn0iqt7/NDQTMkZL9KOWfQi7loEXcsRk6uvXuj5nLesqyyxSgiRbWQhFC2Hl4strGNFWPxg3OzboJZpcQTChmW9PLj3VSZ8HKMg0gAAIABJREFUhEnUlnpBPYajPiu/7VGsmFHGi+viTbN4c9KM4jRjFsPGj7I9rDf12OQ0B46eZOv6pXOe823LL+fUqbOJ5yqEyDYShKKlcAL73e7Jewesb/mSvq58pJIzcV/2QQJ09dULZ7WGC4stCyqTclH7XOuhI4iHRsd9u4SMTU6zfbelPcccV25Xvt3TMuYnZDevWcI2nySPIPx6K9ej5l1St7tzD84zH5ucnnnmlcQNuseP80XELar9RPrw6HjdnrMQon5IEIqW4sG9r85xT7o7TLiJY72Ja73ye5F3tufYdfhErESTIAvc6fGpWeeXWwODkmUK4OnKzXd0zOkwEtYL+Ut/+xqnznm7yL3wGi8oeaLatRiTWjmHRse5+aEDnJuYZqL0sKcLF+6v0jkmsTo6Ym/jzoNNUSxdCJEO7Tt27Kj3HDLD9HRhx9jYRL2nITzo7JxHGmvzUICr1k13vp1/uy5ezNnSRZdyx/vfxa/feCV3vP9dLF10qe+xC+fP44XXTzLpUmSdHW3k57Vz5vxs69vkdIHBoXe44/3v8h3r719721fcuc+/6yuHOeUTuxiV85PTbPvIdQwOvcOZ81P0deW566ZrAp/VksVd7Dvy1qz7dTOvLcelF7VzfqrgOZ4jZJ25v3N+ihdeP8llPXle/dEZ331BaxAHr/WKyvhUYc7ahK1pVJYuupTLevKx1sLB7zN4103XeD63tH4HRX3Q+jU+Xmt4ySX5N4GdaYwvC6EQHsy/KLxtWiX4WRSj1M/zolAIFirO+WlkHPd25UNdiuUWu09/2MyKS+vKt5PL5Tg9NhnJovfg3lcDkycqzdYOw2u9Tp09z5hH9rSfG76ctLK/o7p3vayoXrGCchUL0ZpIEIqWoscnVrCctEu1gPcLubzcSJT6eeUE1bcrPz+p69MhaZLK5772MlvXLfUsr+I8l+277SxR4m4h6EfQOqW9huXCq/w+gTmu9CBq6Zr1Sxzaut57TYQQrYfKzoiWYstN14SWaYG5L+s4ZVm88GsHVj5O1NIq7vmECTz3+V7jxyFK6RbPUigT0+wYsHOen99z2fzf/vesFoJ+9HblY5VzqXQd3fiVtumLIPRq0ZXETdzyNEKI1kMWQtFSlLv+ujs7ZhVFhrkv6zQ6ikQtQh0lOcXLMuVHeSZreZZpVPemM1aU+/WzzE17FJ72Eyrf+P7pSHNy1ilKYkUa6+i28ga5vcvn05GDS/IdkV3kaRO3PI0QovWQIBQth5frL0iAJelC4iZuEeqwmLAoNfEcAeLVWq58/BX9+wjThJ0dbbPK4bjFUHdnB4VCgdHxKXq78r5ladyMTRYthglyNGa4eF7bnHUKioVLYx3dQs99j349gbMSmxe3PI0QovWQIBQtT5gAq9S6klYR6ijXzQFd+XbOTUzPiNAwS1hYXGFfqU2buxyOWwy5xe7Q6Djz2nJ05OaWrCmnEjEIMDE5zcDg8Mz6hQmuNNYxSIi7xWXW6vhVoyi2EKK5kCAUIoRKrStBgiPqC9ltxczlwC+p+J5bDA/vP8bp8dnXdCxyh344woGjJ2dZroIKR7flivMPS+5wMzFd4OJ5bUxPTicSfZ0dbbznsktD3caTBVLp+5zGOpYfU+26iHHJotVSCJEtJAiFwPsFDv5Zv3GsK35CpDvfnshVGVRhxrkHL6YL8PihoZmfh0bH2bbb0tPZwQ3/uNtTgDmCLqSqzRzOTcRr89bXlZ8jVCrNMi6nUitZlAzt3q58KrGK1SBrVkshRLbIhdUvayUmJqYK6tWZTRYsmF+1PqpxkjQgXsuxgcFh+p97bU4MYWdHG1vXLwXCrTZ+HSW8yJGstExnRxu3Xr94xnqYi5FsUil9XfnQ0id+zyDKuW4qsdyFfU6cNfX7EhF3rlmjmr+Dovpo/RofrzVctKjrW8AH0hhfFkLR8kRJ0nAIe6mXZ6G6W5Y5dOfbufvmawEiWZLiWMG68u2elrAwxianOXD05My9rejfF/ncShkaHWfjzoOB4iytGLhKrGTlble/LOOkxcWFEKKeSBCKlifOizro2KAsVDdOF5SNOw9GynqNY/FzXLVb1y+NncXrvrewa3YHZBkn7fkb5lbNu4o+O6K61i7QoAx1J3lIGb1CiEZEglC0PHFETFjHkChWOcci5nfNctHpZx3L5ebG6k1MF3h4/7EZS18cS6H73oISTcKspDc/dCC07IwXfiVgvFy15z1axtUav1jBW69fPCsjG5TRK4TIPupUIupOmt0jkhCne8fqqxf67otjaQwSoOWi068jxphP4oYjOAFuvX4xERqzAHD2/GSkZx92n3fffC0dEa8ZZeysdtnwm9eBoyc910sJHUKILCMLoagrWcjIdK7z4N5XQy1buw6fYPkVPYnq+UXBsSSF9T0eGBwOLD8zNDrOvQOWXC4X2W18enxqVgcRP8JcnxuW9XLohyMzGcJtOeic187Z8+FWQ6+xs9plI2heyugVQjQaEoSirlTaPaISykWXk+jhrvdXLqaC5rZ5zRLue+rIrCSSNqCrs8O3U4mbqMkmjogOE3qTBWLXi3Hur5LaiQODw+w6fGJmftMFOD85xby23JwEGzd+btWgmLx61vtTrKAQopmQy1jUlXpZfxxRNTQ6ToHZouvJTSt5cctaXy0VNLfyMk5x5JiTbBLmIo2TFZ0ER1x50dPZESq4vOY3OV2Mb3Tc131deT62vC+SW9XLpe+00vNaQ8ftXe1QBL95KVZQCNGIyEIo6oqflaUAoaVIKiGKZTKuBejh/cfmtGsrQCTrIFwQmmEiudpi2bG0eSWybLnpmtDzg9zm04ULoskrW3f7bjvH0ufXZaP/udcChXO1QxHq3f0ja91QhBCNjQShqCtBNfPcL/HbV12V6nWjWCZXX71wVmcPCLYAVSrUujs72LjzoK9V0RGiacQq+lEu1uIKjihWuHLhHSWO1Kvci5/QdkrA1CIUwWteG3cejPzMkoq6LMTeCiGaCwlCUVfcwsNL5Dgv8dtXXZWqRSTM+ufEwZVz6/WLfa9ZqVA7Mz7pK3LcQjRJ4WkHJ07R6/zy2n5JEiOiZv66xXMS8RaW9FKPUIS4Iq0SUVfP2FshRHOiGEJRdzYs6+XJTSvxq1QyPDrOE4eOB8aLxcWrfIxbdPnF6R04etJ3zDjla7wodzc7lMfXlZehicq8ttyM4Csvi3LvLYa9d66uWExEFVxu4R21HmPUfZvXLKEr3+65z297GsQtjxN2fFAMZFYzr4UQjYsshCIzBFnt+vcc8Xx57hiwbN9t53TLCLIeRrH+JXnherU282pdF4cceBaBdlvvovY6vnheW0XWvyhEsZK6S+vcO+Bd/NoZK+51uvPtbFjWS/9zr3mel8sVJbRjbR4aHaetlE0ep0e1F3E/M0Hbw6yHynAWQqRNTQWhMWYtcDfwfuBy4FettX/u2p8DtgObgIXAQeCT1trDrmMWAn8M3Fba9ATwKWvtKdcx7wEeAlYAbwOPAvdZa+vf3kD4EtSv1q8/rKO13K7WodFxtu22HPrhCJ/50HVzzoli/Uv6wi0XWg88e2RWPb73v6ubb7/5TqLuIX4u86gu5FGfGotpuuK95jKvLccl+XZGzs3u+btx50Ffq6gzVpzrdHa0zZTtOe3jej89NjlHbDmfoUrj8OJ+ZoKOD3MJp9XbWQghHGptIbwUeBn4T6U/5fwOsAX4FcAC24A9xhhjrR0tHfMY8BPAR0o//wnwl8BGAGNMN7AH2AfcALwb+DPgDNCf+h2J1AhKZHjkwBscHxmLNd7jh4Z4/NDQHMuPn2XG6fAxPDpOd2cHHbnZbty4L1yvenz/8IPTzIvoVnZfL0q8WVD9RPAWJkni2IIEpN8a3r7qKk6dOjtrnDD3ZpAoC0t6iSu2HCqJw4sr0pJ8AXKeWb0znIUQzUeuvG5arTDGvAPc6VgIS9bB48BD1trfK227GDgB3G2tfdQYswz4DvBBa+2B0jEfBPYD77bWWmPMbwK/D/Raa8+Vjvk88JvAu4KshBMTU4Xyl5bIBvveOMXnvvpy4vp7nR1tM3F4UV2s89pyXDyvLZIb2ouo1/GiLQc7NphQt7BXX2Gv3r/u+48yx+58O3vvXD1H/K2+eqFnn96w1mwLFsyfIwiDnk9Yv+Qwgp7B9t02sD5kDnhxy9rE140j0vyOj7PetcJrDUXjoPVrfLzWcNGirm8BH0hj/CzFEF4F9AHPOBusteeMMfuAGym6fVcB7wDPu847QNH6dyNFq+IqYL8jBks8DdwHLAFer94tiGpx2/LLOXN2PNQK5keYu82LiekCP35RB3vvXJ1ozkkD/L0EVpw4tCjWI3cMnRenx6d44Nkjs8Tf0Oj4nDI8kNyqtnnNEu4dsHPcxvPachW7PoOeQdB9Q2VxeHFjM/2Ol0tYCFFrsiQI+0p/l6eNDgNXuI55y23ls9YWjDEnXOf3AT/wGMPZ5ysI29tzLFgwP8HURbX5+ktv8siBNxgeHeeynk5+xiziv3/rB0xMRVeFw6Pj7HvjFI8ceIOxyWnaczBVgMt7On3d0cOj44k/E5cFjOvHgos7+N1bf5Lbll8eaazLejo953f7qqt8azduf/Iwf/Xi90O7qHz1pSGiPt6w59Te3jZn/+2rruKS+Xnu2/UdTp0rxvwtnD+Pz9+ybM79J8HvGXz6w4bPfe1lxibmfiHonNfGpz9s6v7/gPNs+vcc4c2RMS7r6WTLuutSeS5J8VpD0Tho/Rqfaq9hlgRh3ZmaKsiknkEGBoe5f88rMy/w4yNj/Pdv/oDJmNm73Z0ds9zOU6WuGZ9YfaWv1ai3Kz/rM+HlQj1w9KSnJe4Tq6+MXS9wbGKaM2fH53wOVy1Z4GmdW7VkQazP7MDgMI+9+P1Ix8bQ2rOek5cb1B1DWL7/rp+9Zo6VrJq/h2uvXMDWdUt9s4zXXhnvmVZznmt/bcWsbfWcl1yOjY3Wr/HxcRmnNn6WBKHztusFvufa3uvaNwQsMsbkHCthKfZwcdkx5T6YXtc+0WA8vP/YHGuOXymXNh9XcmdHG4VCwTdzM4qLzisBwy3SnOzmB/e+OqvA844BG9m97ed+9at/eODoyVhxa1ELR4P/sywnSvLLJfPzrL1yQSodNtKK0ys/J6h9Xi1RSzohRD3IUmHq1ykKtnXOBmNMJ7CGCzGDL1DMVF7lOm8VcEnZMWtK5zqso5iwcqwaExfVJU4sXqEA39iylo8t76OtVLW5LVesMehXdmV4dNyzWHN5HF9Qdqqb0+NTM0WzNyzrJW7eltf9BmVGb9ttIxfsjpPk8tH39s0ptN3Z0cbHlvf5Pie/cin9e44E7o8qVB1BGfV+ox4fd9xqkZV5CCFaj1rXIbwUuLb0YxvwE8aYnwLettZ+zxjzR8BWY8x3gSPA5ykmkTwGYK0dNMY8BTxqjNlUGudR4OvWWqdOw2MUaxn+uTHmC8B1wGeAe1SHsDGJ0xKutyvvWe5l1+ETdOXbOe0hCp0kgrCEgDjC1G3pi9vSziupIc4YflbGOKKiO9/OZz50Hcuv6IllrfJ7RsdHxhgYHK64w0bclm1Rj89KK7iszEMI0XrU2kL4AeAfSn8uBu4p/fve0v4/AP4Q+DLwTeAyYL2rBiHAHcAhipnDT5f+/S+cndbaEYoWwctLY3yZYv3BL1XrpkR12bxmCZ3zZn9U2316tq2+eqHvSzWXy3m2lvNqY+dF3OxTp65h3NIzZ89PzhFvcdvieQmsqFY4d4Fnp63gi1vW8uSmlaGiJOgZ3f/MK3R3en8Hjfps0+wGUsn51SIr8xBCtB41tRBaa/8O/Nuvlix4O0p//I45CfxyyHW+DSQrJCYyx4ZlvVwyP88Xn7Yzlqqz5yc9rX1OgocXI2OT3PCPu/nG90/P2r7r8AmWX9ETKnailqtxk6QO4enxqTmdVpy5bfMpWFyOV4eToLn0deWr1qnEYWxymovai6I8aTmVNLuBVDJutcjKPIQQrUeWkkqE8OW25Zez9soFMz+v6N/neVyYACsXg1AUKttLySBBRai9atuNnDvPuaD+a2XkILTci8Pjh4ZmCdUoNfRgbpLHfU8dCeynHFbsOE6SQ5hwHR2f4p5bDA/ufXVG0OdjWD6Dkn+85hm1nl9W6v5lZR5CiNajfceOHfWeQ2aYni7sGBubqPc0hAednfNwr80TLw/xznnvJJGkjJfqrLxzfooXXj/JZT15Xv3RGe76ymH+6O+O8sTLQ9xw5QK2fcTw6zdeyR3vfxd9PZ288PrJ2CVwovI/Xv0//L/Pv8ETLw+xcP48LurIMTj8ju/xfV157rrpQhmX3/xvL3HWo96eQ2dHG3fddA1LF13qud9JcjhV6g3sfjZ+5yxddClP+qxPX1eeG65cwN+9+n9mntn45PSsMQcGh2c984Xz581ca+miS7msJ8/g0DucOT81c7+A5zzXXPPjrLnmx+ccXy5o/catddxeVubhRfnvoGgstH6Nj9caXnJJ/k1gZxrj1611XRZR67rsUl5/yas1Wdp059s5P1WYY60pzz4eGByO7MqthM6ONi5qz3m6yp1Wc+Xc4GNJhWL29fvf1c33T437Wv+StlALah3nZ+V06gBGbbvnJout3poN1bFrbLR+jU+1W9dlqeyMyAADg8Ns3HmQFf372LjzYGbLXbjLxFSL0+NTkUqkHPrhSEXXmdfmG1Y759peYhCKrti4azddKLrQ3SVOtu22fOjLz8+cG1TuJuga5WV8Lu/pnBF1QYkTScvSKBlDCCEqQzGEYoY0igbXEqdMzIr+fZHj8tLALTIGBoc9O4jE4eJ5bfzU4ks84xujUoBZsYKOuEvCyNjkzLoHlbsp/3x4xfA51jn3N9ugxImkwi4LyRgqKC2EaGRkIRQzVFo0uF5U46Xf2dFGj0+JFHfplDSezenxKf7hB6f52PK+0GN7Ojt8y88EJY7EZWxymgf3vhpaksf5fMQpqOxVQsdJnAjKFgZ/C3bQmLVABaWFEI2OBKGYoVHdbn41+j62vI9vbFmbyK28df1Sttx0jac7d3RsMtSlGpfJAuz57luBc+3saGPLTdewdf1S/9pNKXJ6fIqvvRRu/Yzr6g3qChMk7IJEV3kIQVtutlitNo36ZUoIIRzkMhYzZMHt5sbtgrusp5NPrL7S0wXnVQ7G7a7bvGZJLPdpX1d+xgXqZXWbBvqfey1RF5IgTo9PcffN13omy3Tn21n37kWRys6kSZSKOl359thfJvy6wmxY1suhH47wlZeGmC5caDu4YVkvG3ceDOzi4YxXj7CHRv0yJYQQDrIQihnq7XZzU24NOj4yFuiCczpq3HOLAWD7bjvjUowrBFZfvZAHnj0SKCJHSlbCs+cnY40dhpf17N5bDHfffC27Dp+oqRiMSi6XC3X1RsWv7WDUtnf1stSldf9CCFEvZCEUM4RZ2mpJkp6uQUkxfTEseV97aSiSZSxu2ZuwotQXtedY+aV9M5axX1jeN9Op5ENffr5qJXb6uvKcm5hiZCyZuD09NsmWm65JpaBy0LpHsWDXy1KngtJCiEZHglDMws+VV2uSvNj9xMSOAUucfIuojUfiCrSgYdtycH7qwhHThWKnkv/1/VMMnR6P1Q0lDm7REtbRxI/ekosdKv8yEbTu99xiPEW4UwLHSUqpR9hDlr5MCSFEEiQIRSaJ82J/4NkjMzFnXlSpiUhs2nLec/HbDvD622NVm09fmWj5d88cIaCpiSedHW2svnohG3cenBFC99xiEguhoHV3xnS3vXNwrMG3Xr+YXYdP1MVSl5UvU0IIkQTFEIpM4ZQV8RIFXi/2B549wuOH/MVglpgu4BmjuWODqflc7r3F8OSmlbMETFQrZFuOmfhGR4ClVW4lShyr25LqZmxymgNHT/pmMAshhPBHFkJRE6IU7Q1qR3d5Tyerlizg4f3H2L7b0t3ZQaFQ8O3ckUUci5zXc4jr1na4uCNHgVxVW/iVUyjAi1vWAoRm/sYlzPXqFRbgZnh0XJY6IYRIgAShqDpRO6D4vez7uvJsWXcdn/vqyzP7oyRAhCVx1BLHyuUnVj763r5EHU8u6mhny03X0P/ca7GSQrye///f3p2HyVWVeRz/VneHbpakgxqSIJIgyEtkEBEDgyyyJIaAOMzi8MCMy4zKQAB1DPtgCHHggZHAg5LMgMugqCMujwuallUlExwEVBggvoAxkTGmAwohQDp0d2r+OPcmt6tv3aquruqq6vp9nqefdNU9detWnXTX2+855z2TOtvLCrBrvYgjK6ArZ8cSEREZOQWEUnPlrhjO2jf3wm8/SpGRwqLac6EkSjV38KhUXEuvUM/q3hEHc0kv9g1sD6DiLGw5q6njnUiSmbi5B0wpucK6cPh2rBdxZNV91KpeEZHKaQ6h1FxWoJeca5YVRIw0GISwWrgRgkGA7zy6Ydi8up7VvXzqR09WHAxCyIDG27gB3H7m4Sw5yVJ3WCn04tbBIXP/fvj4Rg7ZaxLxQ9tyMPsNkzLn41Vau7JndS9zlt3P7KX3MXvpfZxw46rMeYdZc0shZDc1V1BEpHLKEErNZWV1kkOXabXcxott+eHDtMtXri0rYG3PZQfEcUC3aIXzyO83ba9dGGf/yg2J+wa28eAzLw655gefCXssx+csVEm5lTgQTr72F7cOsqTHh5wz2b7Y/4vCldIiIlKZXD7fGBmURtDfP5h/4YVX6n0Z407WBzqED/Xbzzx8e9ux3p5trMVBzOUrvKxgrVRAWGhJouxLz+resp+n3HNWYvLkXYh/tuYsu79oVjT5fyFWLDOY1lZqJ9mH0nzUf80vrQ+nTJn4MPD2apxfQ8ZSc/F2bMUkP+zjLei6u9KT17noq7urg0md7ZQeGG088aKaiZ3tZbUf6XB5vE1bHIhX40++am391rO6N3OIPG16QT12H4mHqOPh+ErL6IiINAsNGUtZyikbkyWrtEradLdimeuJne3cc+6R22/HdQibTd/ANjo7Okac/StHHCiVKtFSyTlHq1RgmTaPdKwXrpS7Kl5EZDxRhlBKij8gR1t8eCQ7iWwuUv4keX/P6t6mDAZjL/YNsOtO5WUJRyIOlKqZQatW8JV1TR05UhejVLpwpVJZq+JFRMYrBYRSUrU+IKcVCSrS7i8WgCTvv/aep0f0/I0mDzUprB0HStUK4qoZfGVd06L56fMU4ykHY7X7SD2GqEVE6k0BoZRUrQ/ItEzPhLYcr7w6MGyuVjlZoWbapWSsJEff097DUqZN7GTJSVaz4KtYv5ZatBLPLf35wmOGbblXbeX8MSIiMt4oIJSSqvUBWZjp6U5sP5csnTJn2f0AQ9ru2d01JDBpxUn+OYbvhVwoz9B5ep2J9pM625n9hklFH9uRgy39g1y+IpR/uSJlv+PRqjTbN5aLPMZ6iFpEpBGo7EyCys6kSysb09XRNurMUVah4cLzJ5fbp9WxawVd7Tkunbd/WfUF07ah6+poY6f2XNHM6oS2obu6VKOPY/ete4FP3+EVLUoqVrYoqz7iaI12EdV4pLIlzU391/xqXXZGq4ylpEqKD5cja8g5OUfx2nue3h7E7DyhjS39zVW4uloribcO5ofs83v4dfcVXaiTFvT1DWwja1OUwgA7bXvBSvSs7uWqu56ir7+yVbvFVkt/+5ENHPz67poEaln7KYuIjEcKCKUstfiAzNrBBELgsKTHh+yt22zBIFSvrMzEzvYhmauxyI+OZJ5osaza8pVrtweDscJgMysjl3UN1QhYRUREAaFUwUiG15JtJ3V10JFjSMCXlKP4sVb00tbBUQ+V7zyhjXyeYcP/nR1tqQWjy50nmlW7r9SipFJ1/7L+cNDKXxGR6tCiEhmVcmsU9qzuZc6y+1m0wre33dQ3wEA+LGZIo1hwqG0MH9Ydqf6BbZx84B7DFnUsPH7fUS2kyCpNVGpRUqmyRlnXoJW/IiLVoQxhixvt5PmsD/PkcGDWXsYD+bBgoq/aW3bIMAN5WLXm+aJ7AFf6f6FYpm7D5q10d3XQ0QbJ7k8Gm6UyiPNnTeWR328aVoRcK39FRKpHAWELq8YWXeXUKCxnCzUFgzuUWg08WsX6bDTzRLOGdTf1DTChPcekzjY2bx0cFmyWszXdxXP25+DXd2vlr4hIjSggbGHlZPdKKefDXPO8RubkA/fg4Nd3Z2ZVR6MWw6wLjp6Zeb39g3leu0vHkH2osx6blv3Tyl8RkdrRHMIWVo0dSIrthvGGyZ3bCwnniswRlHQ/fHwjEApzT+qs7l7HtRpmTRacLiYrMzmWW9OJiMhwyhC2sHKye2kK5x0eNH03HnzmxSFtkrdV+3xk4izt7WcezvKVa1OHjiupxzitxsOscQavWMHxrP9Xyv6JiNSXMoQtrJItutJWFRcGg8W0KVNYtg2bt2bu5DLSYLAtFzJ0y1eurfm2f6n/ryZoAYiISCNThrCFVbIDSTkLRIrJ50OWKqsYtexQ6fvU1dE2rI/iajWVLBwaqbT/VxfMM46ZMbkmzyciIqOngLDFFX54x7XfigULo1kgEgectVos0SpKrULO5cJexpu3DpLLMWx7u2ptSZelcAhY+6iKiDQ2BYRNZLQ1A4udcySlZ0ptN1dMPBRdGIBO7Gwnl8uxqW+AtpTgRYaK5wECRQPrLf3bGGjLccVJxqIVnnoeZWlFRCRJAWGTqEbNwDQjLT1TSYZv2sROjnzj7ixfuZbLV/j2YBbioCZkulotGMyRvhtLsfunTewcVlB6cY+nvm/92/IsX7m2aJCt+ZwiIpKkRSVNotT2XpUaaemZuERIueVQ4ozWDx/fOGQhyqIVzqIV3tJDx8Xi37T7J7TleOXVAQ5beh+n3PwAPat7mT9rauYK7t7NW4sG2a0WfIuISDZlCJtENWoGpik2BDyxs51Tbn4gdXh6/qypRcuhJMXDxKNZiCLQ3dXBy1sHtr/fyexw1hAaMUFEAAAN/0lEQVR+XOYl7XhWvUAREWk94zZDaGYLzOy3ZtZnZg+b2dH1vqae1b3bizXHWZ5yFavhNtpdJ9JKhHTkwjy0ZEbvqjufGnK95QSiJx+4B/NnTdVOJaMwbWInO09oZ6DIwpAFR8+kI2X4d0JbjgVHz6yotJCIiLSecRkQmtlpwA3AVcAhwP1Aj5ntXa9rSqvfVxhkZanVB3vaLhG7dnbQXzCmWDg8XU4gumrN82W3lXS9m7dmZofnz5rKovk2ZAi/u6uDT564//aVvtoFREREShmvQ8afAG5x989Ft88zsxOBs4FL6nFBo903uJKageUqLBFy2NL7UtslA5NyFpfE7VVqpnJZw77xsVK7fGgXEBERKWXcBYRmthNwKHBtwaE7gXeM/RUF1ZgDOFYf7OVsaRdfR7FVrsn2yWC2Fcqd5CC1/t9IJTPAhQG1hn1FRKSaxl1ACLwOaAcKx2J7gTlZD2xvzzF58i41uajp3V2s39SXen+tnrNSF8wz/uV7j9GX2B6ta0IbF8yzIdd6+hH7cHmROnfxeeL2px+xD6cfsQ8A339kPUvvejL1/Wh2e3Z38dPzj+X7j6wf9h6Wetz6TX2052AwH24vnLs/7zl4TwB23aWTpXc9yR829TG94FgzaG9va7j/5zIy6sPmpv5rfrXuw/EYEFZscDBfs90UzjpyRmqW56wjZzTcDg7HzJjMpXPfNGx4+pgZk4dda7FsYndXR2r7+PzHfPgwAK6++0m+8+gGtuVDbbxD95pU9t7IjaYjx/b+THsPt/QPsqlvYNjjpk3s5HvR+1Eofv+S71nhsWagnUqan/qwuan/ml9aH06ZMrFq5x+PAeFzwCBQOLY6Fdgw9pcT1HIOYC2UOzydNj+wq6ONhcfvW9bzXDxnfy6es/+Q+wqLcI9UXNi5u6uDfD7P5q2DQ3ZEqYadJ7RBPs+WaPnvpM52zj9hvyHvWeF7mPa6NPQrIiKNYNwFhO7+qpk9DMwFvpk4NBf4dn2uKhiPk/trEeimnfOCecbLr2xl6b2/2R7UpQVh5Si2BWDP6t5h5597wBRWrXm+Kq+t2f4oEBGR1pHLZ2110KSisjO3AguAVcBZwIeAA919XbHH9fcP5pVSb0wa7mhu6r/mpz5sbuq/5ldkyPhh4O3VOP+4yxACuPttZvZa4DJgOvAYcFJWMCgiIiLSqsZlQAjg7suB5fW+DhEREZFGNy53KhERERGR8ikgFBEREWlxCghFREREWpwCQhEREZEWp4BQREREpMUpIBQRERFpcQoIRURERFqcAkIRERGRFjcut64bhWcB7WYiIiIizWAGMKUaJ1JAKCIiItLiNGQsIiIi0uIUEIqIiIi0OAWEIiIiIi1OAaGIiIhIi1NAKCIiItLiFBCKiIiItLiOel+ASBYzWwBcAEwHHgc+7u4r63tVrcfMLgH+CjBgK/A/wCXu/liiTQ64HDgT2B14ADjH3R9PtNkd+Azwnuiu7wPnufsLiTYHATcChwF/Am4CPuXuqpFVJVF/XgUsc/dzo/vUfw3OzKYDVwMnAROBNcDZ7v7T6Lj6sEGZWTuwGPh7wufZH4CvAovdfSBqU9f+U4ZQGpaZnQbcQPjgOgS4H+gxs73remGt6VhgOfAO4HhgALjbzF6TaHMhsBA4D5gNbATuMrOJiTZfA94GnBh9vQ24NT5oZpOAu4De6BwfI/xB8IlavKhWZGZ/TvjAebTgkPqvgZnZZGAVkANOBmYR+mpjopn6sHFdBJwDfBQ4gPC+ngNckmhT1/5TYWppWGb2APCou38kcd9TwLfc/ZLij5RaM7PdgE3Aqe5+e/SX7XrgRne/MmqzM+EX2vnufpOZzQKeAI5y91VRm6OAlcAB7u5mdjZwDTDV3bdEbS4Dzgb2UoZidMysG/gF8GFCJuIxdz9X/df4zOwq4J3ufmSR4+rDBmZmPwD+6O4fSNz3JeC17v7uRug/ZQilIZnZTsChwJ0Fh+4kZKmkviYSfn8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          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ],
      "source": [
        "fig, ax = plt.subplots(figsize=(10,6))\n",
        "ax.scatter(df['Credit RM million'], df['Debit RM million'])\n",
        "ax.set_xlabel('Credit RM million')\n",
        "ax.set_ylabel('Debit RM million')\n",
        "plt.show()"
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "**Heat Maps**<br>\n",
        "Heat maps is also a way to find the relationship between features. The color of heat maps represented the value. "
      ],
      "metadata": {
        "id": "oskyFa6QCwnI"
      }
    },
    {
      "cell_type": "code",
      "execution_count": 25,
      "metadata": {
        "id": "fOQ9cTWiVJJ8",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 592
        },
        "outputId": "45f83fe5-5093-477d-afa0-786ad3c7f210"
      },
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "                       Year  Credit RM million  Debit RM million  \\\n",
              "Year               1.000000           0.048623          0.043342   \n",
              "Credit RM million  0.048623           1.000000          0.906899   \n",
              "Debit RM million   0.043342           0.906899          1.000000   \n",
              "Net RM million     0.033404           0.658947          0.280664   \n",
              "\n",
              "                   Net RM million  \n",
              "Year                     0.033404  \n",
              "Credit RM million        0.658947  \n",
              "Debit RM million         0.280664  \n",
              "Net RM million           1.000000  "
            ],
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              "      <th>Year</th>\n",
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              "      <td>1.000000</td>\n",
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              "      <td>0.658947</td>\n",
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              "\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-9bee2882-9670-4d67-be54-e2043a495c11 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-9bee2882-9670-4d67-be54-e2043a495c11');\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",
              "  </div>\n",
              "  "
            ]
          },
          "metadata": {},
          "execution_count": 25
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 720x360 with 2 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ],
      "source": [
        "plt.figure(figsize=(10,5))\n",
        "c= df.corr()\n",
        "sns.heatmap(c,cmap=\"BrBG\",annot=True)\n",
        "c"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "E0U3IWm8VJJ9"
      },
      "source": [
        "## Asking and Answering Questions\n",
        "\n",
        "A total of 6 questions will be asked in this section and all of them were answered by using pandas, series or visualization(matplotlib & seaborn).\n",
        "\n"
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "import pandas as pd\n",
        "import numpy as np\n",
        "import seaborn as sns\n",
        "import matplotlib.pyplot as plt"
      ],
      "metadata": {
        "id": "f2ASfZ61LLEK"
      },
      "execution_count": 26,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "7Lor5rHMVJJ9"
      },
      "source": [
        "#### Q1: Which quarter of every year is profiting?"
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "We can observe the profit quarter by looking at the “Net RM million” column. Pandas groupby function has been used to group the data based on year and quarter. Then, the sum function computes the sum of numeric columns based on year and quarter. "
      ],
      "metadata": {
        "id": "jamFmNunBxzp"
      }
    },
    {
      "cell_type": "code",
      "execution_count": 27,
      "metadata": {
        "id": "D-PdOKqCVJJ9",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 1000
        },
        "outputId": "1b636434-e5dd-4071-e312-c2d331440e82"
      },
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "              Credit RM million  Debit RM million  Net RM million\n",
              "Year Quarter                                                     \n",
              "2008 1Q                   29440             24355            5084\n",
              "     2Q                   27531             18186            9345\n",
              "     3Q                   31605             26779            4829\n",
              "     4Q                   29230             21602            7628\n",
              "2009 1Q                   30333             26869            3466\n",
              "     2Q                   27618             28344            -726\n",
              "     3Q                   28227             23483            4741\n",
              "     4Q                   37322             27720            9603\n",
              "2010 1Q                   32989             26529            6460\n",
              "     2Q                   37189             26376           10806\n",
              "     3Q                   28325             21258            7067\n",
              "     4Q                   25158             19125            6032\n",
              "2011 1Q                   23771             14173            9599\n",
              "     2Q                   30116             21054            9062\n",
              "     3Q                   36813             29331            7482\n",
              "     4Q                   34518             24809            9710\n",
              "2012 1Q                   35232             21865           13366\n",
              "     2Q                   41689             30798           10888\n",
              "     3Q                   34384             21818           12564\n",
              "     4Q                   35143             26574            8569\n",
              "2013 1Q                   39481             25101           14380\n",
              "     2Q                   30443             22843            7601\n",
              "     3Q                   39283             25184           14097\n",
              "     4Q                   16331             10694            5638\n",
              "2014 1Q                   38281             28889            9390\n",
              "     2Q                   32416             22136           10275\n",
              "     3Q                   29894             23526            6366\n",
              "     4Q                   32339             24304            8036\n",
              "2015 1Q                   27899             21763            6137\n",
              "     2Q                   30505             23010            7498\n",
              "     3Q                   27113             23742            3371\n",
              "     4Q                   23546             16658            6888\n",
              "2016 1Q                   25232             21478            3755\n",
              "     2Q                   30039             21763            8274\n",
              "     3Q                   41079             32648            8429\n",
              "     4Q                   27341             20179            7162\n",
              "2017 1Q                   35242             20341           14903\n",
              "     2Q                   36409             22477           13929\n",
              "     3Q                   23370             17753            5619\n",
              "     4Q                   28398             23667            4730\n",
              "2018 1Q                   44464             31004           13459\n",
              "     2Q                   22639             17333            5304\n",
              "     3Q                   35648             31956            3694\n",
              "     4Q                   40219             27946           12271\n",
              "2019 1Q                   30128             23047            7079\n",
              "     2Q                   20768             18876            1893\n",
              "     3Q                   23118             19754            3363\n",
              "     4Q                   27319             22715            4606\n",
              "2020 1Q                   45396             35082           10315\n",
              "     2Q                   22505             19761            2742\n",
              "     3Q                   22559             20616            1949\n",
              "     4Q                   26067             20292            5775\n",
              "2021 1Q                   31800             24085            7714\n",
              "     2Q                   28372             21364            7008\n",
              "     3Q                   33553             26048            7508\n",
              "     4Q                   32338             21237           11101\n",
              "2022 1Q                   28396             17518           10875\n",
              "     2Q                   29059             19857            9204\n",
              "     3Q                   18124             13772            4353"
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-55044bf5-f0c2-45ad-9d60-3e4d6a49ab7e\">\n",
              "    <div class=\"colab-df-container\">\n",
              "      <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></th>\n",
              "      <th>Credit RM million</th>\n",
              "      <th>Debit RM million</th>\n",
              "      <th>Net RM million</th>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Year</th>\n",
              "      <th>Quarter</th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th rowspan=\"4\" valign=\"top\">2008</th>\n",
              "      <th>1Q</th>\n",
              "      <td>29440</td>\n",
              "      <td>24355</td>\n",
              "      <td>5084</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2Q</th>\n",
              "      <td>27531</td>\n",
              "      <td>18186</td>\n",
              "      <td>9345</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3Q</th>\n",
              "      <td>31605</td>\n",
              "      <td>26779</td>\n",
              "      <td>4829</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4Q</th>\n",
              "      <td>29230</td>\n",
              "      <td>21602</td>\n",
              "      <td>7628</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th rowspan=\"4\" valign=\"top\">2009</th>\n",
              "      <th>1Q</th>\n",
              "      <td>30333</td>\n",
              "      <td>26869</td>\n",
              "      <td>3466</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2Q</th>\n",
              "      <td>27618</td>\n",
              "      <td>28344</td>\n",
              "      <td>-726</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3Q</th>\n",
              "      <td>28227</td>\n",
              "      <td>23483</td>\n",
              "      <td>4741</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4Q</th>\n",
              "      <td>37322</td>\n",
              "      <td>27720</td>\n",
              "      <td>9603</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th rowspan=\"4\" valign=\"top\">2010</th>\n",
              "      <th>1Q</th>\n",
              "      <td>32989</td>\n",
              "      <td>26529</td>\n",
              "      <td>6460</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2Q</th>\n",
              "      <td>37189</td>\n",
              "      <td>26376</td>\n",
              "      <td>10806</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3Q</th>\n",
              "      <td>28325</td>\n",
              "      <td>21258</td>\n",
              "      <td>7067</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4Q</th>\n",
              "      <td>25158</td>\n",
              "      <td>19125</td>\n",
              "      <td>6032</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th rowspan=\"4\" valign=\"top\">2011</th>\n",
              "      <th>1Q</th>\n",
              "      <td>23771</td>\n",
              "      <td>14173</td>\n",
              "      <td>9599</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2Q</th>\n",
              "      <td>30116</td>\n",
              "      <td>21054</td>\n",
              "      <td>9062</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3Q</th>\n",
              "      <td>36813</td>\n",
              "      <td>29331</td>\n",
              "      <td>7482</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4Q</th>\n",
              "      <td>34518</td>\n",
              "      <td>24809</td>\n",
              "      <td>9710</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th rowspan=\"4\" valign=\"top\">2012</th>\n",
              "      <th>1Q</th>\n",
              "      <td>35232</td>\n",
              "      <td>21865</td>\n",
              "      <td>13366</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2Q</th>\n",
              "      <td>41689</td>\n",
              "      <td>30798</td>\n",
              "      <td>10888</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3Q</th>\n",
              "      <td>34384</td>\n",
              "      <td>21818</td>\n",
              "      <td>12564</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4Q</th>\n",
              "      <td>35143</td>\n",
              "      <td>26574</td>\n",
              "      <td>8569</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th rowspan=\"4\" valign=\"top\">2013</th>\n",
              "      <th>1Q</th>\n",
              "      <td>39481</td>\n",
              "      <td>25101</td>\n",
              "      <td>14380</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2Q</th>\n",
              "      <td>30443</td>\n",
              "      <td>22843</td>\n",
              "      <td>7601</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3Q</th>\n",
              "      <td>39283</td>\n",
              "      <td>25184</td>\n",
              "      <td>14097</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4Q</th>\n",
              "      <td>16331</td>\n",
              "      <td>10694</td>\n",
              "      <td>5638</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th rowspan=\"4\" valign=\"top\">2014</th>\n",
              "      <th>1Q</th>\n",
              "      <td>38281</td>\n",
              "      <td>28889</td>\n",
              "      <td>9390</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2Q</th>\n",
              "      <td>32416</td>\n",
              "      <td>22136</td>\n",
              "      <td>10275</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3Q</th>\n",
              "      <td>29894</td>\n",
              "      <td>23526</td>\n",
              "      <td>6366</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4Q</th>\n",
              "      <td>32339</td>\n",
              "      <td>24304</td>\n",
              "      <td>8036</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th rowspan=\"4\" valign=\"top\">2015</th>\n",
              "      <th>1Q</th>\n",
              "      <td>27899</td>\n",
              "      <td>21763</td>\n",
              "      <td>6137</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2Q</th>\n",
              "      <td>30505</td>\n",
              "      <td>23010</td>\n",
              "      <td>7498</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3Q</th>\n",
              "      <td>27113</td>\n",
              "      <td>23742</td>\n",
              "      <td>3371</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4Q</th>\n",
              "      <td>23546</td>\n",
              "      <td>16658</td>\n",
              "      <td>6888</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th rowspan=\"4\" valign=\"top\">2016</th>\n",
              "      <th>1Q</th>\n",
              "      <td>25232</td>\n",
              "      <td>21478</td>\n",
              "      <td>3755</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2Q</th>\n",
              "      <td>30039</td>\n",
              "      <td>21763</td>\n",
              "      <td>8274</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3Q</th>\n",
              "      <td>41079</td>\n",
              "      <td>32648</td>\n",
              "      <td>8429</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4Q</th>\n",
              "      <td>27341</td>\n",
              "      <td>20179</td>\n",
              "      <td>7162</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th rowspan=\"4\" valign=\"top\">2017</th>\n",
              "      <th>1Q</th>\n",
              "      <td>35242</td>\n",
              "      <td>20341</td>\n",
              "      <td>14903</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2Q</th>\n",
              "      <td>36409</td>\n",
              "      <td>22477</td>\n",
              "      <td>13929</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3Q</th>\n",
              "      <td>23370</td>\n",
              "      <td>17753</td>\n",
              "      <td>5619</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4Q</th>\n",
              "      <td>28398</td>\n",
              "      <td>23667</td>\n",
              "      <td>4730</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th rowspan=\"4\" valign=\"top\">2018</th>\n",
              "      <th>1Q</th>\n",
              "      <td>44464</td>\n",
              "      <td>31004</td>\n",
              "      <td>13459</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2Q</th>\n",
              "      <td>22639</td>\n",
              "      <td>17333</td>\n",
              "      <td>5304</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3Q</th>\n",
              "      <td>35648</td>\n",
              "      <td>31956</td>\n",
              "      <td>3694</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4Q</th>\n",
              "      <td>40219</td>\n",
              "      <td>27946</td>\n",
              "      <td>12271</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th rowspan=\"4\" valign=\"top\">2019</th>\n",
              "      <th>1Q</th>\n",
              "      <td>30128</td>\n",
              "      <td>23047</td>\n",
              "      <td>7079</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2Q</th>\n",
              "      <td>20768</td>\n",
              "      <td>18876</td>\n",
              "      <td>1893</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3Q</th>\n",
              "      <td>23118</td>\n",
              "      <td>19754</td>\n",
              "      <td>3363</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4Q</th>\n",
              "      <td>27319</td>\n",
              "      <td>22715</td>\n",
              "      <td>4606</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th rowspan=\"4\" valign=\"top\">2020</th>\n",
              "      <th>1Q</th>\n",
              "      <td>45396</td>\n",
              "      <td>35082</td>\n",
              "      <td>10315</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2Q</th>\n",
              "      <td>22505</td>\n",
              "      <td>19761</td>\n",
              "      <td>2742</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3Q</th>\n",
              "      <td>22559</td>\n",
              "      <td>20616</td>\n",
              "      <td>1949</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4Q</th>\n",
              "      <td>26067</td>\n",
              "      <td>20292</td>\n",
              "      <td>5775</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th rowspan=\"4\" valign=\"top\">2021</th>\n",
              "      <th>1Q</th>\n",
              "      <td>31800</td>\n",
              "      <td>24085</td>\n",
              "      <td>7714</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2Q</th>\n",
              "      <td>28372</td>\n",
              "      <td>21364</td>\n",
              "      <td>7008</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3Q</th>\n",
              "      <td>33553</td>\n",
              "      <td>26048</td>\n",
              "      <td>7508</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4Q</th>\n",
              "      <td>32338</td>\n",
              "      <td>21237</td>\n",
              "      <td>11101</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th rowspan=\"3\" valign=\"top\">2022</th>\n",
              "      <th>1Q</th>\n",
              "      <td>28396</td>\n",
              "      <td>17518</td>\n",
              "      <td>10875</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2Q</th>\n",
              "      <td>29059</td>\n",
              "      <td>19857</td>\n",
              "      <td>9204</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3Q</th>\n",
              "      <td>18124</td>\n",
              "      <td>13772</td>\n",
              "      <td>4353</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>\n",
              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-55044bf5-f0c2-45ad-9d60-3e4d6a49ab7e')\"\n",
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              "  "
            ]
          },
          "metadata": {},
          "execution_count": 27
        }
      ],
      "source": [
        "data = df.groupby(['Year', 'Quarter']).sum()\n",
        "data"
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "A line chart of “Net RM million” against “Quarter” for each year was plotted by using seaborn library(lineplot) and the label the legend by using the library from matplotlib. "
      ],
      "metadata": {
        "id": "QgTtYJJxCyEJ"
      }
    },
    {
      "cell_type": "code",
      "execution_count": 28,
      "metadata": {
        "id": "pR1HdQ4JVJJ9",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 368
        },
        "outputId": "64d8d9e9-084c-46c5-fb7c-d1b491b69551"
      },
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<matplotlib.legend.Legend at 0x7f57e2b12f70>"
            ]
          },
          "metadata": {},
          "execution_count": 28
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 648x360 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ],
      "source": [
        "for i in range(2008, 2023):\n",
        "  sns.lineplot(data=df[df['Year']==i], x='Quarter',y='Net RM million', ci=None, label = i)\n",
        "plt.legend(bbox_to_anchor=(1.02, 1), loc='upper left', borderaxespad=0)"
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "**Answer:** By observing both dataframe and line chart, there is only the second quarter of 2009 with negative value.Therefore, all of the quarters in every year are profitable except second quarter. "
      ],
      "metadata": {
        "id": "621Ud1P7Dsiq"
      }
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "c_REVnrhVJJ-"
      },
      "source": [
        "#### Q2: Which country has the most confidence in Malaysia?"
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "The confidence of other countries toward Malaysia can be measured by the amount of funds that invested by that country. In this case, we can get the data by grouping the data(pandas library) based on countries and calculate the sum of “Credit RM million“. Then, sort the data by using the sort_values() function from pandas library in order to make the observation easier. "
      ],
      "metadata": {
        "id": "Q7KsUdu8FK3_"
      }
    },
    {
      "cell_type": "code",
      "execution_count": 41,
      "metadata": {
        "id": "ShA3QyQpVJJ-",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "1d998798-8eee-47fa-cebf-f272a235334b"
      },
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Countries\n",
              "Total Country                  683353\n",
              "Singapore                      157157\n",
              "Japan                          156172\n",
              "United States                  136923\n",
              "Netherlands                    136494\n",
              "Hong Kong, SAR                 111870\n",
              "Germany                         69634\n",
              "United Kingdom                  61669\n",
              "China, People's Republic of     58694\n",
              "Thailand                        33134\n",
              "Switzerland                     31029\n",
              "Korea, Republic of              29641\n",
              "Cayman Islands                  24937\n",
              "Virgin Islands (British)        23641\n",
              "France                          21675\n",
              "Australia                       21308\n",
              "Bermuda                         21151\n",
              "Taiwan                          16966\n",
              "Luxembourg                      13099\n",
              "Denmark                          5199\n",
              "Name: Credit RM million, dtype: int64"
            ]
          },
          "metadata": {},
          "execution_count": 41
        }
      ],
      "source": [
        "data = df.groupby('Countries')\n",
        "max = data['Credit RM million'].sum().sort_values(ascending = False)\n",
        "max"
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "A bar chart from seaborn library has been used to plot the top 5 countries that have the largest credit of funds to Malaysia. "
      ],
      "metadata": {
        "id": "N3Vhe9_vIPTP"
      }
    },
    {
      "cell_type": "code",
      "execution_count": 45,
      "metadata": {
        "id": "dvyLd9MdVJJ-",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 615
        },
        "outputId": "1c68f847-b23a-4181-a231-afd799cf1bf6"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "/usr/local/lib/python3.8/dist-packages/seaborn/_decorators.py:36: FutureWarning: Pass the following variables as keyword args: x, y. From version 0.12, the only valid positional argument will be `data`, and passing other arguments without an explicit keyword will result in an error or misinterpretation.\n",
            "  warnings.warn(\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 1440x648 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ],
      "source": [
        "plt.figure(figsize=(20, 9))\n",
        "bar_chart = sns.barplot(max.index[1:6], max.values[1:6])\n",
        "for bar in bar_chart.patches:\n",
        "  bar_chart.annotate(bar.get_height(),\n",
        "                   (bar.get_x() + bar.get_width() / 2,\n",
        "                    bar.get_height()), ha='center', va='center',\n",
        "                   size=9, xytext=(0, 8),\n",
        "                   textcoords='offset points')\n",
        "plt.show()"
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "**Answer:** Singapore has the most confident on Malaysia, followed by Japan. "
      ],
      "metadata": {
        "id": "xx_3N_qYIk6Z"
      }
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "ya3o0SurVJJ-"
      },
      "source": [
        "#### Q3: Which block of country brings the positive effect to Malaysia in terms of economy?"
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "We want to investigate which blocks of countries profit from the investment in Malaysia. We can get the data by grouping the data based on blocks of countries(pandas library) and compute the “Net RM million”. "
      ],
      "metadata": {
        "id": "_fdKACY1Kr8-"
      }
    },
    {
      "cell_type": "code",
      "execution_count": 31,
      "metadata": {
        "id": "CaF9SiPeVJJ-",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 300
        },
        "outputId": "c59c6b43-b20e-4439-bf96-78ee6e8110be"
      },
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "                            Year  Credit RM million  Debit RM million  \\\n",
              "Blocks of countries                                                     \n",
              "East Asia                 598348             470895            352750   \n",
              "Europe                    797700             417194            317371   \n",
              "Latin America             437194             180599            121158   \n",
              "North America             161198             278818            207882   \n",
              "Oceania                   237756              49271             42886   \n",
              "Other Block of Countries  108804              79277             52175   \n",
              "Southeast Asia            251700             337692            267245   \n",
              "\n",
              "                          Net RM million  \n",
              "Blocks of countries                       \n",
              "East Asia                         118146  \n",
              "Europe                             99802  \n",
              "Latin America                      59447  \n",
              "North America                      70937  \n",
              "Oceania                             6386  \n",
              "Other Block of Countries           27104  \n",
              "Southeast Asia                     70444  "
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-ffc4190b-351b-4871-84df-9b643ccb413c\">\n",
              "    <div class=\"colab-df-container\">\n",
              "      <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>Year</th>\n",
              "      <th>Credit RM million</th>\n",
              "      <th>Debit RM million</th>\n",
              "      <th>Net RM million</th>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Blocks of countries</th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>East Asia</th>\n",
              "      <td>598348</td>\n",
              "      <td>470895</td>\n",
              "      <td>352750</td>\n",
              "      <td>118146</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Europe</th>\n",
              "      <td>797700</td>\n",
              "      <td>417194</td>\n",
              "      <td>317371</td>\n",
              "      <td>99802</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Latin America</th>\n",
              "      <td>437194</td>\n",
              "      <td>180599</td>\n",
              "      <td>121158</td>\n",
              "      <td>59447</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>North America</th>\n",
              "      <td>161198</td>\n",
              "      <td>278818</td>\n",
              "      <td>207882</td>\n",
              "      <td>70937</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Oceania</th>\n",
              "      <td>237756</td>\n",
              "      <td>49271</td>\n",
              "      <td>42886</td>\n",
              "      <td>6386</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Other Block of Countries</th>\n",
              "      <td>108804</td>\n",
              "      <td>79277</td>\n",
              "      <td>52175</td>\n",
              "      <td>27104</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Southeast Asia</th>\n",
              "      <td>251700</td>\n",
              "      <td>337692</td>\n",
              "      <td>267245</td>\n",
              "      <td>70444</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>\n",
              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-ffc4190b-351b-4871-84df-9b643ccb413c')\"\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 0 24 24\"\n",
              "       width=\"24px\">\n",
              "    <path d=\"M0 0h24v24H0V0z\" fill=\"none\"/>\n",
              "    <path d=\"M18.56 5.44l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94zm-11 1L8.5 8.5l.94-2.06 2.06-.94-2.06-.94L8.5 2.5l-.94 2.06-2.06.94zm10 10l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94z\"/><path d=\"M17.41 7.96l-1.37-1.37c-.4-.4-.92-.59-1.43-.59-.52 0-1.04.2-1.43.59L10.3 9.45l-7.72 7.72c-.78.78-.78 2.05 0 2.83L4 21.41c.39.39.9.59 1.41.59.51 0 1.02-.2 1.41-.59l7.78-7.78 2.81-2.81c.8-.78.8-2.07 0-2.86zM5.41 20L4 18.59l7.72-7.72 1.47 1.35L5.41 20z\"/>\n",
              "  </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",
              "      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-ffc4190b-351b-4871-84df-9b643ccb413c 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-ffc4190b-351b-4871-84df-9b643ccb413c');\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",
              "  </div>\n",
              "  "
            ]
          },
          "metadata": {},
          "execution_count": 31
        }
      ],
      "source": [
        "country = df.groupby('Blocks of countries').sum()\n",
        "country"
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "To obtain a better view, we plot the pie chart by using matplotlib library function (pie) and label the legends based on blocks of countries. "
      ],
      "metadata": {
        "id": "yFeOvyqCNzi1"
      }
    },
    {
      "cell_type": "code",
      "execution_count": 32,
      "metadata": {
        "id": "bGV1nEzqVJJ-",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 303
        },
        "outputId": "da31808e-febf-48e1-bc5a-6960056967ee"
      },
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 648x360 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ],
      "source": [
        "plt.pie(country['Net RM million'], labels=country['Net RM million'])\n",
        "plt.legend(country.index, loc='right', bbox_to_anchor=(2,0.5))\n",
        "plt.show()"
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "**Answer:** According to both dataframe and pie chart, all blocks of countries brought the positive effect to the economy of Malaysia. "
      ],
      "metadata": {
        "id": "rw9hEGbFOZgh"
      }
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "p4CcVO1TVJJ-"
      },
      "source": [
        "#### Q4: Which year is the most profitable?"
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "We can observe the profit by looking at the “Net RM million” column. Pandas groupby function has been used to group the data based on year Then, the sum function computes the sum of \"Net RM million\" columns based on year. "
      ],
      "metadata": {
        "id": "L2fHQTWWQJdv"
      }
    },
    {
      "cell_type": "code",
      "execution_count": 33,
      "metadata": {
        "id": "Wa96BGX1VJJ-",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "645eafc0-2ad6-40f1-98c7-a1d8ba2da26a"
      },
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Year\n",
              "2012    45387\n",
              "2013    41716\n",
              "2017    39181\n",
              "2011    35853\n",
              "2018    34728\n",
              "2014    34067\n",
              "2021    33331\n",
              "2010    30365\n",
              "2016    27620\n",
              "2008    26886\n",
              "2022    24432\n",
              "2015    23894\n",
              "2020    20781\n",
              "2009    17084\n",
              "2019    16941\n",
              "Name: Net RM million, dtype: int64"
            ]
          },
          "metadata": {},
          "execution_count": 33
        }
      ],
      "source": [
        "data2 = df.groupby('Year')\n",
        "max2 = data2['Net RM million'].sum().sort_values(ascending = False)\n",
        "max2"
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "A bar chart(bar()) from matplotlib library has been used to plot the \"Year\" vs \"Net RM million\"."
      ],
      "metadata": {
        "id": "6rqQ4GslizaS"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "plt.bar(max2.index, max2.values)\n",
        "plt.show()"
      ],
      "metadata": {
        "id": "cCVb37dgmNY4",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 324
        },
        "outputId": "3ab5a689-1192-4363-dd3d-77a80612af93"
      },
      "execution_count": 34,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 648x360 with 1 Axes>"
            ],
            "image/png": "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\n"
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "**Answer:** By observing both series and bar chart, 2012 is the most profitable year."
      ],
      "metadata": {
        "id": "97xJwF2-p5gb"
      }
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "uFuZBqX1VJJ_"
      },
      "source": [
        "#### Q5: How many countries for each block of countries are considered as a main investor in Malaysia?"
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "The number of invested countries in each block of countries can be obtained by grouping the data(groupby) based on blocks of countries first. Then, nunique() function of the pandas library will be used to calculate the number of distinct countries in each block of countries. "
      ],
      "metadata": {
        "id": "FLdFhf_44Bsm"
      }
    },
    {
      "cell_type": "code",
      "execution_count": 35,
      "metadata": {
        "id": "0XCOkgIHVJJ_",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "39a11c84-f9b2-485b-d6c3-fc24005a241d"
      },
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Blocks of countries\n",
              "East Asia                   6\n",
              "Europe                      8\n",
              "Latin America               4\n",
              "North America               2\n",
              "Oceania                     2\n",
              "Other Block of Countries    1\n",
              "Southeast Asia              3\n",
              "Name: Countries, dtype: int64"
            ]
          },
          "metadata": {},
          "execution_count": 35
        }
      ],
      "source": [
        "data2 = df.groupby('Blocks of countries')['Countries'].nunique()\n",
        "data2"
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "The horizontal bar chart was plotted by using the matplotlib library function(barh) and set the title(title), x axis label(xlabel) and y axis label(ylabel) also. "
      ],
      "metadata": {
        "id": "TyFxXZp858Gf"
      }
    },
    {
      "cell_type": "code",
      "execution_count": 36,
      "metadata": {
        "id": "xZWIg8jJVJJ_",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 362
        },
        "outputId": "4a63ee25-41ca-48b0-81dd-b9f7fafbec94"
      },
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 648x360 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ],
      "source": [
        "data2.plot.barh()\n",
        "\n",
        "plt.title('Number of Countries in Each Blocks of Countries')\n",
        "plt.ylabel('Number of countries')\n",
        "plt.xlabel('Blocks of countries')\n",
        "plt.show()"
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "**Answer:** There are 6 countries for East Asia, 8 countries for Europe, 4 countries for Latin America, 3 countries for Southeast Asia, 2 countries for North America and Oceania are considered as the investors in Malaysia. "
      ],
      "metadata": {
        "id": "gPMGa7UB1PI-"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "#### Q6: Which of the top 3 countries have the highest impact toward Malaysia investment during all these years?"
      ],
      "metadata": {
        "id": "5ONLPbxqmuay"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "We had used 'groupby' function to group up based on the countries names and 'sum()' to sum up each of their “Net RM million” column based on countries name in order to indicate the most impactful country. "
      ],
      "metadata": {
        "id": "ZetwaEZ1q-32"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "data1 = df.groupby('Countries')\n",
        "max1 = data1['Net RM million'].sum().sort_values(ascending = False)\n",
        "m = max1[1:]\n",
        "m"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "LLRudbY2paW7",
        "outputId": "2c77080f-c1b1-4bcf-e938-6fd924401ecb"
      },
      "execution_count": 37,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Countries\n",
              "Japan                          46279\n",
              "United States                  35244\n",
              "Singapore                      34101\n",
              "Netherlands                    31025\n",
              "Hong Kong, SAR                 27607\n",
              "United Kingdom                 18707\n",
              "China, People's Republic of    17362\n",
              "Bermuda                        14602\n",
              "Virgin Islands (British)       13638\n",
              "Switzerland                    13093\n",
              "Germany                        10843\n",
              "Thailand                        8255\n",
              "Korea, Republic of              7949\n",
              "France                          4513\n",
              "Denmark                         2613\n",
              "Taiwan                          2457\n",
              "Australia                       2170\n",
              "Cayman Islands                  1730\n",
              "Luxembourg                      1261\n",
              "Name: Net RM million, dtype: int64"
            ]
          },
          "metadata": {},
          "execution_count": 37
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "A histogram graph about sum of amount “Net RM million”  countries' name."
      ],
      "metadata": {
        "id": "x3wqwINtrxz0"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "plt.title('Countries with highest Impact')\n",
        "plt.bar(m.index, m.values)\n",
        "plt.xticks(rotation=90)\n",
        "plt.show()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 519
        },
        "id": "CmfyXjvMqjjL",
        "outputId": "28fd3614-0c00-4773-f883-2dfe356f4c87"
      },
      "execution_count": 38,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 648x360 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "**Answer:** Based on the graph shown above, the highest is Japan, followed by United States and the third is Singapore.\n"
      ],
      "metadata": {
        "id": "meXOsoFcseJL"
      }
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "VxoO755tVJJ_"
      },
      "source": [
        "## Inferences and Conclusion\n",
        "Summary of all the inferences drawn from the analysis and conclusion about answering all the interesting questions has been drawn. "
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "In summary, we have gone through a series of steps from obtaining the dataset until analyzing the data. There are several interesting questions that have been asked in order to gain some insight about the data. It can be observed that the foreign direct investment in the second quarter of 2009 experienced a loss of RM 726 million and also 2009 is the year with lower profit(RM 17084 million) compared to other years. This is because there was a global crisis in 2009 and the investment in Malaysia has never fully recovered from the impact of the global crisis. <br><br>\n",
        "\n",
        "Other than that, major foreign direct investment in Malaysia came from the East Asia block which is RM 470895 million and there are 6 countries in East Asia that invested in Malaysia. This is probably due to education, market size, inflation rate and exchange rate of Malaysia. From all of the invested countries, Singapore contributed the most to Malaysia's economy by investment and this can prove the strong bilateral cooperation between Singapore and Malaysia. As a result, both countries will benefit from an increase in economy. <br><br>\n",
        "Moreover, there are 8 countries in Europe, 4 countries for Latin America, 3 countries for Southeast Asia, 2 countries for North America and Oceania that invested in Malaysia. Thus, it still has many opportunities to expand the investment market in Malaysia. From that, Japan has the most impact in Malaysia with RM 46279 million of net investment. The investments involve  the strategic and high potential sectors like research and development (R&D). \n"
      ],
      "metadata": {
        "id": "HAqcyG28GDkT"
      }
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "xfuc6sJgVJKA"
      },
      "source": [
        "## References and Future Work\n",
        "\n",
        "Future investigation about the foreign direct investment in Malaysia and some resources that help to complete this assignment. "
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "Since this dataset contains the information about foreign direct investment, we can predict the future flows of investment based on existing data in order to investigate the economy of Malaysia as FDI plays an important role by helping maintain stable foreign exchange reverse levels. Furthermore, we can find the countries which have a high possibility to cooperate with Malaysia to speed up economic growth in order to employ local workers, provide skill training to local vendors, as well as encourage local employment."
      ],
      "metadata": {
        "id": "NFLsasJaGJfA"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "**Resources**<br>\n",
        "[Matplotlib](https://colab.research.google.com/drive/1Sk44p68l7wwrldwtZ_jpQ9-CTeDDcpTH)<br>\n",
        "[Seaborn](https://colab.research.google.com/drive/1GWKtrW5GqZ8ifOh2deHLThxCpBE14A2c)<br>\n",
        "[Exploratory Data Analysis(Boston)](https://colab.research.google.com/drive/1DjKNfvPGkYyHQWpiEdyK4ozm-nXVa43D#scrollTo=PXWgPKbjEOOs)<br>\n",
        "[Exploratory Data Analysis(Car Features)](https://colab.research.google.com/drive/1E99RyuEAZM8j2dvoxRqV8oWpg3kjqfBg#scrollTo=dB_j6LtTTO5j)<br>\n",
        "[Exploratory Data Analysis(Housing)](https://colab.research.google.com/drive/1p8GVSVIOFFJEcFdZZdbtVd3Rysd5MDyf#scrollTo=YSe8158sqFT4)<br>\n",
        "[How to Create a Horizontal Bar Chart using Matplotlib](https://datatofish.com/horizontal-bar-chart-matplotlib/)<br>\n",
        "[Malaysia leads emerging Southeast Asia for FDI appeal](https://www.fdiintelligence.com/content/news/malaysia-leads-emerging-southeast-asia-for-fdi-appeal-80692)<br>\n",
        "[Statistics of Foreign Direct Investment in Malaysia, 2017](https://www.dosm.gov.my/v1/index.php?r=column/cthemeByCat&cat=322&bul_id=TENVb0xWNXFiTnJ4ekk3R2d0NkFkdz09&menu_id=azJjRWpYL0VBYU90TVhpclByWjdMQT09)\n",
        "\n"
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