notebooks/04_electric_disturbance_events.ipynb

{"cells":[{"cell_type":"markdown","metadata":{"id":"Hs4RRm6Vzd3U"},"source":["# Electric Disturbance Events"]},{"cell_type":"markdown","source":["## Install Dependencies"],"metadata":{"id":"ZnYZcgwUt2ib"}},{"cell_type":"code","source":["%%capture\n","%pip install pandas==1.3.5\n","%pip install numpy==1.21.6"],"metadata":{"id":"3NTi8ifut5pW","executionInfo":{"status":"ok","timestamp":1661191363693,"user_tz":300,"elapsed":12183,"user":{"displayName":"Garrett Woody","userId":"07956492903988148138"}}},"execution_count":1,"outputs":[]},{"cell_type":"markdown","metadata":{"id":"35aP1FlDzijs"},"source":["## Import Modules"]},{"cell_type":"code","execution_count":2,"metadata":{"id":"58wJUD7zzfvh","executionInfo":{"status":"ok","timestamp":1661191364392,"user_tz":300,"elapsed":723,"user":{"displayName":"Garrett Woody","userId":"07956492903988148138"}}},"outputs":[],"source":["import os\n","import pandas as pd\n","import numpy as np\n","\n","import warnings\n","warnings.simplefilter(action='ignore', category=FutureWarning)\n","pd.options.mode.chained_assignment = None"]},{"cell_type":"markdown","metadata":{"id":"3EqloWlsz14A"},"source":["## Mount Drive"]},{"cell_type":"code","execution_count":3,"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"rRgYpx2TzslK","executionInfo":{"status":"ok","timestamp":1661191380272,"user_tz":300,"elapsed":15885,"user":{"displayName":"Garrett Woody","userId":"07956492903988148138"}},"outputId":"ade4af7e-219f-4d07-f635-e56e8e251472"},"outputs":[{"output_type":"stream","name":"stdout","text":["Drive not mounted, so nothing to flush and unmount.\n","Mounted at /content/drive\n","\n","Current working directory is:\n","/content/drive/Shareddrives/capstone-power-grid-protagonists/project\n"]}],"source":["import os\n","\n","team_name = 'capstone-power-grid-protagonists'\n","colab_path = f'/content/drive/Shareddrives/{team_name}/project'\n","studiolab_path = f'/home/studio-lab-user/sagemaker-studiolab-notebooks/{team_name}'\n","\n","try:\n","    # Try to mount Google Drive and set project path\n","    from google.colab import drive\n","    drive.flush_and_unmount()\n","    drive.mount('/content/drive')\n","    print('')\n","\n","    root_path = colab_path\n","    os.chdir(root_path)\n","\n","except:\n","    try:\n","        # Try to set AWS SageMaker Studio Lab project path\n","        root_path = studiolab_path\n","        os.chdir(root_path)\n","    \n","    except:\n","        # Set current working directory as root path\n","        root_path = os.getcwd()\n","        os.chdir(root_path)\n","\n","        # If the current folder is 'notebooks', move up one level\n","        if root_path.endswith('/notebooks'):\n","            root_path = '/'.join(root_path.split('/')[:-1])\n","            os.chdir(root_path)\n","        \n","print('Current working directory is:')\n","print(os.getcwd())"]},{"cell_type":"markdown","metadata":{"id":"_ZZTkIY40rFu"},"source":["## Import Data"]},{"cell_type":"code","execution_count":4,"metadata":{"id":"DY5N7BWsz56g","executionInfo":{"status":"ok","timestamp":1661191384238,"user_tz":300,"elapsed":3972,"user":{"displayName":"Garrett Woody","userId":"07956492903988148138"}}},"outputs":[],"source":["# Columns to exclude in case notebook is being re-run\n","exclude = ['weight', 'outage', 'disturbance_prob', 'outage_prob', 'potential_population_affected', 'ba_affected']\n","\n","# Processed data\n","cols = list(pd.read_csv('data/processed/hifld/power_plants.csv', nrows =1))\n","plants = pd.read_csv('data/processed/hifld/power_plants.csv',\n","                     low_memory=False,\n","                     usecols=[i for i in cols if i not in exclude])\n","\n","cols = list(pd.read_csv('data/processed/hifld/substations.csv', nrows =1))\n","subs = pd.read_csv('data/processed/hifld/substations.csv',\n","                   low_memory=False,\n","                   usecols=[i for i in cols if i not in exclude])\n","\n","cols = list(pd.read_csv('data/processed/eia/balancing_authorities.csv', nrows =1))\n","bas = pd.read_csv('data/processed/eia/balancing_authorities.csv',\n","                  low_memory=False,\n","                  usecols=[i for i in cols if i not in exclude])\n","\n","cols = list(pd.read_csv('data/processed/doe/disturbances.csv', nrows =1))\n","disturb = pd.read_csv('data/processed/doe/disturbances.csv',\n","                      low_memory=False,\n","                      usecols=[i for i in cols if i not in exclude],\n","                      dtype={'event_type': 'category'},\n","                      parse_dates=['date_start', 'date_end'])\n","\n","egrid = pd.read_csv('data/processed/epa/egrid.csv',\n","                    low_memory=False,\n","                    usecols=['orispl', 'fipscnty','pstatabb','bacode'])\n","egrid.dropna(subset=['bacode'], inplace=True)\n","egrid.drop_duplicates(inplace=True)"]},{"cell_type":"code","source":["# Import states and abbreviations\n","states = pd.read_csv('data/raw/doe/states.csv',\n","                     header=None,\n","                     names=['name', 'abbr'])\n","states = dict(states.values)\n","\n","# Import census data\n","census = pd.read_csv('data/raw/doe/census.csv',\n","                     usecols=['SUMLEV', 'STATE', 'COUNTY', 'STNAME','CTYNAME','POPESTIMATE2021'],\n","                     encoding='latin-1')\n","census.columns = census.columns.str.lower()\n","census['stname'] = census['stname'].apply(lambda x: states[x] if x in states.keys() else np.NaN)\n","census['county'] = census['county'].astype(str).str.pad(width=3, side='left', fillchar='0')\n","census['county'] = census['state'].astype(str) + census['county']\n","census['county'] = census['county'].astype('int64')"],"metadata":{"id":"O91ryoI8hqHk","executionInfo":{"status":"ok","timestamp":1661191385241,"user_tz":300,"elapsed":1026,"user":{"displayName":"Garrett Woody","userId":"07956492903988148138"}}},"execution_count":5,"outputs":[]},{"cell_type":"markdown","metadata":{"id":"V6_AvinQvFlO"},"source":["## Analysis"]},{"cell_type":"code","source":["# Assign a lower weight to those disturbances where there is not county specified and only a state\n","disturb['weight'] = 1\n","disturb.loc[disturb['county_affected'].isna(), 'weight'] = .25\n","\n","# Assign a boolean value as to whether there was an actual outage\n","disturb['outage'] = 0\n","disturb.loc[(disturb['demand_loss_mw'] > 0) | (disturb['num_customers_affected'] > 0), 'outage'] = 1"],"metadata":{"id":"teycHkTVfpFD","executionInfo":{"status":"ok","timestamp":1661191385242,"user_tz":300,"elapsed":7,"user":{"displayName":"Garrett Woody","userId":"07956492903988148138"}}},"execution_count":6,"outputs":[]},{"cell_type":"markdown","source":["#### Population"],"metadata":{"id":"tkqtTplIgpim"}},{"cell_type":"code","source":["# Merge disturbances, power plants, and substations, with census population data\n","disturb = disturb.merge(census[census['sumlev']==50][['stname', 'ctyname', 'popestimate2021']],\n","                        how='left',\n","                        left_on=['state_affected', 'county_affected'],\n","                        right_on=['stname', 'ctyname']) \\\n","                 .rename(columns={'popestimate2021':'potential_population_affected'}) \\\n","                 .drop(columns=['stname', 'ctyname'])\n","\n","plants = plants.merge(census[['county', 'popestimate2021']],\n","                      how='left',\n","                      left_on=['countyfips'],\n","                      right_on=['county'],\n","                      suffixes=[None, '_census']) \\\n","               .rename(columns={'popestimate2021':'potential_population_affected'}) \\\n","               .drop(columns=['county_census'])\n","\n","subs = subs.merge(census[['county', 'popestimate2021']],\n","                  how='left',\n","                  left_on=['countyfips'],\n","                  right_on=['county'],\n","                  suffixes=[None, '_census']) \\\n","            .rename(columns={'popestimate2021':'potential_population_affected'}) \\\n","            .drop(columns=['county_census'])\n","\n","disturb = disturb.merge(census[census['sumlev']==40][['stname', 'popestimate2021']],\n","                        how='left',\n","                        left_on='state_affected',\n","                        right_on='stname') \\\n","                 .rename(columns={'popestimate2021':'state_population'}) \\\n","                 .drop(columns=['stname'])\n","\n","disturb['potential_population_affected'].fillna(disturb['state_population']*.25, inplace=True)\n","disturb.drop(columns=['state_population'], inplace=True)"],"metadata":{"id":"grBadscngkr4","executionInfo":{"status":"ok","timestamp":1661191385603,"user_tz":300,"elapsed":366,"user":{"displayName":"Garrett Woody","userId":"07956492903988148138"}}},"execution_count":7,"outputs":[]},{"cell_type":"markdown","source":["#### Balancing Authorities"],"metadata":{"id":"YdPopmpXgtgD"}},{"cell_type":"code","source":["orispl_count_by_ba = egrid.groupby(['fipscnty','bacode']).orispl.count().reset_index()\n","orispl_count_by_ba = orispl_count_by_ba.sort_values('orispl').drop_duplicates('fipscnty', keep='last')\n","\n","# Merge the balancing authority that is most likely affected\n","disturb = disturb.merge(orispl_count_by_ba[['bacode','fipscnty']],\n","                        how='left',\n","                        left_on='county_affected_fips',\n","                        right_on='fipscnty')\n","\n","disturb.rename(columns={'bacode': 'ba_affected'}, inplace=True)\n","\n","# If a balancing authority was not found by county, match by state\n","orispl_count_by_ba = egrid.groupby(['pstatabb','bacode']).orispl.count().reset_index()\n","orispl_count_by_ba = orispl_count_by_ba.sort_values('orispl').drop_duplicates('pstatabb', keep='last')\n","state_majority_ba_dict = dict(zip(orispl_count_by_ba.pstatabb, orispl_count_by_ba.bacode))\n","disturb['ba_affected_by_state'] = disturb['state_affected'].apply(lambda x: state_majority_ba_dict[x])\n","\n","disturb['ba_affected'].fillna(disturb['ba_affected_by_state'], inplace=True)\n","\n","disturb.reset_index(drop=True, inplace=True)"],"metadata":{"id":"Nwp_SbN9bfwJ","executionInfo":{"status":"ok","timestamp":1661191385604,"user_tz":300,"elapsed":14,"user":{"displayName":"Garrett Woody","userId":"07956492903988148138"}}},"execution_count":8,"outputs":[]},{"cell_type":"code","source":["# Calculate probability of a disturbance, whether there was an actual outage or not\n","bas = bas.merge(disturb.groupby('ba_affected')[['weight', 'potential_population_affected']].sum(),\n","                how='left',\n","                left_on='ba_code',\n","                right_on='ba_affected') \\\n","         .rename(columns={'weight': 'disturbance_count'})\n","\n","bas['disturbance_prob'] = bas['disturbance_count']/len(disturb['event_id'].unique())\n","bas['disturbance_prob'].fillna(0, inplace=True)\n","\n","bas.drop(columns=['disturbance_count'], inplace=True)"],"metadata":{"id":"4rVxgRA0m-FO","executionInfo":{"status":"ok","timestamp":1661191385605,"user_tz":300,"elapsed":13,"user":{"displayName":"Garrett Woody","userId":"07956492903988148138"}}},"execution_count":9,"outputs":[]},{"cell_type":"code","source":["# Calculate probability of an actual outage\n","bas = bas.merge(disturb[disturb['outage'] == 1].groupby('ba_affected')['weight'].sum(),\n","                how='left',\n","                left_on='ba_code',\n","                right_on='ba_affected') \\\n","         .rename(columns={'weight': 'outage_count'})\n","\n","bas['outage_prob'] = bas['outage_count']/len(disturb['event_id'].unique())\n","bas['outage_prob'].fillna(0, inplace=True)\n","\n","bas.drop(columns=['outage_count'], inplace=True)"],"metadata":{"id":"_hPPx_1YmjRq","executionInfo":{"status":"ok","timestamp":1661191385605,"user_tz":300,"elapsed":12,"user":{"displayName":"Garrett Woody","userId":"07956492903988148138"}}},"execution_count":10,"outputs":[]},{"cell_type":"markdown","source":["#### Power Plants"],"metadata":{"id":"ZByvqASng1DO"}},{"cell_type":"code","source":["# Calculate probability of a disturbance, whether there was an actual outage or not\n","plants = plants.merge(disturb.groupby('county_affected_fips')['weight'].sum(),\n","                      how='left',\n","                      left_on='countyfips',\n","                      right_on='county_affected_fips') \\\n","               .rename(columns={'weight': 'disturbance_count'})\n","\n","plants = plants.merge(disturb.groupby('state_affected')['weight'].sum(),\n","                      how='left',\n","                      left_on='state',\n","                      right_on='state_affected',\n","                      suffixes=[None, '_state']) \\\n","               .rename(columns={'weight': 'disturbance_count_state'})\n","\n","# If county data was not available, fill in data based on the state which has a lower weight\n","plants['disturbance_count'].fillna(plants['disturbance_count_state'], inplace=True)\n","\n","plants['disturbance_prob'] = plants['disturbance_count']/len(disturb['event_id'].unique())\n","plants['disturbance_prob'].fillna(0, inplace=True)\n","\n","plants.drop(columns=['disturbance_count', 'disturbance_count_state'], inplace=True)"],"metadata":{"id":"4JTfX3wugbes","executionInfo":{"status":"ok","timestamp":1661191385736,"user_tz":300,"elapsed":142,"user":{"displayName":"Garrett Woody","userId":"07956492903988148138"}}},"execution_count":11,"outputs":[]},{"cell_type":"code","source":["# Calculate probability of an actual outage\n","plants = plants.merge(disturb[disturb['outage'] == 1].groupby('county_affected_fips')['weight'].sum(),\n","                      how='left',\n","                      left_on='countyfips',\n","                      right_on='county_affected_fips') \\\n","               .rename(columns={'weight': 'outage_count'})\n","\n","plants = plants.merge(disturb[disturb['outage'] == 1].groupby('state_affected')['weight'].sum(),\n","                      how='left',\n","                      left_on='state',\n","                      right_on='state_affected') \\\n","               .rename(columns={'weight': 'outage_count_state'})\n","\n","plants['outage_count'].fillna(plants['outage_count_state'], inplace=True)\n","\n","plants['outage_prob'] = plants['outage_count']/len(disturb['event_id'].unique())\n","plants['outage_prob'].fillna(0, inplace=True)\n","\n","plants.drop(columns=['outage_count', 'outage_count_state'], inplace=True)"],"metadata":{"id":"96BC3QP6kT25","executionInfo":{"status":"ok","timestamp":1661191385899,"user_tz":300,"elapsed":166,"user":{"displayName":"Garrett Woody","userId":"07956492903988148138"}}},"execution_count":12,"outputs":[]},{"cell_type":"markdown","source":["#### Substations"],"metadata":{"id":"5yDOhJVjg4kc"}},{"cell_type":"code","source":["# Calculate probability of a disturbance, whether there was an actual outage or not\n","subs = subs.merge(disturb.groupby('county_affected_fips')['weight'].sum(),\n","                      how='left',\n","                      left_on='countyfips',\n","                      right_on='county_affected_fips') \\\n","               .rename(columns={'weight': 'disturbance_count'})\n","\n","subs = subs.merge(disturb.groupby('state_affected')['weight'].sum(),\n","                      how='left',\n","                      left_on='state',\n","                      right_on='state_affected',\n","                      suffixes=[None, '_state']) \\\n","               .rename(columns={'weight': 'disturbance_count_state'})\n","\n","# If county data was not available, fill in data based on the state which has a lower weight\n","subs['disturbance_count'].fillna(subs['disturbance_count_state'], inplace=True)\n","\n","subs['disturbance_prob'] = subs['disturbance_count']/len(disturb['event_id'].unique())\n","subs['disturbance_prob'].fillna(0, inplace=True)\n","\n","subs.drop(columns=['disturbance_count', 'disturbance_count_state'], inplace=True)"],"metadata":{"id":"fjxokJ-xk_Op","executionInfo":{"status":"ok","timestamp":1661191386269,"user_tz":300,"elapsed":372,"user":{"displayName":"Garrett Woody","userId":"07956492903988148138"}}},"execution_count":13,"outputs":[]},{"cell_type":"code","source":["# Calculate probability of an actual outage\n","subs = subs.merge(disturb[disturb['outage'] == 1].groupby('county_affected_fips')['weight'].sum(),\n","                      how='left',\n","                      left_on='countyfips',\n","                      right_on='county_affected_fips') \\\n","               .rename(columns={'weight': 'outage_count'})\n","\n","subs = subs.merge(disturb[disturb['outage'] == 1].groupby('state_affected')['weight'].sum(),\n","                      how='left',\n","                      left_on='state',\n","                      right_on='state_affected') \\\n","               .rename(columns={'weight': 'outage_count_state'})\n","\n","subs['outage_count'].fillna(subs['outage_count_state'], inplace=True)\n","\n","subs['outage_prob'] = subs['outage_count']/len(disturb['event_id'].unique())\n","subs['outage_prob'].fillna(0, inplace=True)\n","\n","subs.drop(columns=['outage_count', 'outage_count_state'], inplace=True)"],"metadata":{"id":"Dkn-hlYUk_mb","executionInfo":{"status":"ok","timestamp":1661191386634,"user_tz":300,"elapsed":370,"user":{"displayName":"Garrett Woody","userId":"07956492903988148138"}}},"execution_count":14,"outputs":[]},{"cell_type":"markdown","metadata":{"id":"FpagBFgWYxY8"},"source":["## Enriched Output"]},{"cell_type":"code","source":["plants.sample(3)"],"metadata":{"colab":{"base_uri":"https://localhost:8080/","height":393},"id":"35iaPemLoPnz","executionInfo":{"status":"ok","timestamp":1661191386634,"user_tz":300,"elapsed":8,"user":{"displayName":"Garrett Woody","userId":"07956492903988148138"}},"outputId":"98f03315-4313-4a52-e93e-d64bdb2c0a90"},"execution_count":15,"outputs":[{"output_type":"execute_result","data":{"text/plain":["     plant_code               name            address              city state  \\\n","6324      57590  Minco Wind I, Llc    491 County Road             Minco    OK   \n","2752       7869   Glenwood Landing     400 Shore Road  Glenwood Landing    NY   \n","9030      60423        Fairhaven C  197 New Boston Rd         Fairhaven    MA   \n","\n","        zip       telephone  \\\n","6324  73059  (561) 691-7171   \n","2752  11547  (800) 642-4272   \n","9030   2719             NaN   \n","\n","                                                   type status   county  ...  \\\n","6324                               Onshore Wind Turbine     Op    Grady  ...   \n","2752  Natural Gas Fired Combustion Turbine; Petroleu...     Op   Nassau  ...   \n","9030                                 Solar Photovoltaic     Op  Bristol  ...   \n","\n","       net_gen cap_factor  lines  source_lat  source_lon connected_sub  \\\n","6324  281073.0   0.323447      0   35.280278  -97.975556           NaN   \n","2752   80093.0   0.093583      1   40.827500  -73.647800        124150   \n","9030    2925.0   0.208690      0   41.663030  -70.863230           NaN   \n","\n","     connected_ba potential_population_affected disturbance_prob outage_prob  \n","6324         SWPP                       55508.0         0.011155    0.006751  \n","2752         NYIS                     1390907.0         0.000783    0.000783  \n","9030         ISNE                      580164.0         0.009393    0.005969  \n","\n","[3 rows x 46 columns]"],"text/html":["\n","  <div id=\"df-7bd1c997-aaa6-400e-8a60-d996a8622f33\">\n","    <div class=\"colab-df-container\">\n","      <div>\n","<style scoped>\n","    .dataframe tbody tr th:only-of-type {\n","        vertical-align: middle;\n","    }\n","\n","    .dataframe tbody tr th {\n","        vertical-align: top;\n","    }\n","\n","    .dataframe thead th {\n","        text-align: right;\n","    }\n","</style>\n","<table border=\"1\" class=\"dataframe\">\n","  <thead>\n","    <tr style=\"text-align: right;\">\n","      <th></th>\n","      <th>plant_code</th>\n","      <th>name</th>\n","      <th>address</th>\n","      <th>city</th>\n","      <th>state</th>\n","      <th>zip</th>\n","      <th>telephone</th>\n","      <th>type</th>\n","      <th>status</th>\n","      <th>county</th>\n","      <th>...</th>\n","      <th>net_gen</th>\n","      <th>cap_factor</th>\n","      <th>lines</th>\n","      <th>source_lat</th>\n","      <th>source_lon</th>\n","      <th>connected_sub</th>\n","      <th>connected_ba</th>\n","      <th>potential_population_affected</th>\n","      <th>disturbance_prob</th>\n","      <th>outage_prob</th>\n","    </tr>\n","  </thead>\n","  <tbody>\n","    <tr>\n","      <th>6324</th>\n","      <td>57590</td>\n","      <td>Minco Wind I, Llc</td>\n","      <td>491 County Road</td>\n","      <td>Minco</td>\n","      <td>OK</td>\n","      <td>73059</td>\n","      <td>(561) 691-7171</td>\n","      <td>Onshore Wind Turbine</td>\n","      <td>Op</td>\n","      <td>Grady</td>\n","      <td>...</td>\n","      <td>281073.0</td>\n","      <td>0.323447</td>\n","      <td>0</td>\n","      <td>35.280278</td>\n","      <td>-97.975556</td>\n","      <td>NaN</td>\n","      <td>SWPP</td>\n","      <td>55508.0</td>\n","      <td>0.011155</td>\n","      <td>0.006751</td>\n","    </tr>\n","    <tr>\n","      <th>2752</th>\n","      <td>7869</td>\n","      <td>Glenwood Landing</td>\n","      <td>400 Shore Road</td>\n","      <td>Glenwood Landing</td>\n","      <td>NY</td>\n","      <td>11547</td>\n","      <td>(800) 642-4272</td>\n","      <td>Natural Gas Fired Combustion Turbine; Petroleu...</td>\n","      <td>Op</td>\n","      <td>Nassau</td>\n","      <td>...</td>\n","      <td>80093.0</td>\n","      <td>0.093583</td>\n","      <td>1</td>\n","      <td>40.827500</td>\n","      <td>-73.647800</td>\n","      <td>124150</td>\n","      <td>NYIS</td>\n","      <td>1390907.0</td>\n","      <td>0.000783</td>\n","      <td>0.000783</td>\n","    </tr>\n","    <tr>\n","      <th>9030</th>\n","      <td>60423</td>\n","      <td>Fairhaven C</td>\n","      <td>197 New Boston Rd</td>\n","      <td>Fairhaven</td>\n","      <td>MA</td>\n","      <td>2719</td>\n","      <td>NaN</td>\n","      <td>Solar Photovoltaic</td>\n","      <td>Op</td>\n","      <td>Bristol</td>\n","      <td>...</td>\n","      <td>2925.0</td>\n","      <td>0.208690</td>\n","      <td>0</td>\n","      <td>41.663030</td>\n","      <td>-70.863230</td>\n","      <td>NaN</td>\n","      <td>ISNE</td>\n","      <td>580164.0</td>\n","      <td>0.009393</td>\n","      <td>0.005969</td>\n","    </tr>\n","  </tbody>\n","</table>\n","<p>3 rows × 46 columns</p>\n","</div>\n","      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-7bd1c997-aaa6-400e-8a60-d996a8622f33')\"\n","              title=\"Convert this dataframe to an interactive table.\"\n","              style=\"display:none;\">\n","        \n","  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n","       width=\"24px\">\n","    <path d=\"M0 0h24v24H0V0z\" fill=\"none\"/>\n","    <path d=\"M18.56 5.44l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94zm-11 1L8.5 8.5l.94-2.06 2.06-.94-2.06-.94L8.5 2.5l-.94 2.06-2.06.94zm10 10l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94z\"/><path d=\"M17.41 7.96l-1.37-1.37c-.4-.4-.92-.59-1.43-.59-.52 0-1.04.2-1.43.59L10.3 9.45l-7.72 7.72c-.78.78-.78 2.05 0 2.83L4 21.41c.39.39.9.59 1.41.59.51 0 1.02-.2 1.41-.59l7.78-7.78 2.81-2.81c.8-.78.8-2.07 0-2.86zM5.41 20L4 18.59l7.72-7.72 1.47 1.35L5.41 20z\"/>\n","  </svg>\n","      </button>\n","      \n","  <style>\n","    .colab-df-container {\n","      display:flex;\n","      flex-wrap:wrap;\n","      gap: 12px;\n","    }\n","\n","    .colab-df-convert {\n","      background-color: #E8F0FE;\n","      border: none;\n","      border-radius: 50%;\n","      cursor: pointer;\n","      display: none;\n","      fill: #1967D2;\n","      height: 32px;\n","      padding: 0 0 0 0;\n","      width: 32px;\n","    }\n","\n","    .colab-df-convert:hover {\n","      background-color: #E2EBFA;\n","      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n","      fill: #174EA6;\n","    }\n","\n","    [theme=dark] .colab-df-convert {\n","      background-color: #3B4455;\n","      fill: #D2E3FC;\n","    }\n","\n","    [theme=dark] .colab-df-convert:hover {\n","      background-color: #434B5C;\n","      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n","      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n","      fill: #FFFFFF;\n","    }\n","  </style>\n","\n","      <script>\n","        const buttonEl =\n","          document.querySelector('#df-7bd1c997-aaa6-400e-8a60-d996a8622f33 button.colab-df-convert');\n","        buttonEl.style.display =\n","          google.colab.kernel.accessAllowed ? 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Y           NaN  0.000044  0.000017        0.0   \n","19244          Y        133141  0.000067  0.000040        0.0   \n","\n","      potential_population_affected  disturbance_prob  outage_prob  \n","64648                       16179.0          0.000391     0.000391  \n","37076                     1497987.0          0.000783     0.000783  \n","19244                      572114.0          0.012133     0.008023  \n","\n","[3 rows x 30 columns]"],"text/html":["\n","  <div id=\"df-fb425b70-42e8-4d0b-9e1e-a675bddbf906\">\n","    <div class=\"colab-df-container\">\n","      <div>\n","<style scoped>\n","    .dataframe tbody tr th:only-of-type {\n","        vertical-align: middle;\n","    }\n","\n","    .dataframe tbody tr th {\n","        vertical-align: top;\n","    }\n","\n","    .dataframe thead th {\n","        text-align: right;\n","    }\n","</style>\n","<table border=\"1\" class=\"dataframe\">\n","  <thead>\n","    <tr style=\"text-align: right;\">\n","      <th></th>\n","      <th>sub_code</th>\n","      <th>name</th>\n","      <th>city</th>\n","      <th>state</th>\n","      <th>zip</th>\n","      <th>type</th>\n","      <th>status</th>\n","      <th>county</th>\n","      <th>countyfips</th>\n","      <th>country</th>\n","      <th>...</th>\n","      <th>min_volt</th>\n","      <th>max_infer</th>\n","      <th>min_infer</th>\n","      <th>connected_sub</th>\n","      <th>deg_cent</th>\n","      <th>bet_cent</th>\n","      <th>clust_coef</th>\n","      <th>potential_population_affected</th>\n","      <th>disturbance_prob</th>\n","      <th>outage_prob</th>\n","    </tr>\n","  </thead>\n","  <tbody>\n","    <tr>\n","      <th>64648</th>\n","      <td>208303</td>\n","      <td>Unknown208239</td>\n","      <td>Rocky Boy</td>\n","      <td>MT</td>\n","      <td>0</td>\n","      <td>Substation</td>\n","      <td>In Service</td>\n","      <td>Hill</td>\n","      <td>30041</td>\n","      <td>USA</td>\n","      <td>...</td>\n","      <td>69.0</td>\n","      <td>Y</td>\n","      <td>Y</td>\n","      <td>208302</td>\n","      <td>0.000022</td>\n","      <td>0.000000</td>\n","      <td>0.0</td>\n","      <td>16179.0</td>\n","      <td>0.000391</td>\n","      <td>0.000391</td>\n","    </tr>\n","    <tr>\n","      <th>37076</th>\n","      <td>151925</td>\n","      <td>Military Trail</td>\n","      <td>West Palm Beach</td>\n","      <td>FL</td>\n","      <td>33415</td>\n","      <td>Substation</td>\n","      <td>In Service</td>\n","      <td>Palm Beach</td>\n","      <td>12099</td>\n","      <td>USA</td>\n","      <td>...</td>\n","      <td>138.0</td>\n","      <td>Y</td>\n","      <td>Y</td>\n","      <td>NaN</td>\n","      <td>0.000044</td>\n","      <td>0.000017</td>\n","      <td>0.0</td>\n","      <td>1497987.0</td>\n","      <td>0.000783</td>\n","      <td>0.000783</td>\n","    </tr>\n","    <tr>\n","      <th>19244</th>\n","      <td>132616</td>\n","      <td>Aldene</td>\n","      <td>Cranford Twp</td>\n","      <td>NJ</td>\n","      <td>7016</td>\n","      <td>Substation</td>\n","      <td>In Service</td>\n","      <td>Union</td>\n","      <td>34039</td>\n","      <td>USA</td>\n","      <td>...</td>\n","      <td>230.0</td>\n","      <td>Y</td>\n","      <td>Y</td>\n","      <td>133141</td>\n","      <td>0.000067</td>\n","      <td>0.000040</td>\n","      <td>0.0</td>\n","      <td>572114.0</td>\n","      <td>0.012133</td>\n","      <td>0.008023</td>\n","    </tr>\n","  </tbody>\n","</table>\n","<p>3 rows × 30 columns</p>\n","</div>\n","      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-fb425b70-42e8-4d0b-9e1e-a675bddbf906')\"\n","              title=\"Convert this dataframe to an interactive table.\"\n","              style=\"display:none;\">\n","        \n","  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n","       width=\"24px\">\n","    <path d=\"M0 0h24v24H0V0z\" fill=\"none\"/>\n","    <path d=\"M18.56 5.44l.94 2.06.94-2.06 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CISO  37.614709 -120.720719  0.001109  4.515416e-06    0.044944   \n","12   BPAT; CHPD  48.172212 -119.686599  0.000475  9.030831e-07    0.307692   \n","66         NBSO  46.000000  -75.140082  0.000634  2.023378e-04    0.500000   \n","\n","    potential_population_affected  disturbance_prob  outage_prob  \n","56                      2211996.0          0.001566     0.000391  \n","12                        42634.0          0.000391     0.000391  \n","66                            NaN          0.000000     0.000000  "],"text/html":["\n","  <div id=\"df-a8954f89-0cb6-4c58-b40a-92ab5e00ba21\">\n","    <div class=\"colab-df-container\">\n","      <div>\n","<style scoped>\n","    .dataframe tbody tr th:only-of-type {\n","        vertical-align: middle;\n","    }\n","\n","    .dataframe tbody tr th {\n","        vertical-align: top;\n","    }\n","\n","    .dataframe thead th {\n","        text-align: right;\n","    }\n","</style>\n","<table border=\"1\" class=\"dataframe\">\n","  <thead>\n","    <tr style=\"text-align: right;\">\n","      <th></th>\n","      <th>ba_code</th>\n","      <th>ba_name</th>\n","      <th>time_zone</th>\n","      <th>region_country_code</th>\n","      <th>region_country_name</th>\n","      <th>generation_only_ba</th>\n","      <th>demand_by_ba_subregion</th>\n","      <th>us_ba</th>\n","      <th>connected_ba</th>\n","      <th>lat</th>\n","      <th>lon</th>\n","      <th>deg_cent</th>\n","      <th>bet_cent</th>\n","      <th>clust_coef</th>\n","      <th>potential_population_affected</th>\n","      <th>disturbance_prob</th>\n","      <th>outage_prob</th>\n","    </tr>\n","  </thead>\n","  <tbody>\n","    <tr>\n","      <th>56</th>\n","      <td>TIDC</td>\n","      <td>Turlock Irrigation District</td>\n","      <td>Pacific</td>\n","      <td>CAL</td>\n","      <td>California</td>\n","      <td>No</td>\n","      <td>No</td>\n","      <td>Yes</td>\n","      <td>BANC; CISO</td>\n","      <td>37.614709</td>\n","      <td>-120.720719</td>\n","      <td>0.001109</td>\n","      <td>4.515416e-06</td>\n","      <td>0.044944</td>\n","      <td>2211996.0</td>\n","      <td>0.001566</td>\n","      <td>0.000391</td>\n","    </tr>\n","    <tr>\n","      <th>12</th>\n","      <td>DOPD</td>\n","      <td>PUD No. 1 of Douglas County</td>\n","      <td>Pacific</td>\n","      <td>NW</td>\n","      <td>Northwest</td>\n","      <td>No</td>\n","      <td>No</td>\n","      <td>Yes</td>\n","      <td>BPAT; CHPD</td>\n","      <td>48.172212</td>\n","      <td>-119.686599</td>\n","      <td>0.000475</td>\n","      <td>9.030831e-07</td>\n","      <td>0.307692</td>\n","      <td>42634.0</td>\n","      <td>0.000391</td>\n","      <td>0.000391</td>\n","    </tr>\n","    <tr>\n","      <th>66</th>\n","      <td>HQT</td>\n","      <td>Hydro-Quebec TransEnergie</td>\n","      <td>NaN</td>\n","      <td>CAN</td>\n","      <td>Canada</td>\n","      <td>No</td>\n","      <td>No</td>\n","      <td>No</td>\n","      <td>NBSO</td>\n","      <td>46.000000</td>\n","      <td>-75.140082</td>\n","      <td>0.000634</td>\n","      <td>2.023378e-04</td>\n","      <td>0.500000</td>\n","      <td>NaN</td>\n","      <td>0.000000</td>\n","      <td>0.000000</td>\n","    </tr>\n","  </tbody>\n","</table>\n","</div>\n","      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-a8954f89-0cb6-4c58-b40a-92ab5e00ba21')\"\n","              title=\"Convert this dataframe to an interactive table.\"\n","              style=\"display:none;\">\n","        \n","  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n","       width=\"24px\">\n","    <path d=\"M0 0h24v24H0V0z\" fill=\"none\"/>\n","    <path d=\"M18.56 5.44l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94zm-11 1L8.5 8.5l.94-2.06 2.06-.94-2.06-.94L8.5 2.5l-.94 2.06-2.06.94zm10 10l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94z\"/><path d=\"M17.41 7.96l-1.37-1.37c-.4-.4-.92-.59-1.43-.59-.52 0-1.04.2-1.43.59L10.3 9.45l-7.72 7.72c-.78.78-.78 2.05 0 2.83L4 21.41c.39.39.9.59 1.41.59.51 0 1.02-.2 1.41-.59l7.78-7.78 2.81-2.81c.8-.78.8-2.07 0-2.86zM5.41 20L4 18.59l7.72-7.72 1.47 1.35L5.41 20z\"/>\n","  </svg>\n","      </button>\n","      \n","  <style>\n","    .colab-df-container {\n","      display:flex;\n","      flex-wrap:wrap;\n","      gap: 12px;\n","    }\n","\n","    .colab-df-convert {\n","      background-color: #E8F0FE;\n","      border: none;\n","      border-radius: 50%;\n","      cursor: pointer;\n","      display: none;\n","      fill: #1967D2;\n","      height: 32px;\n","      padding: 0 0 0 0;\n","      width: 32px;\n","    }\n","\n","    .colab-df-convert:hover {\n","      background-color: #E2EBFA;\n","      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n","      fill: #174EA6;\n","    }\n","\n","    [theme=dark] .colab-df-convert {\n","      background-color: #3B4455;\n","      fill: #D2E3FC;\n","    }\n","\n","    [theme=dark] .colab-df-convert:hover {\n","      background-color: #434B5C;\n","      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n","      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n","      fill: #FFFFFF;\n","    }\n","  </style>\n","\n","      <script>\n","        const buttonEl =\n","          document.querySelector('#df-a8954f89-0cb6-4c58-b40a-92ab5e00ba21 button.colab-df-convert');\n","        buttonEl.style.display =\n","          google.colab.kernel.accessAllowed ? 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0.0   \n","168        system_operations             0.0                     0.0   \n","\n","      potential_population_affected  \n","3305                      858527.00  \n","3099                     1542046.75  \n","168                       849316.00  "],"text/html":["\n","  <div id=\"df-b69146d3-a542-4139-8bfb-8bf25bf92dc2\">\n","    <div class=\"colab-df-container\">\n","      <div>\n","<style scoped>\n","    .dataframe tbody tr th:only-of-type {\n","        vertical-align: middle;\n","    }\n","\n","    .dataframe tbody tr th {\n","        vertical-align: top;\n","    }\n","\n","    .dataframe thead th {\n","        text-align: right;\n","    }\n","</style>\n","<table border=\"1\" class=\"dataframe\">\n","  <thead>\n","    <tr style=\"text-align: right;\">\n","      <th></th>\n","      <th>event_id</th>\n","      <th>date_start</th>\n","      <th>date_end</th>\n","      <th>state_affected</th>\n","      <th>county_affected</th>\n","      <th>county_affected_fips</th>\n","      <th>ba_affected</th>\n","      <th>nerc_region</th>\n","      <th>event_type</th>\n","      <th>demand_loss_mw</th>\n","      <th>num_customers_affected</th>\n","      <th>potential_population_affected</th>\n","    </tr>\n","  </thead>\n","  <tbody>\n","    <tr>\n","      <th>3305</th>\n","      <td>1703</td>\n","      <td>2015-05-25 22:45:00</td>\n","      <td>2015-05-28 01:25:00</td>\n","      <td>TX</td>\n","      <td>Fort Bend County</td>\n","      <td>48157.0</td>\n","      <td>ERCO</td>\n","      <td>TRE</td>\n","      <td>severe_weather</td>\n","      <td>NaN</td>\n","      <td>61000.0</td>\n","      <td>858527.00</td>\n","    </tr>\n","    <tr>\n","      <th>3099</th>\n","      <td>1564</td>\n","      <td>2016-05-24 08:00:00</td>\n","      <td>1900-12-01 00:00:00</td>\n","      <td>MO</td>\n","      <td>NaN</td>\n","      <td>NaN</td>\n","      <td>SWPP</td>\n","      <td>SERC</td>\n","      <td>vandalism/cyber_attack</td>\n","      <td>0.0</td>\n","      <td>0.0</td>\n","      <td>1542046.75</td>\n","    </tr>\n","    <tr>\n","      <th>168</th>\n","      <td>91</td>\n","      <td>2021-11-16 17:37:00</td>\n","      <td>2021-11-16 18:21:00</td>\n","      <td>MD</td>\n","      <td>Baltimore County</td>\n","      <td>24005.0</td>\n","      <td>PJM</td>\n","      <td>RF</td>\n","      <td>system_operations</td>\n","      <td>0.0</td>\n","      <td>0.0</td>\n","      <td>849316.00</td>\n","    </tr>\n","  </tbody>\n","</table>\n","</div>\n","      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-b69146d3-a542-4139-8bfb-8bf25bf92dc2')\"\n","              title=\"Convert this dataframe to an interactive table.\"\n","              style=\"display:none;\">\n","        \n","  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n","       width=\"24px\">\n","    <path d=\"M0 0h24v24H0V0z\" fill=\"none\"/>\n","    <path d=\"M18.56 5.44l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94zm-11 1L8.5 8.5l.94-2.06 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