egyptian-endeavour-moment-of-truth.ipynb

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    "<h1 style = 'background-color:#283270;\n",
    "             border-style: solid;\n",
    "             color:#f6f5f5;\n",
    "             border-color:black;\n",
    "             font-family:serif'><center><strong><br>Egyptian Endeavour  - Moment of Truth"
   ]
  },
  {
   "cell_type": "markdown",
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   "source": [
    "# Statement\n",
    "As the world moves forward with the challenging of the Coronavirus.<br>\n",
    "**Egypt Governoment** has realized the huge gap between their universities education and the world market demand.<br>\n",
    "Especially in data science and programming domains. <br>\n",
    "<br>\n",
    "<br>\n",
    "Many initiatives had been taken by the **Egyptian government** in the past two years to conquer this gap.<br>\n",
    "Such as :\n",
    "* [FWD initiative](https://egfwd.com/)\n",
    "* [MAHARA TECH initiative](https://maharatech.gov.eg/)\n",
    "* and others.."
   ]
  },
  {
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   "source": [
    "# Notebook Objective\n",
    "\n",
    "**We are here to use kaggle survey datasets to measure the success of the Egyptian Endeavour** "
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c3ae5526",
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   "source": [
    "# Focus Group\n",
    "The Egyptian participants ( with less than 3 years experince in coding )<br>\n",
    "As I consider they were the most impacted by at least one of the **Egyptian government initiations**"
   ]
  },
  {
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   "id": "79b073f7",
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   "source": [
    "# Approach\n",
    "\n",
    "* First we will compare the number of Egyptian participants in kaggle survey in the past three years 2019  , 2020 and 2021 **as an indication of the total Egyptian kaggle users**.\n",
    "* We will focus in the rest of the analysis on the participants who have less than three years of coding experience as they were the most impacted by the recent  Egyptian initiatives."
   ]
  },
  {
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   "id": "0979ff17",
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   "source": [
    "# Content Outlines\n",
    "\n",
    "<ul>\n",
    "    <li>(Q1) Investigating the number of Egyptian participants.</li>\n",
    "    <li>(Q2) Investigating the level of experience of the Egyptian participants.</li>\n",
    "    <li>(Q3) Investigating the chartaristics and background of the Egyptain Juniors</li>\n",
    "    <li>(Q4)What can we offer to our employers</li>\n",
    "    </ul>"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ca5b9c4b",
   "metadata": {
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    "tags": []
   },
   "source": [
    "# Implementation"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "99c8bc29",
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    "tags": []
   },
   "source": [
    "## Setting up and importing the libraries and reading the datasets"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "f8364ec5",
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   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "We are ready to go\n"
     ]
    }
   ],
   "source": [
    "#Import the basic liberaries\n",
    "import numpy as np # linear algebra\n",
    "import pandas as pd # data processing, CSV file I/O (e.g. pd.read_csv)\n",
    "import matplotlib.pyplot as plt #visulaization\n",
    "import seaborn as sns #visulaization\n",
    "\n",
    "\n",
    "#visualization style\n",
    "plt.style.use('seaborn-poster') #set the visualization style\n",
    "#Set the Box prop for the text\n",
    "box = {'facecolor':'#f6f5f5',\n",
    "       'edgecolor':'black', \n",
    "       'boxstyle':'round', \n",
    "       'linewidth':0.4}\n",
    "#Set the annotation text props\n",
    "text_prop = {'ha':'center',\n",
    "            'va':'center',\n",
    "            'fontsize': 14,\n",
    "            'fontweight': 'bold',\n",
    "            'fontfamily':'serif',\n",
    "            'bbox': box}\n",
    "#Set the annotation title props \n",
    "title_prop = {'ha':'center',\n",
    "            'va':'center',\n",
    "            'fontsize': 20,\n",
    "            'fontweight': 'bold',\n",
    "            'fontfamily':'serif',\n",
    "            'bbox': box}\n",
    "#set the Bar charts colors\n",
    "color = ['#283270' , 'lightgray' , 'lightgray']\n",
    "\n",
    "#shut down warning\n",
    "import warnings\n",
    "warnings.filterwarnings('ignore')\n",
    "\n",
    "\n",
    "\n",
    "#reading the data for the past three years\n",
    "df_2019 = pd.read_csv('/kaggle/input/kaggle-survey-2019/multiple_choice_responses.csv')\n",
    "df_2020 = pd.read_csv('/kaggle/input/kaggle-survey-2020/kaggle_survey_2020_responses.csv')\n",
    "df_2021 = pd.read_csv('/kaggle/input/kaggle-survey-2021/kaggle_survey_2021_responses.csv')\n",
    "\n",
    "\n",
    "#All done\n",
    "print('We are ready to go')"
   ]
  },
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    "tags": []
   },
   "source": [
    "## (Q1) Comparing the number of Egyptian participants in kaggle survey in the past three years 2019  , 2020 and 2021 "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "582efb91",
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   },
   "outputs": [
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       "  <thead>\n",
       "    <tr>\n",
       "      <th class=\"blank level0\" >&nbsp;</th>\n",
       "      <th class=\"col_heading level0 col0\" >survey year</th>\n",
       "      <th class=\"col_heading level0 col1\" >Number_of_Egyptian_participants</th>\n",
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      "text/plain": [
       "<Figure size 1296x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "#Calculate the numbers of Egyptian Participants\n",
    "number_egypt_2019 = df_2019[df_2019.Q3 =='Egypt'].shape[0]\n",
    "number_egypt_2020 = df_2020[df_2020.Q3 =='Egypt'].shape[0]\n",
    "number_egypt_2021 = df_2021[df_2021.Q3 =='Egypt'].shape[0]\n",
    "\n",
    "\n",
    "#Build a dataframe\n",
    "num_egypt_dict = {'survey year': [ 'Survey 2021' , 'Survey 2020' , 'Survey 2019'] , \n",
    "                  'Number_of_Egyptian_participants':[ number_egypt_2021 , number_egypt_2020 , number_egypt_2019]}\n",
    "num_egypt_df  = pd.DataFrame(num_egypt_dict)\n",
    "\n",
    "\n",
    "#Display the dataframe\n",
    "display (num_egypt_df.style.background_gradient())\n",
    "\n",
    "\n",
    "\n",
    "\n",
    "#Plot the bar plot\n",
    "fig , ax  = plt.subplots(figsize = (18 , 5 ))\n",
    "ax.bar(num_egypt_df['survey year'] , \n",
    "       num_egypt_df['Number_of_Egyptian_participants']  ,\n",
    "       color = color )\n",
    "\n",
    "\n",
    "#ax settings\n",
    "ax.set_xlabel('Kaggle Survey year' , fontfamily='serif' )\n",
    "ax.set_ylabel('Counts of Participants' , fontfamily='serif')\n",
    "ax.set_title('Total Numbers of Egyptian Participants over years' , title_prop)\n",
    "ax.set_ylim(0 , 530)\n",
    "\n",
    "#Remove spines\n",
    "for s in [\"top\",\"right\"]:\n",
    "    ax.spines[s].set_visible(False)\n",
    "    \n",
    "\n",
    "    \n",
    "#Annotate texts\n",
    "ax.text(0, 310, '482  Participant', text_prop)\n",
    "ax.text(1, 110, '179', text_prop)\n",
    "ax.text(2, 60, '122', text_prop)\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f8168d42",
   "metadata": {
    "papermill": {
     "duration": 0.027887,
     "end_time": "2021-11-24T12:07:54.915523",
     "exception": false,
     "start_time": "2021-11-24T12:07:54.887636",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "Number of Egyptian participants increases tremendously in an annual basis<br>\n",
    "if we calculate only the **increasing percentage** from 2020 to 2021 it will be around 170%<br>\n",
    ">I am intersted to compare the annualy increasing percentage in participants numbers of Egypt to the rest of world"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "3198ab43",
   "metadata": {
    "papermill": {
     "duration": 0.027789,
     "end_time": "2021-11-24T12:07:54.971402",
     "exception": false,
     "start_time": "2021-11-24T12:07:54.943613",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "### (Q1-2) Investigate the increasing percentage in number of Egyptian participants to the rest of world from 2020 to 2021"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "f207076d",
   "metadata": {
    "_kg_hide-input": true,
    "execution": {
     "iopub.execute_input": "2021-11-24T12:07:55.036605Z",
     "iopub.status.busy": "2021-11-24T12:07:55.035859Z",
     "iopub.status.idle": "2021-11-24T12:07:55.430399Z",
     "shell.execute_reply": "2021-11-24T12:07:55.429858Z",
     "shell.execute_reply.started": "2021-11-24T11:19:38.960125Z"
    },
    "papermill": {
     "duration": 0.431092,
     "end_time": "2021-11-24T12:07:55.430551",
     "exception": false,
     "start_time": "2021-11-24T12:07:54.999459",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
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       "<table id=\"T_aadc5_\">\n",
       "  <thead>\n",
       "    <tr>\n",
       "      <th class=\"blank level0\" >&nbsp;</th>\n",
       "      <th class=\"col_heading level0 col0\" >Number_of_participants_in_2021</th>\n",
       "      <th class=\"col_heading level0 col1\" >Number_of_participants_in_2020</th>\n",
       "      <th class=\"col_heading level0 col2\" >Increasing_percentage_%</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th class=\"index_name level0\" >Countries</th>\n",
       "      <th class=\"blank col0\" >&nbsp;</th>\n",
       "      <th class=\"blank col1\" >&nbsp;</th>\n",
       "      <th class=\"blank col2\" >&nbsp;</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th id=\"T_aadc5_level0_row0\" class=\"row_heading level0 row0\" >Egypt</th>\n",
       "      <td id=\"T_aadc5_row0_col0\" class=\"data row0 col0\" >482</td>\n",
       "      <td id=\"T_aadc5_row0_col1\" class=\"data row0 col1\" >179</td>\n",
       "      <td id=\"T_aadc5_row0_col2\" class=\"data row0 col2\" >169</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_aadc5_level0_row1\" class=\"row_heading level0 row1\" >Bangladesh</th>\n",
       "      <td id=\"T_aadc5_row1_col0\" class=\"data row1 col0\" >317</td>\n",
       "      <td id=\"T_aadc5_row1_col1\" class=\"data row1 col1\" >143</td>\n",
       "      <td id=\"T_aadc5_row1_col2\" class=\"data row1 col2\" >121</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_aadc5_level0_row2\" class=\"row_heading level0 row2\" >Ghana</th>\n",
       "      <td id=\"T_aadc5_row2_col0\" class=\"data row2 col0\" >99</td>\n",
       "      <td id=\"T_aadc5_row2_col1\" class=\"data row2 col1\" >52</td>\n",
       "      <td id=\"T_aadc5_row2_col2\" class=\"data row2 col2\" >90</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_aadc5_level0_row3\" class=\"row_heading level0 row3\" >South Korea</th>\n",
       "      <td id=\"T_aadc5_row3_col0\" class=\"data row3 col0\" >359</td>\n",
       "      <td id=\"T_aadc5_row3_col1\" class=\"data row3 col1\" >190</td>\n",
       "      <td id=\"T_aadc5_row3_col2\" class=\"data row3 col2\" >88</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_aadc5_level0_row4\" class=\"row_heading level0 row4\" >Viet Nam</th>\n",
       "      <td id=\"T_aadc5_row4_col0\" class=\"data row4 col0\" >277</td>\n",
       "      <td id=\"T_aadc5_row4_col1\" class=\"data row4 col1\" >147</td>\n",
       "      <td id=\"T_aadc5_row4_col2\" class=\"data row4 col2\" >88</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_aadc5_level0_row5\" class=\"row_heading level0 row5\" >United Arab Emirates</th>\n",
       "      <td id=\"T_aadc5_row5_col0\" class=\"data row5 col0\" >111</td>\n",
       "      <td id=\"T_aadc5_row5_col1\" class=\"data row5 col1\" >59</td>\n",
       "      <td id=\"T_aadc5_row5_col2\" class=\"data row5 col2\" >88</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_aadc5_level0_row6\" class=\"row_heading level0 row6\" >Pakistan</th>\n",
       "      <td id=\"T_aadc5_row6_col0\" class=\"data row6 col0\" >530</td>\n",
       "      <td id=\"T_aadc5_row6_col1\" class=\"data row6 col1\" >283</td>\n",
       "      <td id=\"T_aadc5_row6_col2\" class=\"data row6 col2\" >87</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_aadc5_level0_row7\" class=\"row_heading level0 row7\" >China</th>\n",
       "      <td id=\"T_aadc5_row7_col0\" class=\"data row7 col0\" >814</td>\n",
       "      <td id=\"T_aadc5_row7_col1\" class=\"data row7 col1\" >474</td>\n",
       "      <td id=\"T_aadc5_row7_col2\" class=\"data row7 col2\" >71</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_aadc5_level0_row8\" class=\"row_heading level0 row8\" >Kenya</th>\n",
       "      <td id=\"T_aadc5_row8_col0\" class=\"data row8 col0\" >248</td>\n",
       "      <td id=\"T_aadc5_row8_col1\" class=\"data row8 col1\" >153</td>\n",
       "      <td id=\"T_aadc5_row8_col2\" class=\"data row8 col2\" >62</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_aadc5_level0_row9\" class=\"row_heading level0 row9\" >Ireland</th>\n",
       "      <td id=\"T_aadc5_row9_col0\" class=\"data row9 col0\" >84</td>\n",
       "      <td id=\"T_aadc5_row9_col1\" class=\"data row9 col1\" >54</td>\n",
       "      <td id=\"T_aadc5_row9_col2\" class=\"data row9 col2\" >55</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n"
      ],
      "text/plain": [
       "<pandas.io.formats.style.Styler at 0x7fbf8840ad10>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1296x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "#create and combine the dataframe\n",
    "countries_2020 = df_2020.groupby('Q3').size().reset_index().rename(columns = \n",
    "                                                                   {'Q3':'Countries' , \n",
    "                                                                    0:\"Number_of_participants_in_2020\"}\n",
    "                                                                  )\n",
    "countries_2021 = df_2021.groupby('Q3').size().reset_index().rename(columns = \n",
    "                                                                   {'Q3':'Countries' , \n",
    "                                                                    0:\"Number_of_participants_in_2021\"}\n",
    "                                                                  )\n",
    "countries_df = countries_2021.set_index('Countries').join(countries_2020.set_index('Countries'))\n",
    "countries_df.dropna(inplace = True)\n",
    "\n",
    "\n",
    "#Calculate the increasing percentage\n",
    "countries_df['Increasing_percentage_%'] = (((countries_df.Number_of_participants_in_2021 - \n",
    "                                             countries_df.Number_of_participants_in_2020)/\n",
    "                                            countries_df.Number_of_participants_in_2020)*\n",
    "                                           100)\n",
    "#sort the dataframe\n",
    "countries_df.sort_values(by = 'Increasing_percentage_%'  , \n",
    "                         inplace = True , \n",
    "                         ascending = False)\n",
    "#convert to int\n",
    "countries_df.Number_of_participants_in_2020 =countries_df.Number_of_participants_in_2020.apply(np.int64)\n",
    "countries_df['Increasing_percentage_%'] =countries_df['Increasing_percentage_%'].apply(np.int64)\n",
    "\n",
    "#here is the top 10 countries\n",
    "top_10_contries = countries_df.iloc[:10]\n",
    "display (top_10_contries.style.background_gradient(subset=['Increasing_percentage_%']))\n",
    "\n",
    "\n",
    "\n",
    "top_10_contries.sort_values(by ='Increasing_percentage_%' ,\n",
    "                            inplace = True)\n",
    "#Create the figure\n",
    "fig , ax = plt.subplots(figsize = (18 , 5))\n",
    "#set the parameters\n",
    "colorh = ['lightgray' ,'lightgray' ,'lightgray' ,\n",
    "          'lightgray' ,'lightgray' ,'lightgray' ,\n",
    "          'lightgray' , 'lightgray', 'lightgray' ,\n",
    "          '#283270']\n",
    "\n",
    "ax.barh( top_10_contries.index  ,\n",
    "        top_10_contries['Increasing_percentage_%'] ,\n",
    "        color = colorh )\n",
    "\n",
    "\n",
    "#ax setting\n",
    "ax.set_xlabel('Percentage of increasing %' , \n",
    "              fontfamily='serif' )\n",
    "ax.set_title('Increasing percentage in survey participants (Top 10 countries)' , \n",
    "             title_prop)\n",
    "\n",
    "ax.set_ylim(0,11)\n",
    "\n",
    "#remove spines\n",
    "for s in [\"top\",\"right\"]:\n",
    "    ax.spines[s].set_visible(False)\n",
    "    \n",
    "#Add Text    \n",
    "ax.text(170,  9 ,'170 %', text_prop)\n",
    "ax.text(120, 8 ,  '120 %', text_prop)\n",
    "ax.text(90,  7 ,  '90 %', text_prop)\n",
    "\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "34d5d632",
   "metadata": {
    "papermill": {
     "duration": 0.03076,
     "end_time": "2021-11-24T12:07:55.492304",
     "exception": false,
     "start_time": "2021-11-24T12:07:55.461544",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "The nearst country to Egypt in this indecator will be :\n",
    "* Banglades with increasing **percentage 120 %**\n",
    "* Ghana with increasing **percentage 90 %**\n",
    "\n",
    "but still none of the countries included in the survey come even near to the Egypt percentage."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "a034525a",
   "metadata": {
    "papermill": {
     "duration": 0.030125,
     "end_time": "2021-11-24T12:07:55.552913",
     "exception": false,
     "start_time": "2021-11-24T12:07:55.522788",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "### (Q1-3) visualizing Egypt annualy upranking in the number of paricipants among the rest of the world"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "35e726af",
   "metadata": {
    "_kg_hide-input": true,
    "execution": {
     "iopub.execute_input": "2021-11-24T12:07:55.641243Z",
     "iopub.status.busy": "2021-11-24T12:07:55.634054Z",
     "iopub.status.idle": "2021-11-24T12:07:55.915495Z",
     "shell.execute_reply": "2021-11-24T12:07:55.916133Z",
     "shell.execute_reply.started": "2021-11-24T11:21:12.405711Z"
    },
    "papermill": {
     "duration": 0.332044,
     "end_time": "2021-11-24T12:07:55.916307",
     "exception": false,
     "start_time": "2021-11-24T12:07:55.584263",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Survey_Year</th>\n",
       "      <th>Egypt_Rank</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Survey 2019</td>\n",
       "      <td>30</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Survey 2020</td>\n",
       "      <td>21</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Survey 2021</td>\n",
       "      <td>10</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   Survey_Year  Egypt_Rank\n",
       "0  Survey 2019          30\n",
       "1  Survey 2020          21\n",
       "2  Survey 2021          10"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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eJc2l7hSAmh8kaz5PJ+O0006rNUrh4YcfZu/evceNajmRvn361GocWrNYUFdWdjZBQUG1ej6405DXxIABAygqLHR781Z+fn6t+0OHDq11/abWvXt3khITeemll1w/87zVq7nv/vvrPW5scjKDBw/m5Zdecv37eOutt/joo4+aPOfRdX6Gdf+P2NeA/zNERKRlU5FDRERalWNHj5KdnU1ZWRkAV9ZYQaW0tLRWE8zMBvQIOOcHPyAmJub78x87xnXXXnvC45YvX+76Pjc315UPwFU1en3UneJQHff4E09w7rnnnvA6H3z4IYWFhTzwwAMkJSYed/vlL39ZK7561EdzGjJ4cK37u50jIQCW1OgVcbJurbEyzpEjR7jssstOOJXEnZk1enisWrXK7Qo+VVVVvPjii1z2wx8SFhZW7/ka+ppoLFFRUbXuV49GqaysPK4A0pSioqL4+9//7rr/8ssv89nnn5/wuLPOOos7br/ddf+nP/tZo/TnqE/fvn2ZPHmy6/7KlStd31dWVroauoqISOulIoeIiDSrsrIyvv32W1avWVNre0FBAd9+++1xt7pxV111Feecc47r/s/vvJMlS5bw7rvv8sabb57w+n5+fvzkpptc988880z69et3wuNef+MN/vWvf7FkyRLuvOsu1/bp06dzxRVXuO4PHz68VlPEz+fOZVlmJv/85z+JrbECRl0VFRXk5+fz2muvMTklBYDi4uLjYoYNHVprREJOTg6fz51LwY4dbN26lb11pmFs3bqVo0ePUrBjx3GjKvLz8zlw4ABHjx4lPz+fiooK176jx46xdetWiouLj/sAffDgwVrbUlNTGREf77r/7LPPsmLFCn778MPH/aW8+prV5635GKu31cwD4Ec/+lGt0SIzvWg4WtOv776bKTU+8P748sv505/+xPKsLNasWcMXX3zBxZdcwt69e/nDH/5wwvM19DVRn+qfu7vnoWDHjlqx55xzDp07d3bdf+zRR1mxYgX33XdfrUayNZ/bPXv2sHXr1lrn2bt3L3v27OHAgQPsqHONHTt2ULBjhyuvozXOW72toqKCcaefXqtod9ttt7FixYp6X0vgWEWpb9++ABw6dIjrb7iB/Px8j3k2JBdPz1/1tuf+/GfX8rZZWVn87sknWZ6VxR0//SkHDx2q+yMREZHWxlqrm2666aabbk16u+qqq2YVFRZad7d169ZZwOvb6rw81zkOHTxoH3nkETt06FAbFBRkO3fubKdPn26ff/75Wsd88/XXbnMo2L7ddujQwQL23XffdRvzxdy5tc71wgsv2PPOO8926tTJBgUF2WHDhtnHH3vMHj506Lhj537+uR0/fryNiIiwfn5+tmvXrvaSSy6xW7dscXutosJCuzov77jH/MXcuSeMqb6lpKTY/v37u9330osv2pSUFLf7HnjgAfvSiy+63de/f//jnoeat5q55X73nT333HNteHi4DQkJsfFxcfbPf/6zfeCBB9xes77z1vxZV9/u/tWvLGBHxMd7fA4bcjt65Ij9xyuv2GnTptmoqCgbHBxsg4KCbI/u3W3qlCn2j888Y/ft3dvorwlvfu41f6Z149PS0uzEiRNtRESEjYiIsFNTU+1n//mP25/vF3Pn2quvusrtua++6iq3P5vq69aX1+q8PI/nre+1VFRY6PE16ul8DcnF076a/36+W7XKXv7jH9vu3brZwMBA279/f3vPPffYGVdc4YofNGhQvT+ryy677B/N/X+rbrrppptux9+MtRYREZGmdPXVV8965eWXr26q85eUlBASEnLc9s/nzuWyGr0aNmzYQO86Q/yr3XLrrXz55ZesX7fO7XKdCxYsYFqNv1R/MXdurWHv4lvbtm1j6LBhPPvHP9bqq+JLek20TpWVlVRVVbn9d37lVVfx8ccfA3DWmWfy6aefejzPtddd9+oHH3xwk8cAERFpFpquIiIirVpFRQWRXbvy1VdfHbdv6dKlru/PPOOMWgWO+++/v9Zyl+vWrePqq65y+8FHmt+iRYv4fY0pI2vXriUkJKTB00BEqr01axbxI0Yct5JKZWVlrb4qTdFHRUREmp7nRcVFRERakdvvuIPHHn2UESNGUFRUxDfz5vG3v/0NgCFDhvB/L75YK/7fH3/Mtu3bue/ee/l0zhxWrVrFu++84/bcBTt2eOxV0KdGPwxpOvn5+TzzzDMkjBlDp06duPvXv+YnN91Uq9+JL+k10bpt376dGVdeyR2330737t3ZuXMnz7/wAtu2bQPglltu4fLLL2/mLEVE5GS0++kq06ZNs1988UVzpyEi0qa98MILXH+SzSFPxFrLX//6VxYuWkRubi779++nqKiITp06ERcXx4UXXMCNN9543HSWn995J3PnzmXfvn3ExsTw1FNPceaZZ7q9xjnTppGenn7c9pSUFL7Ue4hPLFmyhHvuvZc1a9bg7+/PRRddxF+ee47g4OBmyUevidZrw4YNvP766yxesoQtW7Zw4MABAHr16sVpY8dy/fXXk5qaesLzvP7669x+xx1NnK2IiADGq+D2XuRITk62DVliUERETt4Lzz/P9ddf39xpiIg0iqqqKt586y1ur7EEroiINBmvihzqySEiIk1u2PDh5OXlNXcaIiKNYtmyZYwdO7a50xARETdU5BARkSY3ZcoUMjIymjsNEZFGkb1iBcnJyc2dhoiIuKEih4iINDl/f39iBw1yuwKKiEhr8tlnnzFyxAiM8Wr0tIiI+IiKHCIi4hPnn38+/gEBvPTyyyxcuJCqqqrmTklEpEEqKyuZP38+L770El26dOGss89u7pRERMQDNR5V41EREZ+y1rJy5UoWL14MeNlJSkTExyxgjGHSpEmMGDGiudMREWmPvPp1MaCpshAREXHHGMOYMWMYM2ZMc6ciIiIi0i6UlVVw9FgxEeGhBAW17TJAsz46Y0xf4F4gGRgNhAIDrbWb68SFAI8DVwOdgRXAvdbaBT5MV0RERERERKTVyM7ZzFvvzufreasor6gkMMCfs84YxbVXTmbMyOjmTq9JNHdPjkHAj4GDQHo9ca8CPwF+C5wP7AS+NMaMaeoERURERERERFqb9z9axNU3/pUv/reC8opKAMorKpn732yuuuGvvP/RombOsGk0d5FjgbW2p7X2POADdwHGmNHAlcAvrLWvWGu/xlEY2Qo85rtURURERERERFq+7JzNPPr7D6mqct+Ds6rK8ujvP2TFqs2+TcwHmrXIYa1tSGv9C4Fy4L0ax1UA/wLOMcYEN1F6IiIiIiIiIq3OW+/O91jgqFZVZXnr3bbXAaK5R3I0RDywyVpbVGd7LhCEY8qLV4wxy6tvjZGgiIiIiIiISHOz1rJ67Xb++/XKBsV/9U0OZWUVTZyVb7WGtqqROHp21HWgxn4RERERERGRdqesrIJlyzeQlp5HWkYu2wsOnPggp/KKSo4VlhAZFN6EGfpWayhyNDprbVL198nJyfWP4RERERERERFpQfbtP8qChXmkpeexcMlaiopKT+o8gQH+hIeFNHJ2zas1FDkOAgPcbK8ewdHwMpWIiIiIiIhIK2OtZc26HaSl55K2IJec3K1u4/z8DAmjB3LsWAlr1+844XnPOmMUQUGtoSzQcK3h0eQClxhjOtTpyxEHlAEbmictERERERERkaZRUlLG4m/XMz8jl7T0PHbvOew2rmNEKCkThpOaEsekCcPo3CmMFas2c9UNf623+aifn+HaKyc3VfrNpjUUOeYAjwI/At4EMMYEAJcD/7XWnty4HBEREREREZEWZNfuQ8zPyCMtPZcl366npLTcbVxMdA9SU+KZkhJHwqiBBAb619o/ZmQ0D99/mcdlZP38DA/f/yPGjIxuiofRrJq9yGGMucz5bXWfjHONMXuBvdba+dbabGPMe8BzxphAYBNwGzAQuMr3GYuIiIiIiIicuqqqKr7L2+ZoGpqey+q1BW7jAvz9SE6KJTUlntSUOAb0637Cc//40gkMGdybt95dwFff5FBeUUlggD9nnzmKa2ZMbpMFDgBjbfP23TTGeEpgvrU21RkTCvwOuBLoDKwE7rXWpp3q9ZOTk21mZuapnkZERERERETkhAoLS1i4dB3z03OZn5HH/gPH3MZ16RzGlElxpKbEMeH0oUREhJ70NcvKKjhWWEJ4WEhr7MFhvAlu9kdnrT1hwtbaYuCXzpuIiIiIiIhIq7G9YL+jaWh6Ht8u30B5eaXbuKGDe5OaEseUlHhGxffH39+vUa4fFBTQppaJrU+zFzlERERERERE2pKKikpWrtrCvPRc0tJzyd+4221cUFAAp48dTOqkOFJT4ukd1cXHmbY9KnKIiIiIiIiInKLDR4rIWLyG+el5LFi0msOHi9zGde/WkdQUR1Fj3GmD6RAa7ONM2zYVOURERERERES8ZK1l85a9rmkoy1dspLKyym3siLh+rsLG8KF98PNrnGkocjwVOUREREREREQaoKy8gqzsTcxL/4609Dy2btvnNi40JIgJpw9hSko8UyYNp0f3Tj7OtP1SkUNERERERETEgwMHj7Fg4Wrmp+eSsXgtxwpL3MZF9erC1MmOJV5PSxpEcHCgjzMVUJFDRERERERExMVay/oNO0lLzyMtI5cVOVuw1h4XZ4xhzKgBpE5yFDYGD4rCGK9WO5UmoCKHiIiIiIiItGulpeV8u3wD8xY4+mvs3HXQbVx4WAiTxg9lSko8kycOJ7JL+1iWtTVRkUNERERERETanT17DzM/wzENZdHSdRSXlLmN69+vm2MayqR4EhMGEhSoj9EtmX46IiIiIiIi0uZVVVWxem2BazWU7/K2uY3z9/cjaUyMazWU6AHdNQ2lFVGRQ0RERERERNqkouJSlny73lXY2LvviNu4Th07MHnicKakxDFp/DA6dezg40ylsajIISIiIiIiIm3Gjp0HHUWNjDyWLltPWVmF27jYmJ6kpsQzNSWe0SMHEBDg7+NMpSmoyCEiIiIiIiKtVmVlFTm5W5nvHK2xdv0Ot3GBAf6cljyI1JQ4pkyKo1/fbj7OVHxBRQ4RERERERFpVY4dK2HhkjWkpeexYOFqDhw85jaua2Q4UybFMSUlnomnDyEsLMTHmYqvqcghIiIiIiIiLd7WbfuYl55LWnouy7M2Ul5R6TZu+NA+TJkUx9TJ8YyI64efn5+PM5XmpCKHiIiIiIiItDgVFZVkrdzE/PQ80tJz2bh5j9u44OBAxp82mNSUeKZMiqNXz86+TVRaFBU5REREREREpEU4dLiQjEWOaSjpi1Zz5Gix27iePTo5e2vEM27sYEJDg3ycqbRUKnKIiIiIiIhIs7DWsnHzHuYt+I609DyyV26iqsq6jR0V358pKfFMnRzPsCG9Mcb4OFtpDVTkEBEREREREZ8pK6tgWVa+azWUbQX73cZ16BDMxHFDSU2JI2XCcLp36+jjTKU1UpFDREREREREmtT+A0dZkLGatIxcMhavpaio1G1cn96RTE2JJzUljrFJgwgK0kdW8Y5eMSIiIiIiItKorLWsXb+DeQscozVW5W7F2uOnofj5GRJGRbumocQO7KlpKHJKVOQQERERERGRU1ZSUsaSZetJS89jfkYeu3YfchsXER5CysThpE6KZ9KEYXTpHObbRKVNU5FDRERERERETsruPYeYn5FHWnoei5euo6S03G3cwAE9SE2JIzUlnoTRAwkM9PdxptJeqMghIiIiIiIiDVJVVUXu6u2kpecyb0Euq9cWuI0L8PcjOTGWKc7CRnT/7j7OVNorFTlERERERETEo8KiUhYtWUtaRh4LMvLYt/+o27jOncKYPGk4U1PimThuKBERoT7OVERFDhEREREREamjYMcB0pxLvC7NXE95eaXbuCGDokh1roYyasQA/P39fJypSG0qcoiIiIiIiLRzlZVVrFy1mbT0POal57Ihf5fbuMBAf8aNHcyUlHhSJ8XRp3ekjzMVqZ+KHCIiIiIiIu3QkaPFZCxeQ1p6LukL13DocKHbuG5dI5gyKY6pk+MZd9oQwjoE+zhTkYZTkUNERERERKSd2LRlD/PT80hLz2V59kYqKqvcxsUP7+uahhI3rC9+fpqGIq2DihwiIiIiIiJtVHl5JVkrNrqmoWzZutdtXEhwIBPGDWXKpDimTBpOzx6dfZuoSCNRkUNERERERKQNOXjwGAsWrSYtPY+MRWs4VljiNi6qZ2empMQzdXI8pyXFEhIS5ONMRRqfihwiIiIiIiKtmLWW9fm7mO9cDWXFqs1UVdnj4owxjB45gNSUOFJT4hkyKApjTDNkLNJ0VOQQERERERFpZUpLy1m2PJ+0DEdho2DHAbdxYWHBTBo3jNSUOFImDqdrZISPMxXxLRU5REREREREWoG9+44wPyOPtPQ8Fi9dS1Fxmdu4fn26kjrZMQ0lKSGGoEB97JP2Q692ERERERGRFshaS96a7aSl5zE/I49VuVvdxvn7+5E4ZiCpkxyroQyM7qFpKNJuqcghIiIiIiLSQhQXl7Fk2TrS0h0jNvbsPew2rlPHDqRMGEZqSjwTxw+lc6cwH2cq0jKpyCEiIiIiItKMdu46yPyMPOYtyGVp5gZKS8vdxsUO7MkUZ9PQhFHRBAT4+zhTkZZPRQ4REREREREfqqqqIid3q2MaSnoua9btcBsXGOBPclIsU1PimTIpjv79uvk4U5HWR0UOERERERGRJnbsWAmLlq519dc4cPCY27jILuFMmRRHakocE04fSnh4iI8zFWndVOQQERERERFpAtu27yMtPY956blkLs+nvKLSbdywIb2ZkuJoGjoqvj9+fn4+zlSk7VCRQ0REREREpBFUVFSSnbOZtPRc5qfnkb9pt9u4oKAAxo0dzNTJjmkoUb26+DhTkbZLRQ4REREREZGTdPhIERmL1pCWnkv6ojUcPlLkNq5H906kpjimoZw+djAdQoN9nKlI+6Aih4iIiIiISANZa9m0eY9rGkr2yk1UVla5jR0Z39/VXyNuWF+MMT7OVqT9UZFDRERERESkHmXlFWRm5TtXQ8lj6/Z9buM6hAYx/vShTJ0cz+SJw+neraOPMxVf+vjjj9myeTP+AY6P1SpinTprLRXl5fTp25cf/ehHJ3UOFTlERERERETq2H/gKOkLV5OWnkfGkjUUFpa6jesd1YWpk+NJnRTP2KRYgoMDfZypNIdZs2YRGxPDOT/4QXOn0ibl5uby6quvcuONN3p9rIocIiIiIiLS7llrWbdhJ2npucxbkEvOd1ux1h4X5+dnGDMymtSUOKakxDM4tpf+gt/OlJWVcfjwYRISEpo7lTYrPj6eZZmZFBcXExoa6tWxKnKIiIiIiEi7VFpazpJl653TUHLZufuQ27iI8BAmTRhOakocKeOH0aVLuG8TlRZl6dKlnH7aac2dRpuXMmkS8+fPZ9q0aV4dpyKHiIiIiIi0G3v2HnYUNTLyWLx0HcUlZW7jogd0J3VSPKkpcSSOiSEw0N/HmUpLtW/vXo3i8IEePXqQvWKF18epyCEiIiIiIm1WVVUVeWu2O1ZDWZBL3prtbuMC/P1ISoghNSWeKSlxDBzQw8eZSmtRZS1+fn61tqWlpXH33XeTt3o1ABEREURFRbF9+3a6devGOeecw0MPPkj37t0bPZ/Fixdzw403smXLFgBW5+UxYMAAr86xb98+7r33Xv75r38B8MXcuUyePLlWTHFxMU8++STvf/ABfn5+BAQEMPO66/jFL37hej5WrlzJnP/8B4CHHnzQdezlV1zB119/TVFREVdfdRUvv/zyCXPy8/NzO2XsRJq1yGGM6QvcCyQDo4FQYKC1dnOdOE+PLMFau6IpcxQRERERkdalqLiUxUvXMW9BLvMz8ti3/6jbuM6dwpg8aTipk+KYOH4YHSO8m/svUi01NZXMzEw6hIUBMHHiRD6aPZsdO3cyefJkXnnlFVatWsU3X3/d6NceP348L734ItPOPfekjk9LS+OWW28lNiam3rjrZs7kP//5D888/TR33HEHjzz6KL/57W/ZvXs3Tz/9NAA5OTk8+eSTQO0ix3v/+hfnTJtGenr6SeXojeYeyTEI+DGwHEgH6mtN+wbwUp1t65omLRERERERaU0Kdh5w9dZYmrmBsrIKt3GDY6NITYkjNSWO0SOj8ff3cxsn0hh6R0VxycUX8/wLL7BkyRK2FxTQt0+f5k6rlrKyMr784gvS09NJmz/fbUxGRgb/cY7QOO+881xfn376aV74v//jjjvu8Hr0SFNp7iLHAmttTwBjzE3UX+QosNYu8U1aIiIiIiLSklVWVpHz3RbS0vNIS89l3YadbuMCA/05PXmws7ART5/ekT7OVNq7isrK7+/UmH7x2OOP8/HHHxMYEMD2ggJ6R0Vx8y238JObbgJg9uzZ3HvffezYsQOA559/nrfffpuVK1cyYcIE/vHKK/To4Xla1Ywrr+STTz5h6NCh3Hrrrdxy881u437gXAa3vlEWn3/+uev76ik3PZxfq6qq+OLLL+nSuTOPPvaYKy45ORmAr776is6dO7u27923j5tvvpn5CxZQWlLCLbfeyv333efx2t5q1iKHtbaqOa8vIiIiIiKtx9GjxSxcspZ56bksyFjNocOFbuO6dY1gyiRHUWP86UMI6xDs40xFHNatW8dHs2cDcP7559O3b1/Xvjmffsqzf/wjU6dOZd++fYwbP54777yTqKgozp8+nR/+8IcUFRVxy623uo75+quvuPyKK5gzZw6/e/JJ/vLcc26va62la9euPPTQQzxw//2n/DjWb9jg+r56SdeaS7tuWL+eZ555htLSUle+mZmZbs+1dOlSVq5YgTGGmNhYHn/8cc466yzGOosip6q5R3J44zZjzK+BSmAJ8LC19qQm9Bhjlld/n5SU1EjpiYiIiIhIY9u8dS9p6bnMT88jMyufikr3fyeNG9bXNVojfnjf4xpDivjSokWLGDpsGNu2bSMqKoqXXnyRK6+8slbM7Nmz6d+/PwDdunVj4oQJfPDhh3zy8cecP336cee88IILABg+fDhz5szh22+/dXttay13/eIXhAQHN0qBA6Dw2DHX9/7+jpWGav4bO1bovuDozvjx478fDdKjBzt27GDZt9+2uyLH28B/gB3AAODXwDfGmLOttWnNmZiIiIiIiDSe8vJKslduIi09l7T0PDZt2eM2LiQ4kPGnDyE1JY4pk+Lo2aOzbxMVqceECRN45+23OW/6dJYuXcrrb7zBjBkzasVs376dX99zD+vWrcPfz4+du3a5trsTGemYahUQ4PgYf+jQIbdx9953H3PmzCEpKYmKigpX/KkICw93fV9ZWYm/vz9VVd8XHMOdDVcbIrJLF9f31bkd9PBYTkarKHJYa6+pcTfdGPMJ8B3wBDDpJM7nGr6RnJzs/Zo0IiIiIiLSaA4eKiRj0RrmpeeSsWg1R4+VuI3r1bMzUybFMXVyPKcnDyIkJMjHmYo0XGhoKE88/jhn/+AHLFmyhLdmzeKG668HYNu2bVxw4YUUFxfz9qxZXHrppdx88828/c47VHlYNtUYU+u+p+VVu3fvTmRkJMuXL+epp5/mwQceOOXHMnjQINf3xcXFhIeHU1xc7No2aPDgBp+r7uMAz4/lZLSKIkdd1tqjxpjPgBubOxcREREREfGOtZYNG3e5VkPJztlMVdXxH3KMMYwa0Z/UlHhSU+IYOri32w9IIi3VxIkTOf3001m6dCnPPvss1117Lf7+/mRmZrqKBNOdU1MqazYoPQW/vvtuUqdM4drrruOpp55i2rRpJCUmntI5zz33XJ77y18A2Lt3L+Hh4ezdtw9wTFs5x9m8tO40sSNHjlBSUlJvg9TG1iqLHDVoFIaIiIiISCtQVlbBsuUbHKuhZOSyveCA27gOHYKZNH4oqZPiSZk4nG5dI3ycqUjjuuuuu5gxYwabNm3i/fffZ8aMGfSp0YB07dq1DBo0iGUeGnWejMsuu4w5c+bwwYcfctNNN7Fo4cJajUK9lZKSwnnnncfnn3/OF198wW233cYXX3wBwC233EJ0dDQAvXv3dh1z4MABnn/hBcpKS3n88cdP6fF4wzTmsJBT4VxC9hVgoLV28wliO+KYrrLZWjv5VK6bnJxsPXV9FRERERGRk7dv/1EWLMxj3oJcFi1ZS1Fxmdu4vn0imZoST+rkeJITYgkKau1/i5W2bPbs2YxNTnY1zwRIS0vj7rvvJm/1agAiIiKIjo5m6ZIlVFVVkZCYyPr16+nUqROXXHIJLzz/PA899BCvv/EGkZGRXHzRRaxZu5bPPvuMDh06cN5553HRhRfWWkI2JSWF2267jTt//nP27ttHYGAgY8eO5fHHHuOGG29ky5YtAAwePJj5aWlMmDiRzZs3A9C/f3+++t//aq3uUm3x4sX87Gc/49Dhw65rDRgwgLAOHXjvvfeIjY0FoKioiN/97nd88OGH+Pv74+/vz3XXXsuvfvUr1wiOyspKbrnlFuZ+8QUdO3YkKiqK1159lUcffZQ5//kPRUVFdO7cmQfuv58VK1bwwYcfUl5eTvdu3fjlL3/JnXfe6cqrsLCQz+fO5dprr/Vq+FazFzmMMZc5vz0TuBW4HdgL7LXWzjfG3A0MBebxfePR6m1nnuwKK9VU5BARERERaRzWWlavLXBNQ8nJ3eo2zs/PkDgmxrUaSkx0D01DkVbDXZFDGt/JFjlaQon0gzr3X3B+nQ+kAmuBS5y3TsARYCFwo7XW/Zo5IiIiIiLiE8XFZSxZtp75GY7VUHbvOew2rmNEKCkThpOaEsekCcPo3KnhqzGIiDRUsxc5rLX1VmWstXOAOT5KR0RERERETmDX7kPMz3BMQ1mybD2lpeVu42Kieziahk6OJ2FUNAEB/j7OVKTx+fv5NVqTUPGssrLyuEamDdHsRQ4REREREWnZqqqq+C5vG/MW5DI/I4/VawvcxgUG+JOcFEvqpDimpMQxoJ+G80vbE9W7N9sLCujVq1dzp9Kmbd++nT59+nh9nIocIiIiIiJynMLCEhYuXcf8dEdhY/+BY27junQOY8qkOFJT4pg4bhjh4SE+zlTEt8aOHctf//pXkpOSmjuVNm3hwoXcdvvtXh+nIoeIiIiIiACwvWA/aemO3hrfLt9Aebn7IflDB/d2NA2dHM/IuP74+3s/pFyktfLz82PQoEHMnTuXadOmqWluI7PW8vU339C3Xz8CAwO9Pr5RV1cxxgy31q5utBP6gFZXEREREZH2qqKikpWrtjAvPZe09FzyN+52GxcUFMC4sYNJTYlnyqQ4ekd18XGmIi3PsmXLWLRoEf7+jl4zKnWcmurKRGVlJWPHjmXChAnVu5pmCVljzEvW2ltOELPDWtvbmwSam4ocIiIiItKeHD5SRMbiNcxPz2PBotUcPlzkNq57t46uJV7HnTaYDqHBPs5URATwssjhzXSVCwG3RQ5jjD9wP9DNm4uLiIiIiEjTstayecte1zSU5Ss2UllZ5TZ2RFw/V2Fj+NA+J7WygYhIc/KmyNHTGPM7a+2DNTcaYxKBV4HRfD/CREREREREmklZeQVZ2ZuYl/4dael5bN22z21caEgQE04fQurkeCZPHE6P7p18nKmISOPypsixHxhhjPmTtfaXxphg4DHgF0ARcKvzvoiIiIiI+NiBg8dYsHA189NzyVi8lmOFJW7jonp1YerkeFJT4jgtaRDBwd439hMRaam8KXI8ArwEvGuM+SeQCAwGPgNutdYWGGPcL5gtIiIiIiKNylrL+g07SUvPIy0jlxU5W3DXb88Yw5hRA0id5ChsDB4UpdUgRKTNanCRw1r7PIAx5gpgFhALXGOtfadGmHpyiIiIiIg0kdLScr5dvoF5Cxz9NXbuOug2LjwshEnjh5I6OZ6UCcOJ7BLu40xFRJqHNyM5ALDWVhljrgZKgGnGmHft9yXj3wNvNmaCIiIiIiLt2Z69h5mf4ZiGsmjpOopLytzG9e/XzTENZVI8iQkDCQr0+ld9EZFWz+P/fMaYygae40oNdxMRERERaRxVVVWsXlvgWg3lu7xtbuP8/f1IGhPjWg1lYHQPH2cqItLy1FfeLQXe8+JcBvjRqaUjIiIiItL+FBWXsuTb9a7Cxt59R9zGderUgckThpM6OZ5J44fRMSLUx5mKiLRs9RU5Dltrr/fmZMaYc04xHxERERGRdmHHzoOOokZGHkuXraesrMJt3KDYXqROcozWGD1yAAEB/j7OVESk9aivyDHuJM4Xc7KJiIiIiIi0ZZWVVeTkbmW+c7TG2vU73MYFBvpzWtIgUlPimDIpjn591dtfRKShPBY5rLVbTuJ8i4ExJ52NiIiIiEgbcuxYCQuXrCEtPY8FC1dz4OAxt3FdI8OZ4hytMeH0IYSFhfg4UxGRtsGrlsvGmN7AD4AoINBNiEZyiIiIiEi7tnXbPual55KWnsvyrI2UV7jv5z98aB9SU+JJTYljRFw//Pz8fJypiEjb0+AihzFmOvAhEFxPmK1nn4iIiIhIm1NRUUnWyk3MT88jLT2XjZv3uI0LDg5k/GmDSU2JZ8qkOHr17OzbREVE2gFvRnI8BXwO/B3YDtRdoNsA3zZSXiIiIiIiLdahw4VkLHJMQ0lftJojR4vdxvXs0cnZWyOecWMHExoa5ONMRUTaF2+KHL2BMdZa922fAWPMb089JRERERGRlsVay8bNe5i34DvS0vPIXrmJqir3g5hHxfcndXI8qSnxDBvSG2OMj7MVEWm/vCly5AIhgPtuSQ5LTi0dEREREZGWoaysgmVZ+a7VULYV7Hcb16FDMBPHDSU1JY7JE+Po1jXCx5mKiEg1b4ocPwdeMMb83lq72kPM5zhGfIiIiIiItDr7DxxlQcZq0jJyyVi8lqKiUrdxfXpHMtXZNHRs0iCCgrzq5y8iIk3Em/+NZwPhwFXGmCJgP1BVJ6Z7YyUmIiIiItLUrLWsXb+DeQscozVW5W7F2uOnofj5GRJGRbumocQO7KlpKCIiLZA3RY4+wKJ69hs0ikNEREREWriSkjKWLFtPWnoe8zPy2LX7kNu4iPAQUiYOJ3VSPJMmDKNL5zDfJioiIl7zpshxwFo7tb4AY8zOU8xHRERERKTR7d5ziPkZeaSl57F46TpKSsvdxg0c0IPUlDhSU+JJGD2QwEB/H2cqIiKnwpsix48aEDPlZBMREREREWksVVVV5K7eTlp6LvMW5LJ6bYHbuAB/P5ITY0mdHM+USXFE99fsaxGR1qzBRQ5rbUYDwu4Cbj/pbERERERETlJhUSmLlqwlLSOPBRl57Nt/1G1cl85hTJ44nNSUeCaOG0pERKiPMxURkabidRtoY0wIMAiIdLP7x6jIISIiIiI+UrDjAGnOJV6XZq6nvLzSbdyQQVGkOldDGTViAP7+fj7OVEREfKHBRQ5jTADwOxyjNbRGloiIiIj4XGVlFStXbSYtPY956blsyN/lNi4w0J9xYweTmhLPlJQ4+kS5+/uciIi0Nd4UKx4EbgGeBTYAfwLudO7rD/wUeK1RsxMRERGRdu/I0WIyFq8hLT2X9IVrOHS40G1ct64RrtEa404bQliHYB9nKiIizc2bIsfVwEXW2vkAxpgnrLVvVu80xswFHmrk/ERERESkHdq0ZQ/z0/NIS89lefZGKiqr3MbFD+/rKmzEDeuLn5+moYiItGfeFDm6VBc4nGq9g1hrM40xQxsnLRERERFpT8rLK8lasdE1DWXL1r1u40KCA5kwbihTJsWRmhJHj+6dfJypiIi0ZN4UOY4ZY0KstSXO+weNMbHW2nwAY0xvIKrRMxQRERGRNungwWMsWLSatPQ8Mhat4Vhhidu4qJ6dSZ0cT2pKPKclxRISEuTjTEVEpLXwpsixEnjZGHOPtXYXsAT4lzHm94AB7gVymiBHEREREWkDrLWsz9/FfOdqKCtWbaaqyh4XZ4xh9MgBpKbEkZoSz5BBURhjmiFjERFpbbwpcrwK/Ab4AzDT+fVb4AMcRY5C4NxGzk9EREREWrHS0nKWLc8nLcNR2CjYccBtXFhYMJPGDSM1JY7Jk+KI7BLu40xFRKQtaHCRw1r7KfBpjftrjTEjgEuBUuALa+3mRs9QRERERFqVPXsPs2ChYxrK4qVrKSoucxvXv283Uic7RmskJcQQFOjN399ERESOd0rvJNbabcBfqu8bY16y1t5yylmJiIiISKthrSVvzXbS0vOYn5HHqtytbuP8/f1IHDOQ1EnxTJ0cT/SA7pqGIiIijaqxy+UXAipyiIiIiLRxxcVlLFm2jnkLcpmfsZo9ew+7jevUsQMpE4aROjmeSeOH0aljBx9nKiIi7ckJixzGmDHAEGAfsNhaW1xnfyBwFfALoEcT5CgiIiIiLcCOnQeZn5FHWnouSzM3UFpa7jYuNqYnqSnxpKbEMWZkNAEB/j7OVERE2iuPRQ5jTAfgE+CMGpsLjDHnWWu/M8Z0AX4K3I6juFEBvN6UyYqIiIiI71RWVrEqb6tjGkp6LmvW7XAbFxjgz9ikWFJT4pkyKY7+/br5OFMRERGH+kZyPAScCawHVgF+wEjgJWPMPTgKIF1wNB19HnjG2aNDRERERFqpY8dKWLR0LfMW5LJg4WoOHDzmNi6ySzhTJsWROjmeiacPISwsxMeZioiIHK++IselwMPW2sdrbjTGPAm8A3QE/gr83lq7p+lSFBEREZGmtHXbPtLSc0nLyCNzeT7lFZVu44YP7eMobKTEMzK+H35+fj7OVEREpH71FTn6An9ws/0PwH3AZdbaj5okKxERERFpMhUVlWTnbCYtPZf56Xnkb9rtNi44OJBxYweTmhLHlElxRPXq4uNMRUREvFNfkeOotfa4blLW2iPGmIPuChzGmMHW2vWNmqGIiIiInLLDR4rIWLSGeQtyyVi8hsNHitzG9ejeidQUx2iNcWMHExoa5ONMRURETl59RQ5bz75SD9vnA71PPh0RERERaQzWWjZt3sO89FzS0vPIXrmJysoqt7Gj4vszxbkayvChfTDG+DhbERGRxlFfkaODMeYawN27XKiHfaGNlpmIiIiIeKWsvILMrHznaih5bN2+z21ch9AgJowbSmpKPJMnDqd7t44+zlRERKRp1Ffk6Ai84WGfcbPPUP/oDxERERFpZPsPHCV94WrS0vPIWLKGwkL3A2779I4kNSWOqSnxjE0aRFBQfb8GioiItE71vbsdAe704lwG+POppSMiIiIi9bHWsm7DTuYtyCUtPZec77Zi7fF/Z/LzMySMinZNQxkU00vTUEREpM2rr8hRbK1905uTGWN+f4r5iIiIiEgdJSVlLM3c4JyGksvO3YfcxkWEhzBpwnBSU+JIGT+MLl3CfZuoiIhIM6uvyNHnJM7X4GOMMZcBM4BkoAewFfgIeNJae7RGXBfgGeBiHD0/FgO/sNauOon8RERERFqFPXsPO4oaGXksXrqO4pIyt3HRA7qTOimeqZPjSRg9kMBAfx9nKiIi0nJ4LHJYa923366Hl8fcjaOw8QCwHUgAHgGmGmMmWGurjGNM5RwgGvgZcBC4H5hnjBljrd3ubY4iIiIiLVFVVRV5a7Y7p6HkkbfG/a85Af5+JCXEkDo5nimT4hg4oIePMxUREWm5mrPj1AXW2r017s83xhwA3gRSgW+AC4GJwBnW2nkAxpjFwCbgHuDnPs1YREREpBEVFpWyeOk60tJzmZ+Rx779R93Gde4UxuRJw0mdFMfE8cPoGKEF7URERNxptiJHnQJHtWXOr9XTXi4EdlQXOJzHHTbGzAEuQkUOERERaWUKdh5w9dZYmrmBsrIKt3GDY6NITYkjNSWO0SOj8ff383GmIiIirU9LWztsivPraufXeOA7N3G5wLXGmHBr7TFvL2KMWV79fVJSktdJioiIiDRUZWUVOd9tcU1DWZ+/021cYKA/pycPJnVyPKmT4ujTO9LHmYqIiLR+LabIYYzpAzwGfGWtzXRujgQ2uwk/4PzaBfC6yCEiIiLSlI4eLSZj8RrSMvJYkLGaQ4cL3cZ16xrBlElxpKbEM/70IYR1CPZxpiIiIm1LoxQ5jDH9gCJr7f6TPD4c+ASoAK5vjJzqY611Dd9ITk4+fmF5ERERES9t3rrX0VsjPY/MrHwqKt33Y48b1tc5DSWe+OF98fPTNBQREZHG0uAihzHmG2vtGR523wL8whhzp7X2H94kYIwJxbGCSgwwpc6KKQdxjNaoK7LGfhERERGfKy+vJHvlJsc0lIxcNm9x124MQoIDGX/6EFJT4pkyaTg9e3T2baIiIiLtiDcjOYZ72mGtfcgY8zrwX6DBRQ5jTCDwIZAMnG2tXVUnJBf4gZtD44CtJ9OPQ0RERORkHTxUSPqi1aSl55GxaDVHj5W4jYvq2ZkpKfGkpsRxevIgQkKCfJypiIhI++RNkeNE0zoOARENPZkxxg94BzgDON9au8RN2KfA9caYKdba+c7jOgIXAO829FoiIiIiJ8Nay4aNu1yroWTnbKaq6vhfiYwxjBrRn1RnYWPo4N4YY5ohYxERkfat3iKHMWZjjbvd69yve54eQLoX134e+BHwO6DQGDOuxr7tzmkrnwKLgbeNMb/GMT3lfsAAT3txLREREZEGKSurYNnyDaSl55GWkcv2ggNu4zp0CGbS+KFMTYknZeJwukY2+G89IiIi0kRONJJjK9+P4OgNbPEQV4Rj2ddnvbj2uc6vDzpvNT0KPGKtrTLGnA/8EXgBCMFR9Jhqrd3mxbVEREREPNq3/yjzM/JIS89l0ZK1FBWXuY3r16erY4nXlDiSE2MJCmwxC9WJiIgIYKxt2OIixpid1tqoJs7H55KTk21mZuaJA0VERKRFKyur4OixYiLCQwkKqr/4YK1l9doC1zSUnNytbuP8/f1IGD3QtRpKTHQPTUMRERHxLa/eeL3588O4E4eIiIiI+FZ2zmbeenc+X89bRXlFJYEB/px1xiiuvXIyY0ZGu+KKi8tYsmw98zNySUvPY/eew27P1zEilJQJw0lNiWPShGF07hTmo0ciIiIip6rBIzlcBxjTBTgLGOjctAn4ylrbKpdz1UgOERGR1uv9jxbx6O8/dNsM1M/PcNcd04kIDyEtPY8ly9ZTWlru9jwx0T2c01DiSRgVTUCAf1OnLiIiIg3j1UgOr4ocxpiHgAeA4BoXskAp8IS19klvLt4SqMghIiLSOmXnbObqG//qtsBxIoEB/iQnxZI6KY4pKXEM6Ne9CTIUERGRRtA001WMMXcDjwELgbnALueuXsB5wOPGmBJr7Z+8SUBERETkZLz17nyvChxdOocxZVIcqSlxTBw3jPDwkCbMTkRERJqDNz05fgrcZK19zc2+J40xNwC/BVTkEBERkSZRWVnF2vU7WPLtOr78amWDjvHzM7zx0u0kjo7B39+viTMUERGR5uRNkSPMQ4EDAGvta8aYPzRCTiIiIiIAlJdXkrdmO8uyNpCZtZGsFRs5eqzEq3NUVVliB/ZSgUNERKQd8KbIUWCM6WytPeRup7Mh6ZY625KttWp4ISIiIg1SWlpOTu5WMrPyWZaVz4qVmykuKTulcwYG+BMepqkpIiIi7YE3RY4ngFnGmFustTtq7jDG9Ab+Atxb55hPgd6nlqKIiIi0VUXFpWSv3ExmVj6Z2RvJ+W4LZWUVHuM7dexAUkIMyQkxpC9aw+Jv153wGmedMYqgIG9+5REREZHWypt3/DuAeGCzMWYjsNu5vQcQCxQADzlXYKkW2ShZioiISJtw5GgxWSs2siwrn8ysjeSt3kZFZZXH+K6R4SQnxDI2KZbkxFgGx/bCz88x7SRhzECWZq6vt/mon5/h2isnN/rjEBERkZbJmyJHCrANKMSxhGz/GvsKnF8H1jlGi8yLiIi0YwcOHiMze6NjpEZWPmvW7aC+5et79ezM2MRYkhNjGJs4iOgB3THG/cpxY0ZG8/D9l/Ho7z90W+jw8zM8fP+PGDMyurEejoiIiLRw3hQ59lpr6xYx6mWM2ellPiIiItKK7dl7mGVZ+Sxbnk9mdj75G3fXG9+/bzeSk2IZmxBDcmIsfXpHeixquPPjSycwZHBv3np3AV99k0N5RSWBAf6cfeYorpkxWQUOERGRdsabIsc9J3H+X57EMSIiItIKWGsp2HHA0SQ0eyOZy/PZun1fvcfExvT8fvpJQgw9e3Q+5TzGjIxmzO+jKSur4FhhCeFhIerBISIi0k558xvA08Asb05urf2nd+mIiIhIS2WtZfOWva7lXDOz8tm5+5DHeGMMw4b0JjnR0U8jOSGGyC7hTZZfUFAAkUFNd34RERFp+bwpcvQ0xqwC3gBmWWv3NE1KIiIi0hJUVVWxPn+XY6SGc/rJ/gPHPMb7+/sRP7yfs59GLIljYugYEerDjEVERKS986bIsRu4HpgJ5BhjvgVeB+ZYaz2v9SYiIiKtQkVFJavXFriWc12evZHDR4o8xgcFBTBqxACSnf00xoyKJqxDsA8zFhEREanNmyLHLdbaTCDTGPNL4ELgRuB5Y8z7wOvW2pVNkaSIiIg0vrKyCr7L20pmlmNJ16yVmygqKvUYHxoSxJjR0c7VT2IZFd+f4OBAH2YsIiIiUj9T3zJuDTqBMQOBfwHJQA6O0R3vWGv3n3p6TS85OdlmZmY2dxoiIiJNrri4jJWrtpCZ7VjOdcWqLZSWlnuMDw8LISkhxrWca9ywvgQGanV4ERER8amGL7uGFyM5jDEXWGvn1Lg/DsfUlcuBTsBh4FtgKPCdMeZL4G5rbf1t1kVERKRJHDtWQnbOJlc/je9yt1FeUekxvnOnMFc/jeTEWIYO7o2/v58PMxYRERE5Nd5MV3nJGLMMuM55GwpY4GsczUj/ba0tATDG/AK4A5gNTGnMhEVERMS9g4cKyVqx0Tn9ZAOr1xZQVeV5xGb3bh2dS7k6lnSNie6Bn5+KGiIiItJ6eVPk6AFsA/yB9cBvgLestdvrBlpry4A/G2Pub5QsRURE5Dh79x1hebajn0ZmVj7rNuysN75P70jXKI2xibH069sVY7waASoiIiLSonlT5KjCMWLjDWvtovoCjTEdgH8DZSefmoiIiNS0Y+dBVz+NZVn5bN6yt974gQN6uPppJCXE0Duqi48yFREREWke3hQ5Vlhrb25gbBnwJI4+HSIiIuIlay1bt+9z9NNwFjV27DxY7zFDB/cmOTGG5ATHaI1uXSN8lK2IiIhIy+BNkWNJQwOttRXAfO/TERERaZ+qqqrI37TbtZxrZlY+e/cd8Rjv52eIG9bXNf0kccxAOncK82HGIiIiIi2PN0WOy40xz1D/8i1VwAFrbdGppSUiItK2VVZWsWZdAZnZG8nMyiczayOHDhd6jA8M8GdkfH+SE2NJTowhYdRAwsNDfJixiIiISMvnTZGjO7C5AXHWGJMNPGit/e9JZSUiItLGlJdXkrtmm2v6SdaKTRwrLPEYHxwcyJiRA1yrn4waMYDQ0CAfZiwiIiLS+nhT5HgcuAU4BCwAdjm39wRSnN+/j2MVltOBz4wx51hrv2mcVEVERFqP0tJyVn63xbWc68qcLRSXeO7H3aFDMEljBrqWc42P60dQoDdv0yIiIiLizW9PFcDL1trfuttpjHkY2GetfcR5/wHgt4CKHCIi0uYVFpWyImezq59GzndbKC+v9BjfqWMHkhJinD01Yhg2pA8BAf4+zFhERESk7THW2oYFGrMWGGmtdftnKGNMMJBtrY2rcX+3tbZzI+XaJJKTk21mZmZzpyEiIq3MkaPFLM/e6FjSdXk+uWu2U1lZ5TG+W9cIkhNiSE4axNiEGAbF9sLPz8+HGYuIiIi0SvX1BT2ONyM5egL1VUQs0Mt1x9pSY4wakIqISJtw4OAxZ4PQfDKzN7Jm3Q7q+0NBVM/OJDv7aYxNiiW6f3eM8eo9WkRERES85E2RYxPwV2PM3dbaWu3fjTFhwLPUaExqjBkHHG6MJEVERHxt955Drn4amVkbyd+0u974/v26kZwYy1jnrU/vSB9lKiIiIiLVvClyPAh8AlxtjFnE941HewETgSDgQgBjzP3Ar4F3Gy9VERGRpmGtZXvBfjKzHNNPli3PZ1vB/nqPGRTbi+QERz+NsYmx9OjeyUfZtjxfffUVubm5BAQEaLQKjtdTRUUFY8aMYcqUKc2djoiISLvS4J4cAMaYM4CngcQ6u5YD91hr5znjzgUigQxr7ZZGyrVJqCeHiEj7Y61l0+Y9roJGZvZGdu0+5DHeGMOwIb1dy7kmJcQQ2SXcdwm3YC+++CIjRowgKbHurwayaNEitm3fzsyZM5s7FRERkdasyXpy4FwONtkY0xOIdm7ebK3dXSdurjfnFRERaUpVVVWs27DT2VPDMVpj/4FjHuMD/P2Ij+vnmn6SMHogHSNCfZhx67Bp0ya6dOmiAocHEyZM4L3332fv3r107969udMRERFpF7wqclRzFjXqn5wsIiLSTCoqKlm9tsA5SiOf5dkbOXK02GN8UFAAo0YMcC3nOmZUNB1Cg32Ycev01VdfcdkPf9jcabRo506bxueff851113X3KmIiIi0Cx6LHMaYydXfW2sX1HcSY8xDgJ8z9rFGy05ERKQBysoqWJW71TX9JDtnM0VFpR7jO4QGMWZUtGOkRlIsI+P6Exwc6MOM24aysjJCQkKaO40WrWPHjhQVabE5ERERX6lvJMf/gEWANcacaetv3mGctwcBFTlERKRJFReXsWLVZtf0k5XfbaG0tNxjfER4CEkJMSQnOnpqxA3rS2Cgvw8zbpvUZLRh9CyJiIj4Tn1FjgPW2qnVd4wxrwO1Ch3W2hucXx93xtzXFEmKiEj7duxYCVkrN7Fs+QYyszfyXe5WKiqrPMZ36Rzm6qeRnBjLkEFR+Pv7+TDj9istLY27776bvNWrAYiIiCAqKort27fTrVs3zjnnHB568MEm6VGxePFibrjxRrZscfQ8X52Xx4ABAxp0bH5+Po899hg5q1bh7+fHzl276N+/PzNnzuTGG24gIKD2r0wZGRnc8dOfsn79evr3788a5+MVERGR5lVfkaPuyI0059fngLsaeIyIiIjXDh4qZHn298u5rllXQFWV57eYHt07ufppjE0aREx0D40yaCapqalkZmbSISwMgIkTJ/LR7Nns2LmTyZMn88orr7Bq1Sq++frrRr/2+PHjeenFF5l27rleH5ufn88XX37JgvnzGTp0KN9++y1nnnUWv/jFL1i5ciUvPP+8K/aee+7hm2++obzc8+ghERERaR4NbjxqrX0TwBjzh+rvRUREGsOevYdZnr2RZc7pJ+vzd9Yb37dPJGMTB5GcGENyQiz9+nZVUaOF6x0VxSUXX8zzL7zAkiVL2F5QQN8+fZo7LZfw8HBuuvFGhg4dCsBpp51GyqRJpM2fz9tvv80zTz9NmLNwExcfzxNPPMEFF17I5s2bmzFrERERqetkVlfRaA0RETklBTsPuPppLMvKZ8vWvfXGx0T3cPXTSE6MIapXFx9lKo2porLy+zs1Wn099vjjfPzxxwQGBLC9oIDeUVHcfMst/OSmmwCYPXs29953Hzt27ADg+eef5+2332blypVMmDCBf7zyCj169PB43RlXXsknn3zC0KFDufXWW7nl5puPi5kwYQITJkyota2bc0pNRUUFpaWlriLHTK2UIiIi0mKd1BKyIiIiDWWtZcu2fa7lXDOz8tmx86DHeGMMQwZFuaafJCXE0q1rhA8zlqawbt06Ppo9G4Dzzz+fvn37uvbN+fRTnv3jH5k6dSr79u1j3Pjx3HnnnURFRXH+9On88Ic/pKioiFtuvdV1zNdffcXlV1zBnDlz+N2TT/KX555ze11rLV27duWhhx7igfvv9yrn/Px8AEaOHElkZKSXj1hERESaQ31Fjg7GmGs4vil4qIftAGpVLyLSzlVVVbFh424ys/Kd00/y2bf/qMd4f38/4ob1JTkhhrFJsSSMHkjnTmE+zFia0qJFixg6bBjbtm0jKiqKl158kSuvvLJWzOzZs+nfvz8A3bp1Y+KECXzw4Yd88vHHnD99+nHnvPCCCwAYPnw4c+bM4dtvv3V7bWstd/3iF4QEB3td4FielUV2djbh4eH87W9/8+pYERERaT71FTk6Am+42W7q2a6pLCIi7UxlZRVr1hW4+mksz97IocOFHuMDA/wZGd+fsUmO6ScJo6MJCwvxYcbiSxMmTOCdt9/mvOnTWbp0Ka+/8QYzZsyoFbN9+3Z+fc89rFu3zrWySfV2d6pHVVSveHLo0CG3cffedx9z5swhKSmJioqK41ZI8aRgxw5mzpzJwIEDefeddxg9enSDjhMREZHmV9+7/RHgTi/OZYCXTi0dERFp6crKK8hdvZ3M5RtYlr2R7BWbOFZY4jE+JDiQMaOiHSufJA5i1Ij+hIQE+TBjaW6hoaE88fjjnP2DH7BkyRLemjWLG66/HoBt27ZxwYUXUlxczNuzZnHppZdy88038/Y771Bl3f/tpG6TWeshrnv37kRGRrJ8+XKeevppHnzggRPmujwrixkzZpCamsqzf/wjERER5Ofn069fP4KC9LoVERFp6eorchR7u4qKMeb/TjEfERFpYUpKysj5bqtjpEZ2PitWbqak1PPSmWFhwSSOiWFsQgzJibHEx/UjKFAtoNq7iRMncvrpp7N06VKeffZZrrv2Wvz9/cnMzKS4uBiA6c6pKZU1G5Segl/ffTepU6Zw7XXX8dRTTzFt2jSSEhM9xj///PP8+bnnePbZZ7nowgtd22+/4w5efuklBgwY0Ch5iYiISNOp77fOk1nXTZOoRURaucLCElbkbHb108jJ3Up5uecPnZ06dSB5TAzJSbGMTYxl6ODeBASoRZMc76677mLGjBls2rSJ999/nxkzZtCnRgPStWvXMmjQIJZlZjbaNS+77DLmzJnDBx9+yE033cSihQsJDQ09Lu6DDz7g1/fcQ4cOHfjpT3/KT3/6U9e+w4cPN1o+IiIi0rQ8FjmstVXenuxkjhERkeZ1+EgRWSs2upZzzVuzncpKz/+dd+sa4VjONdFR1BgU0xM/Pz8fZiwtWVpaGnfffbfr/sKFCzl93DiWLlnCBeefz+DBg1m/fj2//NWvSM/I4IXnn+eXv/gFr7/xBlddfTUXX3QRQ4cOZcOGDSxfvpxrr7uOiy68kEcfe8x1znOmTeO2227jlZdfBmDnzp2cdfbZPP7YY7VWYLnwoouYn5bmKpqsXbuWhMREvvrf/2qt7gJQUuKYclVUVERRUVG9j/GBBx7gv//9L5u3bHFdPzk5mbj4eN5606tBsCIiItLIjKd5rO1FcnKyzWzEvxiJiLR0+w8cJdPZJDQzO5+163d67GkAENWri6tJaHJiDNH9ux/XE0HapxdeeIHrZ85s7jRavDfffJNbb7utudMQERFprbz6xVOTpEVE2rhduw/VWs514+Y99cYP6N/dtZxrcmIsfaIifZSptDbt/Q8lDaVnSURExHearchhjLkMmAEkAz2ArcBHwJPW2qPOmGhgk4dTdLHWHmr6TEVEWg9rLdu27yczO985/WQD2wsO1HvMoNhejHVOP0lOiKFH904+ylZaO2MMVVVVmq5Uj/Lycj0/IiIiPtScIznuxlHYeADYDiQAjwBTjTET6vT3+D3waZ3jj/oiSRGRlsxay8bNexwjNZY7Vj/Zvcdzk0Q/P8OwIX1cy7kmjRlIly7hPsxY2pLTTjuNb7/9lnHjxjV3Ki3WvHnzSE1Nbe40RERE2o3mLHJcYK3dW+P+fGPMAeBNIBX4psa+jdbaJb5MTkSkJaqsrGLdhp2OnhrO0RoHDh7zGB/g78eI+P4kO5dzTRw9kIiI41eWEDkZSUlJPPH44wwbNozOnTs3dzotzr59+1i9Zg0XXXxxc6ciIiLSbjRbkaNOgaPaMufXk1m+VkSkzSkvr2T12u2ufhpZKzZx5Gixx/igoABGjxxAckIsY5NiGT1yAB1Cg32YsbQnxhjuufdeXnvtNcrKyggICCDAX8sHV1RWUl5eTmhoaK2VZkRERKTptajVVYwxtwL/B4y11mbW6MmxD+gCFALzgQettatO4TrLq79PSkpK1OoqItJSlJVVkJO7xdFPY/kGVuRspqi4zGN8h9AgEkYPdC7pGsOo+AEEBamntDSPqqoqKisrmzuNZufv768+HCIiIo2nda6uYozpAzwGfGWtra46lAIvAf8F9gLDcPTwWGSMOc1au7pZkhURaSRFxaWsyNnsWs515aotlJVVeIyPCA8hKcHRTyM5MYbhQ/sSGKi/nEvL4Ofnpw/3IiIi0qxaxEgOY0w4kAb0Bk6z1m6vJ7YfkAt8aq29+lSvnZycbDWSQ0R85ejRYrJWbnJNP8nN20ZFZZXH+Mgu4SQnxrimnwyOjcLfXx8iRURERKTdaF0jOYwxocAcIAaYUl+BA8Bau80YkwGM9UV+IiKn4uDBY2RmO0ZpLFuez9r1O6iq8lxc7tmj0/fLuSbGEhPdA2O8+n9dRERERKTdatYihzEmEPgQSAbO9rLPRvMPQRERqWPP3sNkZm90Lee6IX9XvfH9+nQlOTHWWdiIoW+fripqiIiIiIicpGYrchhj/IB3gDOA8xu6RKwxpj8wCfi46bITEWmYgh0HXFNPlmXls3XbvnrjY6J7MDYpluQEx0iNXj07+yZREREREZF2oDlHcjwP/Aj4HVBojBlXY992a+12Y8yzgB+wGEfj0aHA/UCV8zgREZ+x1rJ5617XKI3MrI3s3HXQY7wxhqGDo1z9NJISYugaGeHDjEVERERE2pfmLHKc6/z6oPNW06PAIzgajN4GzATCgf3AN8Cj1tq1PslSRNqtqqoqNuTvYln2RjKdozX27T/qMd7f34/4YX1dy7kmjomhU8cOPsxYRERERKR9a7Yih7U2ugExrwGvNX02IiJQUVHJmnUFjuVcs/LJXLGRw4eLPMYHBvozKr4/yUmDGJsQw5hR0YSFhfgwYxERERERqanZV1cREWkuZeUV5OZtc00/yVq5icLCUo/xIcGBjBkd7Zp+Miq+PyEhQT7MWERERERE6qMih4i0GyUlZaxctcXVT2NFzmZKSss9xoeHhZA4ZqBrOdf44X0JCtR/myIiIiIiLZV+WxeRNquwsITslZtdq5+syt1KeUWlx/hOnTq4RmkkJ8QwbEgf/P39fJixiIiIiIicChU5RKTNOHS4kKwVm1zLua5eW0BlZZXH+G5dIxibNIjkhBiSE2MZFNMTPz8VNUREREREWisVOUSk1dq3/yjLs/OdIzU2sm7DTqy1HuN7R3UhOTGWsc7pJwP6dcMY48OMRURERESkKanI0UBHjx7lk08+4dChQxho9x+MrLVUWUvv3r05//zzCQ4Obu6UpB3YueugY+WT7HyWLc9n05Y99cZHD+hOcoJjOdfkxFj6REX6KFMREREREWkOKnI0wJ49e3j5pZe4/vrriYzUh6SathcU8Pvf/557772X0NDQ5k5H2hBrLdu273f108jMzmd7wYF6jxkcG0VyYgxjE2NJSoihR/dOPspWRERERERaAlPf0O72IDk52WZmZtYb8+c//5mbbryRgADVhNw5cuQIn3z6KTfffHNzpyKtmLWW/E27Xf00MrM2smfvYY/xfn6G4UP7OFY+SXAUNbp0DvNhxiIiIiIi4gNeTaPQp/YG8PPzU4GjHh07dqSkuLi505BWprKyirXrdzhHaWwkMyufg4cKPcYH+PsxIr6/q59GwqhoIiI0ekhERERERL6nT+4nUF5eToj6TZyQn79/c6cgLVx5eSV5a7azLGsDmVkbyVqxkaPHSjzGBwcHMnrEAOf0k0GMHjmA0NAgH2YsIiIiIiKtjYocJ1BZWalRHA3Q3huxyvFKS8vJyd3qmn6yYuVmikvKPMZ36BBM4uiBjiahCbGMjO9PUJD+7YmIiIiISMPpE8RJSEtL4+677yZv9WoAIiIiiIqKYvv27XTr1o1zzjmHhx58kO7duzf6tRcvXswNN97Ili1bAFidl8eAAQMadGxFRQU/+/nPyc7Oxt/fn82bNxMSEsKECRO4/777iIuLc8UeOHCAhx95hM8//5zAwEAiwsO546c/ZeZ11zX6Y5K2oai4lBU5m1m23DH9JOe7LZSVVXiM7xgRSlJCjGv6yfChfQgI0IggERERERE5eSpynITU1FQyMzPpEOZocjhx4kQ+mj2bHTt3MnnyZF555RVWrVrFN19/3ejXHj9+PC+9+CLTzj3X62MrKip4++23+frrrzlt7FiOHj3KtHPPZfbs2SyYP5/169cTFBRERUUFF150EVlZWbz33ntccP753HDDDdx+++0UHjvGHXfc0eiPS1qfI0eLyVqxkczsjSxbnk/e6m1UVFZ5jO8aGe5aznVs0iAGx/bCz8/PhxmLiIiIiEhbpyJHI+odFcUlF1/M8y+8wJIlS9heUEDfPn2aOy2XwMBAZs2axWljxwKOEShTJk8mOzubvfv2sWXLFgYPHsx7771HVlYWfn5+TDvnHADOO+88/vXeezz2+ONcf/31dOjQoTkfijSDAwePuRqEZmbls2bdDupbnalnj06MTYxlbJJj9ZOB0T00rUlERERERJqUihyNrKKy8vs7NT4APvb443z88ccEBgSwvaCA3lFR3HzLLfzkppsAmD17Nvfedx87duwA4Pnnn+ftt99m5cqVTJgwgX+88go9evTweN0ZV17JJ598wtChQ7n11lu5xc1yrv7+/lx80UWu+zt27uTzuXMBGDduHDExMQCubV26dCEwMBDANfXm6NGjLFiwgGnTpnn93EjrsmfvYZZl5Tunn+STv3F3vfH9+3Zz9dMYmxRLn96RKmqIiIiIiIhPqcjRiNatW8dHs2cDcP7559O3b1/Xvjmffsqzf/wjU6dOZd++fYwbP54777yTqKgozp8+nR/+8IcUFRVxy623uo75+quvuPyKK5gzZw6/e/JJ/vLcc26va62la9euPPTQQzxw//0NyvXcc89lQXo61lqmT5/OP155BX/nCikb1q8HICQkxBUfWmPkxoYNGxr2hEirYa2lYMcBR5PQ7I1kLs9n6/Z99R4TO7AnyYmxjE2MJSkhhl49O/smWREREREREQ9U5GgEixYtYuiwYWzbto2oqCheevFFrrzyyloxs2fPpn///gB069aNiRMm8MGHH/LJxx9z/vTpx53zwgsuAGD48OHMmTOHb7/91u21rbXc9YtfEBIc3OACB8DcuXPZvHkzl112GZ999hnnTJvGvG++ITQ0lGOFhQCuogdQq3dC9X5pvay1bN6y17Wca2ZWPjt3H/IYb4xh2JDeJCfEkJw0iKQxA+kaGeG7hEVERERERBpARY5GMGHCBN55+23Omz6dpUuX8vobbzBjxoxaMdu3b+fX99zDunXr8PfzY+euXa7t7kRGRgK4lq89dOiQ27h777uPOXPmkJSUREVFhVfL3UZHR/Pbhx/miiuuICcnh3+99x7Xz5xJuLOhamWNqTdVVd83lKzeL61HVVUV6/N3ufppZGZvZN/+ox7j/f39iB/Wl2RnP43EMQPp1FF9WEREREREpGVTkaORhIaG8sTjj3P2D37AkiVLeGvWLG64/noAtm3bxgUXXkhxcTFvz5rFpZdeys0338zb77xDlYfGjXV7GXhq8Ni9e3ciIyNZvnw5Tz39NA8+8IDHHIuKijh69Cg9e/Z0bRsyeLDr+/Xr1gEwaPBgVn33HSUlJa59xUVFru8HDRrk8RrSMlRUVLJmXYFrOdfl2Rs5fKTIY3xgoD+jRgxwTT8ZMyqasA7BPsxYRERERETk1KnI0YgmTpzI6aefztKlS3n22We57tpr8ff3JzMzk+LiYgCmO6em1BwlcSp+fffdpE6ZwrXXXcdTTz3FtGnTSEpMdBubmZnJc3/5i6tvCMDOnTtd31c3Fz132jT+/e9/c/DgQdfokH37HP0ZwsPDSUlJaZTcpfGUlVXwXd5WMrM2siwrn6yVmygqKvUYHxoSxJjR0a4lXUePGEBwcKAPMxYREREREWl8KnI0srvuuosZM2awadMm3n//fWbMmEGfGg1I165dy6BBg1iWmdlo17zsssuYM2cOH3z4ITfddBOLFi4kNDTUbexXX33FwoULmThxIkePHuUPTz0FOPqEXHHFFQBcfvnlvPB//8eKFSv48r//Zfp55/HFF18A8NCDDxKm6SrNrri4jJWrtpCZ7Zh+smLVFkpLyz3Gh4eFkDhmoGM518RY4ob1JShQ//xFRERERKRtMZ6mQbQXycnJNrOegkNJSQnvvP12rUaiaWlp3H333eStXg1AREQE0dHRLF2yhKqqKhISE1m/fj2dOnXikksu4YXnn+ehhx7i9TfeIDIykosvuog1a9fy2Wef0aFDB8477zwuuvDCWkvIpqSkcNttt3Hnz3/O3n37CAwMZOzYsTz+2GPccOONbNmyBYDBgwczPy2NCRMnsnnzZgD69+/PV//7X63VXcAxbeaJ3/2O5ZmZ+Pn5sWXrVjp27EjqlCk88MADDBw40BW7f/9+fvvww8ydO5egoCDCwsK4/fbbufGGG9w+T6+9/jp33HGH9z8AaZBjx0rIztnkWs71u9xtlFd4Hg3UuVOYYzlX5/SToYN74+/v5zFeRERERESkhTInDqkRrCKH90UOOZ6KHI3r4KFCslZsdE4/2cDqtQVUVXn+t9q9W0dXQSM5MYbYgT1rrYgjIiIiIiLSSnlV5NB49QZo74WghtBzdGr27jvC8mxHP43MrHzWbdhZb3yf3pGO5VwTYxmbFEv/vt2Oa1YrIiIiIiLS3qjIcQLBwcGupqEijWXHzoOufhrLsvLZvGVvvfHRA7o7R2k4lnTtHdXFR5mKiIiIiIi0HipynIAxxuMyr+JgrW201WLaImstW7fvc/TTyHIs6Vqw40C9xwwZFOWafpKUEEP3bh19lK2IiIiIiEjrpSJHA4wZM4YvvviCadOmNXcqLdLb77zDD37wg+ZOo8Ww1rJh4y7Xcq6ZWfns3XfEY7yfn2H40D6MTRxEcmIMiWNi6NJZK9iIiIiIiIh4S41HT9B4tFravHmsXLmS4OBgOnXujF87739QWVXFwYMHqaioYPLkySQkJDR3Ss2msrKKNesKyMzeSGZWPsuzN3LwUKHH+MAAf0bE93MVNRJGDSQ8PMSHGYuIiIiIiLQaWl3FGw0tclQrKyvjyJEj7b7Rpp+fHx07diQwMLC5U/G58vJKctdsc00/yVqxiWOFJR7jg4MDGTNygGv6yagRAwgNDfJhxiIiIiIiIq2WVldpSkFBQXTr1q250xAfKi0tZ+V3W1zLua7M2UJxSZnH+A4dgkkcPdC1nOuIuP4EBemfmoiIiIiISFPTJy+ROgqLSlmRs9nVTyPnuy2Ul3turNqpYweSEmJITohhbFIsw4b0ISDA34cZi4iIiIiICKjIIcKRo8Usz97oWNJ1eT65a7ZTWVnlMb5rZPj3y7kmxjI4thd+fn4+zFhERERERETcUZFD2p0DB485lnJ1Lue6Zt2Oenus9OrZ2VXUGJsYS/SA7ph23nhWRERERESkJVKRQ9q83XsO1VrONX/T7nrj+/ftRnJSLGMTYkhOjKVP70gVNURERERERFoBFTmkTbHWUrDjgGPlk+x8MrM2snX7vnqPiY3pSXJCLGOTYklOiKFnj86+SVZEREREREQalYoc0qpZa9m0eQ+Z2fnOwsZGdu0+5DHeGMOwIb1d/TSSE2KI7BLuu4RFRERERESkyajIIa1KVVUV6zbsdPbUcDQL3X/gmMd4f38/4of3c43SSBwTQ8eIUB9mLCIiIiIiIr6iIoe0aBUVlaxeW+CafrI8eyNHjhZ7jA8KCmDUiAGu5VxHj4wmrEOwDzMWERERERGR5qIih7QoZWUVrMrd6pp+kp2zmaKiUo/xoSFBjBkd7Vr9ZFR8f4KDA32YsYiIiIiIiLQUKnJIsyouLmPlqi0sy9pAZtZGVn63hdLSco/xEeEhJI6JITkxhrGJg4gb1pfAQH8fZiwiIiIiIiItlYoc4lPHjpWQtXITmVn5LMvKJzdvG+UVlR7ju3QOczUITU6MZejg3vj7+/kwYxEREREREWktVOSQJnXwUCHLszc6l3PNZ/XaAqqqrMf47t06MjYp1jX9JHZgT4wxPsxYREREREREWisVOaRR7dl7mOXZG1nmXP1kff7OeuP79I50FTTGJsbSr29XFTVERERERETkpKjIIaekYOcB13Kuy7Ly2bJ1b73xAwf0cPXTSEqIoXdUFx9lKiIiIiIiIm2dihzSYNZatmzb51rONTMrnx07D9Z7zNDBvUlOjCE5wTFao1vXCB9lKyIiIiIiIu2NihziUVVVFRs27nY1Cc3Mymff/qMe4/38DHHD+rqmnySOGUjnTmE+zFhERERERETaMxU5xKWysoo16wpc/TSWZ2/k0OFCj/GBAf6MjO/v6qeRMDqasLAQH2YsIiIiIiIi8j0VOdqxsvIKcldvd43UyF6xiWOFJR7jQ4IDGTMq2jX9ZPTIAYSEBPkwYxERERERERHPVORohcrKKjh6rJiI8FCCghr+IywpKSPnu62OkRrZ+axYuZmS0nKP8WFhwSSOHuiafhIf14+gQL1kREREREREpGVq1k+sxphzgHuBOKALsBdYBDxirc2rEdcP+DNwNmCAr4C7rLVbfZ50M8rO2cxb787n63mrKK+oJDDAn7POGMW1V05mzMjo4+ILC0tYkbPZ1U8jJ3cr5eWVHs/fqWMHkhNiSE6MJTkxhmFD+hAQ4N+Ej0hERERERESk8RhrbfNd3JgZQCKwFEeBoz9wH9APGGmt3WKM6QCsBEqBhwALPAF0AEZZaz03jWiA5ORkm5mZeSqn8In3P1rEo7//kKqq439efn6Gh++/jHPOGkPWio2u5Vzz1mynsrLK4zm7dY1wFDWSBjE2IYZBsb3w8/NryochIiIiIiIi4g3jVXBzFjncMcYMBdYAd1trnzXG3An8CRhqrd3gjBkIrAfusdb+6VSu1xqKHNk5m7n6xr+6LXB4I6pnZ5KTYklOiGVsUizR/btjjFevFxERERERERFf8upDa0tssLDf+bXC+fVCYEl1gQPAWrvJGLMQuAhHAaRNe+vd+SdV4Ojfr5tr5ZOxibH06R3ZBNmJiIiIiIiItAwtoshhjPEH/IEBwB+AXcA/nbvjgU/cHJYL/Ogkr7e8+vukpKSTOYXPlJVV8PW8VQ2O/9El4xl32mCSE2Lo0b1TE2YmIiIiIiIi0rK0iCIHjp4c1dWGDcAZ1to9zvuRwEE3xxzA0ay0TTt6rJjyCs/NQuu6647ziOwS3oQZiYiIiIiIiLRMLaXL5DXAOOBK4AjwP2NMdFNdzFqbVH1rqms0lojwUAIbuMJJYIA/4WEhTZyRiIiIiIiISMvUIooc1trV1tql1tp/AmcC4ThWWQHHKA53IzY8jfBoU4KCAjhz6sgGxZ51xiiCglrK4BwRERERERER32oRRY6arLWHcExZGeTclIujL0ddcUCej9JqVtddNQU/v/obyvr5Ga69crKPMhIRERERERFpeVpckcMY0xMYBuQ7N30KjDPGxNSIiQYmOve1eWNGRvPw/Zd5LHT4+Rkevv9HjBkZ7dvERERERERERFoQY633S5M22sWN+TeQBeTg6MUxBPgF0As4zVq7zhgTBqwEioGHAAs8DkQAo6y1x04lh+TkZJuZmXkqp/CZFas289a7C/jqmxzKKyoJDPDn7DNHcc2MySpwiIiIiIiISFtU/7SGusHNXOS4F/gxEAsEAduANOD31trNNeL6A38GzsbxAL8G7qoZc7JaU5GjWllZBccKSwgPC1EPDhEREREREWnLWk+RoyVojUUOERERERERkXbCqyJHi+vJISIiIiIiIiJyMlTkEBEREREREZE2QUUOEREREREREWkTVOQQERERERERkTah3TceNcbsBbY0dx5eGu78urpZsxAREWlZ9P4oIiLiXmt+j9xnrZ3W0OB2X+RojYwxywGstUnNnYuIiEhLofdHERER99rTe6Smq4iIiIiIiIhIm6Aih4iIiIiIiIi0CZquIiIiIiIiIiJtgkZyiIiIiIiIiEiboCKHiIiIiIiIiLQJKnKIiIiIiIiISJugIoeIiIiIiIiItAkqcoiIiIiIiIhIm6Aih4iIiIiIiIi0CSpyiIiIiIiIiEiboCKHiIiIiIiIiLQJKnKIiIiIiIiISJugIoeIiIiIiIiItAkqcoiIiIiIiIhIm9AuixzGmIuNMQuMMXuMMcXGmC3GmI+NMdOaO7emYIw50xjztjEm3/l4840x/2eM6eEmNsQY84wxZqczdrExZrKbuF8aY+Y446wx5hEP1/Y3xvzGGLPJGFNqjFlvjLmr8R+liIg0Br1Hntp7pDFmiDHmL8aYHGPMMWfsp8aY0R6u/xNjzBrne+RaY8ytTfVYRUTk5On90Xfvj8aY64wxs53PsTXGvOFN7u2uyGGM+Tnwb2A9cCMwHXjCufuM5sqrid0KdMXxOKcBvwcuBJYYY8LrxL4K/AT4LXA+sBP40hgzpk7cT4AewMcnuPYLwEPO854PfAD80Rjz0Ek+FhERaSJ6j2yU98gfAFOBN4ELgNuB7s7zJdU8mTHmJ8BLwGzntT8AXjDG3NaIj09ERE6R3h99+/4IXA3EAv8DjnibuLHWentMq2aM2Qost9Ze4mafn7W2qhGuEQhU2Bby5Bpjultr99bZNhmYD9xorX3NuW00sAK4wVr7unNbAJALrLXWXljjeD9rbZVzfznwqLX2kTrX6A9sAh6vuc8Y83cc/zn0sdYeaOSHKyIiJ0nvka5tJ/0eaYzpBuyv+fiMMZ2AzcAca+21NY7dAcy11l5XI/Y1HL9ERllry5vkQYuIiFf0/uja1uTvj87trufUGLMd+MpaO7Ohube7kRxAJLDL3Y6aL05jzCPGmONeYMaYN4wxm2vcj3YOobndGPO0MWYHUAokO7df6OYcLxhj9jpfyNXbbjbGrDTGlBhj9hljXjXGRNbYv8oY828350p1XsfjMKm6L06nZc6vfWpsuxBHweK9GsdWAP8CzjHGBNfY3pB/yKfheI3NrbP9CyAEOLcB5xAREd/Re6TDSb9HWmv31f0F1Vp7GFhX53zjcfwF6+06156F4y9nkzzlLCIiPqf3RwdfvD829LOmR+2xyPEtcJ0x5tfGmCGNeN4HgSHAzcAlwHfAWhxDbVyMMUHA5cC/qv9CY4z5A/A88BWOF8mvcQwJmmuM8Xce+n/A+caY3nWuewuO0RJfepnvFOfX1TW2xQObrLVFdWJzgSBgkJfXqHR+LauzvdT5dYSX5xMRkaal90iHRn2PdP7COcLN+cDxXNQ9H0CcNwmLiEiT0vujgy/eH09Zeyxy3ApsAJ4G1jorXv80xvzgFM+7G7jEWvsfa+0n1tpiHH+NucA5DKfaeTgqgbPAUcXD8YJ83Fr7K2vtf53DfH6MYyTEBc7jZgHFOKZ54Dy2O3Ap8LI3w5qMMRHAczheTB/X2BUJHHRzyIEa+72x1vl1XJ3t40/yfCIi0rT0Htk075F/A4zzvDXPh5tznux7roiINB29P/ru/fGUtbsih7V2HZCAowr1Oxzzhy7B0RjlVJphfuzmRfI2EAz8qMa2a3DMTfrWef9sHD+Hd4wxAdU3YClwFJjszPuo83w3GWOqf24zcbwoXmtoks5z/xPHkKArnEOJmoS1Ng9HZfFRY8w5xpjOxphLgLucIac8d01ERBqP3iMb/z3SGHM/cCXwU2vthlM9n4iI+J7eH1vX+2O7K3IAWGsrrbULrLUPWWvPAmKAVcDDxpguJ3nanW6uswVYgONFiTGmM45OvLNqhFUvwbMBx1ymmrcIHPNyq70A9AfOM8YYHMOa/m2t3dOQBJ0v7DeBs4CLrbU5dUIOAu4ef3X17WSahM4E8nD04TgIvAHc79x33HMmIiLNS++RjfceaRzLwT4JPFTdoK3O+XBzzlN5zxURkSai90efvT+esoDGPmFrZK3dYYz5B/AXYDCOOVcl4Jj/ZK2t2VOiq5tTAHga6jMLeMUYMwA4B8e8pJpNxvY7v/4A98N8qvdjrf3OGJOOYw5VCY75TbfU89DqehHHXK7LrLVfu9mfC1xijOlQZ05VHI6+Gl5X2Ky1BUCqcx5YJJAPjHLuzvD2fCIi4lt6j3Tx6j3SGHMNjl8sn7XW/s7D+cAxl7nmL7nVvTjyvMhdRER8TO+PLo39/njK2t1IDmNMlIddw5xfq7vmbnF+dTXHdFbRJnh5yQ9wNNq8Ckc1Lt1Znav2PxzTNvpbazPd3DbVOd8LOFYleQRYZ639piFJGGOeBW4CrrfWfuwhbA4QSI2hUc6hSZcD/7XWlno47oSstTustd/h+Id1F7AGSDvZ84mISOPTe2TjvEc6p2a+DvzDWnu3h/MtBvbheOw1XY3jr14LG5K7iIg0Pb0/+vT98ZS1x5Ec3xljvgI+x9FRtiOORi63Au9ba7c64+YCh3FU0B7GMS/qHuCYNxez1h4xxnwC3AFEAT+psz/fGPMU8HdjzFAc6w6XAP1wzLX6h7V2Xo1DZuNozDIR+FVDcjDG3Av8Ese8q/XGmJqNQPdaa/OduWQbY94DnjOOpYk2AbcBA6nzS5gxJhmI5vtCWZwx5jLn959XV/GMMbc5H88moBdwHY5l8c60jbCetIiINCq9R57ie6QxZjKOecsrgTfqnK/UWpvtPF+5MeY3wAvGmAIcPazOAG4AflbnL4AiItK89P7oo/dHZ2wc349sDAUG1PisOd+6X972e9badnXD8UL8FEeVrQQoBLJxvPiC6sROwrEWcBGO9XuvxtFTYnONmGgcw4xuquea050xxUAnDzHXAEuc+RzD0bX270BfN7EvOc/VtYGPOc15fXe3N+rEhgJ/wlGNLMHRvCbVzTnfqOec0TXifopjlZUSHH+Z+giIb+7XgW666aabbsff9B556u+ROP5K5ul8m91c/xbn81cKrAdub+7XgW666aabbrVven/07fvjCWJTT5S7cZ5EWgnn0J8NOIYsXdPc+YiIiLQUeo8UERE5Xnt7f2yP01VaJWNMRxxzu67EMQzp2ebNSEREpGXQe6SIiMjx2uv7o4ocrUciMA/YA9xprV3RvOmIiIi0GHqPFBEROV67fH/UdBURERERERERaRPa3RKyIiIiIiIiItI2qcghIiIiIiIiIm2CihwiIiIiIiIi0iaoyCEiIuJjxhh/Y8wuY8xhY4x1ft1ljPF37r/LGLPXue+gMeaz5s4ZwBiT4syzzBizuQnOH2mM+b0x5jtjzE5jzG5jTJ4xZpYx5iZjTFBjX1NERETaFjUeFRERaSbGmJnA68D11to3amwPAv4FBAKXWWtLmyVBD4wxaUC0tTa6Ec/ZGcgG8oGfWGs3GWP8gNOBV4HhQJS1dldjXVNERETaHo3kEBERaUGMMcHAR4AFLm1pBY4mdCMQDdxsrd0EYK2tstYuBmY2Y14iIiLSiqjIISIi0kIYY0KBT4GjwOXW2vJmTsmXhji/7nWzbxnwClDsu3RERESkNVKRQ0REpAUwxoQBnwO7gKuttRVuYsKNMQ8aYzKNMQXOXh7pxpizPZzzOmPMWmPMAWPMamPMbcaYN5y9PnYZY+6tEXu6MWahMeaoMWaTMeY5Z7x1Hv9JAx7DCGPMJ8aY/c5jlhljrmjgU1A9DeW6ujusw83W2sPO6/y2Rs+SR2pc/6MafU5Snduq+58cc25PdPb42O68n+HM1Rpjjhhjcmqc7zPntiJjzIs1tk8yxnzjPO6AMWa+MeasGvuXGWPKjTGVzmtf5Nx+kfO+dfYb6e7mOZxgjNnnjDlWs/eJMeZd5+MrMca829B8nDE9nP1Ocpz9Tg4ZY740xiTXifukxvNxgzHmYWPMOudj0RxnERFp8VTkEBERaX4RwJfAehz9OSo9xEUDjwK/t9b2AXoAi4G5xpjRNQONMdcCbwDvOuPGAqcB5wJYa3tZa59yxsYBXwMHgT7AYGA18LDzdJdaay+q7wEYY0YCi4ADQH/nNV8F/mmMua0Bz8GHQBXwV2PMv40x5zun7hzHWvuY8/HU3X4pcGedbZXW2l7AH52bngX+aq3tCzwBVACDgDLgM2vtqBrHTscxdegX1tpbnY/zbOAb52PtBUQBGcCXxpjpzuPG4njuAZKstZ84t38CXADkWWt7WmuPG7VirV0E9AOOAAtr9j2x1l4JvA381vl9g/JxOg34KXC7tTYKx89oL/C1MSaqxjUuAi513r0L2AwMA35QN1cREZGWSEUOERGR5vcHIBl4ylpbVU9cMfCatXY2gLNfx33AbuCe6iBjTADwFLAVeMxaW2GtPQbcAbhboeQxIAy401p7xBn/EpDjJtaTv+IoFNxhrS10nuNFHMWTJ4wxIfUdbK1dhaMvx1HgYmAOsM8Y874x5hwv8jiRz6y1y5zf/wP4u7X2APAf4GJjTKfqQOfomunAe877fsCLOIpRv7HWljl/Br/B0TD1mRrXeQPH71nX1rn+TL4vgLhlrS0G3gfOMsb0qZFPMPAjYNZJ5HMIeNZam+G8xhHgFqADjuKHO1uttW86X5NpwC/qy1tERKQlUJFDRESk+a0DgnGMyDhuCkM1a22+tfbmOtuqcHygHV5jczKOv+r/19ZYRs1aWwRk1jzeOJatnQZssNbm17nk/IYkb4zpBqQCi5zXqGk5EOnMqV7OFWaigZ8B6Tg+gP8I+MIY86Ez11OVUeN6W6y1HzrvvgmEAD+uEftDYJ619pDzfiIQA3xd53mtwrEyzHBjTF/ntoU4ig+u6TfOIsVlOIsUJ/AGxxdJLgSWWWt3nkQ+GdbaR2pewFpbCOyk9munpprPVaW19rkG5C0iItKsVOQQERFpfn8BnscxTeRzY0y4p0BjzI+d/Re2Ofs77ALG4SgkVIt2fnW33Grdbd1xjOJoSKwnsc6vZ1XnVCO3m4BCoGdDTmStPWit/bu1djLQG8cIlUM4Cg43NTCf+uzxsH0ujukbNXuCXIej+FGt+nFe7+Zx/gDH44yqEf8mMNQYM8F5v7pIccLntUaRZGaNzTNxLDnsdT7O3iQ3G2MWGUc/l+q4PtR+7dTk6bkSERFpsVTkEBERaRl+DvwLx4iHD40xgXUDjDF34Zg68S0w3NlXoxeOfgwtwezqnGrculprw6un2HjDWrvbWvsM34+uOKu+eKcT/W7jdjqQcyWbd4GJxphBxpj+OEY4fOkm/Dk3j7OL83EuqxH3lvN6M533Z1K7SHEibwJDnM1Ie+F4bXx6kvk8C7wE/BOIrfHa2VbP9eubOiUiItIiqcghIiLSAjinGFyL40P1OcBrxhhTJ2wmjr/O3+/sseHJZufXXm721R1RsRcoamCsJ9XTXPrU3WGMCTDGnGWMiajvBMaYB4wxz3jYvdD5tUONbdWrzwTUifU43acBqkdtXAtcA/yrzio3G5xf3T3OcOfjdBWnrLXbcPQkudwYEwMk4eg10lDVRZLrnfm8b60tO8l8ZuJoePo3a22JFzmIiIi0KipyiIiItBDO0QQ/BJYCVwNP1wkpBdwt49mvzv1MHFNNflCzUGKMCaVObwznSi5zgUHGmEF1zjO5gXnvw7HCx0Q3PUXOw9FEs+y4A2sLAqa6KewAxDm/Lq+xbQ+OQkffOrHjGpKzO9babGAVjiLHtTiKDDVl4ygsnOdmpM0NwF+cP8Oa3gA64hilU7dIcaJ8qoskP8bRlLXuKBBv8imte35jTBANL2SJiIi0CipyiIiItCDOZpDnAXnA3caYX9bYPRsIBx5zjpDwN8Y8gKP5ZM1zVAD34lgm9DfOuDAcvT+OW7YUx2ochcBzxpiOznP/xHl8Q/0cx+ovLxtjIgGMMQnA33Cs/HHch2w3koC/O6dmYBzG4fhwv815rurHWAb8D5hujBnqjP0h3/cjOVlvAgOAEmvtipo7nKNtbgG6AH8xxnRw5nkG8Ahwv5vz/Rs4jGPJW2+mqlR7A0eRpNRam3UK+cwG4px9OYxztZvncDRbFRERaTNU5BAREfExZ9FhF46iAzg+oO6qXj3EuaTpOTiWgP2jc99tOPoqPAhcCewDsnB8AF4C9HPGTXWe4y0cUxSuwlHYWIxjVMAS6owGsdauBs7E8WF5O7AGxwiJPztDqpx5pzjznlDjepc7z5GLYxRFFbDWGLMDxxKtD1hrn2/A0/IKcBeOgs0i53UO4xhN8Q0w1lpbt0BzA44VQJbgmDIzku8LIR8ZYz5y5p0L3O3cvswYk4Vn7+AYIVJ3FAfOx/kNMAVH089txpgC4FHgSmvtcf0yaiwHm+McKeKt6iLJG6eYz904Xj8P4Xg9LAI24SgeTXD+LAcZY14BPnIeU/26jD6JvEVERJqFqbHimIiIiLRxxpi5QLK19oS9K4wx9wJ/AEY4ixhyEowxLwDrTmYJVueys1tx/AzcjcIRERGRGjSSQ0REpA0yxtxkjJlZZ1sQMAZIr7N9jDHm725OczqOv/qvaaI02yRjTKBzelB1keJSHCNEGnp8ePWoHuAiYLEKHCIiIg2jIoeIiEjb1At41BgzDMC5uslzQGcc0xlqCgduNsZc6IwNdBZILgQecjYnlYabCPzb2UT1duC/XhYp/g5c4SyQ3A38tQlyFBERaZPqLrsmIiIibcOnwGDgM+eoghAcfTlSrLUr68SuwfFB+kljzEtAGLAOuMZa+08f5txWHAZG4BgFsxrHijne2AK8ADwDvObsuyEiIiINoJ4cIiIiIiIiItImaLqKiIiIiIiIiLQJKnKIiIiIiIiISJugIoeIiIiIiIiItAkqcoiIiIiIiIhIm6Aih4iIiIiIiIi0Cf8P7waHmZvc/fMAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 1296x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "#Remove the first row\n",
    "df_2019c = df_2019.iloc[1:]\n",
    "df_2020c = df_2020.iloc[1:]\n",
    "df_2021c = df_2021.iloc[1:]\n",
    "\n",
    "#count the number of participants\n",
    "df_2021c = df_2021c.Q3.value_counts().sort_values(ascending = False).reset_index()\n",
    "df_2020c = df_2020c.Q3.value_counts().sort_values(ascending = False).reset_index()\n",
    "df_2019c = df_2019c.Q3.value_counts().sort_values(ascending = False).reset_index()\n",
    "\n",
    "#Get the Rank\n",
    "Egypt_rank_2021  = df_2021c[df_2021c['index'] == 'Egypt'].index.values.astype(int)[0]\n",
    "Egypt_rank_2020  = df_2020c[df_2020c['index'] == 'Egypt'].index.values.astype(int)[0]\n",
    "Egypt_rank_2019  = df_2019c[df_2019c['index'] == 'Egypt'].index.values.astype(int)[0]\n",
    "\n",
    "#Build a dataframe\n",
    "rank_egypt_dict = {'Survey_Year': [  'Survey 2019' , 'Survey 2020' , 'Survey 2021'] , \n",
    "                  'Egypt_Rank':[ Egypt_rank_2019 , Egypt_rank_2020  , Egypt_rank_2021]}\n",
    "rank_egypt_df  = pd.DataFrame(rank_egypt_dict)\n",
    "\n",
    "\n",
    "\n",
    "#Display the dataframe\n",
    "display (rank_egypt_df)\n",
    "\n",
    "\n",
    "\n",
    "\n",
    "#Plot the bar plot\n",
    "fig , ax  = plt.subplots(figsize = (18 , 5 ))\n",
    "ax.plot(rank_egypt_df['Survey_Year'] , \n",
    "       rank_egypt_df['Egypt_Rank']  ,\n",
    "        marker  = 'o',\n",
    "       color = '#283270')\n",
    "\n",
    "\n",
    "#ax settings\n",
    "ax.set_xlabel('Kaggle Survey year' , fontfamily='serif' )\n",
    "ax.set_ylabel('Egypt Rank' , fontfamily='serif')\n",
    "ax.set_title('Egypt Annuly Up-rankking' , title_prop)\n",
    "#ax.set_ylim(0 , 530)\n",
    "\n",
    "#Remove spines\n",
    "for s in [\"top\",\"right\"]:\n",
    "    ax.spines[s].set_visible(False)\n",
    "\n",
    "ax.invert_yaxis();\n",
    "\n",
    " \n",
    "#Annotate texts\n",
    "ax.text(2, 15, 'Rank 10th', text_prop)\n",
    "ax.text(1, 24, 'Rank 21', text_prop)\n",
    "ax.text(0, 27, 'Rank 30', text_prop)\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "4fd23a9b",
   "metadata": {
    "papermill": {
     "duration": 0.032094,
     "end_time": "2021-11-24T12:07:55.981095",
     "exception": false,
     "start_time": "2021-11-24T12:07:55.949001",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "We can obviously notice how Egypt **uprank** in an annualy basis:\n",
    "* At 2019 : Egypt ranked in the **30th** place with total number of participants 122.\n",
    "* At 2020 : Egypt ranked in the **21th** place with total number of participants 179.\n",
    "* At 2021 : Egypt ranked in the **10th** place with total number of participants 482.\n",
    "\n",
    "I will assume that all the Egyptain who got the most binifit from the latest initiations has experince less than 3 years of coding<br>\n",
    "Fortunately Qustion number 6 in the survey _For how many years have you been writing code and/or programming?_ <br>could give us a clue to continue our analysis<br>\n",
    ">for the rest of the analysis we will mark all participants with less than 3 years of experince and label them as Juniors<br>\n",
    ">the next question would be <br><strong>out of the 482 Egyptian participants in 2021 survey , How many of them we could mark them as Juniors?</strong>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "211a7bb0",
   "metadata": {
    "_kg_hide-input": true,
    "_kg_hide-output": true,
    "execution": {
     "iopub.execute_input": "2021-11-24T12:07:56.051897Z",
     "iopub.status.busy": "2021-11-24T12:07:56.051182Z",
     "iopub.status.idle": "2021-11-24T12:07:57.288907Z",
     "shell.execute_reply": "2021-11-24T12:07:57.288290Z",
     "shell.execute_reply.started": "2021-11-24T10:24:01.708052Z"
    },
    "papermill": {
     "duration": 1.274999,
     "end_time": "2021-11-24T12:07:57.289071",
     "exception": false,
     "start_time": "2021-11-24T12:07:56.014072",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "\n",
    "#-------------------------------------------------------------------------------------#\n",
    "# In this cell I will change the long str varibales to short for better visualization #\n",
    "# I will Also change the bins of the Question Answers a littel bit to serve my story  #\n",
    "# For Example the Age band I only care how many people over 30                        #\n",
    "#_____________________________________________________________________________________#\n",
    "\n",
    "\n",
    "#Load the kaggle survey data for 2021\n",
    "df_2021 = pd.read_csv('/kaggle/input/kaggle-survey-2021/kaggle_survey_2021_responses.csv')\n",
    "\n",
    "\n",
    "#subset the data frame for country Egypt\n",
    "Egypt_2021 = df_2021[df_2021.Q3=='Egypt']\n",
    "\n",
    "\n",
    "# Create Experince_level column.\n",
    "# Junior : from 0 to 3 years coding experince.\n",
    "# Senior : from 3 to 10 years coding experince.\n",
    "# Master : more than 10 years experince in coding.\n",
    "Egypt_2021['Experince_level'] = Egypt_2021['Q6']\n",
    "Egypt_2021['Experince_level'] = Egypt_2021['Experince_level'].apply(lambda x: 'Junior'  if x == 'I have never written code' else x)\n",
    "Egypt_2021['Experince_level'] = Egypt_2021['Experince_level'].apply(lambda x: 'Junior'  if x == '< 1 years' else x)\n",
    "Egypt_2021['Experince_level'] = Egypt_2021['Experince_level'].apply(lambda x: 'Junior'  if x == '1-3 years' else x)\n",
    "Egypt_2021['Experince_level'] = Egypt_2021['Experince_level'].apply(lambda x: 'Senior' if x == '3-5 years' else x)\n",
    "Egypt_2021['Experince_level'] = Egypt_2021['Experince_level'].apply(lambda x: 'Senior' if x == '5-10 years' else x)\n",
    "Egypt_2021['Experince_level'] = Egypt_2021['Experince_level'].apply(lambda x: 'Master' if x == '10-20 years' else x)\n",
    "Egypt_2021['Experince_level'] = Egypt_2021['Experince_level'].apply(lambda x: 'Master' if x == '20+ years' else x)\n",
    "\n",
    "\n",
    "\n",
    "# Change the long answers in the degree column for better visualization.\n",
    "Egypt_2021.Q4 = Egypt_2021.Q4.apply(lambda x:'High School' if x == 'No formal education past high school' else x)\n",
    "Egypt_2021.Q4 = Egypt_2021.Q4.apply(lambda x:'Still in College' if x == 'Some college/university study without earning a bachelor’s degree' else x)\n",
    "\n",
    "\n",
    "\n",
    "# Change the answers in are you using ML in your work to be yes or no for the analysis purpos.\n",
    "Egypt_2021.Q23 = Egypt_2021.Q23.apply(lambda x: 'Yes' if x == 'We have well established ML methods (i.e., models in production for more than 2 years)' else x)\n",
    "Egypt_2021.Q23 = Egypt_2021.Q23.apply(lambda x: 'Yes' if x == 'We recently started using ML methods (i.e., models in production for less than 2 years)' else x)\n",
    "Egypt_2021.Q23 = Egypt_2021.Q23.apply(lambda x: 'Yes' if x == 'We use ML methods for generating insights (but do not put working models into production)' else x)\n",
    "Egypt_2021.Q23 = Egypt_2021.Q23.apply(lambda x: 'No' if x == 'No (we do not use ML methods)' else x)\n",
    "Egypt_2021.Q23 = Egypt_2021.Q23.apply(lambda x: 'No' if x == 'I do not know' else x)\n",
    "Egypt_2021.Q23 = Egypt_2021.Q23.apply(lambda x: 'No' if x == 'We are exploring ML methods (and may one day put a model into production)' else x)\n",
    "\n",
    "\n",
    "\n",
    "#change the age band in the Q1.\n",
    "Egypt_2021.Q1 = Egypt_2021.Q1.apply(lambda x: 'Older Than 30 Years' if x =='30-34' else x)\n",
    "Egypt_2021.Q1 = Egypt_2021.Q1.apply(lambda x: 'Older Than 30 Years' if x =='30-34' else x)\n",
    "Egypt_2021.Q1 = Egypt_2021.Q1.apply(lambda x: 'Older Than 30 Years' if x =='35-39' else x)\n",
    "Egypt_2021.Q1 = Egypt_2021.Q1.apply(lambda x: 'Older Than 30 Years' if x =='40-44' else x)\n",
    "Egypt_2021.Q1 = Egypt_2021.Q1.apply(lambda x: 'Older Than 30 Years' if x =='45-49' else x)\n",
    "Egypt_2021.Q1 = Egypt_2021.Q1.apply(lambda x: 'Older Than 30 Years' if x =='50-54' else x)\n",
    "Egypt_2021.Q1 = Egypt_2021.Q1.apply(lambda x: 'Older Than 30 Years' if x =='55-59' else x)\n",
    "Egypt_2021.Q1 = Egypt_2021.Q1.apply(lambda x: 'Older Than 30 Years' if x =='60-69' else x)\n",
    "Egypt_2021.Q1 = Egypt_2021.Q1.apply(lambda x: 'Older Than 30 Years' if x =='70+' else x)\n",
    "\n",
    "\n",
    "\n",
    "\n",
    "#-------------------------------------------------------------------------------#\n",
    "#                                  We are Good to Go                            #\n",
    "#_______________________________________________________________________________#"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "2f6aeda0",
   "metadata": {
    "papermill": {
     "duration": 0.032472,
     "end_time": "2021-11-24T12:07:57.355465",
     "exception": false,
     "start_time": "2021-11-24T12:07:57.322993",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "## (Q2) Invistigate the level of experience of the Egyptian participants in Kaggle 2021 survey."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "2094d785",
   "metadata": {
    "papermill": {
     "duration": 0.03211,
     "end_time": "2021-11-24T12:07:57.420096",
     "exception": false,
     "start_time": "2021-11-24T12:07:57.387986",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "For the purpose of my analysis I will use Qustion number 6 in the survey _For how many years have you been writing code and/or programming?_ with a littel modifications as follow:\n",
    "\n",
    ">Junior : Who have less than 3 years ecperince in coding.<br>\n",
    ">Senior : From 5 to 10 years ecperince in coding.<br>\n",
    ">Master : Who have more than 10 years ecperince in coding.<br>\n",
    "\n",
    "**Now Let's count the numbers**\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "3459bf76",
   "metadata": {
    "_kg_hide-input": true,
    "execution": {
     "iopub.execute_input": "2021-11-24T12:07:57.489473Z",
     "iopub.status.busy": "2021-11-24T12:07:57.488789Z",
     "iopub.status.idle": "2021-11-24T12:07:57.809964Z",
     "shell.execute_reply": "2021-11-24T12:07:57.809429Z",
     "shell.execute_reply.started": "2021-11-24T10:24:02.734701Z"
    },
    "papermill": {
     "duration": 0.356635,
     "end_time": "2021-11-24T12:07:57.810101",
     "exception": false,
     "start_time": "2021-11-24T12:07:57.453466",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
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       "#T_00329_row0_col1 {\n",
       "  background-color: #023858;\n",
       "  color: #f1f1f1;\n",
       "}\n",
       "#T_00329_row1_col1 {\n",
       "  background-color: #d7d6e9;\n",
       "  color: #000000;\n",
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       "#T_00329_row2_col1 {\n",
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       "</style>\n",
       "<table id=\"T_00329_\">\n",
       "  <thead>\n",
       "    <tr>\n",
       "      <th class=\"blank level0\" >&nbsp;</th>\n",
       "      <th class=\"col_heading level0 col0\" >Experince_level</th>\n",
       "      <th class=\"col_heading level0 col1\" >Number_of_Egyptian_participants</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th id=\"T_00329_level0_row0\" class=\"row_heading level0 row0\" >0</th>\n",
       "      <td id=\"T_00329_row0_col0\" class=\"data row0 col0\" >Junior</td>\n",
       "      <td id=\"T_00329_row0_col1\" class=\"data row0 col1\" >354</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_00329_level0_row1\" class=\"row_heading level0 row1\" >1</th>\n",
       "      <td id=\"T_00329_row1_col0\" class=\"data row1 col0\" >Senior</td>\n",
       "      <td id=\"T_00329_row1_col1\" class=\"data row1 col1\" >100</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_00329_level0_row2\" class=\"row_heading level0 row2\" >2</th>\n",
       "      <td id=\"T_00329_row2_col0\" class=\"data row2 col0\" >Master</td>\n",
       "      <td id=\"T_00329_row2_col1\" class=\"data row2 col1\" >28</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n"
      ],
      "text/plain": [
       "<pandas.io.formats.style.Styler at 0x7fbf88237ad0>"
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\n",
      "text/plain": [
       "<Figure size 1296x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "ex_level_count = Egypt_2021.Experince_level.value_counts().reset_index().rename(columns = {'index':'Experince_level' , 'Experince_level': 'Number_of_Egyptian_participants'})\n",
    "display (ex_level_count.style.background_gradient())\n",
    "\n",
    "fig , ax  = plt.subplots(figsize = (18 , 5 ))\n",
    "ax.bar(ex_level_count.Experince_level , ex_level_count.Number_of_Egyptian_participants  , color = color )\n",
    "ax.set_xlabel('Experince_level (Years in Coding)' , fontfamily='serif' )\n",
    "ax.set_ylabel('Counts of Participants' , fontfamily='serif')\n",
    "ax.set_title('Level of experience of the Egyptian participants' , title_prop)\n",
    "ax.set_ylim(0 , 400)\n",
    "for s in [\"top\",\"right\"]:\n",
    "    ax.spines[s].set_visible(False)\n",
    "ax.text(0, 310, '354 Junior Participant', text_prop)\n",
    "ax.text(1, 110, '90', text_prop)\n",
    "ax.text(2, 60, '28', text_prop)\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "a2d2cc5f",
   "metadata": {
    "papermill": {
     "duration": 0.034067,
     "end_time": "2021-11-24T12:07:57.878652",
     "exception": false,
     "start_time": "2021-11-24T12:07:57.844585",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "354 Egyptian participants out of 482 have less than three years of Coding experince.<br>\n",
    "Most of them was directly impacted with one or more of the current intitations in Egypt<br>\n",
    "But still the question exist **Who are thoose Juniors , What are thier ages , Whats are thier education background !!**<br>\n",
    ">Let's Dig Deep \n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "33ef84f7",
   "metadata": {
    "papermill": {
     "duration": 0.034608,
     "end_time": "2021-11-24T12:07:57.948026",
     "exception": false,
     "start_time": "2021-11-24T12:07:57.913418",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "## (Q3) Invistigate the chartaristics and background of the Egyptain who got the most binifits from the Egyption initiations"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "a0afbe69",
   "metadata": {
    "papermill": {
     "duration": 0.034547,
     "end_time": "2021-11-24T12:07:58.017489",
     "exception": false,
     "start_time": "2021-11-24T12:07:57.982942",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "To answer this research question we will re-shape the survey dataset<br>\n",
    "Using the following helper function we will create a data frame shows the three experince level in columns and indexing with the other variables<br>\n",
    "like Age band , Education background  , etc..."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "ae106a23",
   "metadata": {
    "_kg_hide-input": true,
    "execution": {
     "iopub.execute_input": "2021-11-24T12:07:58.102730Z",
     "iopub.status.busy": "2021-11-24T12:07:58.101996Z",
     "iopub.status.idle": "2021-11-24T12:07:58.105489Z",
     "shell.execute_reply": "2021-11-24T12:07:58.106085Z",
     "shell.execute_reply.started": "2021-11-24T11:52:06.371168Z"
    },
    "papermill": {
     "duration": 0.054044,
     "end_time": "2021-11-24T12:07:58.106261",
     "exception": false,
     "start_time": "2021-11-24T12:07:58.052217",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Helper functions are ready to use\n"
     ]
    }
   ],
   "source": [
    "\n",
    "#--------------------------------------------------------------------------------------------------------#\n",
    "#                                        Helper Functions                                                #\n",
    "#________________________________________________________________________________________________________#\n",
    "\n",
    "\n",
    "def varibale_experince_level_df (df , Qx , new_df = None):\n",
    "    \"\"\"\n",
    "    Define a Function to create a data frame showing deffrinet variables accross the Experince level \n",
    "    imput\n",
    "    df : pandas dataframe\n",
    "    Qx : str ,  column name of the required varibale\n",
    "    new_df : a place holder for the new generated data frame\n",
    "    return\n",
    "    new_df : new pandas dataframe\n",
    "    \"\"\"\n",
    "    Egypt_Jonuirs = df[df.Experince_level == 'Junior'][Qx].reset_index().groupby(Qx)['index'].count().reset_index()\n",
    "    Egypt_Jonuirs.rename(columns ={'index':'Juniors'} , inplace = True)\n",
    "\n",
    "    Egypt_Seniors = df[df.Experince_level == 'Senior'][Qx].reset_index().groupby(Qx)['index'].count().reset_index()\n",
    "    Egypt_Seniors.rename(columns ={'index':'Seniors'} , inplace = True)\n",
    "\n",
    "    Egypt_Master = df[df.Experince_level == 'Master'][Qx].reset_index().groupby(Qx)['index'].count().reset_index()\n",
    "    Egypt_Master.rename(columns ={'index':'Masters'} , inplace = True)\n",
    "    \n",
    "    new_df = Egypt_Jonuirs.set_index(Qx).join(Egypt_Seniors.set_index(Qx))\n",
    "    new_df = new_df.join(Egypt_Master.set_index(Qx))\n",
    "    \n",
    "    return (new_df)\n",
    "\n",
    "\n",
    "\n",
    "\n",
    "def variable_experince_level_stacked_bars (df , title):\n",
    "    \"\"\"\n",
    "    Define a function to plot a stacked bar chart for the experince levels accross diffrent variables\n",
    "    input\n",
    "    df    : pandas dataframe\n",
    "    title : str  , tiltle of the chart\n",
    "    return \n",
    "    matplotlib stacked bar chart\n",
    "    \"\"\"\n",
    "    fig , ax = plt.subplots(figsize = (18 , 5 ))\n",
    "    ax.bar(df.index  , df.Juniors , label   ='Juniors' , color = '#283270')\n",
    "    ax.bar(df.index  , df.Seniors ,bottom  = df.Juniors ,  label   ='Seniors' , color = 'darkgray')\n",
    "    ax.bar(df.index  , df.Masters ,bottom  = df.Juniors+ df.Seniors ,  label   ='Masters' , color = '#323236')\n",
    "    ax.set_title (title , title_prop)\n",
    "    ax.set_xticklabels(df.index , rotation  = 45)\n",
    "    for s in [\"top\",\"right\"]:\n",
    "        ax.spines[s].set_visible(False)\n",
    "    plt.legend()\n",
    "    return fig , ax\n",
    "\n",
    "print ('Helper functions are ready to use')\n",
    "    \n",
    "#--------------------------------------------------------------------------------------------------------#\n",
    "#                                        We are Good to Go                                               #\n",
    "#________________________________________________________________________________________________________#"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ba06dbc3",
   "metadata": {
    "papermill": {
     "duration": 0.034609,
     "end_time": "2021-11-24T12:07:58.175707",
     "exception": false,
     "start_time": "2021-11-24T12:07:58.141098",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "### (Q3-2) How old are the Egyptian Juniors ?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "13b58504",
   "metadata": {
    "_kg_hide-input": true,
    "execution": {
     "iopub.execute_input": "2021-11-24T12:07:58.251137Z",
     "iopub.status.busy": "2021-11-24T12:07:58.250468Z",
     "iopub.status.idle": "2021-11-24T12:07:58.647577Z",
     "shell.execute_reply": "2021-11-24T12:07:58.646914Z",
     "shell.execute_reply.started": "2021-11-24T11:52:09.327502Z"
    },
    "papermill": {
     "duration": 0.435688,
     "end_time": "2021-11-24T12:07:58.647725",
     "exception": false,
     "start_time": "2021-11-24T12:07:58.212037",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
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       "<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>Juniors</th>\n",
       "      <th>Seniors</th>\n",
       "      <th>Masters</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Age Band</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>18-21</th>\n",
       "      <td>114</td>\n",
       "      <td>8</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22-24</th>\n",
       "      <td>95</td>\n",
       "      <td>34</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25-29</th>\n",
       "      <td>50</td>\n",
       "      <td>32</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Older Than 30 Years</th>\n",
       "      <td>95</td>\n",
       "      <td>26</td>\n",
       "      <td>28.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                     Juniors  Seniors  Masters\n",
       "Age Band                                      \n",
       "18-21                    114        8      NaN\n",
       "22-24                     95       34      NaN\n",
       "25-29                     50       32      NaN\n",
       "Older Than 30 Years       95       26     28.0"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1296x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "#Create and Display the data frame\n",
    "ages_experince_level = varibale_experince_level_df (Egypt_2021 , 'Q1' , new_df = None)\n",
    "ages_experince_level.index.names = ['Age Band']\n",
    "display (ages_experince_level)\n",
    "\n",
    "#Plot the figure\n",
    "fig , ax = variable_experince_level_stacked_bars (ages_experince_level , 'Ages of Egyptian particibants across thier coding experince level')\n",
    "ax.set_xlabel('Age Bands' , fontfamily='serif' )\n",
    "ax.set_ylabel('Counts of Participants' , fontfamily='serif')\n",
    "ax.text(3, 60, '95 Junior', text_prop)\n",
    "ax.text(2, 20, '50 Junior', text_prop)\n",
    "ax.text(1, 60, '95 Junior', text_prop)\n",
    "ax.text(0, 70, '114 Junior', text_prop)\n",
    "ax.set_ylim(0,165)\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ff126151",
   "metadata": {
    "papermill": {
     "duration": 0.037371,
     "end_time": "2021-11-24T12:07:58.723344",
     "exception": false,
     "start_time": "2021-11-24T12:07:58.685973",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "Did you notice how many particibants older than 30 years old and have only less than 3 years of coding experince ! <br>\n",
    "\n",
    "><strong> A personal experience</strong><br> Iam one of them with my 35 years old I started my career as a civil engineer with more than 12 years experince in construction  and I just found my Passion in data from just seven months ago <br>\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "095c3ed6",
   "metadata": {
    "papermill": {
     "duration": 0.03721,
     "end_time": "2021-11-24T12:07:58.797953",
     "exception": false,
     "start_time": "2021-11-24T12:07:58.760743",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "### (Q3-3) What is the education Level of my group (The Juniors) who started coding in less than 3 years ago?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "084a2846",
   "metadata": {
    "_kg_hide-input": true,
    "execution": {
     "iopub.execute_input": "2021-11-24T12:07:58.890591Z",
     "iopub.status.busy": "2021-11-24T12:07:58.887978Z",
     "iopub.status.idle": "2021-11-24T12:07:59.320893Z",
     "shell.execute_reply": "2021-11-24T12:07:59.321468Z",
     "shell.execute_reply.started": "2021-11-24T11:52:56.386424Z"
    },
    "papermill": {
     "duration": 0.485689,
     "end_time": "2021-11-24T12:07:59.321713",
     "exception": false,
     "start_time": "2021-11-24T12:07:58.836024",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Juniors</th>\n",
       "      <th>Seniors</th>\n",
       "      <th>Masters</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Education Degree</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Bachelor’s degree</th>\n",
       "      <td>232</td>\n",
       "      <td>53</td>\n",
       "      <td>7.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Doctoral degree</th>\n",
       "      <td>11</td>\n",
       "      <td>10</td>\n",
       "      <td>10.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>High School</th>\n",
       "      <td>7</td>\n",
       "      <td>2</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>I prefer not to answer</th>\n",
       "      <td>9</td>\n",
       "      <td>2</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Master’s degree</th>\n",
       "      <td>42</td>\n",
       "      <td>27</td>\n",
       "      <td>9.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Still in College</th>\n",
       "      <td>53</td>\n",
       "      <td>5</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                        Juniors  Seniors  Masters\n",
       "Education Degree                                 \n",
       "Bachelor’s degree           232       53      7.0\n",
       "Doctoral degree              11       10     10.0\n",
       "High School                   7        2      NaN\n",
       "I prefer not to answer        9        2      NaN\n",
       "Master’s degree              42       27      9.0\n",
       "Still in College             53        5      NaN"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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\n",
      "text/plain": [
       "<Figure size 1296x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "Degree_experince_level = varibale_experince_level_df (Egypt_2021 , 'Q4' , new_df = None)\n",
    "Degree_experince_level.index.names = ['Education Degree']\n",
    "display (Degree_experince_level)\n",
    "fig , ax = variable_experince_level_stacked_bars (Degree_experince_level , 'Education level of Egyptian particibants across thier coding experince level')\n",
    "ax.set_ylim(0,345)\n",
    "ax.set_xlabel('Education Level' , fontfamily='serif' )\n",
    "ax.set_ylabel('Counts of Participants' , fontfamily='serif')\n",
    "ax.text(0, 150, '232 Junior', text_prop)\n",
    "ax.text(4, 20, '42 Junior', text_prop)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "6154a5e2",
   "metadata": {
    "papermill": {
     "duration": 0.039586,
     "end_time": "2021-11-24T12:07:59.403148",
     "exception": false,
     "start_time": "2021-11-24T12:07:59.363562",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "Most of us (Holding a Bachelor's degree ) and even thier are some other Egyptian hold a Master's or a Doctral degree and just start coding in the past very few years\n",
    "<p style = 'color:red'>\n",
    "that's very intersting to see high level educated persons just decide to **shift thier old carrer** and jump out from thier comfort zone. <br>\n",
    "</p>\n",
    "But do you think parctice coding and prctice thier newely gained skills in thier full time jop.!\n",
    "\n",
    "furtunally one of the questions in the survey ask the participants of thier emplyers use ML in thier work or not <br>\n",
    "Let's figuer it out"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f7729000",
   "metadata": {
    "papermill": {
     "duration": 0.040779,
     "end_time": "2021-11-24T12:07:59.546454",
     "exception": false,
     "start_time": "2021-11-24T12:07:59.505675",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "### (Q3-4) Did the Egyptian incorporate machine learning methods in their full time work?"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "fc90cdca",
   "metadata": {
    "papermill": {
     "duration": 0.039839,
     "end_time": "2021-11-24T12:07:59.628420",
     "exception": false,
     "start_time": "2021-11-24T12:07:59.588581",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "If we look in the survey question number 23<br>\n",
    "_Does your current employer incorporate machine learning methods into their business?_<br>\n",
    "we can get a hint if Egyptian emplyers know the importancy of the data science or still working in the 90th of the past century"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "69dd0583",
   "metadata": {
    "_kg_hide-input": true,
    "execution": {
     "iopub.execute_input": "2021-11-24T12:07:59.714895Z",
     "iopub.status.busy": "2021-11-24T12:07:59.713841Z",
     "iopub.status.idle": "2021-11-24T12:08:00.053828Z",
     "shell.execute_reply": "2021-11-24T12:08:00.054347Z",
     "shell.execute_reply.started": "2021-11-24T11:53:32.891425Z"
    },
    "papermill": {
     "duration": 0.386072,
     "end_time": "2021-11-24T12:08:00.054534",
     "exception": false,
     "start_time": "2021-11-24T12:07:59.668462",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Juniors</th>\n",
       "      <th>Seniors</th>\n",
       "      <th>Masters</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Q23</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>No</th>\n",
       "      <td>157</td>\n",
       "      <td>48</td>\n",
       "      <td>21</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Yes</th>\n",
       "      <td>45</td>\n",
       "      <td>23</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "     Juniors  Seniors  Masters\n",
       "Q23                           \n",
       "No       157       48       21\n",
       "Yes       45       23        3"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 1296x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "ML_experince_level = varibale_experince_level_df (Egypt_2021 , 'Q23' , new_df = None)\n",
    "display (ML_experince_level)\n",
    "fig , ax = variable_experince_level_stacked_bars (ML_experince_level , 'Did the Egyptian incorporate machine learning methods in their full time work?')\n",
    "ax.set_ylim(0,260)\n",
    "ax.text(0, 100, '157 Junior', ha='center', va='center', fontsize=14, fontweight='bold',bbox=box)\n",
    "ax.text(0, 180, '48 Senior', ha='center', va='center', fontsize=14, fontweight='bold',bbox=box)\n",
    "ax.text(0, 230, '21 Master', ha='center', va='center', fontsize=14, fontweight='bold',bbox=box)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "a5669cce",
   "metadata": {
    "papermill": {
     "duration": 0.042077,
     "end_time": "2021-11-24T12:08:00.140442",
     "exception": false,
     "start_time": "2021-11-24T12:08:00.098365",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "I think that's the most important chart in my Analysis<br>\n",
    "Did you notice how the egyptian employers waste thier employees skills and abalities<br>\n",
    "<p style = 'color :red'>\n",
    "A 21 participants with experience over 10 years in coding and still working in firms that did't recognize the importancy of the data science yet</p>\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "bfa538b2",
   "metadata": {
    "papermill": {
     "duration": 0.042238,
     "end_time": "2021-11-24T12:08:00.224762",
     "exception": false,
     "start_time": "2021-11-24T12:08:00.182524",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "## (Q4) What can we offer to our employees"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "5d26035f",
   "metadata": {
    "_kg_hide-input": true,
    "execution": {
     "iopub.execute_input": "2021-11-24T12:08:00.316879Z",
     "iopub.status.busy": "2021-11-24T12:08:00.316130Z",
     "iopub.status.idle": "2021-11-24T12:08:00.756206Z",
     "shell.execute_reply": "2021-11-24T12:08:00.755659Z",
     "shell.execute_reply.started": "2021-11-24T11:39:16.061320Z"
    },
    "papermill": {
     "duration": 0.489135,
     "end_time": "2021-11-24T12:08:00.756364",
     "exception": false,
     "start_time": "2021-11-24T12:08:00.267229",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Juniors</th>\n",
       "      <th>Seniors</th>\n",
       "      <th>Masters</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>What we can do</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Data Analyst</th>\n",
       "      <td>70</td>\n",
       "      <td>15.0</td>\n",
       "      <td>2.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Data Scientist</th>\n",
       "      <td>54</td>\n",
       "      <td>13.0</td>\n",
       "      <td>2.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Machine Learning Engineer</th>\n",
       "      <td>33</td>\n",
       "      <td>17.0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Software Engineer</th>\n",
       "      <td>16</td>\n",
       "      <td>10.0</td>\n",
       "      <td>3.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Business Analyst</th>\n",
       "      <td>10</td>\n",
       "      <td>3.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Research Scientist</th>\n",
       "      <td>9</td>\n",
       "      <td>9.0</td>\n",
       "      <td>8.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Data Engineer</th>\n",
       "      <td>6</td>\n",
       "      <td>4.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Statistician</th>\n",
       "      <td>3</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Product Manager</th>\n",
       "      <td>2</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Program/Project Manager</th>\n",
       "      <td>2</td>\n",
       "      <td>2.0</td>\n",
       "      <td>4.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                           Juniors  Seniors  Masters\n",
       "What we can do                                      \n",
       "Data Analyst                    70     15.0      2.0\n",
       "Data Scientist                  54     13.0      2.0\n",
       "Machine Learning Engineer       33     17.0      NaN\n",
       "Software Engineer               16     10.0      3.0\n",
       "Business Analyst                10      3.0      1.0\n",
       "Research Scientist               9      9.0      8.0\n",
       "Data Engineer                    6      4.0      1.0\n",
       "Statistician                     3      NaN      NaN\n",
       "Product Manager                  2      NaN      1.0\n",
       "Program/Project Manager          2      2.0      4.0"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1296x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "Role_experince_level = varibale_experince_level_df (Egypt_2021 , 'Q5' , new_df = None)\n",
    "Role_experince_level.drop(index=['Student' , 'Currently not employed' ,'Developer Relations/Advocacy' ,  'Other' ]  , inplace = True )\n",
    "Role_experince_level.sort_values(by = 'Juniors' , inplace = True , ascending =  False)\n",
    "Role_experince_level.index.names = ['What we can do']\n",
    "display (Role_experince_level)\n",
    "fig , ax = variable_experince_level_stacked_bars (Role_experince_level , 'What we can do for our employers')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "758eb927",
   "metadata": {
    "papermill": {
     "duration": 0.045314,
     "end_time": "2021-11-24T12:08:00.847159",
     "exception": false,
     "start_time": "2021-11-24T12:08:00.801845",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "We are data analysts , data scientists , machine learning engineer and more<br>\n",
    "Equipped with the required tools and skills and ready to unleash our power"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "0950a85f",
   "metadata": {
    "papermill": {
     "duration": 0.045974,
     "end_time": "2021-11-24T12:08:00.939081",
     "exception": false,
     "start_time": "2021-11-24T12:08:00.893107",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "# Take away"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "6edb1870",
   "metadata": {
    "papermill": {
     "duration": 0.045616,
     "end_time": "2021-11-24T12:08:01.031310",
     "exception": false,
     "start_time": "2021-11-24T12:08:00.985694",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "Egypt government initiations had a great impact to conquer this gap between the skills of thier youth and the The rapid technological development. <br>\n",
    "A huge step to the future was taken.<br>\n",
    "But still thier are more to do to change the culture and the mindset of the employers.<br>\n",
    "I deeply believe in the capabilities of the Egyptian youth who can shape the future.<br>\n",
    "<p style ='color:red'>\n",
    "Egyptian Corporate Top Management : We are here and ready , wake up and let's do it together.</p>"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "d57b8d69",
   "metadata": {
    "papermill": {
     "duration": 0.046202,
     "end_time": "2021-11-24T12:08:01.122704",
     "exception": false,
     "start_time": "2021-11-24T12:08:01.076502",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "<h1 style = 'background-color:#283270;\n",
    "             border-style: solid;\n",
    "             color:#f6f5f5;\n",
    "             border-color:black;\n",
    "             font-family:serif'><center><strong><br>Thank you for visiting my notebook"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "237f9cf5",
   "metadata": {
    "papermill": {
     "duration": 0.045508,
     "end_time": "2021-11-24T12:08:01.213148",
     "exception": false,
     "start_time": "2021-11-24T12:08:01.167640",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.7.10"
  },
  "papermill": {
   "default_parameters": {},
   "duration": 22.246221,
   "end_time": "2021-11-24T12:08:02.071802",
   "environment_variables": {},
   "exception": null,
   "input_path": "__notebook__.ipynb",
   "output_path": "__notebook__.ipynb",
   "parameters": {},
   "start_time": "2021-11-24T12:07:39.825581",
   "version": "2.3.3"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}