notebooks/Exploratory_analysis.ipynb

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   "cell_type": "markdown",
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   "source": [
    "# Exploratory analysis\n",
    "\n",
    "The data used for the project can be found on [Kaggle](https://www.kaggle.com/shivamb/real-or-fake-fake-jobposting-prediction), and as said in the [introduction](https://github.com/FelixLuciano/Fake-JobPosting-Prediction#readme), the data we chose is about job interviews that are fraudulent or not. It was necessary to make a lot of adaptations and optimization to the dataset due to the large number of lines in the database, and alter the datas that are not relevant for our analysis.\n",
    "\n",
    "**Pandas** allows us to transform our dataset into a dataframe, which transforms the data into a structure of 2 dimensions, rows and columns, below we can visualize the data in the form of a table. Also, **matplotlib** allows us to create graphs to visualize this data in the form of maps, histograms or charts."
   ]
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  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "# pandas - pandas is a fast, powerful, flexible and easy to use open source data analysis and manipulation tool.\n",
    "import pandas as pd\n",
    "\n",
    "# matplotlib - A comprehensive library for creating static, animated, and interactive visualizations\n",
    "import matplotlib.pyplot as plt"
   ]
  },
  {
   "source": [
    "## 1. Load Dataset"
   ],
   "cell_type": "markdown",
   "metadata": {}
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Dataset file path\n",
    "path = \"../src/dataset/fake_job_postings.csv\"\n",
    "\n",
    "# Index column name\n",
    "index_column = \"job_id\"\n",
    "\n",
    "# Load dataset into a DataFrame\n",
    "df = pd.read_csv(path, index_col=index_column)"
   ]
  },
  {
   "source": [
    "## 2. Exploration and Preparation of the Dataset\n"
   ],
   "cell_type": "markdown",
   "metadata": {}
  },
  {
   "cell_type": "code",
   "execution_count": 3,
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    {
     "output_type": "execute_result",
     "data": {
      "text/plain": [
       "['title',\n",
       " 'location',\n",
       " 'department',\n",
       " 'salary_range',\n",
       " 'company_profile',\n",
       " 'description',\n",
       " 'requirements',\n",
       " 'benefits',\n",
       " 'telecommuting',\n",
       " 'has_company_logo',\n",
       " 'has_questions',\n",
       " 'employment_type',\n",
       " 'required_experience',\n",
       " 'required_education',\n",
       " 'industry',\n",
       " 'function',\n",
       " 'fraudulent']"
      ]
     },
     "metadata": {},
     "execution_count": 3
    }
   ],
   "source": [
    "list(df.columns)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "output_type": "execute_result",
     "data": {
      "text/plain": [
       "(17880, 17)"
      ]
     },
     "metadata": {},
     "execution_count": 4
    }
   ],
   "source": [
    "df.shape"
   ]
  },
  {
   "source": [
    "Our dataset contains 17,880 rows and 18 columns. Below is a description of each column in this dataset with the original names and what they contain, which was taken from the author of the dataset:\n",
    "\n",
    "- **job_id** - Unique Job ID\n",
    "- **title** - The title of the job ad entry.\n",
    "- **location** - Geographical location of the job ad.\n",
    "- **department** - Corporate department (e.g. sales).\n",
    "- **salary_range** - Indicative salary range (e.g. \\$50,000-\\$60,000)\n",
    "- **company_profile** - A brief company description.\n",
    "- **description** - The details description of the job ad.\n",
    "- **requirements** - Enlisted requirements for the job opening.\n",
    "- **benefits** - Enlisted offered benefits by the employer.\n",
    "- **telecommuting** - True for telecommuting positions.\n",
    "- **has_company_logo** - True if company logo is present.\n",
    "- **has_questions** - True if screening questions are present.\n",
    "- **employment_type** - Full-type, Part-time, Contract, etc.\n",
    "- **required_experience** - Executive, Entry level, Intern, etc.\n",
    "- **required_education** - Doctorate, Master’s Degree, Bachelor, etc.\n",
    "- **industry** - Automotive, IT, Health care, Real estate, etc.\n",
    "- **function** - Consulting, Engineering, Research, Sales etc.\n",
    "- **fraudulent** - Classification attribute.\n",
    "\n",
    "Then we can define two types of variables\n",
    "\n",
    "- **Feature**: These are the variables that will be used as input by the predictive model;\n",
    "- **Target**: It is the variable we want to predict with the model.\n",
    "\n",
    "We assumed that two variables, `location` and `salary range`, were not relevant for the prediction. In the case of `location`, the information contained made the model biased when predicting fraud, since in the dataset a large part of the frauds were located in the same place. For `salary range`, the payments were described in different currencies, for example some in dollars others in reais, this difference is irrelevant and may cause difficulties in the predictions."
   ],
   "cell_type": "markdown",
   "metadata": {}
  },
  {
   "source": [
    "### 3. Transformations and cleaning\n",
    "\n",
    "Based on the descriptions of each column and the variables of interest, we can make transformations and cleanings that will help us to better visualize our data."
   ],
   "cell_type": "markdown",
   "metadata": {}
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   "cell_type": "code",
   "execution_count": 5,
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   "outputs": [],
   "source": [
    "categories = {   \"telecommuting\": [\"no\", \"yes\"],\n",
    "    \"has_company_logo\": [\"no\", \"yes\"],\n",
    "    \"has_questions\": [\"no\", \"yes\"],\n",
    "    \"fraudulent\": [\"no\", \"yes\"]\n",
    "}\n",
    "\n",
    "for column, column_categories in categories.items():\n",
    "    df[column] = df[column].astype(\"category\")\n",
    "    df[column].cat.categories = column_categories\n",
    "\n",
    "del df[\"location\"]\n",
    "del df[\"salary_range\"]\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 3.1. Fill empty values\n",
    "\n",
    "It is common in large data sets to have null or unfilled values. This can occur due to filling errors, the lack of information, or for any other reason. How to handle null values depends on the purpose of data analysis. In some cases it is possible to ignore them if this absence does not negatively affect the analysis, in others it is necessary to exclude every row that has a null value. It is even possible to fill null values with a specific value.\n",
    "\n",
    "We will analyze the null values of each column and create a strategy to deal with each null value.\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
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\n"
     },
     "metadata": {
      "needs_background": "light"
     }
    }
   ],
   "source": [
    "# Calculate the amount of missing values in each column\n",
    "missing_counts = df.isnull().sum()\n",
    "\n",
    "# Plot a horizontal bar graph with the obtained values\n",
    "plt.figure(figsize=(8, 12))\n",
    "missing_counts.plot(title=\"Missing values\", kind=\"barh\", color=\"#E44\", grid=True, fontsize=\"12\")\n",
    "plt.ylabel(\"% of ocurrence\")\n",
    "plt.rcParams[\"font.size\"] = \"12\"\n",
    "plt.savefig(\"plots/missing_values.png\", dpi=300)\n",
    "plt.show()"
   ]
  },
  {
   "source": [
    "Due to the characteristics of this project, all columns with null values can be filled with an specific value. In this case, the value will be \"Missing\", which will serve as just another category in the columns of interest."
   ],
   "cell_type": "markdown",
   "metadata": {}
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "for column_name in df.columns:\n",
    "    column = df[column_name]\n",
    "\n",
    "    if not str(column.dtype) == \"category\":\n",
    "        df[column_name] = df[column_name].fillna(\"Missing\")\n"
   ]
  },
  {
   "source": [
    "## 4. DataFrame"
   ],
   "cell_type": "markdown",
   "metadata": {}
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "output_type": "execute_result",
     "data": {
      "text/plain": [
       "                                                    title   department  \\\n",
       "job_id                                                                   \n",
       "1                                        Marketing Intern    Marketing   \n",
       "2               Customer Service - Cloud Video Production      Success   \n",
       "3                 Commissioning Machinery Assistant (CMA)      Missing   \n",
       "4                       Account Executive - Washington DC        Sales   \n",
       "5                                     Bill Review Manager      Missing   \n",
       "...                                                   ...          ...   \n",
       "17876                    Account Director - Distribution         Sales   \n",
       "17877                                  Payroll Accountant   Accounting   \n",
       "17878   Project Cost Control Staff Engineer - Cost Con...      Missing   \n",
       "17879                                    Graphic Designer      Missing   \n",
       "17880                          Web Application Developers  Engineering   \n",
       "\n",
       "                                          company_profile  \\\n",
       "job_id                                                      \n",
       "1       We're Food52, and we've created a groundbreaki...   \n",
       "2       90 Seconds, the worlds Cloud Video Production ...   \n",
       "3       Valor Services provides Workforce Solutions th...   \n",
       "4       Our passion for improving quality of life thro...   \n",
       "5       SpotSource Solutions LLC is a Global Human Cap...   \n",
       "...                                                   ...   \n",
       "17876   Vend is looking for some awesome new talent to...   \n",
       "17877   WebLinc is the e-commerce platform and service...   \n",
       "17878   We Provide Full Time Permanent Positions for m...   \n",
       "17879                                             Missing   \n",
       "17880   Vend is looking for some awesome new talent to...   \n",
       "\n",
       "                                              description  \\\n",
       "job_id                                                      \n",
       "1       Food52, a fast-growing, James Beard Award-winn...   \n",
       "2       Organised - Focused - Vibrant - Awesome!Do you...   \n",
       "3       Our client, located in Houston, is actively se...   \n",
       "4       THE COMPANY: ESRI – Environmental Systems Rese...   \n",
       "5       JOB TITLE: Itemization Review ManagerLOCATION:...   \n",
       "...                                                   ...   \n",
       "17876   Just in case this is the first time you’ve vis...   \n",
       "17877   The Payroll Accountant will focus primarily on...   \n",
       "17878   Experienced Project Cost Control Staff Enginee...   \n",
       "17879   Nemsia Studios is looking for an experienced v...   \n",
       "17880   Who are we?Vend is an award winning web based ...   \n",
       "\n",
       "                                             requirements  \\\n",
       "job_id                                                      \n",
       "1       Experience with content management systems a m...   \n",
       "2       What we expect from you:Your key responsibilit...   \n",
       "3       Implement pre-commissioning and commissioning ...   \n",
       "4       EDUCATION: Bachelor’s or Master’s in GIS, busi...   \n",
       "5       QUALIFICATIONS:RN license in the State of Texa...   \n",
       "...                                                   ...   \n",
       "17876   To ace this role you:Will eat comprehensive St...   \n",
       "17877   - B.A. or B.S. in Accounting- Desire to have f...   \n",
       "17878   At least 12 years professional experience.Abil...   \n",
       "17879   1. Must be fluent in the latest versions of Co...   \n",
       "17880   We want to hear from you if:You have an in-dep...   \n",
       "\n",
       "                                                 benefits telecommuting  \\\n",
       "job_id                                                                    \n",
       "1                                                 Missing            no   \n",
       "2       What you will get from usThrough being part of...            no   \n",
       "3                                                 Missing            no   \n",
       "4       Our culture is anything but corporate—we have ...            no   \n",
       "5                                   Full Benefits Offered            no   \n",
       "...                                                   ...           ...   \n",
       "17876   What can you expect from us?We have an open cu...            no   \n",
       "17877   Health &amp; WellnessMedical planPrescription ...            no   \n",
       "17878                                             Missing            no   \n",
       "17879   Competitive salary (compensation will be based...            no   \n",
       "17880                                             Missing            no   \n",
       "\n",
       "       has_company_logo has_questions employment_type required_experience  \\\n",
       "job_id                                                                      \n",
       "1                   yes            no           Other          Internship   \n",
       "2                   yes            no       Full-time      Not Applicable   \n",
       "3                   yes            no         Missing             Missing   \n",
       "4                   yes            no       Full-time    Mid-Senior level   \n",
       "5                   yes           yes       Full-time    Mid-Senior level   \n",
       "...                 ...           ...             ...                 ...   \n",
       "17876               yes           yes       Full-time    Mid-Senior level   \n",
       "17877               yes           yes       Full-time    Mid-Senior level   \n",
       "17878                no            no       Full-time             Missing   \n",
       "17879                no           yes        Contract      Not Applicable   \n",
       "17880               yes           yes       Full-time    Mid-Senior level   \n",
       "\n",
       "       required_education                   industry              function  \\\n",
       "job_id                                                                       \n",
       "1                 Missing                    Missing             Marketing   \n",
       "2                 Missing  Marketing and Advertising      Customer Service   \n",
       "3                 Missing                    Missing               Missing   \n",
       "4       Bachelor's Degree          Computer Software                 Sales   \n",
       "5       Bachelor's Degree     Hospital & Health Care  Health Care Provider   \n",
       "...                   ...                        ...                   ...   \n",
       "17876             Missing          Computer Software                 Sales   \n",
       "17877   Bachelor's Degree                   Internet   Accounting/Auditing   \n",
       "17878             Missing                    Missing               Missing   \n",
       "17879        Professional             Graphic Design                Design   \n",
       "17880             Missing          Computer Software           Engineering   \n",
       "\n",
       "       fraudulent  \n",
       "job_id             \n",
       "1              no  \n",
       "2              no  \n",
       "3              no  \n",
       "4              no  \n",
       "5              no  \n",
       "...           ...  \n",
       "17876          no  \n",
       "17877          no  \n",
       "17878          no  \n",
       "17879          no  \n",
       "17880          no  \n",
       "\n",
       "[17880 rows x 15 columns]"
      ],
      "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>title</th>\n      <th>department</th>\n      <th>company_profile</th>\n      <th>description</th>\n      <th>requirements</th>\n      <th>benefits</th>\n      <th>telecommuting</th>\n      <th>has_company_logo</th>\n      <th>has_questions</th>\n      <th>employment_type</th>\n      <th>required_experience</th>\n      <th>required_education</th>\n      <th>industry</th>\n      <th>function</th>\n      <th>fraudulent</th>\n    </tr>\n    <tr>\n      <th>job_id</th>\n      <th></th>\n      <th></th>\n      <th></th>\n      <th></th>\n      <th></th>\n      <th></th>\n      <th></th>\n      <th></th>\n      <th></th>\n      <th></th>\n      <th></th>\n      <th></th>\n      <th></th>\n      <th></th>\n      <th></th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th>1</th>\n      <td>Marketing Intern</td>\n      <td>Marketing</td>\n      <td>We're Food52, and we've created a groundbreaki...</td>\n      <td>Food52, a fast-growing, James Beard Award-winn...</td>\n      <td>Experience with content management systems a m...</td>\n      <td>Missing</td>\n      <td>no</td>\n      <td>yes</td>\n      <td>no</td>\n      <td>Other</td>\n      <td>Internship</td>\n      <td>Missing</td>\n      <td>Missing</td>\n      <td>Marketing</td>\n      <td>no</td>\n    </tr>\n    <tr>\n      <th>2</th>\n      <td>Customer Service - Cloud Video Production</td>\n      <td>Success</td>\n      <td>90 Seconds, the worlds Cloud Video Production ...</td>\n      <td>Organised - Focused - Vibrant - Awesome!Do you...</td>\n      <td>What we expect from you:Your key responsibilit...</td>\n      <td>What you will get from usThrough being part of...</td>\n      <td>no</td>\n      <td>yes</td>\n      <td>no</td>\n      <td>Full-time</td>\n      <td>Not Applicable</td>\n      <td>Missing</td>\n      <td>Marketing and Advertising</td>\n      <td>Customer Service</td>\n      <td>no</td>\n    </tr>\n    <tr>\n      <th>3</th>\n      <td>Commissioning Machinery Assistant (CMA)</td>\n      <td>Missing</td>\n      <td>Valor Services provides Workforce Solutions th...</td>\n      <td>Our client, located in Houston, is actively se...</td>\n      <td>Implement pre-commissioning and commissioning ...</td>\n      <td>Missing</td>\n      <td>no</td>\n      <td>yes</td>\n      <td>no</td>\n      <td>Missing</td>\n      <td>Missing</td>\n      <td>Missing</td>\n      <td>Missing</td>\n      <td>Missing</td>\n      <td>no</td>\n    </tr>\n    <tr>\n      <th>4</th>\n      <td>Account Executive - Washington DC</td>\n      <td>Sales</td>\n      <td>Our passion for improving quality of life thro...</td>\n      <td>THE COMPANY: ESRI – Environmental Systems Rese...</td>\n      <td>EDUCATION: Bachelor’s or Master’s in GIS, busi...</td>\n      <td>Our culture is anything but corporate—we have ...</td>\n      <td>no</td>\n      <td>yes</td>\n      <td>no</td>\n      <td>Full-time</td>\n      <td>Mid-Senior level</td>\n      <td>Bachelor's Degree</td>\n      <td>Computer Software</td>\n      <td>Sales</td>\n      <td>no</td>\n    </tr>\n    <tr>\n      <th>5</th>\n      <td>Bill Review Manager</td>\n      <td>Missing</td>\n      <td>SpotSource Solutions LLC is a Global Human Cap...</td>\n      <td>JOB TITLE: Itemization Review ManagerLOCATION:...</td>\n      <td>QUALIFICATIONS:RN license in the State of Texa...</td>\n      <td>Full Benefits Offered</td>\n      <td>no</td>\n      <td>yes</td>\n      <td>yes</td>\n      <td>Full-time</td>\n      <td>Mid-Senior level</td>\n      <td>Bachelor's Degree</td>\n      <td>Hospital &amp; Health Care</td>\n      <td>Health Care Provider</td>\n      <td>no</td>\n    </tr>\n    <tr>\n      <th>...</th>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n    </tr>\n    <tr>\n      <th>17876</th>\n      <td>Account Director - Distribution</td>\n      <td>Sales</td>\n      <td>Vend is looking for some awesome new talent to...</td>\n      <td>Just in case this is the first time you’ve vis...</td>\n      <td>To ace this role you:Will eat comprehensive St...</td>\n      <td>What can you expect from us?We have an open cu...</td>\n      <td>no</td>\n      <td>yes</td>\n      <td>yes</td>\n      <td>Full-time</td>\n      <td>Mid-Senior level</td>\n      <td>Missing</td>\n      <td>Computer Software</td>\n      <td>Sales</td>\n      <td>no</td>\n    </tr>\n    <tr>\n      <th>17877</th>\n      <td>Payroll Accountant</td>\n      <td>Accounting</td>\n      <td>WebLinc is the e-commerce platform and service...</td>\n      <td>The Payroll Accountant will focus primarily on...</td>\n      <td>- B.A. or B.S. in Accounting- Desire to have f...</td>\n      <td>Health &amp;amp; WellnessMedical planPrescription ...</td>\n      <td>no</td>\n      <td>yes</td>\n      <td>yes</td>\n      <td>Full-time</td>\n      <td>Mid-Senior level</td>\n      <td>Bachelor's Degree</td>\n      <td>Internet</td>\n      <td>Accounting/Auditing</td>\n      <td>no</td>\n    </tr>\n    <tr>\n      <th>17878</th>\n      <td>Project Cost Control Staff Engineer - Cost Con...</td>\n      <td>Missing</td>\n      <td>We Provide Full Time Permanent Positions for m...</td>\n      <td>Experienced Project Cost Control Staff Enginee...</td>\n      <td>At least 12 years professional experience.Abil...</td>\n      <td>Missing</td>\n      <td>no</td>\n      <td>no</td>\n      <td>no</td>\n      <td>Full-time</td>\n      <td>Missing</td>\n      <td>Missing</td>\n      <td>Missing</td>\n      <td>Missing</td>\n      <td>no</td>\n    </tr>\n    <tr>\n      <th>17879</th>\n      <td>Graphic Designer</td>\n      <td>Missing</td>\n      <td>Missing</td>\n      <td>Nemsia Studios is looking for an experienced v...</td>\n      <td>1. Must be fluent in the latest versions of Co...</td>\n      <td>Competitive salary (compensation will be based...</td>\n      <td>no</td>\n      <td>no</td>\n      <td>yes</td>\n      <td>Contract</td>\n      <td>Not Applicable</td>\n      <td>Professional</td>\n      <td>Graphic Design</td>\n      <td>Design</td>\n      <td>no</td>\n    </tr>\n    <tr>\n      <th>17880</th>\n      <td>Web Application Developers</td>\n      <td>Engineering</td>\n      <td>Vend is looking for some awesome new talent to...</td>\n      <td>Who are we?Vend is an award winning web based ...</td>\n      <td>We want to hear from you if:You have an in-dep...</td>\n      <td>Missing</td>\n      <td>no</td>\n      <td>yes</td>\n      <td>yes</td>\n      <td>Full-time</td>\n      <td>Mid-Senior level</td>\n      <td>Missing</td>\n      <td>Computer Software</td>\n      <td>Engineering</td>\n      <td>no</td>\n    </tr>\n  </tbody>\n</table>\n<p>17880 rows × 15 columns</p>\n</div>"
     },
     "metadata": {},
     "execution_count": 8
    }
   ],
   "source": [
    "df"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 5. Data analysis\n",
    "\n",
    "As you can see from the data above, we can start the exploratory analysis\n"
   ]
  },
  {
   "source": [
    "### 5.1. Target value counts"
   ],
   "cell_type": "markdown",
   "metadata": {}
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "output_type": "display_data",
     "data": {
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     },
     "metadata": {
      "needs_background": "light"
     }
    }
   ],
   "source": [
    "# Calculate the value counts of the target variable\n",
    "fraudulent_counts = df[\"fraudulent\"].value_counts(normalize=True)\n",
    "\n",
    "# Plot a bar chart with the obtained values\n",
    "plt.figure(figsize=(8, 6))\n",
    "fraudulent_counts.plot(title=\"Target counts\", kind=\"bar\", color=\"#E44\", grid=True, fontsize=\"12\")\n",
    "plt.ylabel(\"% of ocurrence\")\n",
    "plt.rcParams[\"font.size\"] = \"12\"\n",
    "plt.savefig(\"plots/target_counts.png\", dpi=300)\n",
    "plt.show()\n"
   ]
  },
  {
   "source": [
    "With this chart it's possible to perceive that there is a big difference in the amount of the occurrences in te target variable. And later, this could affect the results of the perdictive model.\n"
   ],
   "cell_type": "markdown",
   "metadata": {}
  },
  {
   "source": [
    "### 5.2. Most fraudulent of `telecommuting`"
   ],
   "cell_type": "markdown",
   "metadata": {}
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "output_type": "display_data",
     "data": {
      "text/plain": "<Figure size 576x432 with 1 Axes>",
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     },
     "metadata": {
      "needs_background": "light"
     }
    }
   ],
   "source": [
    "# Calculate the \"telecommuting\" columns cross table regarding the target variable in a normalized form\n",
    "telecommuting_cross = pd.crosstab(df[\"telecommuting\"], df[\"fraudulent\"], normalize=True)\n",
    "\n",
    "# Filters the positive occurences\n",
    "telecommuting_cross_filtered = telecommuting_cross[\"yes\"]\n",
    "\n",
    "# Plot a horizontal bar chart with the obtained values\n",
    "plt.figure(figsize=(8, 6))\n",
    "telecommuting_cross_filtered.plot(title=\"Most fraudulent of telecommuting\", kind=\"bar\", color=\"#E44\", fontsize=\"12\", grid=True)\n",
    "plt.xlabel(\"% of ocurrence\")\n",
    "plt.rcParams[\"font.size\"] = \"12\"\n",
    "plt.savefig(\"plots/most_fraudulent_telecommuting.png\", dpi=300)\n",
    "plt.show()\n"
   ]
  },
  {
   "source": [
    "### 5.3. Most fraudulent of `has_company_logo`"
   ],
   "cell_type": "markdown",
   "metadata": {}
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "output_type": "display_data",
     "data": {
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\n"
     },
     "metadata": {
      "needs_background": "light"
     }
    }
   ],
   "source": [
    "# Calculate the \"has_company_logo\" columns cross table regarding the target variable in a normalized form\n",
    "has_company_logo_cross = pd.crosstab(df[\"has_company_logo\"], df[\"fraudulent\"], normalize=True)\n",
    "\n",
    "# Filters the positive occurences\n",
    "has_company_logo_cross_filtered = has_company_logo_cross[\"yes\"]\n",
    "\n",
    "# Plot a horizontal bar chart with the obtained values\n",
    "plt.figure(figsize=(8, 6))\n",
    "has_company_logo_cross_filtered.plot(title=\"Most fraudulent of has_company_logo\", kind=\"bar\", color=\"#E44\", fontsize=\"12\", grid=True)\n",
    "plt.xlabel(\"% of ocurrence\")\n",
    "plt.rcParams[\"font.size\"] = \"12\"\n",
    "plt.savefig(\"plots/most_fraudulent_company_logos.png\", dpi=300)\n",
    "plt.show()\n"
   ]
  },
  {
   "source": [
    "### 5.4. Most fraudulent of `has_questions`"
   ],
   "cell_type": "markdown",
   "metadata": {}
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "output_type": "display_data",
     "data": {
      "text/plain": "<Figure size 576x432 with 1 Axes>",
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\n"
     },
     "metadata": {
      "needs_background": "light"
     }
    }
   ],
   "source": [
    "# Calculate the \"has_questions\" columns cross table regarding the target variable in a normalized form\n",
    "has_questions_cross = pd.crosstab(df[\"has_questions\"], df[\"fraudulent\"], normalize=True)\n",
    "\n",
    "# Filters the positive occurences\n",
    "has_questions_cross_filtered = has_questions_cross[\"yes\"]\n",
    "\n",
    "# Plot a horizontal bar chart with the obtained values\n",
    "plt.figure(figsize=(8, 6))\n",
    "has_questions_cross_filtered.plot(title=\"Most fraudulent of has_questions\", kind=\"bar\", color=\"#E44\", fontsize=\"12\", grid=True)\n",
    "plt.xlabel(\"% of ocurrence\")\n",
    "plt.rcParams[\"font.size\"] = \"12\"\n",
    "plt.savefig(\"plots/most_fraudulent_company_logos.png\", dpi=300)\n",
    "plt.show()\n"
   ]
  },
  {
   "source": [
    "### 5.5. Most fraudulent of `departments`"
   ],
   "cell_type": "markdown",
   "metadata": {}
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "output_type": "display_data",
     "data": {
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     },
     "metadata": {
      "needs_background": "light"
     }
    }
   ],
   "source": [
    "# Calculate the \"department\" columns cross table regarding the target variable in a normalized form\n",
    "department_cross = pd.crosstab(df[\"department\"], df[\"fraudulent\"], normalize=True)\n",
    "\n",
    "# Filters the 20 largest positive occurences in decreasing order\n",
    "department_cross_filtered = department_cross[\"yes\"].sort_values(ascending=False).iloc[0:20]\n",
    "\n",
    "# Plot a horizontal bar chart with the obtained values\n",
    "plt.figure(figsize=(8, 16))\n",
    "department_cross_filtered.plot(title=\"Most fraudulent of departments\", kind=\"barh\", color=\"#E44\", fontsize=\"12\", grid=True)\n",
    "plt.xlabel(\"% of ocurrence\")\n",
    "plt.gca().invert_yaxis()\n",
    "plt.rcParams[\"font.size\"] = \"12\"\n",
    "plt.savefig(\"plots/most_fraudulent_job_departments.png\", dpi=300)\n",
    "plt.show()\n"
   ]
  },
  {
   "source": [
    "### 5.6. Most fraudulent of `employment_type`"
   ],
   "cell_type": "markdown",
   "metadata": {}
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "output_type": "display_data",
     "data": {
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     },
     "metadata": {
      "needs_background": "light"
     }
    }
   ],
   "source": [
    "# Calculate the \"employment_type\" column cross table regarding the target variable in a normalized form\n",
    "employment_type_cross = pd.crosstab(df[\"employment_type\"], df[\"fraudulent\"], normalize=True)\n",
    "\n",
    "# Filters the largest positive occurences in decreasing order\n",
    "employment_type_cross_filtered = employment_type_cross[\"yes\"].sort_values()\n",
    "\n",
    "# Plot a horizontal bar chart with the obtained values\n",
    "plt.figure(figsize=(8, 6))\n",
    "employment_type_cross_filtered.plot(title=\"Most fraudulent of employment_type\", kind=\"barh\", color=\"#E44\", fontsize=\"12\", grid=True)\n",
    "plt.xlabel(\"% of ocurrence\")\n",
    "plt.rcParams[\"font.size\"] = \"12\"\n",
    "plt.savefig(\"plots/most_fraudulent_employment_type.png\", dpi=300)\n",
    "plt.show()\n"
   ]
  },
  {
   "source": [
    "### 5.7. Most fraudulent of `required_experience`"
   ],
   "cell_type": "markdown",
   "metadata": {}
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "output_type": "display_data",
     "data": {
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     },
     "metadata": {
      "needs_background": "light"
     }
    }
   ],
   "source": [
    "# Calculate the \"required_experience\" column cross table regarding the target variable in a normalized form\n",
    "required_experience_cross = pd.crosstab(df[\"required_experience\"], df[\"fraudulent\"], normalize=True)\n",
    "\n",
    "# Filters the largest positive occurences in decreasing order\n",
    "required_experience_cross_filtered = required_experience_cross[\"yes\"].sort_values()\n",
    "\n",
    "# Plot a horizontal bar chart with the obtained values\n",
    "plt.figure(figsize=(8, 6))\n",
    "required_experience_cross_filtered.plot(title=\"Most fraudulent of required_experience\", kind=\"barh\", color=\"#E44\", fontsize=\"12\", grid=True)\n",
    "plt.xlabel(\"% of ocurrence\")\n",
    "plt.rcParams[\"font.size\"] = \"12\"\n",
    "plt.savefig(\"plots/most_fraudulent_required_experience.png\", dpi=300)\n",
    "plt.show()\n"
   ]
  },
  {
   "source": [
    "### 5.8. Most fraudulent of `required_education`"
   ],
   "cell_type": "markdown",
   "metadata": {}
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "output_type": "display_data",
     "data": {
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bcZJ26uB4Rkh6oAPGbZI0sd7jdjRJ20kaU4dxuuT5m5mZdRcujhcDlYrZ8uIzIjaMiOYOOHYvSWdImiipRdJYSWfW+zjdXUTcHxHDGh1HUWf8kWRmZtbdeFmFHQ18GtgCeA0YAny2oRHVgSQBiogPGh2LmZmZdR2eOe4iirOAkpaVdJmkGZKek/STCl/FbyrpaUlvSrpO0jKtDL05cFNETIpkXERcXjjuYEk3SnpD0jRJ55TFdXqOY6ykXQvtAyXdImm6pBclHVro6y3pLEmT8uMsSb2rzMM2kh7N5/WopG0Kfc2STpb0D+AtYK0K+w+UdEM+n7GSjiz0LSvp0nw+z0r6cTGvkkLSOoXXl0o6KT//cDmEpJ9Jur7suL+TdHZ+fnB+32ZLelnSt9o437biHSlplKTL81jPSPp07rsCWBO4NX8j8JNq8mtmZrakc3HcNR0PDCUVfzsDX6+wzXBgF+DjwMbAiFbGegj4oaTvSPpknnEFQFJP4DZgfD7eIODawr5bAmOA/sCvgYsL+18DTAQGAl8BTpG0Y+77ObAVsCmwCWnW+tj2TlrSysDtwNnAKsBvgdslrVLY7ADgMKBfjru4fw/gVuCpfC47Aj+Q9IW8yfHA2vnxBeCg9mJqxTXAbpKWz8ftSXo/rs79rwN7AMsDBwNnStqswvm2Fy/AF0nvyYrALcA5ABFxAPAKsGdE9I2IXy/kuZiZmS1RvKxi8XGzpPcLr3sBT7Sy7XDg2xExA5iRZyRHlm1zdkRMApB0K6kQreRUYAawP3AmME3S0RFxGaloHQj8OCJKsRUvwhsfERfmY1wG/AFYVdLSwLbAHhHxDvCkpItIhes9+Vjfi4jX874nAOcDx7USY8nuwAsRcUV+fU2eSd0TuDS3XRoRz7Sy/+bAgIg4Mb9+WdKFwFeBO0l5/U5ETAem57z+op2YFhAR4yU9AewNXA58DngrIh7K/bcXNr9P0l3Adiz4frcXL8ADEXEHfDhb/INq45R0GOkPCQb0788Tw4dXfY7WtrdWWsn5rEHP5uZ2t2lpaaG5iu2sOs5nfTmf9dXofLo4XnzsHRF3l15IGgEc0sq2A4EJhdcTKmwzufD8rbzPAiJiHnAucK6kZYFvAJdIegQYTCqA36+0b/EYEfFWnjTuS5rVnR4RswvbjietbS7FP76sr2J8Zcr3K+07qPC6Ui5KhgADJc0stPUE7i+MX9y//Fi1uBrYj1Qcf42PZo3Jy0+OB9YlfXuzHPDvhYgXFnyfl5G0VBvv2Yci4gLgAoBhQ4fGZqNGtX9WVpUnhg/H+axeNbdya25upqmpqeODWUI4n/XlfNZXo/PpZRVd02vAGoXXg+sxaES8HRHnkmaSNyAVimtKqvWPqEnAypL6FdrWBF4t9A8p65tU5bhDytqK4wJEG/tPAMZGxIqFR7+I2C33v8b8uVyzbP+3SIVsyWptHOtPQJOkNYAvkYvjvLb6BuB0YNWIWBG4A1CFMdqLtz1t5cLMzMwqcHHcNY0Cjpa0kqRBwBELO5CkH+SLyZaVtJSkg0jrdf8FPEIqGE+T1EfSMpI+096YETEBeBA4Ne+zMfBN4Kq8yTXAsZIGSOpPWrpwZRXh3gGsK+lrOdZ9SUX8bVWe7iPALEk/zefbU9JGkjbP/cW8rgF8r2z/J4Gv5f12AbZv7UAR8QbQDPyRVOA+l7t6Ab2BN4D38yzy5xcy3vZMocJFiWZmZtY6F8dd04mki93GAncD1wNzF3Kst4EzSF/PTwW+C3w5Il7OSy72BNYhXdw1Edi3ynH3I13ENwm4CTg+IkrfnZ4EPAY8TVpO8ERua1NETCNdyHYUMA34CWld89RqAiqcz6ak3E0FLgJWyJucQFpKMRa4C7iibIjv5/1nktZN39zOIa8GdqKwpCIvNTmSVIjPIC25uGUh423PqaQ/QmZK+lGV+5iZmS3RFOFvXrs6Sd8GvhoRrc5kWu2UfpHwyohYo51Nu7xhw4bFmDGL/AN/ljV6vVx35JzWl/NZX85nfXVGPiU9HhGfrtTnmeMuSNLqkj4jqYekYaSZ1JsaHZeZmZlZV+e7VXRNvUi3Pvs46Sv+a0m3UTMzMzOzReDiuAuKiPHARo2Oo7uLiGbmvyuImZmZdXNeVmFmZmZmlrk4NjMzMzPLXBybmZmZmWUujs3MzMzMMhfHZmZmZmaZi2MzMzMzs8zFsZmZmZlZ5uLYzMzMzCzzj4CYGcydy4ydd250FN3GvOHDmXHyye1ut9Lo0Z0QjZmZ1cIzx7ZYkXSppJM6e18zMzMzcHFsC0nSOElvS2qRNEPS7ZIGNzquRSEpFmKfkZLekzQ7P/4r6RxJq3dEjGZmZtaxXBzbotgzIvoCqwNTgN83OJ6FImlRlxddFxH9gJWBLwGrAY93RIFch1jNzMysDS6ObZFFxDvA9cAGpTZJu0v6l6RZkiZIGlncR9K2kh6UNDP3jyh0r5RnomdLeljS2oX91pM0WtJ0SWMkDW8tLkmHSnoxb3uLpIGFvpD0XUkvAC9U2HeEpJdzDGMl7V9FHt6LiGeAfYE3gKMK4+0h6cl8vg9K2rjQt1nO1WxJf5J0XWl5iKQmSRMl/VTSZOCPknpI+pmklyRNkzRK0sqF8bYq5PYpSU3txW5mZmaJi2NbZJKWIxWEDxWa5wAHAisCuwPflrR33n5N4C+kmeYBwKbAk4V99wNOAFYCXgROzvv1AUYDVwMfy9v9QdKGFWL6HHAqMJw0sz0euLZss72BLclFfUSocJyzgV3zjPA2ZfG1KSLmAX8GtsvjbQZcAnwLWAU4H7hFUm9JvYCbgEtJM8/XkGafi1bLfUOAw4Ajc+zbAwOBGcC5+ViDgNuBk/I+PwJukDSg2vjNzMyWZP6K1hbFzZLeB/oCrwNfKHVERHNhu6clXUMq5m4G9gfujohrcv+0/Ci5MSIeAZB0FfDb3L4HMC4i/phfPyHpBuArwDNlse0PXBIRT+RxjgZmSBoaEePyNqdGxPRWzu0DYCNJr0TEa8BrbWZiQZNIxSnAocD5EfFwfn2ZpGOArYAg/Ts8OyICuFHSIxViOT4i5uZz+RZwRERMzK9HAq9IOgD4OnBHRNyR9x0t6TFgN+Cy4qCSDiMV2wzo358nhrc6CW81emullarKZ8/m5g6PpbtoaWmh2fmqG+ezvpzP+mp0Pl0c26LYOyLultQT2Au4T9IGETFZ0pbAacBGQC+gN/CnvN9g4KU2xp1ceP4WqfiGNHO6paSZhf6lgCsqjDEQeKL0IiJaJE0DBgHjcvOESgePiDmS9iXNul4s6R/AURHxfBsxlxsElArvIcBBkr5X6O+VYwzg1VwYl5TH9UZeulIyBLhJ0geFtnnAqrlvH0l7FvqWBu4tDzAiLgAuABg2dGhsNmpUtedm7Xhi+HCqyadv5Va95uZmmpqaGh1Gt+F81pfzWV+NzqeXVdgii4h5EXEjqUDbNjdfDdwCDI6IFYDzAOW+CcDaCwzUvgnAfRGxYuHRNyK+XWHbSaRCEfhwqcQqwKvF0Ns4pzsjYmfSkozngQurDVJSD2BP4P5C3CeXxb1cnjl/DRgkSYUhyu/6UR7nBNKSj+J4y0TEq7nvirK+PhFxWrXxm5mZLclcHNsiU7IXaY3wc7m5HzA9It6RtAXwtcIuVwE7SRouaSlJq0jatIpD3QasK+kASUvnx+aS1q+w7dXAwZI2ldQbOAV4uLCkoq3zWVXSF3NBPRdoIRX+7e23dI7lGtI64dJykAuBwyVtmXPVR+mCxX7AP/PYR+Rc7AVs0c6hzgNOljQkH3dA3g/gSmBPSV+Q1FPSMvmivjXai9/MzMxcHNuiuVVSCzCLdNHcQfluDQDfAU6UNBv4BfDhd8wR8QppDexRpKUHTwKbtHewiJgNfB74KmlmeDLwK9KSjfJt7wGOA24gzc6unferRo8c26Qc3/b5fFqzb87DTNJs+TTgUxExKcfyGGnd8Tmki+deBEbkvneB/wW+mff/OumPgLltHO93+Th35fw+RLqwkIiYQFricgzpjhkTgB/jf+tmZmZV8ZpjWygRMbSd/utJt3drrf9+ckFX1j6i7HUzsEbh9RjS3S8qjVm+73mkWdZK26pSe+57jVQQtysiRgIjq9jur8BfW+l7jHTHDgAkPQzcmvuaKZx/bvuANCv9WyrIF/5VFb+ZmZnNz8WxWYNJ2h4YA0wl3WVjY1oppDtM796+OKyOejY3O59mZl2Ui2OzxhtGWnbSl3QXj6/k2WszMzPrZC6OzRqseEs1MzMzayxfpGNmZmZmlrk4NjMzMzPLXBybmZmZmWUujs3MzMzMMhfHZmZmZmaZi2MzMzMzs8zFsZmZmZlZ5uLYzMzMzCzzj4CYGcydy4ydd250FB3OP+lsZmbt8cyxmZmZmVnm4thsMSDpL5IOKrw+SdJUSZMlrSmpRVLPhRh3qKSQ5G+JzMzMquD/w7RuSVIAn4iIFwttI4F1IuLrDQusFRGxa+m5pMHAUcCQiHg9N/dtSGBmZmZLGM8cmy1+hgDTCoWxmZmZdRIXx7ZEktQkaaKkoyS9Luk1SQcX+neT9Kyk2ZJelfSjsv2Oycsexknav7Bfb0mnS3pF0hRJ50lattC/l6QnJc2S9JKkXXJ7s6RDJO0EjAYG5qUUl5YvjZC0gqSLc8yv5iUYPXNfz3z8qZJeBnbvlISamZl1E15WYUuy1YAVgEHAzsD1km6OiBnAxcDwiLhf0krAx8v265/32wq4Q9JjETEG+BWwFrAp8B5wNfAL4GhJWwCXA18B7gFWB/oVA4qIuyXtClwZEWtAWjdcFvdlwBRgHaAPcBswATgfOBTYA/gfYA5wQ2snL+kw4DCAAf3788Tw4e1nrIvr2dzcKcdpaWmhuZOOtaRwTuvL+awv57O+Gp1PF8e2JHsPODEi3icVuC3AMOCh3LeBpKdysTyjbN/jImIucJ+k24Hhkk4iFacbR8R0AEmnkArko4FvApdEROl+Yq/WGrCkVYFdgRUj4m1gjqQzSUXu+cBw4KyImJC3PxVoqjRWRFwAXAAwbOjQ2GzUqFrD6XI661Zuzc3NNDU1dcqxlhTOaX05n/XlfNZXo/PpZRXWXc0Dli5rW5pU9JZMy4VxyVt8dOHbl4HdgPGS7pO0dWG7GRExp/B6PDAQGAAsBzwuaaakmcBfczvAYOClhT8lIK1HXhp4rXCM84GP5f6BpFnkYmxmZmZWJc8cW3f1CjAUeK7Q9nHgv9XsHBGPAntJWho4AhhFKm4BVpLUp1Agrwn8B5gKvA1sGBGVZoUnAGvXeB6VxpgL9C8r7EteK8RZis3MzMyq5Jlj666uA46VtIakHvlCtz2B69vbUVIvSftLWiEi3gNmkWaii07I221HWuP7p4j4ALgQOFPSx/JYgyR9Ie9zMXCwpB1zTIMkrVfLSUXEa8BdwBmSls/jrC1p+7zJKODIfN4rAT+rZXwzM7MlnYtj665OBB4EHiCtF/41sH9E/KfK/Q8AxkmaBRwOFO+NPDmPOQm4Cjg8Ip7PfT8FXgQeyvveTVrHTEQ8AhwMnAm8CdxHWiZRqwOBXsCzOY7rSRf3QSrO7wSeAp4AblyI8c3MzJZYXlZh3VK+WO3H+VGpvxlYo6xtaOHlLu2MfzJwcoX2d4Bj8qPSfjcBN1Vob2ottogYB6jw+k3g2/lRPs77wP/lR8m5bZ0LAL17d9rFamZmZoszzxybmZmZmWUujs3MzMzMMi+rMKtBpeUYZmZm1n145tjMzMzMLHNxbGZmZmaWuTg2MzMzM8tcHJuZmZmZZS6OzczMzMwyF8dmZmZmZpmLYzMzMzOzzMWxmZmZmVnmHwExM5g7lxk779yph1xp9OhOPZ6ZmVk1PHNsZmZmZpa5OLZOIWmcpHcl9S9rf1JSSBq6iOM3SzpkEce4VNKIGvcZmuNvyY8pkm6T1LnTsGZmZlYXLo6tM40F9iu9kPRJYNnGhfMRST0XcYgVI6IvsAkwGrip1kK7GpK8FMrMzKwDuTi2znQFcGDh9UHA5cUNJO0u6V+SZkmaIGlkoW8ZSVdKmiZppqRHJa0q6WRgO+CcPHt7Tt5+PUmjJU2XNEbS8MJYl0r6f5LukDQH2KEsjnUk3SfpTUlTJV1XzQlGxOSI+B0wEviVpB55vIGSbpD0hqSxko4sHGtZSZdJmiHpOUk/kTSx0D9O0k8lPQ3MkbSUpK0kPZjz8JSkpsL2K0i6WNJrkl6VdFIdin8zM7MlgmehrDM9BBwgaX3gv8C+wLbASYVt5pAK6GeAjYDRkp6MiJtJxfQKwGBgLrAp8HZE/FzSZ4ArI+IiAEl9SDO4vwB2BTYG7pL0TEQ8k4/1NWA3YA+gV0TcXYjjl8BdpKK5F/DpGs/1RuA3wDBJY4BbgT+TZs7XAO6WNCYi7gSOB4YCawF9gDsqjLcfsDswFVgVuB04APgrsCNwg6T1IuIN4DJgCrBOHu82YAJwfnFASYcBhwEM6N+fJ4YPpzP1bG7u1ON1ppaWFpq78fk1gnNaX85nfTmf9dXofLo4ts5Wmj2+D3geeLXYGRHNhZdPS7oG2B64GXgPWAVYJyKeBh5v4zh7AOMi4o/59ROSbgC+Qiq8Af4cEf/Iz98p2/89YAgwMCImAg9Ue4LZpPzflYHNgQERcWJue1nShcBXgTuB4cC3I2IGMEPS2aSZ56KzI2ICgKSvA3dERKmIHi3pMWA3SX8l/TGwYkS8TZppPpNUBM9XHEfEBcAFAMOGDo3NRo2q8RQXTXe+W0VzczNNTU2NDqNbcU7ry/msL+ezvhqdTxfH1tmuAP4OfJyyJRUAkrYETiPNGvcCegN/Kuw7GLhW0orAlcDPI+K9CscZAmwpaWahbak8RsmENuL8CWn2+BFJM4AzIuKS9k6uYFD+73Tgk8DAslh6Avfn5wPLYqkUV7FtCLCPpD0LbUsD9+a+pYHXJJX6erQyppmZmZVxcWydKiLGSxpLWs7wzQqbXA2cA+waEe9IOgvon/d9DzgBOCHf3eIOYAxwMRBl40wA7ouItu4aUb5PMc7JwKEAkrYlLYP4e0S82O5JJl8CXs/xrQiMjYhPtLLta6SlFs/m14PbiXUCcEVEHFq+kaTVSUtO+kfE+1XGamZmZlnNF+RJ+piktYqPjgjMurVvAp+LiDkV+voB03NhvAVpXTAAknaQ9Ml8cdks0tKHebl7CmnNbsltwLqSDpC0dH5sntc7t0vSPpLWyC9nkIrTeW3sUtpvVUlHkNYRHx0RHwCPALPyRXXLSuopaSNJm+fdRgFHS1pJ0iDgiHYOcyWwp6Qv5LGWkdQkaY2IeI20VvoMSctL6iFpbUnbV3PeZmZmS7qqi2NJu0h6lTTL9WLh8UIHxWbdVES8FBGPtdL9HeBESbNJF9MVF8KuBlxPKoyfI61bvjL3/Q74Sr7jw9kRMRv4PGld7yRgMvAr0jKNamwOPCypBbgF+H5EjG1j+5n5rhf/Js2K71NahhER84A9SRcQjiVdVHcR6eJCgBOBibnv7nyOc1s7UF57vBdwDPAGaSb5x3z07/lA0pKUZ0mF/fXA6lWet5mZ2RKtlmUV55LWYF6WL/Qxq1pEDG2l/X1AhdfXk4q5StteA1zTSt8/gXXL2saQ7vBQafsR7cT7E9K64zZFxDgK8bex3SQK93gu65tDuvMEAJK+TSqWS/1DK+zzMOlCxUrjvQl8Oz+q07t3t75AzszMrFq1LKtYCTjfhbFZfUlaXdJn8hKIYcBRwE2NjsvMzGxJVEtxfDFwcEcFYrYE60W6zdps4G+k+yH/oaERmZmZLaFqWVaxFXCkpJ+R1m9+KCI+W9eozJYgETGedOs6MzMza7BaiuOL8sPMzMzMrFuqujiOiMs6MhAzMzMzs0ar6T7Hkg6W9DdJY/J/vQbZzMzMzLqNqmeOJf2cdP/UM4DxpJ+p/YmkgRFxcgfFZ2ZmZmbWaWpZc3wI0JQvHgJA0p3A3wEXx2ZmZmbW5dWyrKIP6de4iqYBy9YvHDMzMzOzxqmlOP4rcJWkYZKWlbQecBlwZ8eEZmZmZmbWuWopjo8g/UjBU0AL8CQwB/he/cMyMzMzM+t8tdzKbRZwoKQRQH9gakR80FGBmVknmjuXGTvvXJehVho9ui7jmJmZNUKbM8eShhaeryVpLWAo0BcYWmizBpO0pqQWST2r2HaopJBUywWZCxPTpZJO6oBxR0q6st7jdged9d6amZl1V+0tq/h34fmLwAv5v8XHCx0TWmNI2lbSg5LelDRd0j8kbd7gmCoWPMXiMyJeiYi+ETGvA46/hqQbJE3Nefl3/gZhsSRpeUlnSXol/8HwYn7dv9GxmZmZ2eKtzeI4IvoVnveIiJ75v8VHuzOVXYWk5YHbgN8DKwODgBOAuY2MazFwBTCBdG/rVUj3u57S0IhaIakXcA+wIbALsDywDenOKlvU+ViL1ezs4haPmZlZV1T1BXmSzm6l/ay6RdN46wJExDURMS8i3o6IuyLiaQBJPSQdK2m8pNclXS5phdxXmt09WNIESTMkHS5pc0lPS5op6ZziwSR9Q9Jzeds7JQ1Z2MDLZ5clfVzS3yXNlnS3pHMrLEXYP8+uTs0/8tKazYFLI2JORLwfEf+KiL8Ujl2abZ+Zz31EYd+VJN2e43hY0tqF/baR9GiejX5U0jaFvoGSbsmz9y9KOrTKVBwIrAl8KSKejYgPIuL1iPhlRNyRx15fUnOO9xlJXywct1nSIYXXIyQ9UHgdkr4r6QXgBSVn5s/Dm/m93ihv21vS6TnHUySdJ2nZ3HefpC8X8heSdsuvd5L0ZH5ezWfum5JeAf5WngxJX5Y0rhSTmZmZta2Wu1WMaKX9gDrEsbj4LzBP0mWSdpW0Uln/iPzYAViLtPb6nLJttgQ+AewLnAX8HNiJNJM5XNL2AJL2Bo4B/hcYANwPXFPHc7kaeIQ00zuSyu/TtsAwYEfgF5LWb2Wsh4BzJX1V0prFjvz6L6TZ9gHApqQ7mZTsR5p9X4m0DOfkvN/KwO3A2TnG3wK3S1ol73cNMBEYCHwFOEXSjlWc907AXyOipVKnpKWBW4G7gI+R7rZylaRhVYxdsjfpfd4A+DzwWdIfViuS3vdpebtf5fZNgXVI30T8IvfdBzTl558FXga2L7y+Lz8fQfufue2B9YEvlJ3rwTmGnSLiPzWcn5mZ2RKr3a9hJX2jtG3heclawNS6R9UgETFL0rbAT4ELgdUk3QEcGhFTgP2B30bEywCSjgb+k4uQkl9GxDvAXZLmANdExOt5+/uB/yEVPt8CTo2I53LfKcAxkoYUf4WwzFRJxdfLAb8u3ygXrJsDO0bEu8ADkm6pMN4JEfE28JSkp4BNgOcqbLdPzslxwHqS/p1z8mjOyd0RUSrsp/FRcQhwY0Q8kuO6ilQEA+wOvBARV+TX10g6EthT0j2kwn2PnMsnJV1EKvDvaSU3JasAj7fRvxWpwDwt323lb5JuIxXxI9sZu+TUiJiez+k9oB+wHvBI4f0UcCiwcWHbU0h/tBxN+gycmcf7LHAq6VcoIRW7v8vPq/nMjYyIObm/1PYD4BukX7WcWOkkJB0GHAYwoH9/nhg+vMrTb1vP5ua6jNOVtbS00Ow81JVzWl/OZ305n/XV6HxWs0axNOPYi/lnH4O07vSgegfVSLm4GQGg9EMnV5JmgPcjzWIWC9fxpByuWmgrrsV9u8Lrvvn5EOB3ks4o9Is0u9hacdw/It7/cGPp0la2GwhMj4i3Cm0TgMFl200uPH+rENt8ImIG8DPgZ0oXtZ0O3CxpjTzmS63E0dYxynNJfj2oEP/ssr5Pt3GckmnA6m30DwQmlN2GsHTcak0oPYmIvyktlzkXWFPSTcCPgGVIf7w8XihYBZTW6P8TWFfSqqSZ5S8CJ+T8bkH6WfZSvO195iawoB8DJ7ZWGOfYLwAuABg2dGhsNmpU22ddJd/KDZqbm2lqamp0GN2Kc1pfzmd9OZ/11eh8trusIiJ2iIgdSDNtOxQen4uI/SLioU6IsyEi4nngUqC0XnMSqagtWRN4n4W7OG0C8K2IWLHwWDYiHlyUmLPXgJUlLVdoKy+MF0pETCUVxwNJFy1OANZuc6fKynMJKZ+v5r6VJfWr0Neeu4EvSOrTxnEHSyp+9otjzyEVtSWrVRgj5nsRcXZEfIq0dGZdUmE6lfTH0IaF93eFiOib93mLNMP9feA/eYb/QeCHwEs5z6V42/vMzRdP9nng2NK6ZjMzM6tO1WuOI+LY0vN8EVKP0qNjQut8ktaTdFSeEUXSYNKMcekPgGuA/1O62K0vcApwXXE2twbnAUdL2jAfawVJ+yz6WUBelvEYMFJSL0lbA3su7HiSfiVpI0lL5YL128CLETENuArYSdLw3L+KpE2rGPYO0szp1/J++5LW8N4WERNIheKpkpaRtDHwzXys9pTurHFDfj975JiOyRe8PUwqgH8iaWlJTaTcXJv3fxL4X0nLSVonH7et3Gwuacu8lnkO8A4wL89MXwicKeljedtBkorrgu8j/fJkaX1xc9lrWPjP3DOku3Wcq8IFh2ZmZta2Wu5WMVDSTZKmkWau3is8uovZpAutHs7rhR8C/gMclfsvIRVffwfGkgqhhfr57Ii4iXSx1LWSZuXj7LpI0c9vf2Br0jKDk4DrWPhb0i0H3ATMJF04NoS0DICIeAXYjZSj6aTicpP2BsyF9R55v2nAT0hrjEszpvuRfnBmUj728RHR7vf1ETGXdFHe88BoYBbpwsT+wMN5hvaLpFxPBf4AHJi/JYC0Dvhd0szsZbRfkC9PKoJnkJY8TCPNrENap/0i8FB+j+8mXQBZch9pvfLfW3kNi/CZi4inSDm+UFI9P1tmZmbdliIqfSNbYUPpVtKa0VNJ/yf+WdIFTHdExIUdFaDVh6TrgOcj4vhGx2KLn2FDh8ZDn/hEXcbymuPGr5frjpzT+nI+68v5rK/OyKekxyOi4rVMtfxowDbAmhExR1JExFOSvkn6+tvF8WJG6Vf9ppNmGz8P7AWc1tCgbPHVu7eLWjMzM2orjueRllMAzJQ0gPSVdS1X+VvnWQ24kXRrs4nAtyPiX40NyczMzGzxVktx/DBpbelNwJ2kNaxvky78ssVMRNxK+rELMzMzM6tSLcXxAXx0Ad8PSBdS9SPdA9jMzMzMrMurujiOiJmF52+T7oBgZmZmZtZt1HIrtxslbVfWtp2k6+sflpmZmZlZ56vlBzy2J92ZoughYIf6hWNmZmZm1ji1FMfvAOU/yduH7vUjIGZmZma2BKulOL4TOF/S8gD5v+cAf+2IwMzMzMzMOlstxfFRpJ/KnS7pddIPTKxAunOFmZmZmVmXV8vdKmYAu0taHVgDmBARkzssMjMzMzOzTlZ1cSypNMs8JT8+bIuID+ofmpl1mrlzmbHzzos8jH+C2szMurpafgTkfSBa6etZh1jMzMzMzBqqljXHHwfWKjw+Q/p54sM6IC6zxY6k/SXdVXj9GUkvSGqRtLekv0g6qAOOe56k4+o9rpmZmS2o6uI4IsaXPR4CDgJ+2nHhmdVG0tckPZYL1tdywbrtQowzVFJI+vDblYi4KiI+X9jsROCciOgbETdHxK4Rcdkixj9C0gPFtog4PCJ+uSjjmpmZWXVqmTmuZHlgQD0CMVtUkn4InAWcAqwKrAn8AdirxnGqXW40BHimlrHNzMxs8VbLz0dfIenywuN64HHgyo4Lz6w6klYgzeR+NyJujIg5EfFeRNwaET+W1EPSzyS9JGmapFGSVs77lmaJvynpFeBvwN/z0DPzLPTWxVldSS+Rlhfdmvt7S2qWdEghpkMlPSdptqRnJW2W20txlNq/lNvXB84Dts5jzsztl0o6qWzcFyVNl3SLpIGFvpB0eF7uMUPSuZLUUXk3MzPrbmq5IO/FstdzgPMi4u46xmO2sLYGlgFuaqX/SGBv0s+gvwGcDZwL7FfYZntgfeAD0szzWGDFiHgfQNKw0oYRsbakccAhpX8DxRpU0j7AyHzMx4C1+ejXJF8CtgMmA/sAV0paJyKek3R4HrPiUhBJnwNOBT5PmrU+HbgW+Gxhsz2AzUnf7DxOujZggR/rkXQY+ZqBAf3788Tw4ZUOWZOezc2LPEZ30NLSQrNzUVfOaX05n/XlfNZXo/NZy32OT+jIQMwW0SrA1FIhW8G3gCMiYiKApJHAK5IOKGwzMiLm5P5FjecQ4NcR8Wh+/eEflxHxp8J210k6GtgC+HMV4+4PXBIRT+Q4jwZmSBoaEePyNqdFxEzSrPe9wKZUKI4j4gLgAoBhQ4fGZqNGVX92rfCt3JLm5maampoaHUa34pzWl/NZX85nfTU6n20Wx5K+Uc0gEXFJfcIxW2jTgP6SlmqlQB4C3CSpeE/ueaQZ4pIJdYxnMGmGeAGSDgR+CAzNTX2B/lWOOxB4ovQiIlokTQMGAeNyc/HHed7K45uZmVkV2ps5Ls6qiXT7tsmkImIwsBrwAODi2Brtn8A7pGUM11fonwB8IyL+Ud4haWh+WryPd2v39K7WBNJSivJjDQEuBHYE/hkR8yQ9Sfr3Vc1xJ5EK/dJ4fUiz5q8uYrxmZmZGOxfkRcQOpQfwb+DHETE4IraJiMHAj3K7WUNFxJvAL4Bz8z2Hl5O0tKRdJf2adKHbybk4RdIASW3dxeIN0trjtRYypIuAH0n6lJJ18rH7kArgN3IcBwMbFfabAqwhqVcr414NHCxpU0m9SXfmeLiwpMLMzMwWQS0X5H2dBb/6PQeYSrrYyayhIuK3kqYAxwJXAbNJF6SdDDxEmp29K9/d4XXgOlpZ5xsRb0k6GfiHpKWBXWqM5U+SViEVs6UlDwdExL8knUGa6f4AuBwozmb/jXSh3WRJH0RE/7Jx78k/CHIDsBLwIPDVWmIzMzOz1tVSHE8Gvsj8dwPYk1RkmC0WIuIqUmFcyW/zo3yfcXy0rKHY/gvSbHTJQ8Clhf6hZds3lb0+jzRjXT7uz4GftxL/u8DuZW0jqhk396ns9YhK2y2gd29fTGdmZkZtxfGRwPWSfkxaT7kmsAHpVlRmZmZmZl1eLbdyGy1pbWBX0hXztwO3R8S0jgrOzMzMzKwz1TJzTERMldQMDIqIhzomJDMzMzOzxqjl56PXlPQP4Hmg9ItgX5F0UUcFZ2ZmZmbWmaoujoHzSUsp+vHRz+COBnaud1BmZmZmZo1Qy7KKLYDdI+IDSQHp3rKSVuiY0MzMzMzMOlctM8dTgHWKDZI2AF6pa0RmZmZmZg1SS3F8OnBb/kWvpSTtR/oRhV91SGRmZmZmZp2sllu5XSJpOnAY6T7HBwLHRcTNHRSbmZmZmVmnqvVWbjcDN7fWL+kPEfGdRYzJzMzMzKwhallWUY2v13k8MzMzM7NOU9PMcRVU5/HMrDPMncuMnRe8K+NKo0c3IBgzM7PGqffMcdR5PLOa5R+saZHUs9GxmJmZWddS7+LYDEnNkmZI6t2I40fEKxHRNyLmtbetpCZJExf2WHn/D3Ix3iJpoqRRkjZf2DHNzMyscepdHHtZxRJO0lBgO9K3CF9sbDSdZlJE9CX9euRWpJ9Yv1/SjvU+kKR6L4UyMzOzgnoXx1fWeTzreg4EHgIuBQ4qdkjaTdKzkmZLelXSj3J7f0m3SZopabqk+yX1yH3r55nomZKekfTFwnjLSjpD0nhJb0p6ILcNlRSlQlLSwZKey8d9WdK3cnsf4C/AwMLM70BJPST9TNJLkqblmeCV2zvxSCZGxC+AiyjcA1zSepJG5/MbI2l4oW8VSbdKmiXpUUknSXqg0B+SvivpBeCF3LaHpCdzXh6UtHFh+4GSbpD0hqSxko6s+t0zMzNbwrU5CyXpG9UMEhGX5P9+ux5BWZd2IPBb4GHgIUmrRsSU3HcxMDwi7pe0EvDx3H4UMBEYkF9vBYSkpYFbgUuAzwPbAn+W9OmIGEP6YZoNgW2AycCWwAcVYnod2AN4Gfgs8BdJj0bEE5J2Ba6MiDVKG0v6AbA3sD3wBnA2cC6wXw15uBH4Ti7AAUYDvwB2BTYG7pL0TEQ8k8eeA6wGDAXuBMaXjbd3Pr+3JW2Wc7In8BjpLjG3SBoGvJdz9ucc7xrA3ZLGRMSdxQElHUa6bzkD+vfnieHDKdezubmGU7aSlpYWmp27unJO68v5rC/ns74anU9FtH4NnaR7iy+Bz5CKkAnAYGBV4B8RsUNHBmldg6RtgXuB1SNiqqTngfMj4szc/wpwMnBNRMwq7HcisAlwVES8WGjfDvgTMDAiPsht1wBjgBNJBeVWEfFUWRxDgbHA0hHxfoU4bwbujYjfSWpiweL4OeCIiLgnv16d9DPpy5aPV2n/3L4e8BypON02j7ddof98YBJwEvAOsFEu+JF0EtAUEdvm1wHsGBF/y6//HzA1Io4rjDeGVOi+A/wpItYs9B0NrBsRB5fnomTY0KHx0Cc+sUC771axcJqbm2lqamp0GN2Kc1pfzmd9OZ/11Rn5lPR4RHy6Ul+byyoiYofSA/g38OOIGBwR20TEYODHud0M0jKKuyJian59NfMvrfgysBswXtJ9krbO7b8BXiTNpr4s6We5fSAwoVQYZ+OBQUB/YBngpfaCkrSrpIfykoaZOYb+bewyBLgpL1mYSSpy55H+GKzWINK665l5vC1L4+Ux9yfNFA8gfYMzobDvBBZUbBsCHFU23mBSvoaQlokU+46pMXYzM7MlVi0X93ydBQuKc4CpgNc0LuEkLQsMB3pKmpybewMrStokIp6KiEeBvfJyiSOAUcDgiJhNWlpxlKQNgXslPUqaWR0sqUehQF4T+C/pc/cOsDYw38xxWVy9gRtIyz3+HBHv5Znj0sWjlb46mQB8IyL+sVDJSL4EPBERcyRNAO6LiAVuJKx0u7n3STPM/83NgyuMV4xzAnByRJxcYbytgbERseA0sJmZmbWrlgvyJrPg3Qf2JK3nNNubNLu6AbBpfqwP3A8cKKmXpP0lrRAR7wGz8vali8vWkaRC+zzSuuU5wE8kLZ2XMOwJXJuL5UuA3+YL0HpK2loL3j6uF6lIfwN4P68x/nyhfwqwiqQVCm3nASdLGpLjGyBpr/YSoGSQpOOBQ0gztgC3AetKOiCfx9KSNpe0fr7d3I3ASEnL5eUYB7ZzqAuBwyVtmY/ZR9LukvoBjwCzJP1U6eLEnpI2km8tZ2ZmVpVaiuMjgUvzlfHXSfoncBnwvY4JzbqYg4A/5nsMTy49SN8u7J+3OQAYJ2kWcDgf/dz4J4C7gRbgn8AfIqI5It4l/UG2K2mm+A/AgRHxfN7vR6RlPY8C00l3h5jvM51npY8kzVLPAL4G3FLofx64Bng5L0MYCPwub3OXpNmku29s2ca5D5TUkuN/FPgkac3wXYUYPg98lTQbPjnHWirkjwBWyO1X5HjmtnawiHgMOJSU2xmkJSkjct880h8Qm5LWXU8l3TljhQpDmZmZWZmql1VExGhJa5MKlYHA7cDtETGto4KzriMidmmlfRSpMAVobZszgTNb6XuGdNeISn1vAz/Ij6JxFO65HRHnku4I0Vrsle7K8tv8aFNENFPFH5n5YrvdW+l7o9gn6Veku3eU+he4f3hE/BX4ayvjTaK2O2tA796++M7MzIza1hyT70DQDAyKiIc6JiSzJUteStGLNAu+OfBN0rIMMzMz62RVL6uQtKakf5B+/evu3PYVSRd1VHBmS4h+pHXHc0iz7GeQ7lNsZmZmnayWmePzSUsptgNKSylGk/6P3MwWUr6LxzqNjsPMzMxqK463AHaPiA/yjxIQEW+WXeVvZmZmZtZl1XK3iimUzW5J2oD0y2FmZmZmZl1eLcXx6cBtkg4GlpK0H3Ad6ZZUZmZmZmZdXi23crtE0nTgMNIvdB0IHBcRN3dQbGZmZmZmnaqq4jj/xO09wBdcDJuZmZlZd1XVsor8q1sfr3Z7MzMzM7OuqJZi9wTg/0kaIqmnpB6lR0cFZ2ZmZmbWmWq5lVvpxz4OKLQJCKBn3SIyMzMzM2uQWorjj3dYFGbWWHPnMmPnnT98udLo0Q0MxszMrHGqXhIREeNbe3RkgGaNIOkzkl6Q1CJp7w4Y/zxJx9V73ArHGSdpp44+jpmZWXfR5syxpAsi4rD8/ArSEooFRMSBHRCbWc0kjQNWBeYBc4A7gO9FREuNQ50InBMRv6tvhElEHN4R45qZmdmiaW9ZxdjC8xc7MhCzOtozIu6WNAi4EzgW+FmpU9JSEfF+O2MMAZ7pwBjNzMxsMdTmsoqIOLXw/ITWHh0fplntIuJV4C/ARpJC0nclvQC8ACDpUEkvSpou6RZJA3P7S8BawK15WUVvSStIuljSa5JelXRSvv83ktaRdJ+kNyVNlXRdbpekMyW9nvuelrRR7rtU0kmlWFuLJfeFpMPzMo8Zks6VpNy3tqS/SZqWj32VpBU7I79mZmbdUdVrjiV9rrVHRwZotrAkDQZ2A/6Vm/YGtgQ2yJ/bU4HhwOrAeOBagIhYG3iFNAPdNyLmApcB7wPrAP8DfB44JI/7S+AuYCVgDeD3uf3zwGeBdYEVgX2BaRXibDWWgj2AzYFN8nZfKO2e9x0IrA8MBkZWlyEzMzMrV8vdKi4uez0A6AVMJM2ymS0ubpb0PvAmcDtwCmlpxakRMR1A0v7AJRHxRH59NDBD0tCIGFccTNKqwK7AihHxNjBH0pmkn1I/H3iPtAxjYERMBB7Iu74H9APWAx6JiOdaibeaWE6LiJnATEn3ApsCf42IF/loydMbkn4LHF9NkiQdls+BAf3788Tw4R/29WxurmYIa0VLSwvNzmFdOaf15XzWl/NZX43OZ9XFcUTMdyu3/JXyscDsegdltoj2joi7iw15FcKEQtNA4InSi4hokTQNGASMKxtvCLA08FoeB9K3LqXxfkKaPX5E0gzgjIi4JCL+Jukc4FxgTUk3AT+KiFll41cTy+TC9m8BffN5fQw4G9iOVIj3AGZUzEqZiLgAuABg2NChsdmoUR/2+VZui6a5uZmmpqZGh9GtOKf15XzWl/NZX43O50L/ul3+SemTSYWBWVdQvNvKJFLRC4CkPsAqwKsV9psAzAX6R8SK+bF8RGwIEBGTI+LQiBgIfAv4g6R1ct/ZEfEpYEPS8oofVxi/lljKnZrPa+OIWB74OmmphZmZmS2ERf3p552BD+oRiFknuxo4WNKmknqTll48XL6kAiAiXiOtKT5D0vL5Z9PXlrQ9gKR9JK2RN59BKlbnSdpc0paSlibdVu4d0i3mFjqWCvoBLaTlFoOoXHybmZlZlWq5IG+CpFcKj6nAnyjcIsusq4iIe4DjgBuA14C1ga+2scuBpDX2z5IK4OtJF89BulDuYUktwC3A9yNiLLA8cGHefjzpYrzT6xBL0QnAZny0vvrGKvczMzOzCmq5IO/rZa/nAP+tsH7SrGEiYmgr7QssNYiI84DzqhknIt4Evp0f5dv+hArLi3LRu3Er44+oIRaVvR5ReP4M8KmyXc5o7Txa1bu31xmbmZlR2wV593VkIGZmZmZmjVZ1cdzWz0cX+aekzczMzKyrquWCvJmkH1HoSbq3cQ9gr9z+UuFhZmZmZtYl1bLmeF1g94i4v9QgaVvguIj4Quu7mZmZmZl1DbXMHG8FPFTW9jCwdf3CMTMzMzNrnFqK438Bp0haFiD/92TgyQ6Iy8zMzMys09VSHI8APgO8KWkK6b6q2wIHdUBcZmZmZmadrpZbuY0DtpE0GBgIvBYRr3RUYGZmZmZmna2mn4+WtArQBGwfEa9IGlj42VwzMzMzsy6tlp+P3h4YA+xP+qlbgE8A/68D4jIzMzMz63S1zByfBewbEbsA7+e2h4Et6h2UmZmZmVkj1FIcD42Ie/Lz0i/lvUtt90o2s8XR3LnM2HlnZuy8c6MjMTMza6haiuNnJZX/2MdOwL/rGI+ZmZmZWcPUUhz/BLhK0mXAspLOBy4FftwRgS3uJI2UdGV+PlRSSPIseieSNELSA42Oo1bFz04nHKtL5sjMzKxRqiqOJfUE7gY2Bp4BLgHGAltExKNV7L+tpAclvSlpuqR/SNp8UQKvB0m9cqHygqQ5ksZJukTS0EbHVi1J60r6k6SpOb9PS/phfs+soCvmSlKzpEMaHYeZmdmSoqriOCLmAf/Nz38dEd+NiNMiYmJ7+0paHrgN+D2wMjAIOAGYu9BR18/1wBeBrwErAJsAjwM7NjKoaklam3RR5ATgkxGxArAP8GmgX52PtVjNitcaT2fmyszMzLquWpZVXAXcJukgSTtK+lzp0c5+6wJExDURMS8i3o6IuyLiaQBJPSQdK2m8pNclXS5phdxXWq5wsKQJkmZIOlzS5nnWb6akc4oHk/QNSc/lbe+UNKRSUJJ2AnYG9oqIRyPi/Yh4MyLOjYiL8zYDJd2SZ7tflHRoNYmStIKkiyW9JulVSSeVZicl9ZR0Rp69HCvpiOKSjLb2reAE4MGI+GFEvJbzPCYivhYRM/N4X5T0TM5Vs6T1C3GGpHUKry+VdFJ+3iRpoqSfSpoM/FFSf0m35bGmS7pfUo9Crm6Q9EY+ryNz+zKS3pbUP78+VtL7+Y8m8vmdVTj3y/MY4/O2pfFH5G8czpQ0HRhZIe+/kfRA6fNT51yNk/Tj/Lmbk9+jVSX9RdJsSXdLWilvW/rcHiZpUn4vj2rj87KV0jcrMyU9Jakpt58MbAecI6ml9FmXtJ6k0fk9GCNpeGGsVfJndpakR4C1WzuumZmZLaiW2bdv5/+OLGsPYK029vsvME9prfK1wEMRMaPQPyI/dgBeBy4HzgEOKGyzJemeyp8FbgH+SroYcGngX5L+FBH3SdobOAbYE3gB+BlwDbBNhbh2Ah6JiAltxH4NaRnJQGA9YLSklwt37WjNZcAUYB2gD2nmfAJwPnAosCuwKTAH+FMN+1Y6h6NbC0LSuvkc9gaagf8DbpW0QUS82845AKxGmu0fQvpD6hfARGBA7t8KiFzA3gr8GdgPWAO4W9KYiLhT0qPA9sANpPdwPOmnyP+SX5+Zx/s9aQZ/LWAV4C7gNeDi3L8l6TP0MdJ7v28+zx45P2sCn4+ItyqcSz1y9WXSH1RLAf8C/gf4JvBsPpcjSUV4yQ6kz+1awN8kPRURd5cddxBwO+nz/lfStxY3SFovIn4u6TPAlRFxUd6+DzCa9F7sSlrqdJekZyLiGeBc4B1gdeDjwJ2kJVCVzvkw4DCAAf3788TwVGP3bG5uLU1WpZaWFpqdx7pyTuvL+awv57O+Gp7PiOjwB7A+6eK9iaR7JN8CrJr77gG+U9h2GPAeqQAZSiq+BxX6p5Hut1x6fQPwg/z8L8A3C309gLeAIRViuhC4to2YBwPzgH6FtlOBS/PzkaSihUKcSwGrkpaMLFvYbz/g3vz8b8C3Cn07VbtvhRjfA3Zp4xyOA0aV5eNVoCm/DmCdQv+lwEn5eRPpVn3LFPpPJBXA65QdZ0vglbK2o4E/5ue/BM7O5zgZ+D5wGrAM8DbQH+iZz32DwhjfAprz8xEVjjGCtFTiuvw56NVGLhY1V+OA/cs+d/+v8Pp7wM1ln4f1Cv2/Bi6u8Nn5KXBFWSx3Agfl583AIYW+fYH7y7Y/Hzg+5/C9suOeAjzQ3r/RdYcMiek77RTTd9opbNHde++9jQ6h23FO68v5rC/ns746I5/AY9HK/yd2yjrSiHiOVMggaT3gStKPiuxHmpUdX9h8PB8ViiVTCs/frvC6b34+BPidpDMK/SKtcy4eA1KRvW4bYQ8EpkfE7LLYPt3GPqUYlgZek1Rq60Ga/S2NW5ytLj5vb99y00gzhK2ZL7cR8YGkCaR8VOONiHin8Po3pMLurhzfBRFxWo57oKSZhW17Avfn5/cBvwU2I936bzRpNngr4MWImCppVaAXC34WirFWysM6pLXiW0Tbs+H1yFW1n8NK8Y4HPlnhuEOAfSTtWWhbGri3lTiHAFuW5Xop4ArSjP5SFY5rZmZmVaplzXFdRMTzpBnKjXLTJNL/4ZesSZpdnkLtJpBmZVcsPJaNiAcrbHs3sIWkNVoZaxKwsqTixVprkmYT24thLtC/EMPyEbFh7n+NtOygZHAN+1Y6hy+3Ect8uVWqaAcXzuEtYLnC9quV7R/zvYiYHRFHRcRapKUrP5S0Y457bFne+0XEbnnXB0nfCHwJuC8iniXlcndS4QwwlTTrWf5ZKOZ7vniy54CDgb9IGtZKHmDRc7Uwiu/tmvkY5SaQZo6LueuT/+iABc95AimHxe37RsS3gTdI/3bKj2tmZmZV6vDiOF88dFSpCJU0mDRj/FDe5Brg/yR9XFJf0tfA10XE+5VHbNN5wNGSNszHWkHSPpU2jLT2czRwk6RPSVpKUj+lC/6+EWkt8oPAqfmiso1J60uvaiuASBd73QWcIWl5pQsO15a0fd5kFPB9SYMkrUj6Wr3afcsdD2yTL0RbLZ/zOpKuzGOPAnZXuoByaeAoUvFd+mPhSeBrShcJ7kJaF9wqSXvk8QXMIi07mQc8AsxSunhv2TzeRsq364u0Bvhx4Lt8VAw/SFo2cV/eZl6O9+T8PgwBfkj6lqFNEXENaa353Up3peiIXC2M4yQtlz+PB5OWf5S7EthT0hdy3pZRuhiy9AfUFOZf038bsK6kAyQtnR+bS1o/5/BGYGQ+7gbAQYsQv5mZ2RKnM2aOZ5PWpD4saQ6pKP4PqfiAdM/kK4C/ky4ceoe0frNmEXET8CvgWkmz8nF2bWOXrwB3kIqWN/P2nybNMkIq4oeSZvxuAo6PiNFVhHIgaYnAs8AM0i3jSl/pX0gqgJ8mXdR1B2m2b14V+5af70vA1jnGZyS9SVoL+xgwOyLGAF8nXeg2lTTbu2dh+cH3c9tMYH/g5nbO6xOk3LQA/wT+EBHNuSjbk3SR4dh8rItIF9eV3EdaLvBI4XU/0vte8j3SRYovAw8AV5M+H+2KiMtIa6L/pgr3qa5DrhbGfcCLpHX1p0fEXRXimgDsRSru3yDNDP+Yj/5t/g74itLdV87Oy3w+D3yV9LmcTPrM987bH0Fa3jGZ9A3NHxchfjMzsyWO0ppkaxRJuwLnRUTFW85Z15OL87HA0gv5DUinGzZsWIwZM6bRYXQbzc3NNDU1NTqMbsU5rS/ns76cz/rqjHxKejwiKl5H1ulrjpd0ednBbnkZxyDS1/03NTouMzMzM3Nx3Agi3Qt3BmlZxXOke9aamZmZWYMtVj8JvCTIF6dt3ug4rONExDjSH0FmZmbWxXjm2MzMzMwsc3FsZmZmZpa5ODYzMzMzy1wcm5mZmZllLo7NzMzMzDIXx2ZmZmZmmYtjMzMzM7PMxbGZwdy5jY7AzMxsseDi2MzMzMwsc3FsZmZmZpa5OLYlnqRxkt6WNFvSTEkPSjpc0iL9+8jj7lSvOCuMP0LSAx01vpmZ2ZLIxbFZsmdE9AOGAKcBPwUublQwkpZq1LHNzMyWZC6OzQoi4s2IuAXYFzhI0kaSVpB0uaQ3JI2XdGxxVlnSoZKeyzPPz0raTNIVwJrArZJaJP0kb/tFSc/kGepmSesXxhkn6aeSngbmSFpK0s8kvVQY+0t52/WB84Ct8/gzc3tvSadLekXSFEnnSVq2s/JnZmbW1SkiGh2DWUNJGgccEhF3l7W/ApwKbA2sAHwdWAW4C/hVRFwsaR/gLGBv4DFgbeC9iBhfPq6kdYF/5W2bgf8DDgM2iIh38/YzgT2BqRHxdh7/H8BkYB/gEmCdiHhN0og8/raFmM8C1gJGAO8BVwP/iYijK5z3Yfn4DOjf/1Oj/vSn2pNnFbW0tNC3b99Gh9GtOKf15XzWl/NZX52Rzx122OHxiPh0pT5/dWvWuknAyqRZ5P+JiNnAbElnAAeQll0cAvw6Ih7N+7zYxnj7ArdHxGgASacD3we2IRXLAGdHxITSDhFRrFivk3Q0sAXw5/LBJQk4FNg4IqbntlNIBfICxXFEXABcADBs6NBoampqI3SrRXNzM85nfTmn9eV81pfzWV+NzqeLY7PWDSL9G+kFjC+0j899AIOBl6ocb2BxnIj4QNKEwlgAE4o7SDoQ+CEwNDf1Bfq3Mv4AYDng8VQnpyGAnlXGZ2ZmtsTzmmOzCiRtTipabyYtTxhS6F4TeDU/n0BaSlFJ+ZqlScVx8kzv4MJY8+0jaQhwIXAEsEpErAj8h1TwVhp/KvA2sGFErJgfK0SEv+szMzOrkotjswJJy0vaA7gWuDIingJGASdL6pcL1h8CV+ZdLgJ+JOlTStbJ2wBMIa3/LRkF7C5pR0lLA0cBc4EHWwmnD6kAfiPHdjCwUaF/CrCGpF6QZqJJxfSZkj6W9xkk6QsLnRAzM7MljItjs+RWSbNJM8E/B34LHJz7vgfMAV4GHiCt4b0EPlwTfHJum02aaV4573cqcGy+M8WPImIM6aK+35Nmefck3ULu3UoBRcSzwBnAP0mF8CdJF+eV/A14BpgsaWpu+ylp3fNDkmYBdwPDFi4lZmZmSx6vObYlXkQMbad/Bqmoba3/PNJt1crb/0zZhXMRcRNwU7VxRMTPScV6pe3fBXYva3sHOCY/qte7d02bm5mZdVeeOTYzMzMzy1wcm5mZmZllLo7NzMzMzDIXx2ZmZmZmmYtjMzMzM7PMxbGZmZmZWebi2MzMzMwsc3FsZmZmZpa5ODYzMzMzy1wcm5mZmZllLo7NzMzMzDIXx2ZmZmZmmYtjq4mkYyRd1AnHaZZ0SEcfp54knSfpuCq3vVTSSR0dk5mZmdXGxXEXIelOSSdWaN9L0mRJS3XAMZskTSy2RcQpEbFYF62V4s7t8xXcudAfK6lF0kRJ17Ux5jhJb0uaLWmmpAclHS7pw39DEXF4RPyy/mdkZmZmncXFcddxKXCAJJW1HwBcFRHvd35IXZekg0i52yki+gKfBu5pZ7c9I6IfMAQ4DfgpcHGHBmpmZmadysVx13EzsDKwXalB0krAHsDlknpLOkvSpPw4S1LvwrZ7SXpS0ixJL0naJbcfLOm5PCP6sqRv5fY+wF+AgXlmtUXSQEkjJV1ZGPeLkp7Js6nNktYv9I2T9CNJT0t6U9J1kpYpxS7pNklvSJqRn6/RoRmc3+bAnRHxEkBETI6IC6rZMSLejIhbgH2BgyRtBPMvlSjNXufZ6ak5F/u3NqakQyW9KGm6pFskDSz0haTvSHohv0+/lLS2pH/m93OUpF5520bn1czMrEtzcdxFRMTbwCjgwELzcOD5iHgK+DmwFbApsAmwBXAsgKQtgMuBHwMrAp8FxuUxXicV2MsDBwNnStosIuYAuwKTIqJvfkwqxiRpXeAa4AfAAOAO4NZSoVaIcRfg48DGwIjc3gP4I2kWdk3gbeCchUjNwnoIOFDSjyV9WlLPWgeIiEeAiRT+YCmzGtAfGAQcBFwgaVj5RpI+B5xKytXqwHjg2rLNdgE+RXqPfwJcAOwPDAY2AvbL2zU6r2ZmZl1a3depWoe6DLhd0vdysXxgboNUKH0vIl4HkHQCcD5wHPBN4JKIGJ23fbU0YETcXhj/Pkl3kYq9J6qIZ1/g9tK4kk4Hvg9sAzTnbc4uFdWSbiUV70TENOCG0kCSTgbureKY1RooaWZZW1/gynz8KyUF6Q+CkcA7kn4TEafVeJxJpBn91hwXEXNJub2dVACXr0ven/T+PAEg6WhghqShETEub/OriJgFPCPpP8BdEfFy3v4vwP8Al9WSV0mHAYcBDBgwgObm5urP2trU0tLifNaZc1pfzmd9OZ/11eh8ujjuQiLiAUlvAHtJeoS0NOB/c/dA0oxjyfjcBml28Y5KY0raFTgeWJc067gc8O8qQ5rvmBHxgaQJpJnSksmF52+VYpK0HHAmaUZ0pdzfT1LPiJjX1kEltRRebhARr1TYbFJEzLecQFJz8XVEXAVcJWlpYO/8/F8RcWdbxy8zCJjeSt+MPANfUnxPigZS+GMkIlokTctjj8vNUwrbv13h9WpQW17zMpILAIYNGxZNTU2tnIbVqrm5GeezvpzT+nI+68v5rK9G59PLKrqey0kzxgeQZg9LRdIk0lfpJWvmNoAJwNrlA+U1yTcApwOrRsSKpCK6dNFftBPLfMfMFwsOpjAz3YajgGHAlhGxPGmpB4Vjt6qwzKNvK4VxTSLivYj4E/A0aYlCVSRtTipgH2hlk5Xy2u2S4ntSVJ7HPsAqVJfHcgudVzMzM3Nx3BVdDuwEHMpHSyogrf09VtIASf2BX5CXEJDuqHCwpB0l9ZA0SNJ6QC+gN/AG8H6eRf58YcwpwCqSVmglllHA7nncpUmF2VzgwSrOox9pxnOmpJVJs9edRtIISbtL6pdzsiuwIfBwFfsuL2kP0rrgKyOirZn2EyT1krQdaW33nypsczXp/dk0/8FyCvBwYUlFLRqaVzMzs67OxXEXkwumB4E+wC2FrpOAx0izn/8mfU1/Ut7nEfLFdsCbwH3AkIiYDRxJKnJnAF8rjhkRz5OK7pfz3SjmWxIQEWOArwO/B6YCe5Jud/ZuFadyFrBs3u8h4K9VpqBeZgHHAK8AM4FfA9+OiNZmgSFdbDibNBP/c+C3pLy2ZjIpr5OAq4DDc07nExH3kNaG3wC8Rprl/2qN51NyFo3Nq5mZWZemiPa+OTezWklqIs0qd4nbqA0bNizGjBnT6DC6jUavl+uOnNP6cj7ry/msr87Ip6THI+LTlfo8c2xmZmZmlrk4NjMzMzPLfCs3sw4QEc1Al1hSYWZmZh/xzLGZmZmZWebi2MzMzMwsc3FsZmZmZpa5ODYzMzMzy1wcm5mZmZllLo7NzMzMzDIXx2ZmZmZmmYtjMzMzM7PMxbGZmZmZWebi2BZbko6RdFEnHKdZ0iEdfRwzMzNb/Lk4tgVIulPSiRXa95I0WVLdf3ZcUpOkicW2iDglIhbrojXH/YGklvyYKGmUpM0bHZuZmZnVzsWxVXIpcIAklbUfAFwVEe93fkiLtUkR0RfoB2wFPA/cL2nHeh+oI/4wMTMzs4+4OLZKbgZWBrYrNUhaCdgDuFxSb0lnSZqUH2dJ6l3Ydi9JT0qaJeklSbvk9oMlPSdptqSXJX0rt/cB/gI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     },
     "metadata": {
      "needs_background": "light"
     }
    }
   ],
   "source": [
    "# Calculate the \"required_education\" column cross table regarding the target variable in a normalized form\n",
    "required_education_cross = pd.crosstab(df[\"required_education\"], df[\"fraudulent\"], normalize=True)\n",
    "\n",
    "# Filters the 20 largest positive occurences in decreasing order\n",
    "required_education_cross_filtered = required_education_cross[\"yes\"].sort_values()\n",
    "\n",
    "# Plot a horizontal bar chart with the obtained values\n",
    "plt.figure(figsize=(8, 6))\n",
    "required_education_cross_filtered.plot(title=\"Most fraudulent of required_education\", kind=\"barh\", color=\"#E44\", fontsize=\"12\", grid=True)\n",
    "plt.xlabel(\"% of ocurrence\")\n",
    "plt.rcParams[\"font.size\"] = \"12\"\n",
    "plt.savefig(\"plots/most_fraudulent_required_education.png\", dpi=300)\n",
    "plt.show()\n"
   ]
  },
  {
   "source": [
    "### 5.9. Most fraudulent of `function`"
   ],
   "cell_type": "markdown",
   "metadata": {}
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "output_type": "display_data",
     "data": {
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     },
     "metadata": {
      "needs_background": "light"
     }
    }
   ],
   "source": [
    "# Calculate the \"function\" column cross table regarding the target variable in a normalized form\n",
    "function_cross = pd.crosstab(df[\"function\"], df[\"fraudulent\"], normalize=True)\n",
    "\n",
    "# Filters the largest positive occurences in decreasing order\n",
    "function_cross_filtered = function_cross[\"yes\"].sort_values()\n",
    "\n",
    "# Plot a horizontal bar chart with the obtained values\n",
    "plt.figure(figsize=(8, 16))\n",
    "function_cross_filtered.plot(title=\"Most fraudulent of functions\", kind=\"barh\", color=\"#E44\", fontsize=\"12\", grid=True)\n",
    "plt.xlabel(\"% of ocurrence\")\n",
    "plt.rcParams[\"font.size\"] = \"12\"\n",
    "plt.savefig(\"plots/most_fraudulent_functions.png\", dpi=300)\n",
    "plt.show()\n"
   ]
  },
  {
   "source": [
    "### 5.10. Most fraudulent of `industries`"
   ],
   "cell_type": "markdown",
   "metadata": {}
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "output_type": "display_data",
     "data": {
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\n"
     },
     "metadata": {
      "needs_background": "light"
     }
    }
   ],
   "source": [
    "# Calculate the \"industry\" column cross table regarding the target variable in a normalized form\n",
    "industry_cross = pd.crosstab(df[\"industry\"], df[\"fraudulent\"], normalize=True)\n",
    "\n",
    "# Filters the 20 largest positive occurences in decreasing order\n",
    "industry_cross_filtered = industry_cross[\"yes\"].sort_values(ascending=False).iloc[0:20]\n",
    "\n",
    "# Plot a horizontal bar chart with the obtained values\n",
    "plt.figure(figsize=(8, 16))\n",
    "industry_cross_filtered.plot(title=\"Most fraudulent of industries\", kind=\"barh\", color=\"#E44\", fontsize=\"12\", grid=True)\n",
    "plt.xlabel(\"% of ocurrence\")\n",
    "plt.gca().invert_yaxis()\n",
    "plt.rcParams[\"font.size\"] = \"12\"\n",
    "plt.savefig(\"plots/most_fraudulent_industries.png\", dpi=300)\n",
    "plt.show()"
   ]
  },
  {
   "source": [
    "## 6. Conclusion\n",
    "\n",
    "With the analysis done, it is possible to determine the type of variable face of interest for each column, to later define transformations in these values to build the predictive model.\n",
    "\n",
    "| **Column**              | **Type** |\n",
    "|:------------------------|:---------|\n",
    "| **title**               | Text     |\n",
    "| **department**          | Category |\n",
    "| **company_profile**     | Text     |\n",
    "| **description**         | Text     |\n",
    "| **requirements**        | Text     |\n",
    "| **benefits**            | Text     |\n",
    "| **telecommuting**       | Boolean  |\n",
    "| **has_company_logo**    | Boolean  |\n",
    "| **has_questions**       | Boolean  |\n",
    "| **employment_type**     | Category |\n",
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