02_reddit_eda.ipynb

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   "source": [
    "# Import Libraries\n",
    "import pandas as pd\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns\n",
    "from sklearn.feature_extraction.text import CountVectorizer\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 69,
   "id": "a4427e7b",
   "metadata": {
    "scrolled": true
   },
   "outputs": [],
   "source": [
    "df = pd.read_csv('./data/subreddit_data_1000.csv') #Read scraped data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 70,
   "id": "3b9c2efd",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
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       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Unnamed: 0</th>\n",
       "      <th>title</th>\n",
       "      <th>selftext</th>\n",
       "      <th>subreddit</th>\n",
       "      <th>created_utc</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0</td>\n",
       "      <td>Accidentally deposited rollover check into my ...</td>\n",
       "      <td>My company closed out my old 401k and I electe...</td>\n",
       "      <td>personalfinance</td>\n",
       "      <td>1637254286</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1</td>\n",
       "      <td>Unemployment Advice</td>\n",
       "      <td>I have been working for my current employers f...</td>\n",
       "      <td>personalfinance</td>\n",
       "      <td>1637254255</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2</td>\n",
       "      <td>Where does the interest in compound interest c...</td>\n",
       "      <td>This may be a stupid question but I feel like ...</td>\n",
       "      <td>personalfinance</td>\n",
       "      <td>1637254028</td>\n",
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       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>3</td>\n",
       "      <td>Debt Settlement and Inflation</td>\n",
       "      <td>I see a lot of posts lately on credit card com...</td>\n",
       "      <td>personalfinance</td>\n",
       "      <td>1637254017</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>4</td>\n",
       "      <td>Taking out money from trad. IRA to put into Ro...</td>\n",
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      "text/plain": [
       "   Unnamed: 0                                              title  \\\n",
       "0           0  Accidentally deposited rollover check into my ...   \n",
       "1           1                                Unemployment Advice   \n",
       "2           2  Where does the interest in compound interest c...   \n",
       "3           3                      Debt Settlement and Inflation   \n",
       "4           4  Taking out money from trad. IRA to put into Ro...   \n",
       "\n",
       "                                            selftext        subreddit  \\\n",
       "0  My company closed out my old 401k and I electe...  personalfinance   \n",
       "1  I have been working for my current employers f...  personalfinance   \n",
       "2  This may be a stupid question but I feel like ...  personalfinance   \n",
       "3  I see a lot of posts lately on credit card com...  personalfinance   \n",
       "4  I had a traditional IRA with primerica and I r...  personalfinance   \n",
       "\n",
       "   created_utc  \n",
       "0   1637254286  \n",
       "1   1637254255  \n",
       "2   1637254028  \n",
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   "source": [
    "df.head() #View first 5 rows"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 71,
   "id": "271a607c",
   "metadata": {
    "scrolled": true
   },
   "outputs": [],
   "source": [
    "df.drop(columns = 'Unnamed: 0',inplace = True) #Drop extra index column"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 72,
   "id": "0ac0c5cf",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "subreddit\n",
       "cscareerquestions    1500\n",
       "personalfinance      1500\n",
       "Name: created_utc, dtype: int64"
      ]
     },
     "execution_count": 72,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.groupby('subreddit')['created_utc'].count() #Count posts for each subreddit"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 73,
   "id": "b8c3a973",
   "metadata": {
    "scrolled": true
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   "outputs": [
    {
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       "      <td>1637254319</td>\n",
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       "      <th>1501</th>\n",
       "      <td>possible implications in returning to work in ...</td>\n",
       "      <td>I've held off my cs studies for most of covid ...</td>\n",
       "      <td>cscareerquestions</td>\n",
       "      <td>1637254205</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1502</th>\n",
       "      <td>VR Career Advice</td>\n",
       "      <td>My background is in designing and programming ...</td>\n",
       "      <td>cscareerquestions</td>\n",
       "      <td>1637253634</td>\n",
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       "      <th>1503</th>\n",
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       "      <td>1637253631</td>\n",
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       "      <th>1504</th>\n",
       "      <td>Has being completely honest and upfront about ...</td>\n",
       "      <td>Hello,\\n\\nI hate playing the game of salary ne...</td>\n",
       "      <td>cscareerquestions</td>\n",
       "      <td>1637253246</td>\n",
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       "                                                  title  \\\n",
       "1500  Anyone graduated/currently enrolled in U Washi...   \n",
       "1501  possible implications in returning to work in ...   \n",
       "1502                                   VR Career Advice   \n",
       "1503               Professional resume writing service?   \n",
       "1504  Has being completely honest and upfront about ...   \n",
       "\n",
       "                                               selftext          subreddit  \\\n",
       "1500  Would like to connect and clarify some doubts....  cscareerquestions   \n",
       "1501  I've held off my cs studies for most of covid ...  cscareerquestions   \n",
       "1502  My background is in designing and programming ...  cscareerquestions   \n",
       "1503                                          [removed]  cscareerquestions   \n",
       "1504  Hello,\\n\\nI hate playing the game of salary ne...  cscareerquestions   \n",
       "\n",
       "      created_utc  \n",
       "1500   1637254319  \n",
       "1501   1637254205  \n",
       "1502   1637253634  \n",
       "1503   1637253631  \n",
       "1504   1637253246  "
      ]
     },
     "execution_count": 73,
     "metadata": {},
     "output_type": "execute_result"
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   ],
   "source": [
    "# Create separate subreddit for cscareerquestions\n",
    "df_cs = df[df['subreddit'] == 'cscareerquestions']\n",
    "df_cs.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 74,
   "id": "8ab1a0c0",
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       "      <td>Accidentally deposited rollover check into my ...</td>\n",
       "      <td>My company closed out my old 401k and I electe...</td>\n",
       "      <td>personalfinance</td>\n",
       "      <td>1637254286</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Unemployment Advice</td>\n",
       "      <td>I have been working for my current employers f...</td>\n",
       "      <td>personalfinance</td>\n",
       "      <td>1637254255</td>\n",
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       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Where does the interest in compound interest c...</td>\n",
       "      <td>This may be a stupid question but I feel like ...</td>\n",
       "      <td>personalfinance</td>\n",
       "      <td>1637254028</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Debt Settlement and Inflation</td>\n",
       "      <td>I see a lot of posts lately on credit card com...</td>\n",
       "      <td>personalfinance</td>\n",
       "      <td>1637254017</td>\n",
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       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Taking out money from trad. IRA to put into Ro...</td>\n",
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       "                                               title  \\\n",
       "0  Accidentally deposited rollover check into my ...   \n",
       "1                                Unemployment Advice   \n",
       "2  Where does the interest in compound interest c...   \n",
       "3                      Debt Settlement and Inflation   \n",
       "4  Taking out money from trad. IRA to put into Ro...   \n",
       "\n",
       "                                            selftext        subreddit  \\\n",
       "0  My company closed out my old 401k and I electe...  personalfinance   \n",
       "1  I have been working for my current employers f...  personalfinance   \n",
       "2  This may be a stupid question but I feel like ...  personalfinance   \n",
       "3  I see a lot of posts lately on credit card com...  personalfinance   \n",
       "4  I had a traditional IRA with primerica and I r...  personalfinance   \n",
       "\n",
       "   created_utc  \n",
       "0   1637254286  \n",
       "1   1637254255  \n",
       "2   1637254028  \n",
       "3   1637254017  \n",
       "4   1637253836  "
      ]
     },
     "execution_count": 74,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "## Create separate subreddit for cscareerquestions\n",
    "df_pf = df[df['subreddit'] == 'personalfinance']\n",
    "df_pf.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 75,
   "id": "80b539dd",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "<ipython-input-75-89fd45039a25>:1: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame\n",
      "\n",
      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  df_pf.drop_duplicates(subset = 'selftext',inplace=True) #Drop duplicates\n"
     ]
    }
   ],
   "source": [
    "df_pf.drop_duplicates(subset = 'selftext',inplace=True) #Drop duplicates"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 76,
   "id": "8a1e9305",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(1253, 4)"
      ]
     },
     "execution_count": 76,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_pf.shape #Shape of this data after duplicates drop"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 77,
   "id": "c10a3a6c",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "<ipython-input-77-44cfffebe3e1>:1: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame\n",
      "\n",
      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  df_cs.drop_duplicates(subset = 'selftext',inplace=True)\n"
     ]
    }
   ],
   "source": [
    "df_cs.drop_duplicates(subset = 'selftext',inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 78,
   "id": "ce1fe490",
   "metadata": {
    "scrolled": true
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   "outputs": [
    {
     "data": {
      "text/plain": [
       "(1180, 4)"
      ]
     },
     "execution_count": 78,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_cs.shape #Shape of this data after duplicates drop"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 79,
   "id": "4dc60a07",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "NaN Values in CS Career Questions Subreddit posts\n",
      "title          0\n",
      "selftext       1\n",
      "subreddit      0\n",
      "created_utc    0\n",
      "dtype: int64\n",
      "NaN Values in Personal Finance Subreddit posts\n",
      "title          0\n",
      "selftext       1\n",
      "subreddit      0\n",
      "created_utc    0\n",
      "dtype: int64\n"
     ]
    }
   ],
   "source": [
    "#Show the number of NaN values in the two subreddit dataframes\n",
    "print('NaN Values in CS Career Questions Subreddit posts')\n",
    "print(df_cs.isna().sum()) #We see 1 NaN value to clean in df_cs\n",
    "print('NaN Values in Personal Finance Subreddit posts')\n",
    "print(df_pf.isna().sum()) #We see 1 NaN value to clean in "
   ]
  },
  {
   "cell_type": "markdown",
   "id": "4f663d2d",
   "metadata": {},
   "source": [
    "#### Let's go ahead and drop these NaN values:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 80,
   "id": "466dbf40",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "                                                  title selftext  \\\n",
      "1657  [Google / FB] Recruiter wants me to name comp ...      NaN   \n",
      "\n",
      "              subreddit  created_utc  \n",
      "1657  cscareerquestions   1637190185  \n"
     ]
    }
   ],
   "source": [
    "print(df_cs[df_cs.isna().any(axis=1)]) #The NaN value in this data\n",
    "df_cs = df_cs.dropna()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 81,
   "id": "b7807c91",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "                                                title selftext  \\\n",
      "78  I’m 25 and I have 40k in savings and 23k in IR...      NaN   \n",
      "\n",
      "          subreddit  created_utc  \n",
      "78  personalfinance   1637241680  \n"
     ]
    }
   ],
   "source": [
    "print(df_pf[df_pf.isna().any(axis=1)]) #The NaN value in this data\n",
    "df_pf = df_pf.dropna()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 82,
   "id": "a4d187df",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "NaN Values in CS Career Questions Subreddit posts\n",
      "title          0\n",
      "selftext       0\n",
      "subreddit      0\n",
      "created_utc    0\n",
      "dtype: int64\n",
      "NaN Values in Personal Finance Subreddit posts\n",
      "title          0\n",
      "selftext       0\n",
      "subreddit      0\n",
      "created_utc    0\n",
      "dtype: int64\n"
     ]
    }
   ],
   "source": [
    "print('NaN Values in CS Career Questions Subreddit posts')\n",
    "print(df_cs.isna().sum()) #We see 1 NaN value to clean in df_cs\n",
    "print('NaN Values in Personal Finance Subreddit posts')\n",
    "print(df_pf.isna().sum()) #We see 1 NaN value to clean in "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "52cb6b38",
   "metadata": {
    "scrolled": true
   },
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 83,
   "id": "27f95472",
   "metadata": {
    "scrolled": true
   },
   "outputs": [],
   "source": [
    "# Adding word count and status length for each subreddit data frame\n",
    "def word_counts(df):\n",
    "    df['post_word_count'] = [len(df['selftext'].iloc[i].split(' ')) for i, status in enumerate(df['selftext'])]\n",
    "    df['post_length'] = [len(df['selftext'].iloc[i]) for i, status in enumerate(df['selftext'])]\n",
    "    return df\n",
    "\n",
    "df_cs = word_counts(df_cs)\n",
    "df_pf = word_counts(df_pf)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 84,
   "id": "bdb2e3ab",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
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       "      <td>My company closed out my old 401k and I electe...</td>\n",
       "      <td>personalfinance</td>\n",
       "      <td>1637254286</td>\n",
       "      <td>126</td>\n",
       "      <td>663</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Unemployment Advice</td>\n",
       "      <td>I have been working for my current employers f...</td>\n",
       "      <td>personalfinance</td>\n",
       "      <td>1637254255</td>\n",
       "      <td>692</td>\n",
       "      <td>3762</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Where does the interest in compound interest c...</td>\n",
       "      <td>This may be a stupid question but I feel like ...</td>\n",
       "      <td>personalfinance</td>\n",
       "      <td>1637254028</td>\n",
       "      <td>171</td>\n",
       "      <td>970</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Debt Settlement and Inflation</td>\n",
       "      <td>I see a lot of posts lately on credit card com...</td>\n",
       "      <td>personalfinance</td>\n",
       "      <td>1637254017</td>\n",
       "      <td>49</td>\n",
       "      <td>279</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Taking out money from trad. IRA to put into Ro...</td>\n",
       "      <td>I had a traditional IRA with primerica and I r...</td>\n",
       "      <td>personalfinance</td>\n",
       "      <td>1637253836</td>\n",
       "      <td>201</td>\n",
       "      <td>1015</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                               title  \\\n",
       "0  Accidentally deposited rollover check into my ...   \n",
       "1                                Unemployment Advice   \n",
       "2  Where does the interest in compound interest c...   \n",
       "3                      Debt Settlement and Inflation   \n",
       "4  Taking out money from trad. IRA to put into Ro...   \n",
       "\n",
       "                                            selftext        subreddit  \\\n",
       "0  My company closed out my old 401k and I electe...  personalfinance   \n",
       "1  I have been working for my current employers f...  personalfinance   \n",
       "2  This may be a stupid question but I feel like ...  personalfinance   \n",
       "3  I see a lot of posts lately on credit card com...  personalfinance   \n",
       "4  I had a traditional IRA with primerica and I r...  personalfinance   \n",
       "\n",
       "   created_utc  post_word_count  post_length  \n",
       "0   1637254286              126          663  \n",
       "1   1637254255              692         3762  \n",
       "2   1637254028              171          970  \n",
       "3   1637254017               49          279  \n",
       "4   1637253836              201         1015  "
      ]
     },
     "execution_count": 84,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_cs.head()\n",
    "df_pf.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 85,
   "id": "c0262513",
   "metadata": {
    "scrolled": true
   },
   "outputs": [],
   "source": [
    "# Function for plotting the distributions of word count and post lengths\n",
    "def plot_length_distributions(df):\n",
    "    plt.tight_layout()\n",
    "    plt.figure(figsize = (8,5));\n",
    "    df['post_word_count'].hist()\n",
    "    plt.title('Distribution of Posts by Word Count',fontsize = 20)\n",
    "    plt.xlabel('Word Count',fontsize = 18);\n",
    "    plt.ylabel('Frequency',fontsize=18);\n",
    "\n",
    "    plt.figure(figsize = (8,5));\n",
    "    df['post_length'].hist()\n",
    "    plt.title('Distribution of Posts by Character Length',fontsize = 20)\n",
    "    plt.xlabel('Character Length',fontsize = 18);\n",
    "    plt.ylabel('Frequency',fontsize=18);\n",
    "\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "41fb31e4",
   "metadata": {},
   "source": [
    "## Word Count and Post Length for r/CSCareerQuestions"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 86,
   "id": "f77ca1ae",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Figure size 432x288 with 0 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 576x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 576x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plot_length_distributions(df_cs);"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "1f4a8085",
   "metadata": {},
   "source": [
    "## Word Count and Post Length for r/personalfinance"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 87,
   "id": "41ad213b",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Figure size 432x288 with 0 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 576x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 576x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plot_length_distributions(df_pf)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f1b4d0e8",
   "metadata": {},
   "source": [
    "### Now let's begin the analysis of the actual texts themselves. To do this, we will have to first vectorize the texts (create numerical features) and make a dataframe of these vectors  "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 88,
   "id": "29dd9a5b",
   "metadata": {
    "scrolled": true
   },
   "outputs": [],
   "source": [
    "# Count vectorizer generator function for definining \n",
    "# single words, bigrams, and trigrams\n",
    "def cvec_generator(df,ngrams = 1):\n",
    "    \n",
    "    cvec = CountVectorizer(stop_words = 'english',ngram_range = (ngrams,ngrams))\n",
    "    print(cvec)\n",
    "    X = df['selftext']\n",
    "    cvec.fit(X)\n",
    "    X_cvec = cvec.transform(X)\n",
    "    X_cvec.shape\n",
    "\n",
    "    X_cvec_df = pd.DataFrame(X_cvec.todense(), \n",
    "                              columns=cvec.get_feature_names())\n",
    "    return X_cvec_df\n",
    "\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 89,
   "id": "f6816388",
   "metadata": {
    "scrolled": true
   },
   "outputs": [],
   "source": [
    "# Function for plotting the top 15 most common words/bigrams/trigrams\n",
    "def word_plots(df,cs_or_pf,n_gram_length):\n",
    "    subreddit_dic = {'cs':'r/CSCareerQuestions','pf':'r/PersonalFinance'}\n",
    "    subr = subreddit_dic[cs_or_pf]\n",
    "    \n",
    "    ngram_dict = {1:'Words',2:'Bigrams',3:'Trigrams'}\n",
    "    ngrm = ngram_dict[n_gram_length]\n",
    "    plt.tight_layout()\n",
    "    plt.figure(figsize=(10,5))\n",
    "    df.sum().sort_values(ascending=False).head(15).sort_values().plot(kind = 'barh')\n",
    "    plt.title(f'Top 15 Most Common {ngrm} for {subr}');\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 90,
   "id": "82c89cfa",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "CountVectorizer(stop_words='english')\n",
      "CountVectorizer(stop_words='english')\n",
      "CountVectorizer(ngram_range=(2, 2), stop_words='english')\n",
      "CountVectorizer(ngram_range=(2, 2), stop_words='english')\n",
      "CountVectorizer(ngram_range=(3, 3), stop_words='english')\n",
      "CountVectorizer(ngram_range=(3, 3), stop_words='english')\n"
     ]
    }
   ],
   "source": [
    "#Count vectorizers using the cvec_generator function\n",
    "X_cvec_cs = cvec_generator(df_cs)\n",
    "X_cvec_pf = cvec_generator(df_pf)\n",
    "X_cvec_cs_bi = cvec_generator(df_cs,ngrams = 2)\n",
    "X_cvec_pf_bi = cvec_generator(df_pf,ngrams = 2)\n",
    "X_cvec_cs_tri = cvec_generator(df_cs,ngrams = 3)\n",
    "X_cvec_pf_tri = cvec_generator(df_pf,ngrams = 3)\n",
    "X_cvecs = ['X_cvec_cs','X_cvec_pf','X_cvec_cs_bi','X_cvec_pf_bi','X_cvec_cs_tri','X_cvec_pf_tri']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 91,
   "id": "35d2d34f",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Figure size 432x288 with 0 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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wKMnjxxlfkiRJU9iUSpCr6jLgPcBZSS4BPjRG0wOBV7Y2lwHPaeVvAF6T5EJg5hjnngFsP9qL9IDPAL8G5re+X9QS308DC4BvARcu5RJeDnysvUjv9qW0kyRJ0hSVKp/hH6R1N9+2Nn/ZhwcdhiRJ0kAN4pP0ksytqqGR5VNtD/IaZ8ctZzI8hT5aUZIkaU03pbZYSJIkSYNmgixJkiT1mCBLkiRJPSbIkiRJUo8JsiRJktRjgixJkiT1mCBLkiRJPSbIkiRJUo8JsiRJktTjJ+kN2IKrFzHr0JMHHYYkSVqKQXwMsgbHFWRJkiSpZ41OkJPMSvKi3uODkhw9gfM+k2T7lRudJEmSBmG1T5DTGes6ZwEvGqNuTFX1qqr68ShjzVjWviRJkjS1rJYJclsZ/kmSjwMXAQ9N8oEklyZZkGT/1vRIYM8k85L8cyvbIskpSa5I8v4x+j8zyVA7vjXJEUnOB3ZPcliSC9tYc5JkZV+vJEmSVpzVMkFuHgF8oap2BoaA2cCjgb2BDyTZHDgUOKeqZlfVf7bzZgP7AzsC+yd56DjjbAhcWlWPrapzgaOrateqehSwPvDMkSckOTjJcJLhxbctWu4LlSRJ0oqzOifIv6qqH7XjxwNfqarFVXUtcBaw6xjnnV5Vi6rqT8CPga3GGWcx8M3e4ycmOT/JAuBJwA4jT6iqOVU1VFVDMzaYuSzXJEmSpJVsdX6btz/2jpdlm8MdvePFjD9Hf6qqxQBJ1gM+DgxV1W+SHA6stwxjS5IkacBW5xXkvrPptkvMSLIZ8ATgAuAWYOMVOM6SZPi6JBsB+63AviVJkrQKrM4ryH0nALsDlwAF/GtV/S7J9cBdSS4BjgFuXJ5BquqmJJ8GFgALgQuXpz9JkiSteqmqQcewRhsaGqrh4eFBhyFJkrTGSTK3qoZGlq8pWywkSZKkCTFBliRJknpMkCVJkqQeE2RJkiSpxwRZkiRJ6jFBliRJknpMkCVJkqQeE2RJkiSpxwRZkiRJ6llTPmp6ylpw9SJmHXryoMOQJGlUC4/cZ9AhSKucK8iSJElSzxqfICd5aJIzkvwkyWVJ3tCr2zTJd5Nc0b4/oFf3b0l+nuTyJH/XK791VV+DJEmSVpw1PkEG7gLeVFWPBP4GeE2S7VvdocDpVbUtcHp7TKs/ANgBeBrw8SQzVnnkkiRJWuGmTIKc5FtJ5rZV3IN75bcmOarVfS/JbknOTHJlkme3Ngcl+XaSU9qK7jtG6X+rthL8oCRrJTknyVOr6rdVdRFAVd0C/ATYsp32HODz7fjzwL698q9W1R1V9Uvg58BuvbH+I8lFSU5PstkKnShJkiStVFMmQQZeUVW7AEPA65M8sJVvCJzZ6m4B3g08BXgucETv/N2AA4HZwAuSDPU7r6pfAUcBnwTeBPy4qk7rt0kyC9gZOL8VPbiqftvO/y3wF618S+A3vVOv4p6kekPgoqp6DHAWMFqyfnCS4STDi29bNM60SJIkaVWaSgny65NcAvwIeCiwbSv/M3BKO14AnFVVd7bjWb3zv1tV11fV7cDxwONHDlBVnwE2Bg4B3tyvS7IR8E3gjVV18zixZpSyat/vBo5rx18aI445VTVUVUMzNpg5zlCSJElalaZEgpxkL2BvYPeqejRwMbBeq76zqvrJ5x0AVXU3936buuLeRj4myQbAQ9rDjXrl69Alx8dW1fG9U65Nsnlrsznw+1Z+FV0Sv8RDgGvGuLz7xCFJkqSpa0okyMBM4Maqui3JdnQvlltWT2nvOrE+3V7hH4zS5ijgWOAw4NMASQJ8FvhJVX1oRPsTgZe145cB3+6VH5Bk3SRb0612X9Dq1gL2a8cvAs6dxLVIkiRpQKbKB4WcAhySZD5wOd02i2V1LvBF4K+BL1fVcL8yyd8CuwJ7VNXiJM9P8nLgCuAlwIIk81rzf6+q7wBHAl9L8krg18ALAKrqsiRfA35M9y4Yr6mqxe3cPwI7JJkLLAL2n8S1SJIkaUByz+6F6SvJQcBQVb120LEsq6GhoRoeHh6/oSRJklaoJHOramhk+VTZYiFJkiRNCVNli8VyqapjgGMGHIYkSZJWA64gS5IkST0myJIkSVKPCbIkSZLUY4IsSZIk9ZggS5IkST0myJIkSVKPCbIkSZLUY4IsSZIk9awWHxQynS24ehGzDj150GFIkqa5hUfuM+gQpNXGarWCnOTW9n2LJN9ox7OTPGOwkUmSJGm6mPIJcpJlXuWuqmuqar/2cDawShLkycQqSZKkqWXgCXKSlyaZn+SSJF9sZcck+VCSM4CjkjwsySlJ5iY5J8l2rd3WSc5LcmGSd/X6nJXk0iT3A44A9k8yL8n+I8beIckFrW5+km2XEtNWSU5v5acn+atliVWSJEnTw0BXPJPsALwN2KOqrkuyaa/64cDeVbU4yenAIVV1RZLHAh8HngR8BPhEVX0hyWtG9l9Vf05yGDBUVa8dJYRDgI9U1bEtmZ6xlJiOBr5QVZ9P8grgo8C+yxCrJEmSpoFBbwl4EvCNqroOoKpu6NV9vSWcGwGPA76eZEnduu37HsDz2/EXgaOWcfzzgLcleQhwfEtqx4ppd+B5vbHev4yx/p8kBwMHA8y4/2bLGLIkSZJWpkEnyAFqjLo/tu9rATdV1ewx2o11/riq6stJzgf2AU5N8qpxYhpr3InGumTcOcAcgHU333bS8UuSJGnFG/Qe5NOBFyZ5IMCILRYAVNXNwC+TvKC1SZJHt+ofAAe04wPHGOMWYOPRKpJsA1xZVR8FTgR2WkpMPxwx1rnLGKskSZKmgYEmyFV1GfAe4KwklwAfGqPpgcArW5vLgOe08jcAr0lyITBzjHPPALYf7UV6wP7ApUnmAdvR7TEeK6bXAy9PMh94SRt7WWKVJEnSNJAqn+EfpHU337Y2f9mHBx2GJGma84NCpGWXZG5VDY0sH/Qe5DXejlvOZNh/1CRJkqaMQe9BliRJkqYUE2RJkiSpxwRZkiRJ6jFBliRJknpMkCVJkqQeE2RJkiSpxwRZkiRJ6jFBliRJknpMkCVJkqQeP0lvwBZcvYhZh5486DAkrab8+GFJWnauIEuSJEk9qzRBTvLGJBtM4rxbl2PMg5JsMUbdMUn2m2zfkiRJWv2s6hXkNwLLnCAvp4OAURNkSZIkaaSVkiAn2TDJyUkuSXJpkv2TvJ4uUT0jyRmt3a29c/ZLckw73jrJeUkuTPKuEX2/pZXPT/LOVjYryU+SfDrJZUlOS7J+Wx0eAo5NMi/J+kuJ+clJLk6yIMnnkqzbyg9r412aZE6StPIzkxyV5IIkP0uyZyvfoZXNazFuuwKnVpIkSSvZylpBfhpwTVU9uqoeBZxSVR8FrgGeWFVPHOf8jwCfqKpdgd8tKUzyVGBbYDdgNrBLkie06m2Bj1XVDsBNwPOr6hvAMHBgVc2uqttHGyzJesAxwP5VtSPdixf/sVUfXVW7tutYH3hm79S1q2o3upXxd7SyQ4CPVNVsuuT8qlHGOzjJcJLhxbctGmcqJEmStCqtrAR5AbB3W2Hds6qWNQvcA/hKO/5ir/yp7eti4CJgO7rEGOCXVTWvHc8FZi3DeI9o5/+sPf48sCTxfmKS85MsAJ4E7NA77/hRxjsP+PckbwW2Gi0pr6o5VTVUVUMzNpi5DGFKkiRpZVspCXJLNHehS5Tfl+SwsZr2jtdbSt0SAd7XVoNnV9VfV9VnW90dvXaLWba3sMuohd3K8seB/drK8qdHxLlkzP8br6q+DDwbuB04NcmTliEOSZIkDdjK2oO8BXBbVX0J+CDwmFZ1C7Bxr+m1SR6ZZC3gub3yHwAHtOMDe+WnAq9IslEbZ8skfzFOOCPHHM1PgVlJ/ro9fglwFvckw9e1Mcd9x4sk2wBXti0lJwI7jXeOJEmSpo6V9UEhOwIfSHI3cCf37OedA/xvkt+2fciHAicBvwEuBTZq7d4AfDnJG4BvLum0qk5L8kjgvPZauVuBF9Ot4I7lGOCTSW4Hdh9jy8Ofkrwc+HqStYELgU9W1R1JPk23Er6wlY9nf+DFSe6k2z99xATOkSRJ0hSRqtF2MmhVGRoaquHh4UGHIUmStMZJMreqhkaW+0l6kiRJUo8JsiRJktRjgixJkiT1mCBLkiRJPSbIkiRJUo8JsiRJktRjgixJkiT1mCBLkiRJPSbIkiRJUs/K+qhpTdCCqxcx69CTBx2GpGlu4ZH7DDoESVptuIIsSZIk9UzrBDnJ4UnePOg4RpNk3yTbDzoOSZIkLZtpnSBPcfsCJsiSJEnTzLRLkJO8LcnlSb4HPKJXPjvJj5LMT3JCkge08jOTHJXkgiQ/S7LnKH1+PMmz2/EJST7Xjl+Z5N3t+FtJ5ia5LMnBvXNvTfKeJJe08R+c5HHAs4EPJJmX5GErdVIkSZK0wkyrBDnJLsABwM7A84Bde9VfAN5aVTsBC4B39OrWrqrdgDeOKF/ibGBJ4rwl96z8Ph44px2/oqp2AYaA1yd5YCvfEPhRVT269fPqqvohcCLwlqqaXVW/GHEdBycZTjK8+LZFyzQHkiRJWrmmVYJMl8SeUFW3VdXNdEkoSWYCm1TVWa3d54En9M47vn2fC8wapd9zgD3bnuEfA9cm2RzYHfhha/P6JJcAPwIeCmzbyv8MnDRO//dSVXOqaqiqhmZsMHO85pIkSVqFpuPbvNUkzrmjfV/MKNdcVVe3LRlPo1sF3hR4IXBrVd2SZC9gb2D3qrotyZnAeu30O6tqSUyj9i9JkqTpY7qtIJ8NPDfJ+kk2Bp4FUFWLgBt7+4tfApw1Rh9jOY9uC8bZdCvKb+ae7RUzgRtbcrwd8DcT6O8WYONljEGSJEkDNq0S5Kq6CDgOmAd8k3sSWICX0b0obj4wGzhiGbs/h26v8s+Bi+hWkZf0fwqwduv7XXTbLMbzVeAtSS72RXqSJEnTR+7ZHaBBGBoaquHh4UGHIUmStMZJMreqhkaWT6sVZEmSJGllM0GWJEmSekyQJUmSpB4TZEmSJKnHBFmSJEnqMUGWJEmSekyQJUmSpB4TZEmSJKnHBFmSJEnqMUGWJEmSetYedABrugVXL2LWoScPOgxJA7bwyH0GHYIkqXEFWZIkSeqZlglyksOTvHkF9LNXkpNWREySJElaPUzLBFmSJElaWaZNgpzkbUkuT/I94BG98tlJfpRkfpITkjyglZ+Z5KgkFyT5WZI9x+l/1yQXJ9mmrVB/rvVxZZLX99r9S5JL29cbW9m/LmmT5D+TfL8dPznJl1b8bEiSJGllmRYJcpJdgAOAnYHnAbv2qr8AvLWqdgIWAO/o1a1dVbsBbxxRPrL/xwGfBJ5TVVe24u2AvwN2A96RZJ0Wx8uBxwJ/A7w6yc7A2cCSBHwI2CjJOsDjgXNGGe/gJMNJhhfftmjiEyFJkqSVblokyHTJ5wlVdVtV3QycCJBkJrBJVZ3V2n0eeELvvOPb97nArDH6fiQwB3hWVf26V35yVd1RVdcBvwceTJfwnlBVf6yqW1v/e7b+d0myMXAHcB5dorwnoyTIVTWnqoaqamjGBjOXZR4kSZK0kk2XBBmgJnHOHe37YsZ+S7vfAn+iW50e7dz++Rk1sKo7gYV0q8s/pEuKnwg8DPjJJOKWJEnSgEyXBPls4LlJ1m+rtM8CqKpFwI29/cUvAc4ao4+x3ATsA7w3yV4TiGPfJBsk2RB4LvesEJ8NvLl9Pwc4BJhXVZNJ7CVJkjQg0+KDQqrqoiTHAfOAX3HvbQsvAz6ZZAPgSrpV3GXt/9okzwL+N8krxonjGOCCVvSZqrq4HZ8DvA04r6r+mORPjLK9QpIkSVNbXOAcrKGhoRoeHh50GJIkSWucJHOramhk+XTZYiFJkiStEibIkiRJUo8JsiRJktRjgixJkiT1mCBLkiRJPSbIkiRJUo8JsiRJktRjgixJkiT1mCBLkiRJPdPio6ZXZwuuXsSsQ08edBiSlmLhkfsMOgRJ0irkCrIkSZLUs9okyElubd+3SPKNdjw7yTNWwdizkly6sseRJEnSyjelE+Qky7wFpKquqar92sPZwApPkCcTlyRJkqaHgSbISV6aZH6SS5J8sZUdk+RDSc4AjkrysCSnJJmb5Jwk27V2Wyc5L8mFSd7V63NWkkuT3A84Atg/ybwk+48Ye0aSDyZZ0GJ4XSs/rPV5aZI5SdLKz0zy3iRnAW9IskuL+zzgNb1+d0hyQRtzfpJtV/I0SpIkaQUa2Epokh2AtwF7VNV1STbtVT8c2LuqFic5HTikqq5I8ljg48CTgI8An6iqLyR5zcj+q+rPSQ4DhqrqtaOEcDCwNbBzVd3VG//oqjqixfhF4JnA/7S6Tarqb1vdfOB1VXVWkg/0+j0E+EhVHduS9BmjXPvBbXxm3H+z8SdLkiRJq8wgV5CfBHyjqq4DqKobenVfb8nxRsDjgK8nmQd8Cti8tdkD+Eo7/uIkxt8b+GRV3TVi/CcmOT/JghbjDr1zjgNIMpMuWT5rlPHPA/49yVuBrarq9pEDV9WcqhqqqqEZG8ycROiSJElaWQa5lzZAjVH3x/Z9LeCmqpo9Rruxzp/U+EnWo1uhHqqq3yQ5HFhvlLjGjL2qvpzkfGAf4NQkr6qq7y9HnJIkSVqFBrmCfDrwwiQPBBixxQKAqroZ+GWSF7Q2SfLoVv0D4IB2fOAYY9wCbDxG3WnAIUtecNfGX5IMX9dWr/cb7cSquglYlOTxI8dPsg1wZVV9FDgR2GmM8SVJkjQFDSxBrqrLgPcAZyW5BPjQGE0PBF7Z2lwGPKeVvwF4TZILgbH2KZwBbD/ai/SAzwC/Bua3vl/UEt9PAwuAbwEXLuUSXg58rL1Ir7+NYn/g0rYlZDvgC0vpQ5IkSVNMqpZnl4KW19DQUA0PDw86DEmSpDVOkrlVNTSyfEq/D7IkSZK0qpkgS5IkST0myJIkSVKPCbIkSZLUY4IsSZIk9ZggS5IkST0myJIkSVKPCbIkSZLUY4IsSZIk9aw96ADWdAuuXsSsQ08edBiSehYeuc+gQ5AkDZAryJIkSVLPKkuQk3wmyfararxBS/Lvg45BkiRJy26VJchV9aqq+vGqGm8KMEGWJEmahsZNkJNsmOTkJJckuTTJ/q38sCQXtrI56TwyyQW9c2clmd+Oz0wy1I5vTfKe1uePkjy4lT+sPb4wyRFJbm3lmyc5O8m8Nt6eo8R5n3ha+V8n+V4b66IkD2vl/5pkQSs/spXNbuPPT3JCkgeMEvuDkixsxwclOT7JKUmuSPL+Vn4ksH6L99jJ/WgkSZI0CBNZQX4acE1VPbqqHgWc0sqPrqpdW9n6wDOr6ifA/ZJs09rsD3xtlD43BH5UVY8GzgZe3co/AnykqnYFrum1fxFwalXNBh4NzBulz/vE08qPBT7Wxnoc8NskTwf2BR7byt/f2n4BeGtV7QQsAN4x/vQwu13njsD+SR5aVYcCt1fV7Ko6cOQJSQ5OMpxkePFtiyYwhCRJklaViSTIC4C9kxyVZM+qWpLRPTHJ+UkWAE8CdmjlXwNe2I73B44bpc8/Aye147nArHa8O/D1dvzlXvsLgZcnORzYsapuGaXP+8STZGNgy6o6AaCq/lRVtwF7A//djqmqG5LMBDapqrNaf58HnrDUmemcXlWLqupPwI+BrcY7oarmVNVQVQ3N2GDmBIaQJEnSqjJuglxVPwN2oUuU39e2MqwHfBzYr6p2BD4NrNdOOQ54YZKHd6fXFaN0e2dVVTtezDhvN1dVZ9Mlq1cDX0zy0n79UuLJGF0GqDHqRnMX98zVeiPq7ugdj3stkiRJmtomsgd5C+C2qvoS8EHgMdyTJF6XZCNgvyXtq+oXdIni/2P01eOl+RHw/HZ8QC+GrYDfV9Wngc+2GPpGjaeqbgauSrJv62fdJBsApwGvaMck2bStjN/Y29/8EmDJavJCuj8S6F/rOO5Mss4E20qSJGmKmMhq547AB5LcDdwJ/GNV3ZTk03SrygvptkD0HQd8ANh6GeN5I/ClJG8CTgaWbOfYC3hLkjuBW4F7rSCPE89LgE8lOaLF/4KqOiXJbGA4yZ+B79C968TLgE+2xPlK4OWtjw8CX0vyEuD7E7yWOcD8JBeNtg9ZkiRJU1Pu2ekweC0xvb2qKskBwN9X1XMGHdfKtO7m29bmL/vwoMOQ1OMn6UnSmiHJ3KoaGlk+1fbL7gIc3d6i7SbgFYMNZ+XbccuZDPufsSRJ0pQxpRLkqjqH7m3cJEmSpIFYZZ+kJ0mSJE0HJsiSJElSjwmyJEmS1GOCLEmSJPWYIEuSJEk9JsiSJElSjwmyJEmS1GOCLEmSJPVMqQ8KWRMtuHoRsw49edBhSGskP1JakjQaV5AlSZKkHhPkniR7Jrksybwk66+A/hYmedCKiE2SJEmrxsAT5CQzBh1Dz4HAB6tqdlXdPuhgJEmStOqNmyAneXGSC9qq6qeWJLRJbk1yVJK5Sb6XZLckZya5MsmzW5sZST6Q5MIk85P8QyvfK8kZSb4MLEiyVpKPt9Xbk5J8J8l+re0uSc5q45yaZPNWfmYb/4IkP0uyZ2/MDyZZ0MZ8XZInJzmhd01PSXL8iOt8FfBC4LAkx7YYT+rVH53koHa8MMk7k1zUxtmulT8wyWlJLk7yKSCT/slIkiRpIJaaICd5JLA/sEdVzQYW062yAmwInFlVuwC3AO8GngI8FziitXklsKiqdgV2BV6dZOtWtxvwtqraHngeMAvYEXgVsHsbfx3gv4D92jifA97TC3HtqtoNeCPwjlZ2MLA1sHNV7QQcC3wfeGSSzVqblwP/3b/WqvoMcCLwlqo6kPFdV1WPAT4BvLmVvQM4t6p2bn391WgnJjk4yXCS4cW3LZrAUJIkSVpVxnsXiycDuwAXJgFYH/h9q/szcEo7XgDcUVV3JllAl+wCPBXYaclqMDAT2Lade0FV/bKVPx74elXdDfwuyRmt/BHAo4DvtvFnAL/txbdkFXhub8y9gU9W1V0AVXUDQJIvAi9O8t90CfhLx7n28fTHfl47fsKS46o6OcmNo51YVXOAOQDrbr5tLWcckiRJWoHGS5ADfL6q/m2UujuraklydzdwB0BV3Z1k7d75r6uqU+/VabIX8McR44w1/mVVtfsY9Xe074u551oCjJZ0/jfwP8Cf6JLxu8boc4m7uPcK+3oTGJsxxpYkSdI0Md4e5NOB/ZL8BUCSTZNstQz9nwr8Y9sqQZKHJ9lwlHbnAs9ve5EfDOzVyi8HNkvyf1sukuwwzpinAYcsSdKTbApQVdcA1wBvB46ZQOy/ArZPsm6SmXSr6eM5m7YFJcnTgQdM4BxJkiRNIUtdQa6qHyd5O3BakrWAO4HX0CWPE/EZuq0PF6XbI/EHYN9R2n2TLgG9FPgZcD7d3uU/t+0ZH21J6trAh4HLxhnz4cD8JHcCnwaObnXHAptV1Y/HC7yqfpPka8B84Arg4vHOAd4JfCXJRcBZwK8ncI4kSZKmkNyzS2KwkmxUVbcmeSBwAd0LA3+3gsc4Gri4qj67IvtdHkNDQzU8PDzoMCRJktY4SeZW1dDI8qn0UdMnJdkEuB/wrpWQHM+l2/f8phXZryRJklYvUyZBrqq9VnL/u6zM/iVJkrR6GPgn6UmSJElTiQmyJEmS1GOCLEmSJPWYIEuSJEk9JsiSJElSjwmyJEmS1GOCLEmSJPVMmfdBXlMtuHoRsw49edBhSFPOwiP3GXQIkqQ1lCvIkiRJUs9qlSAneX2SnyQ5dhLnzkpy6dLKkwwl+Wg7PjzJm5c/akmSJE0lq9sWi38Cnl5Vv1wZnVfVMDC8MvqWJEnS1LDarCAn+SSwDXBikn9OsmGSzyW5MMnFSZ7T2s1I8oFWPj/JPyzDGHslOWmU8lcn+d8k6yd5cZILksxL8qkkM1bcVUqSJGllW20S5Ko6BLgGeGJV/SfwNuD7VbUr8ETgA0k2BF4JLGrluwKvTrL1ZMdN8lrgWcC+wCxgf2CPqpoNLAYOHOWcg5MMJxlefNuiyQ4tSZKklWB122LR91Tg2b19wusBf9XKd0qyXyufCWwL/GwSY7wEuArYt6ruTPJkYBfgwiQA6wO/H3lSVc0B5gCsu/m2NYlxJUmStJKszglygOdX1eX3Kuwy19dV1akjymdNYoxLgdnAQ4BftjE/X1X/NpmAJUmSNHirzRaLUZwKvK4lxCTZuVf+j0nWaeUPb1svJuNi4B/o9j1vAZwO7JfkL1rfmybZankuQpIkSavW6pwgvwtYB5jf3qbtXa38M8CPgYta+adYjpX0qjoXeDNwMt12ircDpyWZD3wX2HzSVyBJkqRVLlVugR2koaGhGh72neMkSZJWtSRzq2poZPnqvIIsSZIkLTMTZEmSJKnHBFmSJEnqMUGWJEmSekyQJUmSpB4TZEmSJKnHBFmSJEnqMUGWJEmSekyQJUmSpJ5Jf8SyVowFVy9i1qEnDzoMaWAWHrnPoEOQJOleXEGWJEmSekyQJUmSpB4TZEmSJKlnWiXISb6VZG6Sy5Ic3Cu/NclRre57SXZLcmaSK5M8u7U5KMm3k5yS5PIk7xhjjE8kGW5jvLNXvjDJe5Oc1+ofk+TUJL9Ickhrs1eSs5OckOTHST6ZZFrNsSRJ0ppuuiVvr6iqXYAh4PVJHtjKNwTObHW3AO8GngI8Fziid/5uwIHAbOAFSYZGGeNtVTUE7AT8bZKdenW/qardgXOAY4D9gL8ZZYw3ATsCDwOeN+mrlSRJ0io33RLk1ye5BPgR8FBg21b+Z+CUdrwAOKuq7mzHs3rnf7eqrq+q24HjgcePMsYLk1wEXAzsAGzfqzuxN8b5VXVLVf0B+FOSTVrdBVV1ZVUtBr4y2hhJDm6r0MOLb1u0DJcvSZKklW3avM1bkr2AvYHdq+q2JGcC67XqO6uq2vHdwB0AVXV3kv41Fvd2r8dJtgbeDOxaVTcmOaY3Bkv67Y/Re7xknKWO0eKaA8wBWHfzbe9TL0mSpMGZTivIM4EbW3K8Hd3WhmX1lCSbJlkf2Bf4wYj6+wN/BBYleTDw9EmMsVuSrdve4/2BcyfRhyRJkgZk2qwg022hOCTJfOByum0Wy+pc4IvAXwNfrqrhfmVVXZLkYuAy4Erum0BPxHnAkXR7kM8GTphEH5IkSRqQaZMgV9UdjLGiW1Ub9Y4PH6sO+H1VvXaccQ4ao3xW7/gYuhfp3asuCcBtVbX/0saQJEnS1DVtEuTV1Y5bzmTYj9qVJEmaMtaYBHnkqu9KGuNM4MyVOYYkSZJWrun0Ij1JkiRppTNBliRJknpMkCVJkqQeE2RJkiSpxwRZkiRJ6jFBliRJknpMkCVJkqQeE2RJkiSpZ435oJCpasHVi5h16MmDDkMamIV+kqQkaYpxBVmSJEnqmTYJcpJbV3L/s5M8Y2WOIUmSpKlv2iTIq8BsYJkS5CRuUZEkSVrNTLsEL0mA9wNPBwp4d1Udl2Qv4HDgOuBRwFzgxVVVbWX4Q63uImCbqnpmr8/7AUcA6yd5PPA+4CTgv4Ad6ebp8Kr6dpKDgH2A9YANk3wB2BeY0cb9D+B+wEuAO4BnVNUNK2k6JEmStIJNuwQZeB7dau+jgQcBFyY5u9XtDOwAXAP8ANgjyTDwKeAJVfXLJF8Z2WFV/TnJYcBQVb0WIMl7ge9X1SuSbAJckOR77ZTdgZ2q6oaWMD+qjb0e8HPgrVW1c5L/BF4KfLg/XpKDgYMBZtx/s+WfEUmSJK0w03GLxeOBr1TV4qq6FjgL2LXVXVBVV1XV3cA8YBawHXBlVf2ytblPgjyGpwKHJpkHnEmX/P5Vq/vuiFXhM6rqlqr6A7AI+J9WvqDFcC9VNaeqhqpqaMYGMycYjiRJklaF6biCnKXU3dE7Xkx3fUtrP944z6+qy+9VmDwW+ONSxr279/hupuccS5IkrbGm4wry2cD+SWYk2Qx4AnDBUtr/FNgmyaz2eP8x2t0CbNx7fCrwurbnmSQ7L1fUkiRJmhamY4J8AjAfuAT4PvCvVfW7sRpX1e3APwGnJDkXuJZuG8RIZwDbJ5mXZH/gXcA6wPwkl7bHkiRJWs2lqgYdw0qXZKOqurWtBn8MuKKq/nPQcQEMDQ3V8PDwoMOQJEla4ySZW1VDI8un4wryZLy6vdjuMmAm3btaSJIkSfexRryArK0WT4kVY0mSJE1ta8oKsiRJkjQhJsiSJElSjwmyJEmS1GOCLEmSJPWYIEuSJEk9JsiSJElSjwmyJEmS1LNGvA/yVLbg6kXMOvTkQYeh1dTCI/cZdAiSJE07riBLkiRJPSbIkiRJUs8amyAnmTHoGCRJkjT1TPkEOcm7kryh9/g9SV7fjt+S5MIk85O8s9fmW0nmJrksycG98luTHJHkfGD3JEcm+XE7/4OjjL1bkh8mubh9f0Qr3yDJ19p5xyU5P8lQq/v7JAuSXJrkqJU4NZIkSVoJpsOL9D4LHA98JMlawAHAbkmeCmwL7AYEODHJE6rqbOAVVXVDkvWBC5N8s6quBzYELq2qw5Js2vrerqoqySajjP1T4AlVdVeSvYH3As8H/gm4sap2SvIoYB5Aki2Ao4BdgBuB05LsW1Xf6nfakvaDAWbcf7MVNE2SJElaEaZ8glxVC5Ncn2Rn4MHAxVV1fUuQnwpc3JpuRJcwnw28PslzW/lDW/n1wGLgm638ZuBPwGeSnAycNMrwM4HPJ9kWKGCdVv544CMtvkuTzG/luwJnVtUfAJIcCzwB+NaIa5oDzAFYd/Nta5knRZIkSSvNlE+Qm88ABwF/CXyulQV4X1V9qt8wyV7A3sDuVXVbkjOB9Vr1n6pqMUBbFd4NeDLdqvRrgSeNGPddwBlV9dwks4Aze2OPZqxySZIkTRNTfg9ycwLwNLoV2lNb2anAK5JsBJBkyyR/Qbfqe2NLjrcD/ma0Dtt5M6vqO8AbgdmjNJsJXN2OD+qVnwu8sPWzPbBjKz8f+NskD2ovAvx74KxlvVhJkiQNzrRYQa6qPyc5A7iptwJ8WpJHAuclAbgVeDFwCnBI2/ZwOfCjMbrdGPh2kvXoVn7/eZQ276fbYvEvwPd75R9v5fPptnjMBxZV1W+T/BtwRuvzO1X17eW5dkmSJK1aqZr6W2Dbi/MuAl5QVVdMgXhmAOtU1Z+SPAw4HXh4Vf15WfsaGhqq4eHhFR6jJEmSli7J3KoaGlk+5VeQ2xaGk4ATpkJy3GwAnJFkHbqV4n+cTHIsSZKkqWfKJ8hV9WNgm0HH0VdVtwD3+WtDkiRJ0990eZGeJEmStEqYIEuSJEk9JsiSJElSjwmyJEmS1GOCLEmSJPWYIEuSJEk9JsiSJElSjwmyJEmS1DPlPyhkdbfg6kXMOvTkQYeh1cTCI/cZdAiSJE17E15BTrJJkn/qPd4ryUkrIogkByU5ekX0NUb/hyd588rqX5IkSauPZdlisQnwT+M1kiRJkqazZUmQjwQelmRekg+0so2SfCPJT5McmyQASQ5LcmGSS5PM6ZWfmeSoJBck+VmSPUcOkmSfJOcleVCSF7Q+Lkly9ihtN0pyepKLkixI8pxe3duSXJ7ke8AjWtkjk1zQazMryfzJxJxkRpIPtnHnJ3ldK98lyVlJ5iY5NcnmyzDHkiRJGrBlSZAPBX5RVbOr6i2tbGfgjcD2wDbAHq386KrataoeBawPPLPXz9pVtVs77x39AZI8t43zjKq6DjgM+LuqejTw7FFi+hPw3Kp6DPBE4D/S2QU4oMX3PGBXgKr6CXC/JNu08/cHvjbJmA8GtgZ2rqqdgGOTrAP8F7BfVe0CfA54z6izKUmSpClped/F4oKquqqq7gbmAbNa+ROTnJ9kAfAkYIfeOce373N77aFLcN8K7FNVN7ayHwDHJHk1MGOU8QO8t60Cfw/YEngwsCdwQlXdVlU3Ayf2zvka8MJ2vD9w3CRj3hv4ZFXdBVBVN9CtVD8K+G6SecDbgYfcJ+jk4CTDSYYX37ZolMuSJEnSoCzvu1jc0TteDKydZD3g48BQVf0myeHAeqOcs3jE+FfSrUI/HBgGqKpDkjwW2AeYl2R2VV3fO+dAYDNgl6q6M8nC3lg1RszHAV9Pcnw3RF0xyZgzyhgBLquq3ccYm3Zdc4A5AOtuvu1YcUqSJGkAlmUF+RZg4wm0W5JYXpdkI2C/Cfb/K7rtEF9IsgNAkodV1flVdRhwHfDQEefMBH7fkuMnAlu18rOB5yZZP8nGwLOWnFBVv6BLdP8f96weTybm04BDkqzdYt0UuBzYLMnurWydJdciSZKk6WHCK8hVdX2SHyS5FPhfYNQ3762qm5J8GlgALAQuXIYxLk9yIN0K77OADyTZlm5l9nTgkhGnHAv8T5Jhui0eP239XJTkuFb2K+CcEecdB3yAbg/xZGP+DN1q9/wkdwKfrqqjk+wHfDTJTLr5/TBw2UTnQJIkSYOVKp/hH6R1N9+2Nn/ZhwcdhlYTflCIJEkTl2RuVQ2NLPeT9AZsxy1nMmxSI0mSNGUs77tYSJIkSasVE2RJkiSpxwRZkiRJ6jFBliRJknp8F4sBS3IL3fsna9k9iO79sbXsnLvJc+4mz7mbHOdt8py7yVtT5m6rqtpsZKHvYjF4l4/29iIaX5Jh525ynLvJc+4mz7mbHOdt8py7yVvT584tFpIkSVKPCbIkSZLUY4I8eHMGHcA05txNnnM3ec7d5Dl3k+O8TZ5zN3lr9Nz5Ij1JkiSpxxVkSZIkqccEWZIkSeoxQR6gJE9LcnmSnyc5dNDxTFVJHprkjCQ/SXJZkje08sOTXJ1kXvt6xqBjnYqSLEyyoM3RcCvbNMl3k1zRvj9g0HFONUke0bu35iW5Ockbve9Gl+RzSX6f5NJe2Zj3WZJ/a//2XZ7k7wYT9dQwxtx9IMlPk8xPckKSTVr5rCS39+6/Tw4s8ClgjLkb83fU++4eY8zdcb15W5hkXitf4+479yAPSJIZwM+ApwBXARcCf19VPx5oYFNQks2BzavqoiQbA3OBfYEXArdW1QcHGd9Ul2QhMFRV1/XK3g/cUFVHtj/OHlBVbx1UjFNd+329Gngs8HK87+4jyROAW4EvVNWjWtmo91mS7YGvALsBWwDfAx5eVYsHFP5AjTF3TwW+X1V3JTkKoM3dLOCkJe3WdGPM3eGM8jvqfXdvo83diPr/ABZV1RFr4n3nCvLg7Ab8vKqurKo/A18FnjPgmKakqvptVV3Ujm8BfgJsOdiopr3nAJ9vx5+n+4NDY3sy8Iuq+tWgA5mqqups4IYRxWPdZ88BvlpVd1TVL4Gf0/2buEYabe6q6rSquqs9/BHwkFUe2DQwxn03Fu+7nqXNXZLQLUJ9ZZUGNYWYIA/OlsBveo+vwqRvXO2v2J2B81vRa9tTkJ9zm8CYCjgtydwkB7eyB1fVb6H7AwT4i4FFNz0cwL3/o/C+m5ix7jP//Vs2rwD+t/d46yQXJzkryZ6DCmqKG+131Ptu4vYErq2qK3pla9R9Z4I8OBmlzP0uS5FkI+CbwBur6mbgE8DDgNnAb4H/GFx0U9oeVfUY4OnAa9rTapqgJPcDng18vRV53y0///2boCRvA+4Cjm1FvwX+qqp2Bv4F+HKS+w8qvilqrN9R77uJ+3vuvSiwxt13JsiDcxXw0N7jhwDXDCiWKS/JOnTJ8bFVdTxAVV1bVYur6m7g06zBT5UtTVVd077/HjiBbp6ubXu7l+zx/v3gIpzyng5cVFXXgvfdMhrrPvPfvwlI8jLgmcCB1V4w1LYHXN+O5wK/AB4+uCinnqX8jnrfTUCStYHnAcctKVsT7zsT5MG5ENg2ydZtheoA4MQBxzQltb1QnwV+UlUf6pVv3mv2XODSkeeu6ZJs2F7YSJINgafSzdOJwMtas5cB3x5MhNPCvVZSvO+WyVj32YnAAUnWTbI1sC1wwQDim7KSPA14K/DsqrqtV75Ze9EoSbahm7srBxPl1LSU31Hvu4nZG/hpVV21pGBNvO/WHnQAa6r2yuTXAqcCM4DPVdVlAw5rqtoDeAmwYMlbzgD/Dvx9ktl0T5EtBP5hEMFNcQ8GTuj+xmBt4MtVdUqSC4GvJXkl8GvgBQOMccpKsgHdO8307633e9/dV5KvAHsBD0pyFfAO4EhGuc+q6rIkXwN+TLd94DVr6jsJwJhz92/AusB32+/vj6rqEOAJwBFJ7gIWA4dU1URfpLbaGWPu9hrtd9T77t5Gm7uq+iz3fc0FrIH3nW/zJkmSJPW4xUKSJEnqMUGWJEmSekyQJUmSpB4TZEmSJKnHBFmSJEnqMUGWJEmSekyQJUmSpJ7/D2QK2qkXEcDVAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<Figure size 720x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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CtULdbvthSScBqzSJq7vYexOjgLts79DLPt3OZXssMBZg5aGbLs41iYiIiOgT2YNcuQH4oKR1ABq2WABg+xngIUkHlDaStG2pvgk4qBwf0mKOZ4E1WtRdBxzV9Ya7Mn9XMvxkWb1u+okTtp8GZkvauYf5JwEHlf3OQ4HRpfw+YD1JO5S5VypbTrocWMp3Bmbbnt3DuUREREQs05IgA7bvotp3O1HSdOC7LZoeAny8tLkL2KeUHwN8WtIdwJAWfccDWzR7kx5wLvBnYEYZ+0Ml8T0H6ASuBO7o5hQOB35Y3qT3Qos2VwAPlPHOAiZCtT+aKvk+tcw9jVd+QsVTkm4GzgY+Xsp+DeybN+lFRETE8kh2/goeS8fKQzf10EO/19dhRERExDLktfwmPUlTbL/qOx+yBzmWmq03HEJHP/i6yIiIiIiFkS0WERERERE1SZAjIiIiImqSIEdERERE1CRBjoiIiIioSYIcEREREVGTBDkiIiIioiYJckRERERETRLkiIiIiIiaJMgRERERETX5Jr1YajofmU3bCeP6OoyIiFd4Lb/GNiKWTVlBjoiIiIioSYLcDUlHS7pH0sXdtBkl6erXMq6IiIiIWHqyxaJ7nwL2sv1QXwcSEREREa+NrCC3IOls4C3AVZI+J2mkpJsl3VkeN2vSZzdJ08rPnZLWKOX/JekOSTMkndxivrMkdUi6q95G0ixJX5d0S6nfXtK1kv4o6ajSZpSkSZKukHS3pLMlveq1lXRiiWOmpLGSVMonSDqtjHGPpBGSLpf0gKSvljZtku6VdEE5j19IWm1JXOuIiIiI/iQJcgu2jwIeBUbbPg24F9jV9nbAicDXm3Q7Dvi07WHALsALkvYANgVGAsOA4ZJ2bdL3i7bbgW2A3SRtU6t72PYOwGTgfGB/4B3AKbU2I4HPA1sDmwAfaDLHGbZH2N4KWBV4T63un7Z3Bc4GfgV8GtgKOEzSOqXNZsBY29sAz1CtsL+CpCNLIt8xf87sJiFERERE9G9JkHtvCHCZpJnAacCWTdrcBHxX0tHAWrZfAvYoP3cCU4HNqRLmRh+UNLW02xLYolZ3VXnsBG6z/aztvwEvSlqr1N1u+0Hb84FLgJ2bzDFa0m2SOoF3NpxDfY67bD9mey7wILBRqXvY9k3l+KJmc9gea7vddvug1YY0CSEiIiKif8se5N77CjDe9r6S2oAJjQ1sj5E0Dng3cKuk3QEB37D9o1YDS9qYavV5hO2nJJ0PrFJrMrc8vlw77nre9Rq6MZyGOVYBzgTabT8s6aQlPUdERETE8iAryL03BHikHB/WrIGkTWx32j4V6KBaLb4W+JikwaXNhpLe0NB1TeB5YLak9YG9FiG+kZI2LnuPDwRubKjvSoafLLHsvwhzvEnSDuX44CZzRERERCzzsoLce98ELpD0n8DvW7Q5VtJoYD5wN/Bb23MlvR24pbwn7jngw8ATXZ1sT5d0J3AX1ZaGm141cs9uAcZQ7UGeBFxRr7T9tKRzqLZQzALuWIQ57gEOlfQj4AHgrEUYIyIiIqJfk52/ki/rJI0CjrP9nh6aLs4cbcDV5Q1+vdLe3u6Ojo6lFVJERETEYpE0pXxIwitki0VERERERE22WCwHbE+gyZsGl/Acs6g+9i0iIiJiuZYV5IiIiIiImiTIERERERE1SZAjIiIiImqSIEdERERE1CRBjoiIiIioSYIcEREREVGTBDkiIiIioiafgxxLTecjs2k7YVxfhxERLcwas3dfhxAR0S9lBTkiIiIiomapJMiSTpJ0XJPyNkkzy3G7pNPL8ShJOy6NWJYHkmZJWrccHy3pHkkXS3qfpBP6Or6IiIiI5Umvt1hIEiDbLy+JiW13AB3l6SjgOeDmJTH2a0nSINvzX8MpPwXsZfuh8vyq13DuiIiIiOVetyvIZcX3HklnAlOBjST9l6Q7JM2QdHKt7Rcl3Sfpd8BmtfLhkqZLugX4dK18lKSrJbUBRwGfkzRN0i4NMQyW9GNJnWXO/Ur5waVspqRTa+2fk3SqpCmSfidppKQJkh6U9L4m5zhK0iRJV0i6W9LZklYodXtIukXSVEmXSRpcymdJOlHSjcABZVX37hLfz0qbtSVdWcpulbRNKT9J0nm1mI6uxXJlifsuSUc2ifVs4C3AVZI+J+kwSWeUuvMlnS7p5jLu/rXrd0M5h05J+zS8tueU+a6TtGqpe2u5dtNLv01KedPXPiIiImJ50pstFpsBF9rerhxvCowEhgHDJe0qaThwELAd8AFgRK3/j4Gjbe/QbHDbs4CzgdNsD7M9uaHJ/wKzbW9texvg95I2AE4F3lniGCHp/aX96sAE28OBZ4GvAv8G7Auc0uIcRwKfB7YGNgE+ULY0fAnY3fb2VKvd/1nr86LtnW3/DDgB2K7Ed1SpPxm4s5R9Abiw1ndz4N/LvF+WtFIp/1iJux04WtI6DdfqKOBRYLTt05qcx1BgZ+A9wJiuOIF9yzmMBr5T/hoA1Wv5Q9tbAk8D+5Xyi0v5tsCOwGOS9qDJa98YgKQjJXVI6pg/Z3aTECMiIiL6t95ssfiT7VvL8R7l587yfDBV0rQGcIXtOQCSriqPQ4C1bE8s7X8C7LWQMe5OlXwDYPupkphNsP23Ms/FwK7AlcA/gWtK805gru15kjqBthZz3G77wTLWJVRJ5ovAFsBNJZ98HXBLrc+lteMZwMWSriwxUMbYr8T8e0nrlOsBMM72XGCupCeA9YG/UCXF+5Y2G1Fd27/3cH3qrixbYO6WtH4pE/D1cs1eBjYs8wE8ZHtaOZ4CtElaA9jQ9hUl9hfLdWn12k+qB2B7LDAWYOWhm3ohYo+IiIjoF3qTID9fOxbwDds/qjeQdCzQLBlSi/KF0WwMNWtYzLPd1f5lYC6A7ZcltTrfxvFd5rje9sEt+tSvy95UCfr7gP+VtGWLGLvmmVsrmw+sKGkU1S8DO9ieI2kCsEqLuVupj9s1/yHAesDw8ovCrNq4jXGs2iLurvFe9dpHRERELG8W9lMsrgU+VtuLu6GkN1CtIu4radWyAvleANtPA7Ml7Vz6H9Ji3GepVqGbuQ74TNcTSa8HbgN2k7SupEHAwcDEFv17Y6Skjcve4wOBG4FbgZ0kvbXMu5qktzV2LH02sj0eOB5Yi2p1dRLlfEvy+6TtZ7qJYQjwVEmONwfesRjn0zjuEyU5Hg28ubvGJca/dG1ZkbSypNVo/dpHRERELFcWKkG2fR3wU+CWsmXhF8AatqdSbTmYBvwSqO8jPhz4oao36b3QYuhfUyXYr3qTHtUe4terejPedKr9t48B/wOMB6YDU23/amHOpcEtVHt2ZwIPUW0X+RtwGHCJpBlUCfPmTfoOAi4q1+NOqr3UTwMnAe2l7xjg0B5iuIZqJXkG8JUy35JwcYmjgyphv7cXfT5Ctd1jBtUni/xLq9d+CcUYERER0W9owW6Egams7h5n+z19HMpyp7293R0dHT03jIiIiOgDkqbYbm8szzfpRURERETU9PqLQpZXticAE/o4jIiIiIjoJ7KCHBERERFRkwQ5IiIiIqImCXJERERERE0S5IiIiIiImiTIERERERE1SZAjIiIiImqSIEdERERE1CRBjoiIiIioGfBfFBJLT+cjs2k7YVxfhxHRr80as3dfhxAREQ2ygryUSBolacelNPYESa/63vCIiIiIWHxJkJeeUcBSSZD7gqT8tSEiIiIGhCTIgKTjJR1djk+T9Pty/C5JF5XjsyR1SLpL0sm1vrMknSxpqqROSZtLagOOAj4naZqkXRrmO0nSBZKuK/0/IOmbpf81klYq7U6UdIekmZLGSlLDOCuUcb4qaZCkb5X2MyT9R5PzXF3SOEnTy5gH1s5h3XLcLmlCLc6xkq4DLpS0nqRfljnukLTTEnoJIiIiIvqNJMiVSUBXEtsODC5J6s7A5FL+RdvtwDbAbpK2qfV/0vb2wFnAcbZnAWcDp9keZnsyr7YJsDewD3ARMN721sALpRzgDNsjbG8FrAq8p9Z/ReBi4H7bXwI+Dsy2PQIYARwhaeOGOfcEHrW9bRnzml5cm+HAPrY/BHy/nNMIYD/g3F70j4iIiFimJEGuTAGGS1oDmAvcQpUo78KCBPmDkqYCdwJbAlvU+l9eG6etl3P+1vY8oBMYxIJktbM2xmhJt0nqBN5Z5u3yI2Cm7a+V53sAH5U0DbgNWAfYtGHOTmB3SadK2sX27F7EeZXtF8rx7sAZZY6rgDXLNfs/ko4sK+0d8+f0ZviIiIiI/iX7SgHb8yTNAg4HbgZmAKOpVnnvKSuxxwEjbD8l6XxgldoQc8vjfHp/TeeWuV+WNM+2S/nLwIqSVgHOBNptPyzppIY5b6ZKoL9j+0VAwGdtX9vNed4vaTjwbuAbkq6zfQrwEgt+WVqlodvzteMVgB1qCXOzOcYCYwFWHrqpW7WLiIiI6K+ygrzAJKokeBLVqvFRwLSSuK5JlSjOlrQ+sFcvxnsWWKPHVq11JapPShoM7N9Q//+A3wCXlTfQXQt8srZ/+W2SVq93kLQBMMf2RcC3ge1L1SyqrRRQbZ1o5TrgM7Xxhi3kOUVERET0e0mQF5gMDAVusf048GIpw/Z0qq0VdwHnATf1YrxfA/s2e5Neb9h+GjiHalvElcAdTdp8F5gK/IRqP/DdwFRJM6m2YDSuZm8N3F62SHwR+GopPxn4vqTJVKvgrRwNtJc3Ad5N9UtERERExHJFC/6yH7FkrTx0Uw899Ht9HUZEv5YvComI6DuSppQPYXiF7EGOpWbrDYfQkX/8IyIiYhmTLRYRERERETVJkCMiIiIiapIgR0RERETUJEGOiIiIiKhJghwRERERUZMEOSIiIiKiJglyRERERERNEuSIiIiIiJokyBERERERNfkmvVhqOh+ZTdsJ4/o6jIh+LV81HRHR/2QFOSIiIiKiJgnyMkDScy3Kz5e0fzk+V9IW5fgLr2V8EREREcuTJMh9RNIS3d5i+xO27y5PkyBHRERELKIBnSBLOl7S0eX4NEm/L8fvknSRpA9K+m4pO0bSg+V4E0k3Shop6fJSto+kFyS9TtIqXW0b5jtf0ncljQdOLeNcI2mKpMmSNi/tNpZ0i6Q7JH2l1l+SzpB0t6RxwBtqdRMktUsaA6wqaZqki5vEsKekqZKmS7qhlK0t6UpJMyTdKmmbUn6SpAskXSdplqQPSPqmpM4S90pL6KWIiIiI6DcGdIIMTAJ2KcftwOCS9O0MTG6o3wX4u6QNa/VTge1q9TOBEcC/Are1mPNtwO62Pw+MBT5rezhwHHBmafN94CzbI4C/1vruC2wGbA0cAezYOLjtE4AXbA+zfUi9TtJ6wDnAfra3BQ4oVScDd9rehmr1+cJat02AvYF9gIuA8ba3Bl4o5a8g6UhJHZI65s+Z3eISRERERPRfA/1TLKYAwyWtAcylSnjbqZLdo23/VdLgUr8R8FNg11J/ue2XJP1B0tuBkcB3S/0gqgS6mctsz5c0mCrBvUxSV93K5XEnYL9y/BPg1HK8K3CJ7fnAo10r3gvhHcAk2w8B2P5HKd+5az7bv5e0jqQhpe63tudJ6izndU0p7wTaGiewPZYq8WfloZt6IeOLiIiI6HMDOkEuid8s4HDgZmAGMJpq1fSe0uyWUn8fVdL7MWAH4POlfjKwFzAP+B1wPlUieVyLaZ8vjysAT9se1iq8hSzvDbXoryZlXe3mAth+WdI8213lLzPA75+IiIhYPg30LRZQbaM4rjxOBo4CptUSwXr9nVQJ9Fzbs2v1xwK32P4bsA6wOXBXd5PafgZ4SNIB8H/7i7ct1TcBB5Xj+jaJScBBkgZJGlpiaWZei/3BtwC7Sdq4zLl2bdxDStko4MkSX0RERMSAkwS5SoqHUiW4jwMv8srtEZOptldMKlsbHgZurNXfBqxPlWRCtQo9o5Zgd+cQ4OOSplMl1PuU8mOAT0u6AxhSa38F8ADV9oazgIktxh0LzGh8k15J4I8ELi9zXlqqTgLaJc0AxgCH9iL2iIiIiOWSepfHRSy89vZ2d3R09HUYEREREU1JmmK7vbE8K8gRERERETVJkCMiIiIiapIgR0RERETUJEGOiIiIiKhJghwRERERUZMEOSIiIiKiJglyRERERERNEuSIiIiIiJokyBERERERNSv2dQCx/Op8ZDZtJ4zr6zAilrpZY/bu6xAiImIJygpyRERERERNEuQaSc/1wZxrSfrUazznLEnrLkb/YZLevSRjioiIiOgvkiD3vbWAhUqQJQ1aOqH0au4VgWFAEuSIiIhYLiVBbkKVb0maKalT0oGlfJSkCZJ+IeleSRdLUql7dym7UdLpkq5uMu6Wkm6XNE3SDEmbAmOATUrZt3qYe7yknwKdkr4i6Zja2F+TdHTDfKtLGidpehnvwFr1ZyVNLXNsXtqvLenKEtutkrYp5SdJGivpOuBC4BTgwBJzfcyIiIiIZV7epNfcB6hWSbcF1gXukDSp1G0HbAk8CtwE7CSpA/gRsKvthyRd0mLco4Dv275Y0uuAQcAJwFa2hwFI2q+buUeWtg9JagMuB74vaQXgoFJftyfwqO29y9hDanVP2t6+bO84DvgEcDJwp+33S3onVTI8rLQfDuxs+wVJhwHttj/TeIKSjgSOBBi05notLkNERERE/5UV5OZ2Bi6xPd/248BEYESpu932X2y/DEwD2oDNgQdtP1TatEqQbwG+IOm/gTfbfmER5n4IwPYs4O+StgP2oEps/94wViewu6RTJe1ie3at7vLyOKWcQ9fcPynj/x5Yp5ZUX9Ui3lewPdZ2u+32QasN6al5RERERL+TBLk5dVM3t3Y8n2oVvrv2/8f2T4H3AS8A15ZV2oWZ+/mG5+cChwGHA+c1me9+qpXfTuAbkk6sVXedR9c5tJrbLeaOiIiIWC4lQW5uEtUe20GS1gN2BW7vpv29wFvKtgeApvtyJb2FaqX5dOAqYBvgWWCNRZz7CqptFCOAa5vMtwEwx/ZFwLeB7bs5h665Dyl9R1Ftw3imSbvGmCMiIiKWG9mD3NwVwA7AdKoV1ONt/7XrzWyNyr7cTwHXSHqS1gntgcCHJc0D/gqcYvsfkm6SNBP4LXB8b+e2/U9J44Gnbc9vMt/WwLckvQzMAz7Zw3mfBPxY0gxgDnBoi3bjgRMkTQO+YfvSHsaNiIiIWGbIds+tokeSBtt+rnyqxQ+BB2yftpTnXAGYChxg+4GlOdeiaG9vd0dHR1+HEREREdGUpCm22xvLs8ViyTmirKjeBQyh+lSLpUbSFsAfgBv6Y3IcERERsazKFoslpKwWL9UV44b57gbe8lrNFxERETFQZAU5IiIiIqImCXJERERERE0S5IiIiIiImiTIERERERE1SZAjIiIiImqSIEdERERE1CRBjoiIiIioSYIcEREREVGTLwqJpabzkdm0nTCur8OIWOpmjdm7r0OIiIglKCvIERERERE1AyZBltQmaWaLusMkbVB7fqyk1V676PqOpFGSrm5RN0vSuuX45vLYJulDr2WMEREREa+lAZMg9+AwYIPa82OBZTpBljRoSY5ne8dy2AYkQY6IiIjl1kBLkAdJOkfSXZKuk7SqpP2BduBiSdMkHUOVLI+XNB5A0nOSviNpqqQbJK1Xyo+WdLekGZJ+1jiZpN9I2qYc3ynpxHL8FUmfkHSmpPeVsisknVeOPy7pq5KOl3R0KTtN0u/L8bskXdRkvlmSTpR0I3CApD0k3VLivkzS4NJuT0n3lnYfqPVfp1yXOyX9CFCt7rlyOAbYpVyrzy3GaxERERHRLw20BHlT4Ie2twSeBvaz/QugAzjE9jDb3wceBUbbHl36rQ5Mtb09MBH4cik/AdjO9jbAUU3mm0SVTK4JvATsVMp3BiZ31ZeyDYEtuqlvBwZLWqlW38yLtncGfgd8Cdi9xN0B/KekVYBzgPeWsf+l1vfLwI22twOuAt7UZPwTgMnlWp3WWCnpSEkdkjrmz5ndIsSIiIiI/mugJcgP2Z5WjqdQbRfojZeBS8vxRVQJKsAMqpXnD1MlwI0mA7uW9uOoEtzVgDbb95X6XSRtAdwNPC5pKLADcHOJcbikNYC5wC1UifIutE6Qu+J8B1XCfZOkacChwJuBzct1eMC2y/l02bXrue1xwFM9X5pXsj3Wdrvt9kGrDVnY7hERERF9bqB9zNvc2vF8YNVFHMflcW+qpPJ9wP9K2tJ2PVG+gyqhfRC4HlgXOIIq8cX2I5JeD+xJtVq8NvBB4Dnbz0K1bQI4nCphngGMBjYB7mkR2/PlUcD1tg+uV0oaVou/u3OLiIiIGJAG2gpyK88Ca3TzfAVg/3L8IeBGSSsAG9keDxwPrAUMrg9q+5/Aw1RJ761Uq77H8crV31uo3hQ4qUX9pFLWVX8UMK2s/nbnVmAnSW8FkLSapLcB9wIbS9qktKsn0JOAQ0r7vYDXNxm38dpERERELFeSIFfOB84ubzxbFRgL/LbrTXpUq7JbSpoCvBM4BRgEXCSpE7gTOM32003Gngw8bntOOX4jr0yAJwMr2v4DMJVqFbmxfihwi+3HgRdpvb3i/9j+G9Wnc1wiaQZVwry57ReBI4Fx5U16f6p1OxnYVdJUYA/gz02GngG8JGl63qQXERERyyP1vBAZkp6zPbjnllHX3t7ujo6Ovg4jIiIioilJU2y3N5ZnBTkiIiIioiYJci9k9TgiIiJi4EiCHBERERFRkwQ5IiIiIqImCXJERERERE0S5IiIiIiImiTIERERERE1SZAjIiIiImqSIEdERERE1KzY1wHE8qvzkdm0nTCur8OI6NGsMXv3dQgREdGPZAU5IiIiIqJmwCbIkk6SdFxfx9FMf44tIiIiYnk3YBPkiIiIiIhmBlSCLOmLku6T9Dtgs1r5MEm3Spoh6QpJry/lm0i6RtIUSZMlbV7KD5A0U9J0SZOazDNK0kRJP5d0v6Qxkg6RdLukTkmblHbvlXSbpDsl/U7S+k3GOkLSbyWtKunDZYxpkn4kaVCT9mMk3V3O5dulbD1Jv5R0R/nZqZSfJOk8SRMkPSjp6FK+uqRx5fxmSjqwlA8v5zVF0rWShi6BlyUiIiKiXxkwCbKk4cBBwHbAB4ARteoLgf+2vQ3QCXy5lI8FPmt7OHAccGYpPxH4d9vbAu9rMeW2wDHA1sBHgLfZHgmcC3y2tLkReIft7YCfAcc3xPwZ4L3A+4E24EBgJ9vDgPnAIQ3t1wb2BbYs5/LVUvV94DTbI4D9SgxdNgf+HRgJfFnSSsCewKO2t7W9FXBNKf8BsH+5HucBX2s8aUlHSuqQ1DF/zuwWlyYiIiKi/xpIn2KxC3CF7TkAkq4qj0OAtWxPLO0uAC6TNBjYsRx3jbFyebwJOF/Sz4HLW8x3h+3Hyhx/BK4r5Z3A6HL8RuDSshL7OuChWv+PAH8B3m97nqR3AcOBO0o8qwJPNMz5DPAicK6kccDVpXx3YIvaeawpaY1yPM72XGCupCeA9UuM35Z0KnC17cmStgK2Aq4v4wwCHms8adtjqX6xYOWhm7rFtYmIiIjotwZSggywMAnbCsDTZbX2lYPYR0n6V2BvYJqkYbb/3tBsbu345drzl1lw3X8AfNf2VZJGASfV+swEhlEl0Q8BAi6w/T+tArb9kqSRwLuoVss/A7yznMsOtl+oty+Jbj3O+cCKtu8vK+7vBr4h6TrgCuAu2zu0mj8iIiJieTBgtlgAk4B9y17eNai2LmB7NvCUpF1Ku48AE20/Azwk6QAAVbYtx5vYvs32icCTwEaLGNMQ4JFyfGhD3Z3AfwBXSdoAuAHYX9IbSgxrS3pzvUNZ9R5i+zfAsVQJNlSr15+ptRtGN8p8c2xfBHwb2B64D1hP0g6lzUqStlyYk42IiIhYFgyYFWTbUyVdCkwD/gRMrlUfCpwtaTXgQeDwUn4IcJakLwErUe0Tng58S9KmVKu6N5SyRXES1RaOR4BbgY0bYr6xfNzbOODfgC8B10laAZgHfLqcS5c1gF9JWqXE9rlSfjTwQ0kzqF7zScBR3cS1dTnHl8s8n7T9T0n7A6eXbSkrAt8D7lrEc4+IiIjol2Rnm2gsHe3t7e7o6OjrMCIiIiKakjTFdntj+UDaYhERERER0aMkyBERERERNUmQIyIiIiJqkiBHRERERNQkQY6IiIiIqEmCHBERERFRkwQ5IiIiIqImCXJERERERE0S5IiIiIiImgHzVdPx2ut8ZDZtJ4zr6zAiejRrzN59HUJERPQjWUGOiIiIiKgZsAmypDZJM1vUHSZpg9rzYyWttgTmbJd0+uKOExERERFLz4BNkHtwGLBB7fmxwGInyLY7bB+9uOP0lip5jSMiIiIWwkBPngZJOkfSXZKuk7SqpP2BduBiSdMkHUOVLI+XNB5A0nOSviNpqqQbJK1Xyo+WdLekGZJ+1jiZpFGSri7HJ0m6oMw7S9IHJH1TUqekayStVNq9W9K9km6UdHpD/+NqY88sq+Jtku6RdCYwFdioIYYRkm6WNF3S7ZLWkLSKpB+Xue+UNLq0PUzSlZJ+LekhSZ+R9J+lza2S1l7yL0lERERE3xroCfKmwA9tbwk8Dexn+xdAB3CI7WG2vw88Coy2Pbr0Wx2Yant7YCLw5VJ+ArCd7W2Ao3ox/ybA3sA+wEXAeNtbAy8Ae0taBfgRsJftnYH1enlemwEX2t7O9p+6CiW9DrgUOMb2tsDuZa5PA5S5DwYuKHMDbAV8CBgJfA2YY3s74Bbgo40TSzpSUoekjvlzZvcy3IiIiIj+Y6AnyA/ZnlaOpwBtvez3MlWiCVViu3M5nkG18vxh4KVejPNb2/OATmAQcE0p7yyxbA48aPuhUn5JL+P7k+1bm5RvBjxm+w4A28/YfqnE/5NSdi/wJ+Btpc9428/a/hswG/h1Q4yvYHus7Xbb7YNWG9LLcCMiIiL6j4GeIM+tHc9n0T/2zuVxb+CHwHBgiqSexpsLYPtlYJ7trnFeLrGom74v8crXb5Xa8fMt+qgWa2N5tzHW4ppbO87HBEZERMRyZ6AnyK08C6zRzfMVgP3L8YeAG8ub4TayPR44HlgLGLyYcdwLvEVSW3l+YK1uFrA9gKTtgY17Od4GkkaUfmuUJH4ScEgpexvwJuC+xYw9IiIiYpmUFcDmzgfOlvQCsAMwFvitpMfKPuTngS0lTaHadnAg1RaJiyQNoVqRPc3204sThO0XJH0KuEbSk8DttepfAh+VNA24A7i/F+P9U9KBwA8krUq1/3h34Mxyvp1UK9OH2Z4rdbewHBEREbF80oK/6kdvSXrO9uKuDvd2rsG2n1OVrf4QeMD2aa/F3Itr5aGbeuih3+vrMCJ6lG/Si4gYmCRNsd3eWJ4V5P7vCEmHAq8D7qT6VItlwtYbDqEjiUdEREQsY5IgL4LXavW4zHUasEysGEdEREQsD/ImvYiIiIiImiTIERERERE1SZAjIiIiImqSIEdERERE1CRBjoiIiIioSYIcEREREVGTBDkiIiIioiYJckRERERETb4oJJaazkdm03bCuL4OIwaAfFV0REQsSVlBjoiIiIioSYK8jJJ0vqT9y/G5krYox194jeafIKn9tZgrIiIi4rWUBLkfkTRoUfrZ/oTtu8vTJZ4gS8pWnIiIiBgwkiA3IalN0r2SLpA0Q9IvJK1W6k6UdIekmZLGqrKJpKm1/ptKmtJk3LdK+p2k6ZKmln6jJI2X9FOgU9IgSd8qc8yQ9B+lrySdIeluSeOAN9TGnSCpXdIYYFVJ0yRd3GT+Pcu80yXdUMpGSrpZ0p3lcbNSfpikyyT9GrhO0qqSflZiuhRYdYle9IiIiIh+Iglya5sBY21vAzwDfKqUn2F7hO2tqJLE99j+IzBb0rDS5nDg/CZjXgz80Pa2wI7AY6V8JPBF21sAHwdm2x4BjACOkLQxsG+JaWvgiNL/FWyfALxge5jtQ+p1ktYDzgH2K/MfUKruBXa1vR1wIvD1WrcdgENtvxP4JDCnXI+vAcObXTRJR0rqkNQxf87sZk0iIiIi+rUkyK09bPumcnwRsHM5Hi3pNkmdwDuBLUv5ucDhZZvEgcBP64NJWgPY0PYVALZftD2nVN9u+6FyvAfwUUnTgNuAdYBNgV2BS2zPt/0o8PuFPJ93AJO65rH9j1I+BLhM0kzgtNr5AFxfa7druQ7YngHMaDaJ7bG22223D1ptyEKGGBEREdH3kiC35sbnklYBzgT2t7011YrsKqX+l8BewHuAKbb/3tBf3cz1fEO7z5ZV4GG2N7Z9XYuYFoZa9P8KML6siL+XBefTGNfizh8RERGxTEiC3NqbJO1Qjg8GbmRB8vikpMHA/l2Nbb8IXAucBfy4cTDbzwB/kfR+AEkrd+1rbnAt8ElJK5V2b5O0OjAJOKjsUR4KjG4R97yuvg1uAXYr2zWQtHYpHwI8Uo4PazEmZf5DSt+tgG26aRsRERGxzEqC3No9wKGSZgBrA2fZfppq1bgTuBK4o6HPxVSrrNfR3EeAo8uYNwP/0qTNucDdwNSy7eFHVF/ocgXwQJn7LGBiiznGAjMa36Rn+2/AkcDlkqYDl5aqbwLfkHQT0N2naJwFDC6xHw/c3k3biIiIiGWW7PzVvJGkNuDqsu1gYfodBwyx/b9LJbBlTHt7uzs6Ovo6jIiIiIimJE2x/arvdcjn2y4hkq4ANqF6415ERERELKOSIDdhexawUKvHtvddOtFERERExGspe5AjIiIiImqSIEdERERE1CRBjoiIiIioSYIcEREREVGTBDkiIiIioiYJckRERERETRLkiIiIiIiafA5yLDWdj8ym7YRxfR1GDACzxuzd1yFERMRyJCvIERERERE1SZCXEEkbSRov6R5Jd0k6pla3tqTrJT1QHl9fq/sfSX+QdJ+kf6+VP9eLOd8vaYva8wmSXvV94ot4PrMkrbskxoqIiIhYliRBXnJeAj5v++3AO4BP15LXE4AbbG8K3FCeU+oPArYE9gTOlDRoIeZ8P7BFT40iIiIioveWuwRZ0pWSppRV3CNr5c9JOrXU/U7SyLLi+qCk95U2h0n6laRryorul5uM/+ayEryupBUkTZa0h+3HbE8FsP0scA+wYem2D3BBOb6AKrHtKv+Z7bm2HwL+AIyszfUdSVMl3SBpvYY4dgTeB3xL0jRJm5SqAyTdLul+SbuUtm0lzqnlZ8dSPqpcg19IulfSxZLUMM+q5XocIWl1SeMkTZc0U9KBC/fqRERERPR/y12CDHzM9nCgHTha0jqlfHVgQql7Fvgq8G/AvsAptf4jgUOAYVTJ5iu2LNj+E3AqcDbweeBu29fV20hqA7YDbitF69t+rPR/DHhDKd8QeLjW9S8sSKpXB6ba3h6YCLwiWbd9M3AV8F+2h9n+Y6la0fZI4NhanyeAfytjHQicXhtqu9J2C+AtwE61usHAr4Gf2j6HapX7Udvb2t4KuIYGko6U1CGpY/6c2Y3VEREREf3e8pggHy1pOnArsBGwaSn/JwsSuk5gou155bit1v9623+3/QJwObBz4wS2zwXWAI4CjqvXSRoM/BI41vYzPcSqJmUujy8Dl5bji5rF0cLl5XEKC85rJeAcSZ3AZbxyW8bttv9i+2VgGq+8Fr8Cfmz7wvK8E9i9rMTvYvtVGbDtsbbbbbcPWm1IL0OOiIiI6D+WqwRZ0ihgd2AH29sCdwKrlOp5tuvJ51yAkhjWP+7OvFLjcyStBryxPB1cK1+JKjm+2PbltS6PSxpa2gylWtGFasV4o1q7NwKPtji9V8XRwtzyOJ8F5/U54HFgW6qV9dc1ad/YB+AmYK+ubRe27weGUyXK35B0Yi9jioiIiFhmLFcJMjAEeMr2HEmbU71ZbmH9W/nUiVWp9grf1KTNqcDFwInAOQAlifx/wD22v9vQ/irg0HJ8KNXKbFf5QZJWlrQx1Wr37aVuBWD/cvwh4MYmcTxLtZLdkyHAY+WXgY8AvX0j4InA34EzASRtAMyxfRHwbWD7Xo4TERERscxY3r4o5BrgKEkzgPuotlksrBuBnwBvpdp721GvlLQbMALYyfZ8SftJOhx4gCr57JQ0rTT/gu3fAGOAn0v6OPBn4AAA23dJ+jlwN9WnYHza9vzS93lgS0lTgNlUe4cb/Yxq68TRLEimmzkT+KWkA4DxZezeOhY4T9I3qT6B41uSXgbmAZ9ciHEiIiIilglasOsgJB0GtNv+TF/Hsjxob293R0dHzw0jIiIi+oCkKbZf9R0Sy9sWi4iIiIiIxbK8bbFYLLbPB87v4zAiIiIiog9lBTkiIiIioiYJckRERERETRLkiIiIiIiaJMgRERERETVJkCMiIiIiapIgR0RERETUJEGOiIiIiKjJ5yDHUtP5yGzaThjX12HEADBrzN59HUJERCxHsoIcEREREVEzYBNkScdKWm0R+j23GHMeJmmDFnXnS9p/UcdehFh6nE/SBEmv+n5ySaMk7bj0oouIiIjoOwM2QQaOBRY6QV5MhwFNE+RlzCggCXJEREQsl5b7BFnS6pLGSZouaaakAyUdTZWojpc0vrR7rtZnf0nnl+ONJd0i6Q5JX2kY+79K+QxJJ5eyNkn3SDpH0l2SrpO0almtbQculjRN0qrdxPwuSXdK6pR0nqSVS/mJZb6ZksZKUimfIOlUSbdLul/SLk3GlKQzJN0taRzwhlrdcEkTJU2RdK2kobWuH5Z0c5lzpKQ24Cjgc+U8XjVXRERExLJsuU+QgT2BR21va3sr4BrbpwOPAqNtj+6h//eBs2yPAP7aVShpD2BTYCQwDBguaddSvSnwQ9tbAk8D+9n+BdABHGJ7mO0Xmk0maRXgfOBA21tTvZHyk6X6DNsjynmsCryn1nVF2yOpVsa/3GTofYHNgK2BIygrwJJWAn4A7G97OHAe8LVav9Vt7wh8CjjP9izgbOC0ch6TW1y3iIiIiGXSQEiQO4HdywrrLrZnL2T/nYBLyvFPauV7lJ87ganA5lSJMcBDtqeV4ylA20LMt1npf395fgHQlXiPlnSbpE7gncCWtX6X9zDfrsAltufbfhT4fW2+rYDrJU0DvgS8sdbvEgDbk4A1Ja3VXfCSjpTUIalj/pyFvdQRERERfW+5/5g32/dLGg68G/iGpOtsn9Ksae14lW7qugj4hu0fvaKw2oIwt1Y0n2q1t7fUtLBaWT4TaLf9sKSTGuLsmnM+rV/XVudxl+0detmn2RgLKu2xwFiAlYdu2m3biIiIiP5ouV9BLp8aMcf2RcC3ge1L1bPAGrWmj0t6u6QVqLYjdLkJOKgcH1Irvxb4mKTBZZ4NJb2B7jXO2cy9QJukt5bnHwEmsiAZfrLMubCfeDEJOEjSoLLHuGtryX3AepJ2KOexkqT6yvSBpXxnYHZZge/NeUREREQsk5b7FWSqPbffkvQyMI8F+3nHAr+V9FjZh3wCcDXwMDATGFzaHQP8VNIxwC+7BrV9naS3A7eU98o9B3yYagW3lfOBsyW9AOzQbB+y7RclHQ5cJmlF4A7gbNtzJZ1DtWVkVilfGFdQbcvoBO6nSrqx/c/yBsLTJQ2huie+B9xV+j0l6WZgTeBjpezXwC8k7QN8NvuQIyIiYnkiO38Fj6Vj5aGbeuih3+vrMGIAyDfpRUTEopA0xfarvvNhIKwgRx/ZesMhdCRxiYiIiGXMcr8HOSIiIiJiYSRBjoiIiIioSYIcEREREVGTBDkiIiIioiYJckRERERETRLkiIiIiIiaJMgRERERETVJkCMiIiIiapIgR0RERETU5Jv0YqnpfGQ2bSeM6+swYhmRr4uOiIj+IivIERERERE1SZCbkHSSpOP6Og4ASc+VxzZJMxei32GSzlh6kUVEREQsn5Igv0YkDerrGCIiIiKiZ0mQC0lflHSfpN8Bm9XKh0m6VdIMSVdIen0pnyDpVEm3S7pf0i5NxhwlabyknwKdkgZJ+pakO8p4/1HaDZZ0g6Spkjol7dNDrJMlDas9v0nSNt2031vSLZLWlXS+pNMl3SzpQUn7lzYqsc0sMRxYys+U9L5yfIWk88rxxyV9tdcXOCIiImIZkQQZkDQcOAjYDvgAMKJWfSHw37a3ATqBL9fqVrQ9Eji2obxuJPBF21sAHwdm2x5R5jhC0sbAi8C+trcHRgPfkaRuQj4XOKzE/jZgZdszWpzbvsAJwLttP1mKhwI7A+8BxpSyDwDDgG2B3YFvSRoKTAK6kv8NgS3K8c7A5CbzHSmpQ1LH/DmzuzmFiIiIiP4pCXJlF+AK23NsPwNcBSBpCLCW7Yml3QXArrV+l5fHKUBbi7Fvt/1QOd4D+KikacBtwDrApoCAr0uaAfyOKhFdv5t4LwPeI2kl4GPA+S3ajQb+G9jb9lO18ittv2z77to8OwOX2J5v+3FgIlUSPxnYRdIWwN3A4yVx3gG4uXFC22Ntt9tuH7TakG5OISIiIqJ/yse8LeBF6DO3PM6n9bV8vnYs4LO2r603kHQYsB4w3PY8SbOAVVoGas+RdD2wD/BBoL1F0weBtwBvAzqaxN0VU/2xca5HyraSPalWk9cucz5n+9lWMUZEREQsq7KCXJkE7CtpVUlrAO8FsD0beKq2v/gjVCuri+pa4JNl5RdJb5O0OjAEeKIkx6OBN/dirHOB04E7bP+jRZs/UW2duFDSlj2MNwk4sOyTXo9qpfz2UncL1TaSSVQrysfRZHtFRERExPIgK8iA7amSLgWmUSWV9eTvUOBsSatRrcgevhhTnUu1FWNq2WP8N+D9wMXAryV1lBju7UXMUyQ9A/y4h3b3SToEuEzSe7tpegXVtonpVKvpx9v+a6mbDOxh+w+S/kS1ipwEOSIiIpZLshdlZ0H0NUkbABOAzW2/3MfhNNXe3u6Ojo6eG0ZERET0AUlTbL9qq2q2WCyDJH2U6k1+X+yvyXFERETEsipbLJZBti+k+vi5iIiIiFjCsoIcEREREVGTBDkiIiIioiYJckRERERETRLkiIiIiIiaJMgRERERETVJkCMiIiIiapIgR0RERETU5HOQY6npfGQ2bSeM6+swYhkxa8zefR1CREQEkBXkiIiIiIhXSILcA0nHSlptEfodJmmDhezTJmnmws61uCS9T9IJPbQ5X9L+r1VMEREREX0lCXLPjgUWKkGWNAg4DFioBLmv2L7K9pi+jiMiIiKiP0iCXEhaXdI4SdMlzZR0oKSjqZLc8ZLGl3ZnSeqQdJekk2v9Z0k6UdKNwMFAO3CxpGmSVpU0XNJESVMkXStpaOk3vMx5C/DpFrGNkjRB0i8k3SvpYkmq9X/FuJLeIGlKqd9WkiW9qTz/Y+OKeFntPqMcv1nSDZJmlMc31ZruLmmypPslvWeJXPiIiIiIfiYJ8gJ7Ao/a3tb2VsA1tk8HHgVG2x5d2n3RdjuwDbCbpG1qY7xoe2fbFwEdwCG2hwEvAT8A9rc9HDgP+Frp82PgaNs79BDfdlSr2VsAbwF2krRSs3FtPwGsImlNYJcSyy6S3gw8YXtON/OcAVxoexvgYuD0Wl0bsBuwN3C2pFUaO0s6svwC0TF/zuweTikiIiKi/8mnWCzQCXxb0qnA1bYnt2j3QUlHUl27oVQJ64xSd2mLPpsBWwHXl4XfQcBjkoYAa9meWNr9BNirxRi32/4LgKRpVMnq083GLe1vBnYCdgW+TvULgIBW59VlB+ADtXi+Wav7ue2XgQckPQhsDkyrd7Y9FhgLsPLQTd3DXBERERH9ThLkwvb9koYD7wa+Iek626fU20jaGDgOGGH7KUnnA/VV1OdbDC/grsZVYklrAb1NIufWjudTvXZNxy0mU60evxn4FfDfZa6rezlfF7c4bvY8IiIiYpmXLRZF+cSJOWV7xLeB7UvVs8Aa5XhNqiR4tqT1ab3a29jvPmA9STuUuVaStKXtp8tYO5d2hyxk2E3HLXWTgA8DD5RV339QJf839TDmzcBBtXhurNUdIGkFSZtQbfO4byHjjYiIiOj3soK8wNbAtyS9DMwDPlnKxwK/lfSY7dGS7gTuAh6k+2TzfKp9ui9QbVvYHzi9bKtYEfheGedw4DxJc4BrFyZg2/8sH732qnFtzyrbLiaV5jcCb7T9VKvhyuPRJZ7/Av5W4utyHzARWB84yvaLCxNvRERExLJAdv5KPtBJ+jywpu0vL8lx29vb3dHRsSSHjIiIiFhiJE0pH77wCllBHuAkHUX1mc0f6KFpRERExICQPcgDnO2zbW9t+4G+jiUiIiKiP0iCHBERERFRkwQ5IiIiIqImCXJERERERE0S5IiIiIiImiTIERERERE1SZAjIiIiImqSIEdERERE1CRBjoiIiIioyTfpxVLT+chs2k4Y19dhxGtk1pi9+zqEiIiIJWJArSBLapM0cwmMM0rS1b1oN0vSuos736KS9IXaca/OXdJRkj66dCOLiIiI6L8GVIK8LFKl5eskaVA33b/QTV1T5aunL2wyT/7aEBEREQPCQEyQV5R0gaQZkn4haTUASSdKukPSTEljJamUv1XS7yRNlzRV0ib1wSSNkHSnpLdIWkfSdeX5jwDV2v1nGXumpGO7Ky+rvfdIOhOYCmzUMOesEu+NwAGSDpbUWcY4tbQZA6wqaZqki0vXQZLOkXRXiXPVxosj6SRJx5XjCZK+LmkicIyk90q6rZzf7yStv1ivREREREQ/NBAT5M2Asba3AZ4BPlXKz7A9wvZWwKrAe0r5xcAPbW8L7Ag81jWQpB2Bs4F9bD8IfBm40fZ2wFXAm0q74cDhwL8C7wCOkLRdq/JanBfa3s72n5qcx4u2dwYmAacC7wSGASMkvd/2CcALtofZPqT02bScy5bA08B+vbhea9nezfZ3gBuBd5Tz+xlwfC/6R0RERCxTBmKC/LDtm8rxRcDO5Xh0WR3tpEo2t5S0BrCh7SsAbL9oe05p/3ZgLPBe238uZbuWMbE9DniqlO8MXGH7edvPAZcDu3RTDvAn27d2cx6XlscRwATbf7P9ElVCv2uLPg/ZnlaOpwBt3YzfOA/AG4FryzX6L2DLxsaSjpTUIalj/pzZvRg+IiIion8ZiAmyG59LWgU4E9jf9tbAOcAq1LZINPEY8CKwXUN54/h0M0534z/fTV29vrsxGs2tHc+nd59iUo/jB1Qr7VsD/0F1jV7B9ljb7bbbB602ZCFCi4iIiOgfBmKC/CZJO5Tjg6m2DXQlek9KGgzsD2D7GeAvkt4PIGnlrj3LVFsU9ga+LmlUKZsEHFLa7gW8vlb+fkmrSVod2BeY3E35wrgN2E3SuuUNewcDE0vdPEkrLeR43RkCPFKOD12C40ZERET0GwMxQb4HOFTSDGBt4CzbT1OtGncCVwJ31Np/BDi6tL8Z+JeuCtuPA+8FfijpX4GTgV0lTQX2AP5c2k0Fzgdup0poz7V9Z6vyhTkZ248B/wOMB6YDU23/qlSPBWbU3qS3uE4CLpM0GXhyCY0ZERER0a/IbrYjIGLxrTx0Uw899Ht9HUa8RvJFIRERsayRNMV2e2N5Pts2lpqtNxxCR5KmiIiIWMYMxC0WEREREREtJUGOiIiIiKhJghwRERERUZMEOSIiIiKiJp9iEUuNpGeB+/o6jmXQuuRj9BZWrtmiyXVbNLluCy/XbNHkui2ahblub7a9XmNhPsUilqb7mn10SnRPUkeu28LJNVs0uW6LJtdt4eWaLZpct0WzJK5btlhERERERNQkQY6IiIiIqEmCHEvT2L4OYBmV67bwcs0WTa7bosl1W3i5Zosm123RLPZ1y5v0IiIiIiJqsoIcEREREVGTBDkiIiIioiYJciwVkvaUdJ+kP0g6oa/jWRZImiWpU9I0SR19HU9/Jek8SU9ImlkrW1vS9ZIeKI+v78sY+6MW1+0kSY+Ue26apHf3ZYz9jaSNJI2XdI+kuyQdU8pzv3Wjm+uW+60FSatIul3S9HLNTi7lude60c11W+x7LXuQY4mTNAi4H/g34C/AHcDBtu/u08D6OUmzgHbb+VD4bkjaFXgOuND2VqXsm8A/bI8pv5C93vZ/92Wc/U2L63YS8Jztb/dlbP2VpKHAUNtTJa0BTAHeDxxG7reWurluHyT3W1OSBKxu+zlJKwE3AscAHyD3WkvdXLc9Wcx7LSvIsTSMBP5g+0Hb/wR+BuzTxzHFcsL2JOAfDcX7ABeU4wuo/jGOmhbXLbph+zHbU8vxs8A9wIbkfutWN9ctWnDlufJ0pfJjcq91q5vrttiSIMfSsCHwcO35X8j/HHvDwHWSpkg6sq+DWcasb/sxqP5xBt7Qx/EsSz4jaUbZgpE/37YgqQ3YDriN3G+91nDdIPdbS5IGSZoGPAFcbzv3Wi+0uG6wmPdaEuRYGtSkLHt5eraT7e2BvYBPlz+JRyxNZwGbAMOAx4Dv9Gk0/ZSkwcAvgWNtP9PX8Swrmly33G/dsD3f9jDgjcBISVv1cUjLhBbXbbHvtSTIsTT8Bdio9vyNwKN9FMsyw/aj5fEJ4AqqrSrRO4+XfY9d+x+f6ON4lgm2Hy//uLwMnEPuuVcp+xp/CVxs+/JSnPutB82uW+633rH9NDCBah9t7rVeql+3JXGvJUGOpeEOYFNJG0t6HXAQcFUfx9SvSVq9vJkFSasDewAzu+8VNVcBh5bjQ4Ff9WEsy4yuf3iLfck99wrlDUD/D7jH9ndrVbnfutHquuV+a03SepLWKserArsD95J7rVutrtuSuNfyKRaxVJSPVPkeMAg4z/bX+jai/k3SW6hWjQFWBH6aa9acpEuAUcC6wOPAl4ErgZ8DbwL+DBxgO29Iq2lx3UZR/QnSwCzgP7r2OwZI2hmYDHQCL5fiL1Dtp8391kI31+1gcr81JWkbqjfhDaJavPy57VMkrUPutZa6uW4/YTHvtSTIERERERE12WIREREREVGTBDkiIiIioiYJckRERERETRLkiIiIiIiaJMgRERERETVJkCMiIiIiapIgR0RERETU/H/Adxm0vpW1OgAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<Figure size 720x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Plotting and saving the top common words/bigrams/trigrams\n",
    "for i, x in enumerate(X_cvecs):\n",
    "    if i % 2 == 0:\n",
    "        cs_or_pf = 'cs'\n",
    "    elif i % 2 == 1:\n",
    "        cs_or_pf = 'pf'\n",
    "    \n",
    "    if 'bi' in x:\n",
    "        n_gram_length = 2\n",
    "    elif 'tri' in x:\n",
    "        n_gram_length = 3\n",
    "    else:\n",
    "        n_gram_length = 1\n",
    "    \n",
    "    word_plots(globals()[X_cvecs[i]],cs_or_pf,n_gram_length)\n",
    "    plt.tight_layout()\n",
    "    plt.savefig(f'./images/{cs_or_pf}_Ngram_length{n_gram_length}')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "099188a6",
   "metadata": {
    "scrolled": true
   },
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 92,
   "id": "5b1ec861",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "((1179, 6), (1179, 8551))"
      ]
     },
     "execution_count": 92,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_cs.shape, X_cvec_cs.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 93,
   "id": "9c782622",
   "metadata": {
    "scrolled": true
   },
   "outputs": [],
   "source": [
    "df_merged = pd.concat([df_cs,df_pf])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 94,
   "id": "ae0d7e15",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "personalfinance      1252\n",
       "cscareerquestions    1179\n",
       "Name: subreddit, dtype: int64"
      ]
     },
     "execution_count": 94,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_merged['subreddit'].value_counts()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 95,
   "id": "5f405a97",
   "metadata": {
    "scrolled": true
   },
   "outputs": [],
   "source": [
    "# \n",
    "df_merged['subreddit'] = df_merged['subreddit'].map({'cscareerquestions':1,'personalfinance':0})"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 96,
   "id": "51dae54f",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0    1252\n",
       "1    1179\n",
       "Name: subreddit, dtype: int64"
      ]
     },
     "execution_count": 96,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_merged['subreddit'].value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 97,
   "id": "76bd5170",
   "metadata": {},
   "outputs": [],
   "source": [
    "df_merged.to_csv('data/clean_subreddit_data.csv',index=False)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "701b6ac7",
   "metadata": {},
   "source": [
    "### References:\n",
    "\n",
    "[Python Optional Arguments](https://realpython.com/python-optional-arguments/)\n",
    "\n",
    "[Convert a String to Variable Name in Python](https://www.delftstack.com/howto/python/python-string-to-variable-name/)"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "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": "3.8.8"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}