Pandas_Day4.ipynb

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   "source": [
    "### Day 4\n",
    "import numpy as np\n",
    "import pandas as pd\n",
    "import seaborn as sns\n",
    "sns.set()\n",
    "import matplotlib.pyplot as plt"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 142,
   "id": "20713ee2",
   "metadata": {},
   "outputs": [],
   "source": [
    "energy = pd.read_csv('Value_of_Energy_Cost_Savings_Program_Savings_for_Businesses_FY2020.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 143,
   "id": "404122d6",
   "metadata": {
    "scrolled": true
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    {
     "data": {
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       "\n",
       "    .dataframe thead th {\n",
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       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Company Name</th>\n",
       "      <th>company contact</th>\n",
       "      <th>company email</th>\n",
       "      <th>company phone</th>\n",
       "      <th>Address</th>\n",
       "      <th>City</th>\n",
       "      <th>State</th>\n",
       "      <th>Postcode</th>\n",
       "      <th>Industry</th>\n",
       "      <th>Industry descr</th>\n",
       "      <th>...</th>\n",
       "      <th>Savings from beginning receiving benefits</th>\n",
       "      <th>Borough</th>\n",
       "      <th>Latitude</th>\n",
       "      <th>Longitude</th>\n",
       "      <th>Community Board</th>\n",
       "      <th>Council District</th>\n",
       "      <th>Census Tract</th>\n",
       "      <th>BIN</th>\n",
       "      <th>BBL</th>\n",
       "      <th>NTA</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1 State Street</td>\n",
       "      <td>David Neiburg</td>\n",
       "      <td>eskoblo@energyspec.com</td>\n",
       "      <td>7186779077</td>\n",
       "      <td>1114 Avenue J</td>\n",
       "      <td>Brooklyn</td>\n",
       "      <td>NY</td>\n",
       "      <td>11230</td>\n",
       "      <td>Commercial</td>\n",
       "      <td>35 story building</td>\n",
       "      <td>...</td>\n",
       "      <td>349.78</td>\n",
       "      <td>Brooklyn</td>\n",
       "      <td>40.624784</td>\n",
       "      <td>-73.964920</td>\n",
       "      <td>314.0</td>\n",
       "      <td>44.0</td>\n",
       "      <td>534.0</td>\n",
       "      <td>3179818.0</td>\n",
       "      <td>3.067130e+09</td>\n",
       "      <td>Midwood</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>100 Church LLC</td>\n",
       "      <td>Edward A. Carroll</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2125663000</td>\n",
       "      <td>100 Church Street</td>\n",
       "      <td>NY</td>\n",
       "      <td>NY</td>\n",
       "      <td>10007</td>\n",
       "      <td>Commercial</td>\n",
       "      <td>21 Floors</td>\n",
       "      <td>...</td>\n",
       "      <td>4423698.05</td>\n",
       "      <td>New York</td>\n",
       "      <td>40.712968</td>\n",
       "      <td>-74.009490</td>\n",
       "      <td>101.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>21.0</td>\n",
       "      <td>1001409.0</td>\n",
       "      <td>1.001250e+09</td>\n",
       "      <td>SoHo-TriBeCa-Civic Center-Little Italy</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>100 Wall Investments</td>\n",
       "      <td>Jerry Branam</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2122487160</td>\n",
       "      <td>96 Wall Street</td>\n",
       "      <td>New York</td>\n",
       "      <td>NY</td>\n",
       "      <td>10005</td>\n",
       "      <td>Landlord</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>1814542.62</td>\n",
       "      <td>New York</td>\n",
       "      <td>40.705052</td>\n",
       "      <td>-74.007199</td>\n",
       "      <td>101.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>1000875.0</td>\n",
       "      <td>1.000380e+09</td>\n",
       "      <td>Battery Park City-Lower Manhattan</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>1-10 Bush Terminal Owner LP</td>\n",
       "      <td>Andrew Kimball</td>\n",
       "      <td>akimball@industrycity.com</td>\n",
       "      <td>3474178429</td>\n",
       "      <td>220 36th St, Suite 2A</td>\n",
       "      <td>Brooklyn</td>\n",
       "      <td>NY</td>\n",
       "      <td>11232</td>\n",
       "      <td>Landlord</td>\n",
       "      <td>Special Eligible Premises for eligible businesses</td>\n",
       "      <td>...</td>\n",
       "      <td>6755.31</td>\n",
       "      <td>Brooklyn</td>\n",
       "      <td>40.656061</td>\n",
       "      <td>-74.007334</td>\n",
       "      <td>307.0</td>\n",
       "      <td>38.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3398687.0</td>\n",
       "      <td>3.006950e+09</td>\n",
       "      <td>Sunset Park West</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>120 Broadway Acquisitions JV, LLC (Ldmk)</td>\n",
       "      <td>Carl Letich</td>\n",
       "      <td>clettich@silvprop.com</td>\n",
       "      <td>2124064020</td>\n",
       "      <td>120 Broadway</td>\n",
       "      <td>New York</td>\n",
       "      <td>NY</td>\n",
       "      <td>10271</td>\n",
       "      <td>Commercial</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>3293055.08</td>\n",
       "      <td>New York</td>\n",
       "      <td>40.708546</td>\n",
       "      <td>-74.011041</td>\n",
       "      <td>101.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>1001026.0</td>\n",
       "      <td>1.000478e+09</td>\n",
       "      <td>Battery Park City-Lower Manhattan</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 26 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                               Company Name    company contact  \\\n",
       "0                            1 State Street      David Neiburg   \n",
       "1                            100 Church LLC  Edward A. Carroll   \n",
       "2                      100 Wall Investments       Jerry Branam   \n",
       "3               1-10 Bush Terminal Owner LP     Andrew Kimball   \n",
       "4  120 Broadway Acquisitions JV, LLC (Ldmk)        Carl Letich   \n",
       "\n",
       "               company email company phone                Address      City  \\\n",
       "0     eskoblo@energyspec.com    7186779077          1114 Avenue J  Brooklyn   \n",
       "1                        NaN    2125663000      100 Church Street        NY   \n",
       "2                        NaN    2122487160         96 Wall Street  New York   \n",
       "3  akimball@industrycity.com    3474178429  220 36th St, Suite 2A  Brooklyn   \n",
       "4      clettich@silvprop.com    2124064020           120 Broadway  New York   \n",
       "\n",
       "  State  Postcode    Industry  \\\n",
       "0    NY     11230  Commercial   \n",
       "1    NY     10007  Commercial   \n",
       "2    NY     10005    Landlord   \n",
       "3    NY     11232    Landlord   \n",
       "4    NY     10271  Commercial   \n",
       "\n",
       "                                      Industry descr  ...  \\\n",
       "0                                  35 story building  ...   \n",
       "1                                          21 Floors  ...   \n",
       "2                                                NaN  ...   \n",
       "3  Special Eligible Premises for eligible businesses  ...   \n",
       "4                                                NaN  ...   \n",
       "\n",
       "  Savings from beginning receiving benefits   Borough   Latitude  Longitude  \\\n",
       "0                                    349.78  Brooklyn  40.624784 -73.964920   \n",
       "1                                4423698.05  New York  40.712968 -74.009490   \n",
       "2                                1814542.62  New York  40.705052 -74.007199   \n",
       "3                                   6755.31  Brooklyn  40.656061 -74.007334   \n",
       "4                                3293055.08  New York  40.708546 -74.011041   \n",
       "\n",
       "  Community Board  Council District  Census Tract        BIN           BBL  \\\n",
       "0           314.0              44.0         534.0  3179818.0  3.067130e+09   \n",
       "1           101.0               1.0          21.0  1001409.0  1.001250e+09   \n",
       "2           101.0               1.0           7.0  1000875.0  1.000380e+09   \n",
       "3           307.0              38.0           2.0  3398687.0  3.006950e+09   \n",
       "4           101.0               1.0           7.0  1001026.0  1.000478e+09   \n",
       "\n",
       "                                      NTA  \n",
       "0                                 Midwood  \n",
       "1  SoHo-TriBeCa-Civic Center-Little Italy  \n",
       "2       Battery Park City-Lower Manhattan  \n",
       "3                        Sunset Park West  \n",
       "4       Battery Park City-Lower Manhattan  \n",
       "\n",
       "[5 rows x 26 columns]"
      ]
     },
     "execution_count": 143,
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   ],
   "source": [
    "energy.head()"
   ]
  },
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   "execution_count": 144,
   "id": "e45202a1",
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     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 450 entries, 0 to 449\n",
      "Data columns (total 26 columns):\n",
      " #   Column                                     Non-Null Count  Dtype  \n",
      "---  ------                                     --------------  -----  \n",
      " 0   Company Name                               450 non-null    object \n",
      " 1   company contact                            450 non-null    object \n",
      " 2   company email                              433 non-null    object \n",
      " 3   company phone                              450 non-null    object \n",
      " 4   Address                                    450 non-null    object \n",
      " 5   City                                       450 non-null    object \n",
      " 6   State                                      450 non-null    object \n",
      " 7   Postcode                                   450 non-null    int64  \n",
      " 8   Industry                                   450 non-null    object \n",
      " 9   Industry descr                             434 non-null    object \n",
      " 10  Company Type                               450 non-null    object \n",
      " 11  Current fulltime                           446 non-null    float64\n",
      " 12  Job created                                11 non-null     float64\n",
      " 13  Job retain                                 14 non-null     float64\n",
      " 14  Effective Date                             450 non-null    object \n",
      " 15  Total Savings                              450 non-null    float64\n",
      " 16  Savings from beginning receiving benefits  450 non-null    float64\n",
      " 17  Borough                                    450 non-null    object \n",
      " 18  Latitude                                   409 non-null    float64\n",
      " 19  Longitude                                  409 non-null    float64\n",
      " 20  Community Board                            409 non-null    float64\n",
      " 21  Council District                           409 non-null    float64\n",
      " 22  Census Tract                               409 non-null    float64\n",
      " 23  BIN                                        401 non-null    float64\n",
      " 24  BBL                                        401 non-null    float64\n",
      " 25  NTA                                        409 non-null    object \n",
      "dtypes: float64(12), int64(1), object(13)\n",
      "memory usage: 91.5+ KB\n"
     ]
    }
   ],
   "source": [
    "energy.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 145,
   "id": "a4187c8e",
   "metadata": {
    "scrolled": true
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   "outputs": [
    {
     "data": {
      "text/plain": [
       "(450, 26)"
      ]
     },
     "execution_count": 145,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "energy.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 146,
   "id": "83bba5a2",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "439"
      ]
     },
     "execution_count": 146,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(energy['Company Name'].unique())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "id": "411eba23",
   "metadata": {
    "scrolled": true
   },
   "outputs": [],
   "source": [
    "# energy_group = energy.groupby('City')['Job created'].value_counts()\n",
    "# energy_group = energy.groupby('City')\n",
    "# energy_group.head(600)\n",
    "# print(energy_group)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 159,
   "id": "c921f842",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "           email\n",
      "0  aaa@gmail.com\n",
      "1  bbb@yahoo.com\n",
      "2    ccc@aol.com\n",
      "           email     domain\n",
      "0  aaa@gmail.com  gmail.com\n",
      "1  bbb@yahoo.com  yahoo.com\n",
      "2    ccc@aol.com    aol.com\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "email     object\n",
       "domain    object\n",
       "dtype: object"
      ]
     },
     "execution_count": 159,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Queens_Job = energy[energy['City'] == 'Queens']['Job created'].sum()\n",
    "Queens_Job\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 214,
   "id": "4f57e1a9",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(357,)"
      ]
     },
     "execution_count": 214,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "### These three line of codes also work\n",
    "# var = ['Company Name', 'company email']\n",
    "# energy_domain = energy[var].dropna()\n",
    "# energy_domain['domain'] = energy_domain['company email'].str.split('@').str[1]\n",
    "# energy_domain_unique = energy_domain['domain'].unique()\n",
    "# energy_domain_unique.shape\n",
    "\n",
    "\n",
    "### This code also works\n",
    "# energy_domain_unique = energy_domain['company email'].str.split('@').str[1].unique()\n",
    "# energy_domain_unique.shape\n",
    "\n",
    "\n",
    "### This code also works\n",
    "# energy_domain_unique = energy_domain.groupby('domain').sum()\n",
    "# energy_domain_unique.shape\n",
    "\n",
    "\n",
    "### Final Code\n",
    "energy_domain_unique = energy['company email'].str.split('@').str[1].unique()\n",
    "energy_domain_unique.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 107,
   "id": "6c788c2c",
   "metadata": {
    "scrolled": false
   },
   "outputs": [],
   "source": [
    "# NTA = energy['NTA'].value_counts()\n",
    "# NTA1 = NTA[NTA >= 5]\n",
    "# NTA1\n",
    "# NTA1.dtypes\n",
    "# NTA_frame = NTA.to_frame().rename(columns={0: 'NTA', 1: 'Bussiness_Num'})\n",
    "# NTA_frame\n",
    "# NTA\n",
    "\n",
    "### \n",
    "# v = energy.NTA.value_counts()\n",
    "# NTA1 = energy[energy.NTA.isin(v.index[v.gt(4)])]\n",
    "# NTA1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 215,
   "id": "14c86799",
   "metadata": {
    "scrolled": true
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   "outputs": [
    {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Company Name</th>\n",
       "      <th>company contact</th>\n",
       "      <th>company email</th>\n",
       "      <th>company phone</th>\n",
       "      <th>Address</th>\n",
       "      <th>City</th>\n",
       "      <th>State</th>\n",
       "      <th>Postcode</th>\n",
       "      <th>Industry</th>\n",
       "      <th>Industry descr</th>\n",
       "      <th>...</th>\n",
       "      <th>Savings from beginning receiving benefits</th>\n",
       "      <th>Borough</th>\n",
       "      <th>Latitude</th>\n",
       "      <th>Longitude</th>\n",
       "      <th>Community Board</th>\n",
       "      <th>Council District</th>\n",
       "      <th>Census Tract</th>\n",
       "      <th>BIN</th>\n",
       "      <th>BBL</th>\n",
       "      <th>NTA</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>100 Church LLC</td>\n",
       "      <td>Edward A. Carroll</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2125663000</td>\n",
       "      <td>100 Church Street</td>\n",
       "      <td>NY</td>\n",
       "      <td>NY</td>\n",
       "      <td>10007</td>\n",
       "      <td>Commercial</td>\n",
       "      <td>21 Floors</td>\n",
       "      <td>...</td>\n",
       "      <td>4423698.05</td>\n",
       "      <td>New York</td>\n",
       "      <td>40.712968</td>\n",
       "      <td>-74.009490</td>\n",
       "      <td>101.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>21.0</td>\n",
       "      <td>1001409.0</td>\n",
       "      <td>1.001250e+09</td>\n",
       "      <td>SoHo-TriBeCa-Civic Center-Little Italy</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>100 Wall Investments</td>\n",
       "      <td>Jerry Branam</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2122487160</td>\n",
       "      <td>96 Wall Street</td>\n",
       "      <td>New York</td>\n",
       "      <td>NY</td>\n",
       "      <td>10005</td>\n",
       "      <td>Landlord</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>1814542.62</td>\n",
       "      <td>New York</td>\n",
       "      <td>40.705052</td>\n",
       "      <td>-74.007199</td>\n",
       "      <td>101.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>1000875.0</td>\n",
       "      <td>1.000380e+09</td>\n",
       "      <td>Battery Park City-Lower Manhattan</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>1-10 Bush Terminal Owner LP</td>\n",
       "      <td>Andrew Kimball</td>\n",
       "      <td>akimball@industrycity.com</td>\n",
       "      <td>3474178429</td>\n",
       "      <td>220 36th St, Suite 2A</td>\n",
       "      <td>Brooklyn</td>\n",
       "      <td>NY</td>\n",
       "      <td>11232</td>\n",
       "      <td>Landlord</td>\n",
       "      <td>Special Eligible Premises for eligible businesses</td>\n",
       "      <td>...</td>\n",
       "      <td>6755.31</td>\n",
       "      <td>Brooklyn</td>\n",
       "      <td>40.656061</td>\n",
       "      <td>-74.007334</td>\n",
       "      <td>307.0</td>\n",
       "      <td>38.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3398687.0</td>\n",
       "      <td>3.006950e+09</td>\n",
       "      <td>Sunset Park West</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>120 Broadway Acquisitions JV, LLC (Ldmk)</td>\n",
       "      <td>Carl Letich</td>\n",
       "      <td>clettich@silvprop.com</td>\n",
       "      <td>2124064020</td>\n",
       "      <td>120 Broadway</td>\n",
       "      <td>New York</td>\n",
       "      <td>NY</td>\n",
       "      <td>10271</td>\n",
       "      <td>Commercial</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>3293055.08</td>\n",
       "      <td>New York</td>\n",
       "      <td>40.708546</td>\n",
       "      <td>-74.011041</td>\n",
       "      <td>101.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>1001026.0</td>\n",
       "      <td>1.000478e+09</td>\n",
       "      <td>Battery Park City-Lower Manhattan</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>120 Wall Street, LLC</td>\n",
       "      <td>Jason McCalla</td>\n",
       "      <td>jmccalla@silvprop.com</td>\n",
       "      <td>2125517391</td>\n",
       "      <td>120 Wall Street</td>\n",
       "      <td>New York</td>\n",
       "      <td>NY</td>\n",
       "      <td>10005</td>\n",
       "      <td>Commercial</td>\n",
       "      <td>Back Offices</td>\n",
       "      <td>...</td>\n",
       "      <td>2090906.36</td>\n",
       "      <td>New York</td>\n",
       "      <td>40.704380</td>\n",
       "      <td>-74.006427</td>\n",
       "      <td>101.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>1000871.0</td>\n",
       "      <td>1.000370e+09</td>\n",
       "      <td>Battery Park City-Lower Manhattan</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",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>443</th>\n",
       "      <td>William Hird &amp; Co., Inc.</td>\n",
       "      <td>Thomas E. Bury</td>\n",
       "      <td>tebury@hirdco.com</td>\n",
       "      <td>7184994881</td>\n",
       "      <td>255 40th Street</td>\n",
       "      <td>Brooklyn</td>\n",
       "      <td>NY</td>\n",
       "      <td>11232</td>\n",
       "      <td>Manufacturing</td>\n",
       "      <td>Manufacture fire protection systems</td>\n",
       "      <td>...</td>\n",
       "      <td>36644.27</td>\n",
       "      <td>Brooklyn</td>\n",
       "      <td>40.653997</td>\n",
       "      <td>-74.009925</td>\n",
       "      <td>307.0</td>\n",
       "      <td>38.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3010468.0</td>\n",
       "      <td>3.007070e+09</td>\n",
       "      <td>Sunset Park West</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>444</th>\n",
       "      <td>Williams Sonoma, Inc.</td>\n",
       "      <td>Christine Hickman</td>\n",
       "      <td>CHickman@WSGC.com</td>\n",
       "      <td>7187804442</td>\n",
       "      <td>55 Water Street</td>\n",
       "      <td>Brooklyn</td>\n",
       "      <td>NY</td>\n",
       "      <td>11201</td>\n",
       "      <td>Wholesale/Warehouse/Distribution</td>\n",
       "      <td>high quality products for the home</td>\n",
       "      <td>...</td>\n",
       "      <td>56547.18</td>\n",
       "      <td>Brooklyn</td>\n",
       "      <td>40.703301</td>\n",
       "      <td>-73.992047</td>\n",
       "      <td>302.0</td>\n",
       "      <td>33.0</td>\n",
       "      <td>21.0</td>\n",
       "      <td>3000019.0</td>\n",
       "      <td>3.000260e+09</td>\n",
       "      <td>DUMBO-Vinegar Hill-Downtown Brooklyn-Boerum Hill</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>445</th>\n",
       "      <td>WONTON FOOD, INC.</td>\n",
       "      <td>DONALD LAU</td>\n",
       "      <td>donaldlau@wontonfood.com</td>\n",
       "      <td>7186286868</td>\n",
       "      <td>220-222  MOORE STREET</td>\n",
       "      <td>Brooklyn</td>\n",
       "      <td>NY</td>\n",
       "      <td>11206</td>\n",
       "      <td>Manufacturing</td>\n",
       "      <td>MFG. PASTA, EGGROLL SKINS</td>\n",
       "      <td>...</td>\n",
       "      <td>965843.58</td>\n",
       "      <td>Brooklyn</td>\n",
       "      <td>40.704425</td>\n",
       "      <td>-73.936010</td>\n",
       "      <td>301.0</td>\n",
       "      <td>34.0</td>\n",
       "      <td>485.0</td>\n",
       "      <td>3071539.0</td>\n",
       "      <td>3.031090e+09</td>\n",
       "      <td>Bushwick South</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>446</th>\n",
       "      <td>Wood Works</td>\n",
       "      <td>Gordon Brawm</td>\n",
       "      <td>brawnworks@gmail.com</td>\n",
       "      <td>9179404950</td>\n",
       "      <td>162 Cook Street</td>\n",
       "      <td>Brooklyn</td>\n",
       "      <td>NY</td>\n",
       "      <td>11206</td>\n",
       "      <td>Manufacturing</td>\n",
       "      <td>Installer of wood furniture</td>\n",
       "      <td>...</td>\n",
       "      <td>3585.40</td>\n",
       "      <td>Brooklyn</td>\n",
       "      <td>40.702869</td>\n",
       "      <td>-73.936466</td>\n",
       "      <td>301.0</td>\n",
       "      <td>34.0</td>\n",
       "      <td>485.0</td>\n",
       "      <td>3071625.0</td>\n",
       "      <td>3.031230e+09</td>\n",
       "      <td>Bushwick South</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>448</th>\n",
       "      <td>WUD Furniture LLC</td>\n",
       "      <td>Keren Springer</td>\n",
       "      <td>keren@wudfurniture.com</td>\n",
       "      <td>7184867952</td>\n",
       "      <td>1102 Atlantic Avenue</td>\n",
       "      <td>Brooklyn</td>\n",
       "      <td>NY</td>\n",
       "      <td>11238</td>\n",
       "      <td>Manufacturing</td>\n",
       "      <td>We make handcrafted furniture, surfaces, lighting</td>\n",
       "      <td>...</td>\n",
       "      <td>12287.32</td>\n",
       "      <td>Brooklyn</td>\n",
       "      <td>40.679518</td>\n",
       "      <td>-73.956819</td>\n",
       "      <td>308.0</td>\n",
       "      <td>35.0</td>\n",
       "      <td>305.0</td>\n",
       "      <td>3027572.0</td>\n",
       "      <td>3.011260e+09</td>\n",
       "      <td>Crown Heights North</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>306 rows × 26 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                                 Company Name    company contact  \\\n",
       "1                              100 Church LLC  Edward A. Carroll   \n",
       "2                        100 Wall Investments       Jerry Branam   \n",
       "3                 1-10 Bush Terminal Owner LP     Andrew Kimball   \n",
       "4    120 Broadway Acquisitions JV, LLC (Ldmk)        Carl Letich   \n",
       "5                        120 Wall Street, LLC      Jason McCalla   \n",
       "..                                        ...                ...   \n",
       "443                  William Hird & Co., Inc.     Thomas E. Bury   \n",
       "444                     Williams Sonoma, Inc.  Christine Hickman   \n",
       "445                         WONTON FOOD, INC.         DONALD LAU   \n",
       "446                                Wood Works       Gordon Brawm   \n",
       "448                         WUD Furniture LLC     Keren Springer   \n",
       "\n",
       "                 company email company phone                Address      City  \\\n",
       "1                          NaN    2125663000      100 Church Street        NY   \n",
       "2                          NaN    2122487160         96 Wall Street  New York   \n",
       "3    akimball@industrycity.com    3474178429  220 36th St, Suite 2A  Brooklyn   \n",
       "4        clettich@silvprop.com    2124064020           120 Broadway  New York   \n",
       "5        jmccalla@silvprop.com    2125517391        120 Wall Street  New York   \n",
       "..                         ...           ...                    ...       ...   \n",
       "443          tebury@hirdco.com    7184994881        255 40th Street  Brooklyn   \n",
       "444          CHickman@WSGC.com    7187804442        55 Water Street  Brooklyn   \n",
       "445   donaldlau@wontonfood.com    7186286868  220-222  MOORE STREET  Brooklyn   \n",
       "446       brawnworks@gmail.com    9179404950        162 Cook Street  Brooklyn   \n",
       "448     keren@wudfurniture.com    7184867952   1102 Atlantic Avenue  Brooklyn   \n",
       "\n",
       "    State  Postcode                          Industry  \\\n",
       "1      NY     10007                        Commercial   \n",
       "2      NY     10005                          Landlord   \n",
       "3      NY     11232                          Landlord   \n",
       "4      NY     10271                        Commercial   \n",
       "5      NY     10005                        Commercial   \n",
       "..    ...       ...                               ...   \n",
       "443    NY     11232                     Manufacturing   \n",
       "444    NY     11201  Wholesale/Warehouse/Distribution   \n",
       "445    NY     11206                     Manufacturing   \n",
       "446    NY     11206                     Manufacturing   \n",
       "448    NY     11238                     Manufacturing   \n",
       "\n",
       "                                        Industry descr  ...  \\\n",
       "1                                            21 Floors  ...   \n",
       "2                                                  NaN  ...   \n",
       "3    Special Eligible Premises for eligible businesses  ...   \n",
       "4                                                  NaN  ...   \n",
       "5                                         Back Offices  ...   \n",
       "..                                                 ...  ...   \n",
       "443                Manufacture fire protection systems  ...   \n",
       "444                 high quality products for the home  ...   \n",
       "445                          MFG. PASTA, EGGROLL SKINS  ...   \n",
       "446                        Installer of wood furniture  ...   \n",
       "448  We make handcrafted furniture, surfaces, lighting  ...   \n",
       "\n",
       "    Savings from beginning receiving benefits   Borough   Latitude  Longitude  \\\n",
       "1                                  4423698.05  New York  40.712968 -74.009490   \n",
       "2                                  1814542.62  New York  40.705052 -74.007199   \n",
       "3                                     6755.31  Brooklyn  40.656061 -74.007334   \n",
       "4                                  3293055.08  New York  40.708546 -74.011041   \n",
       "5                                  2090906.36  New York  40.704380 -74.006427   \n",
       "..                                        ...       ...        ...        ...   \n",
       "443                                  36644.27  Brooklyn  40.653997 -74.009925   \n",
       "444                                  56547.18  Brooklyn  40.703301 -73.992047   \n",
       "445                                 965843.58  Brooklyn  40.704425 -73.936010   \n",
       "446                                   3585.40  Brooklyn  40.702869 -73.936466   \n",
       "448                                  12287.32  Brooklyn  40.679518 -73.956819   \n",
       "\n",
       "    Community Board  Council District  Census Tract        BIN           BBL  \\\n",
       "1             101.0               1.0          21.0  1001409.0  1.001250e+09   \n",
       "2             101.0               1.0           7.0  1000875.0  1.000380e+09   \n",
       "3             307.0              38.0           2.0  3398687.0  3.006950e+09   \n",
       "4             101.0               1.0           7.0  1001026.0  1.000478e+09   \n",
       "5             101.0               1.0           7.0  1000871.0  1.000370e+09   \n",
       "..              ...               ...           ...        ...           ...   \n",
       "443           307.0              38.0           2.0  3010468.0  3.007070e+09   \n",
       "444           302.0              33.0          21.0  3000019.0  3.000260e+09   \n",
       "445           301.0              34.0         485.0  3071539.0  3.031090e+09   \n",
       "446           301.0              34.0         485.0  3071625.0  3.031230e+09   \n",
       "448           308.0              35.0         305.0  3027572.0  3.011260e+09   \n",
       "\n",
       "                                                  NTA  \n",
       "1              SoHo-TriBeCa-Civic Center-Little Italy  \n",
       "2                   Battery Park City-Lower Manhattan  \n",
       "3                                    Sunset Park West  \n",
       "4                   Battery Park City-Lower Manhattan  \n",
       "5                   Battery Park City-Lower Manhattan  \n",
       "..                                                ...  \n",
       "443                                  Sunset Park West  \n",
       "444  DUMBO-Vinegar Hill-Downtown Brooklyn-Boerum Hill  \n",
       "445                                    Bushwick South  \n",
       "446                                    Bushwick South  \n",
       "448                               Crown Heights North  \n",
       "\n",
       "[306 rows x 26 columns]"
      ]
     },
     "execution_count": 215,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "### \n",
    "NTA = energy[energy.groupby('NTA')['NTA'].transform('size') >= 5]\n",
    "NTA\n",
    "\n",
    "### This code also works perfectly fine\n",
    "# v = energy.NTA.value_counts()\n",
    "# NTA1 = energy[energy.NTA.isin(v.index[v.gt(4)])] ### get all items which have more than 4 readings\n",
    "# NTA1\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 216,
   "id": "372c5d1e",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "NTA\n",
      "Battery Park City-Lower Manhattan                   4229017.17\n",
      "Bushwick South                                       261404.55\n",
      "Carroll Gardens-Columbia Street-Red Hook             267711.29\n",
      "College Point                                        120115.61\n",
      "Crown Heights North                                   36326.69\n",
      "DUMBO-Vinegar Hill-Downtown Brooklyn-Boerum Hill     599503.40\n",
      "East New York                                        435897.84\n",
      "East Williamsburg                                    153896.89\n",
      "Greenpoint                                           136551.09\n",
      "Hunters Point-Sunnyside-West Maspeth                1794854.92\n",
      "Hunts Point                                          510198.21\n",
      "Manhattanville                                        24848.00\n",
      "Maspeth                                               59924.55\n",
      "Mott Haven-Port Morris                               249815.13\n",
      "Queensbridge-Ravenswood-Long Island City             989292.33\n",
      "SoHo-TriBeCa-Civic Center-Little Italy               186070.12\n",
      "Springfield Gardens South-Brookville                  88788.31\n",
      "Steinway                                              78590.09\n",
      "Sunset Park West                                     687214.89\n",
      "park-cemetery-etc-Brooklyn                           214911.29\n",
      "Name: Total Savings, dtype: float64\n",
      "Hunters Point-Sunnyside-West Maspeth                75\n",
      "Sunset Park West                                    48\n",
      "Queensbridge-Ravenswood-Long Island City            16\n",
      "park-cemetery-etc-Brooklyn                          15\n",
      "Mott Haven-Port Morris                              14\n",
      "Greenpoint                                          14\n",
      "Hunts Point                                         13\n",
      "East Williamsburg                                   11\n",
      "Carroll Gardens-Columbia Street-Red Hook            11\n",
      "DUMBO-Vinegar Hill-Downtown Brooklyn-Boerum Hill    10\n",
      "Bushwick South                                      10\n",
      "Manhattanville                                       9\n",
      "Maspeth                                              9\n",
      "East New York                                        9\n",
      "Crown Heights North                                  9\n",
      "Battery Park City-Lower Manhattan                    9\n",
      "Steinway                                             7\n",
      "College Point                                        7\n",
      "Springfield Gardens South-Brookville                 5\n",
      "SoHo-TriBeCa-Civic Center-Little Italy               5\n",
      "Name: NTA, dtype: int64\n",
      "Battery Park City-Lower Manhattan                   469890.796667\n",
      "Bushwick South                                       26140.455000\n",
      "Carroll Gardens-Columbia Street-Red Hook             24337.390000\n",
      "College Point                                        17159.372857\n",
      "Crown Heights North                                   4036.298889\n",
      "DUMBO-Vinegar Hill-Downtown Brooklyn-Boerum Hill     59950.340000\n",
      "East New York                                        48433.093333\n",
      "East Williamsburg                                    13990.626364\n",
      "Greenpoint                                            9753.649286\n",
      "Hunters Point-Sunnyside-West Maspeth                 23931.398933\n",
      "Hunts Point                                          39246.016154\n",
      "Manhattanville                                        2760.888889\n",
      "Maspeth                                               6658.283333\n",
      "Mott Haven-Port Morris                               17843.937857\n",
      "Queensbridge-Ravenswood-Long Island City             61830.770625\n",
      "SoHo-TriBeCa-Civic Center-Little Italy               37214.024000\n",
      "Springfield Gardens South-Brookville                 17757.662000\n",
      "Steinway                                             11227.155714\n",
      "Sunset Park West                                     14316.976875\n",
      "park-cemetery-etc-Brooklyn                           14327.419333\n",
      "dtype: float64\n",
      "NTA\n",
      "Battery Park City-Lower Manhattan                    0.0\n",
      "Bushwick South                                      10.0\n",
      "Carroll Gardens-Columbia Street-Red Hook             0.0\n",
      "College Point                                        2.0\n",
      "Crown Heights North                                  0.0\n",
      "DUMBO-Vinegar Hill-Downtown Brooklyn-Boerum Hill     0.0\n",
      "East New York                                       15.0\n",
      "East Williamsburg                                    0.0\n",
      "Greenpoint                                           0.0\n",
      "Hunters Point-Sunnyside-West Maspeth                 0.0\n",
      "Hunts Point                                         12.0\n",
      "Manhattanville                                       0.0\n",
      "Maspeth                                             10.0\n",
      "Mott Haven-Port Morris                              10.0\n",
      "Queensbridge-Ravenswood-Long Island City             0.0\n",
      "SoHo-TriBeCa-Civic Center-Little Italy               0.0\n",
      "Springfield Gardens South-Brookville                 0.0\n",
      "Steinway                                            20.0\n",
      "Sunset Park West                                     0.0\n",
      "park-cemetery-etc-Brooklyn                           0.0\n",
      "Name: Job created, dtype: float64\n"
     ]
    }
   ],
   "source": [
    "NTA_Total = NTA.groupby('NTA')['Total Savings'].sum()\n",
    "NTA_Count = NTA['NTA'].value_counts()\n",
    "NTA_Avg = NTA_Total/NTA_Count\n",
    "NTA_Job_Created = NTA.groupby('NTA')['Job created'].sum()\n",
    "\n",
    "print(NTA_Total.head(25))\n",
    "print(NTA_Count.head(25))\n",
    "print(NTA_Avg.head(25))\n",
    "print(NTA_Job_Created.head(25))\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 226,
   "id": "79be9b64",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Total Savings</th>\n",
       "      <th>Total Bussiness</th>\n",
       "      <th>Job created</th>\n",
       "      <th>Average Saving</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>NTA</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Battery Park City-Lower Manhattan</th>\n",
       "      <td>4229017.17</td>\n",
       "      <td>9</td>\n",
       "      <td>0.0</td>\n",
       "      <td>469890.796667</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Bushwick South</th>\n",
       "      <td>261404.55</td>\n",
       "      <td>10</td>\n",
       "      <td>10.0</td>\n",
       "      <td>26140.455000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Carroll Gardens-Columbia Street-Red Hook</th>\n",
       "      <td>267711.29</td>\n",
       "      <td>11</td>\n",
       "      <td>0.0</td>\n",
       "      <td>24337.390000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>College Point</th>\n",
       "      <td>120115.61</td>\n",
       "      <td>7</td>\n",
       "      <td>2.0</td>\n",
       "      <td>17159.372857</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Crown Heights North</th>\n",
       "      <td>36326.69</td>\n",
       "      <td>9</td>\n",
       "      <td>0.0</td>\n",
       "      <td>4036.298889</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                          Total Savings  Total Bussiness  \\\n",
       "NTA                                                                        \n",
       "Battery Park City-Lower Manhattan            4229017.17                9   \n",
       "Bushwick South                                261404.55               10   \n",
       "Carroll Gardens-Columbia Street-Red Hook      267711.29               11   \n",
       "College Point                                 120115.61                7   \n",
       "Crown Heights North                            36326.69                9   \n",
       "\n",
       "                                          Job created  Average Saving  \n",
       "NTA                                                                    \n",
       "Battery Park City-Lower Manhattan                 0.0   469890.796667  \n",
       "Bushwick South                                   10.0    26140.455000  \n",
       "Carroll Gardens-Columbia Street-Red Hook          0.0    24337.390000  \n",
       "College Point                                     2.0    17159.372857  \n",
       "Crown Heights North                               0.0     4036.298889  "
      ]
     },
     "execution_count": 226,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# S = energy.groupby('City')['Job created'].sum()\n",
    "# S.head(600)\n",
    "\n",
    "### Save NTA datafarme\n",
    "NTA.to_csv('Value_of_Energy_Cost_Savings_Program_With_NTA_More_Than_Five.csv', index=False)\n",
    "\n",
    "NTA_data = NTA_Total.to_frame()\n",
    "NTA_data['Total Bussiness'] = NTA_Count\n",
    "NTA_data['Job created'] = NTA_Job_Created\n",
    "NTA_data['Average Saving'] = NTA_Avg\n",
    "# NTA_data.head()\n",
    "\n",
    "### Save NTA_data\n",
    "NTA_data.to_csv('Average_Energy_Cost_Savings_With_NTA_More_Than_Five.csv')\n",
    "\n",
    "# print(NTA_data)\n",
    "NTA_data.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 224,
   "id": "ff7fef16",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0, 0.5, 'Job created')"
      ]
     },
     "execution_count": 224,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "####### DAY 5 ########\n",
    "\n",
    "plt.plot(NTA_data['Average Saving'], NTA_data['Job created'],'o', color = 'k')\n",
    "plt.xlabel('Average Savings')\n",
    "plt.ylabel('Job created')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 225,
   "id": "9c81ea88",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0, 0.5, 'Job created')"
      ]
     },
     "execution_count": 225,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.plot(NTA_data['Average Saving'], NTA_data['Job created'],'o', color = 'k')\n",
    "plt.xscale('log')\n",
    "plt.xlabel('Average Savings')\n",
    "plt.ylabel('Job created')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 230,
   "id": "5a039d5d",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.hist(NTA_data['Average Saving'], bins=7)\n",
    "plt.xscale('log')\n",
    "# Add some formatting to the plot:\n",
    "plt.xlabel('Average Saving')\n",
    "plt.ylabel('Number of observations')\n",
    "plt.title('Average Saving Histogram');"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 261,
   "id": "1f46b4c4",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\sbsst\\AppData\\Local\\Temp/ipykernel_216768/1053078299.py:3: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame.\n",
      "Try using .loc[row_indexer,col_indexer] = value instead\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",
      "  Date_Job['dt'] = pd.to_datetime(Date_Job['Effective Date'])\n",
      "C:\\Users\\sbsst\\AppData\\Local\\Temp/ipykernel_216768/1053078299.py:4: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame.\n",
      "Try using .loc[row_indexer,col_indexer] = value instead\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",
      "  Date_Job['month'] = Date_Job['dt'].dt.strftime('%m')\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "month\n",
       "01     0.0\n",
       "02    27.0\n",
       "03    20.0\n",
       "04     2.0\n",
       "05     2.0\n",
       "06    63.0\n",
       "07    20.0\n",
       "08     0.0\n",
       "09     0.0\n",
       "10     0.0\n",
       "11     5.0\n",
       "12    10.0\n",
       "Name: Job created, dtype: float64"
      ]
     },
     "execution_count": 261,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from datetime import datetime\n",
    "Date_Job = energy[['Effective Date', 'Job created']]\n",
    "Date_Job['dt'] = pd.to_datetime(Date_Job['Effective Date'])\n",
    "Date_Job['month'] = Date_Job['dt'].dt.strftime('%m')\n",
    "Job_per_month = Date_Job.groupby('month')['Job created'].sum()\n",
    "Job_per_month"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 262,
   "id": "23bdd7a5",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "Job_per_month.plot(xlabel='Months',\n",
    "                       ylabel='Job created',\n",
    "                       title='Total Jobs Created Per Month');\n"
   ]
  }
 ],
 "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": "3.9.7"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}