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asterias/seaborn_tutorial.ipynb

Created May 20, 2016 02:56
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seaborn_tutorial.ipynb
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"%matplotlib inline\n",
"import numpy as np\n",
"import matplotlib as mpl\n",
"import matplotlib.pyplot as plt"
]
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"C:\\Users\\FDH\\Anaconda2\\lib\\site-packages\\pandas\\computation\\__init__.py:19: UserWarning: The installed version of numexpr 2.4.4 is not supported in pandas and will be not be used\n",
"\n",
" UserWarning)\n"
]
}
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"source": [
"import seaborn as sns\n",
"from tqdm import tqdm"
]
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"import pandas as pd"
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"dataset1 = pd.read_csv(\"C:\\ds.txt\", sep=\";\", nrows = 300000, parse_dates=[0])"
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"date_means = dataset1.groupby(\"Date\").mean()"
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"<class 'pandas.core.frame.DataFrame'>\n",
"RangeIndex: 300000 entries, 0 to 299999\n",
"Data columns (total 9 columns):\n",
"Date 300000 non-null datetime64[ns]\n",
"Time 300000 non-null object\n",
"Global_active_power 300000 non-null float64\n",
"Global_reactive_power 300000 non-null float64\n",
"Voltage 300000 non-null float64\n",
"Global_intensity 300000 non-null float64\n",
"Sub_metering_1 300000 non-null float64\n",
"Sub_metering_2 300000 non-null float64\n",
"Sub_metering_3 296225 non-null float64\n",
"dtypes: datetime64[ns](1), float64(7), object(1)\n",
"memory usage: 19.5+ MB\n"
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}
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"dataset1.info()"
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" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>Date</th>\n",
" <th>Time</th>\n",
" <th>Global_active_power</th>\n",
" <th>Global_reactive_power</th>\n",
" <th>Voltage</th>\n",
" <th>Global_intensity</th>\n",
" <th>Sub_metering_1</th>\n",
" <th>Sub_metering_2</th>\n",
" <th>Sub_metering_3</th>\n",
" <th>season</th>\n",
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" <th>0</th>\n",
" <td>2006-12-16</td>\n",
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" <th>1</th>\n",
" <td>2006-12-16</td>\n",
" <td>17:25:00</td>\n",
" <td>5.360</td>\n",
" <td>0.436</td>\n",
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" <th>2</th>\n",
" <td>2006-12-16</td>\n",
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" <td>5.374</td>\n",
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" <tr>\n",
" <th>3</th>\n",
" <td>2006-12-16</td>\n",
" <td>17:27:00</td>\n",
" <td>5.388</td>\n",
" <td>0.502</td>\n",
" <td>233.74</td>\n",
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" <td>0.0</td>\n",
" <td>1.0</td>\n",
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" <td>Winter</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4</th>\n",
" <td>2006-12-16</td>\n",
" <td>17:28:00</td>\n",
" <td>3.666</td>\n",
" <td>0.528</td>\n",
" <td>235.68</td>\n",
" <td>15.8</td>\n",
" <td>0.0</td>\n",
" <td>1.0</td>\n",
" <td>17.0</td>\n",
" <td>Winter</td>\n",
" </tr>\n",
" <tr>\n",
" <th>5</th>\n",
" <td>2006-12-16</td>\n",
" <td>17:29:00</td>\n",
" <td>3.520</td>\n",
" <td>0.522</td>\n",
" <td>235.02</td>\n",
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" <td>0.0</td>\n",
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" </tr>\n",
" <tr>\n",
" <th>6</th>\n",
" <td>2006-12-16</td>\n",
" <td>17:30:00</td>\n",
" <td>3.702</td>\n",
" <td>0.520</td>\n",
" <td>235.09</td>\n",
" <td>15.8</td>\n",
" <td>0.0</td>\n",
" <td>1.0</td>\n",
" <td>17.0</td>\n",
" <td>Winter</td>\n",
" </tr>\n",
" <tr>\n",
" <th>7</th>\n",
" <td>2006-12-16</td>\n",
" <td>17:31:00</td>\n",
" <td>3.700</td>\n",
" <td>0.520</td>\n",
" <td>235.22</td>\n",
" <td>15.8</td>\n",
" <td>0.0</td>\n",
" <td>1.0</td>\n",
" <td>17.0</td>\n",
" <td>Winter</td>\n",
" </tr>\n",
" <tr>\n",
" <th>8</th>\n",
" <td>2006-12-16</td>\n",
" <td>17:32:00</td>\n",
" <td>3.668</td>\n",
" <td>0.510</td>\n",
" <td>233.99</td>\n",
" <td>15.8</td>\n",
" <td>0.0</td>\n",
" <td>1.0</td>\n",
" <td>17.0</td>\n",
" <td>Winter</td>\n",
" </tr>\n",
" <tr>\n",
" <th>9</th>\n",
" <td>2006-12-16</td>\n",
" <td>17:33:00</td>\n",
" <td>3.662</td>\n",
" <td>0.510</td>\n",
" <td>233.86</td>\n",
" <td>15.8</td>\n",
" <td>0.0</td>\n",
" <td>2.0</td>\n",
" <td>16.0</td>\n",
" <td>Winter</td>\n",
" </tr>\n",
" <tr>\n",
" <th>10</th>\n",
" <td>2006-12-16</td>\n",
" <td>17:34:00</td>\n",
" <td>4.448</td>\n",
" <td>0.498</td>\n",
" <td>232.86</td>\n",
" <td>19.6</td>\n",
" <td>0.0</td>\n",
" <td>1.0</td>\n",
" <td>17.0</td>\n",
" <td>Winter</td>\n",
" </tr>\n",
" <tr>\n",
" <th>11</th>\n",
" <td>2006-12-16</td>\n",
" <td>17:35:00</td>\n",
" <td>5.412</td>\n",
" <td>0.470</td>\n",
" <td>232.78</td>\n",
" <td>23.2</td>\n",
" <td>0.0</td>\n",
" <td>1.0</td>\n",
" <td>17.0</td>\n",
" <td>Winter</td>\n",
" </tr>\n",
" <tr>\n",
" <th>12</th>\n",
" <td>2006-12-16</td>\n",
" <td>17:36:00</td>\n",
" <td>5.224</td>\n",
" <td>0.478</td>\n",
" <td>232.99</td>\n",
" <td>22.4</td>\n",
" <td>0.0</td>\n",
" <td>1.0</td>\n",
" <td>16.0</td>\n",
" <td>Winter</td>\n",
" </tr>\n",
" <tr>\n",
" <th>13</th>\n",
" <td>2006-12-16</td>\n",
" <td>17:37:00</td>\n",
" <td>5.268</td>\n",
" <td>0.398</td>\n",
" <td>232.91</td>\n",
" <td>22.6</td>\n",
" <td>0.0</td>\n",
" <td>2.0</td>\n",
" <td>17.0</td>\n",
" <td>Winter</td>\n",
" </tr>\n",
" <tr>\n",
" <th>14</th>\n",
" <td>2006-12-16</td>\n",
" <td>17:38:00</td>\n",
" <td>4.054</td>\n",
" <td>0.422</td>\n",
" <td>235.24</td>\n",
" <td>17.6</td>\n",
" <td>0.0</td>\n",
" <td>1.0</td>\n",
" <td>17.0</td>\n",
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" </tr>\n",
" <tr>\n",
" <th>15</th>\n",
" <td>2006-12-16</td>\n",
" <td>17:39:00</td>\n",
" <td>3.384</td>\n",
" <td>0.282</td>\n",
" <td>237.14</td>\n",
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" <tr>\n",
" <th>16</th>\n",
" <td>2006-12-16</td>\n",
" <td>17:40:00</td>\n",
" <td>3.270</td>\n",
" <td>0.152</td>\n",
" <td>236.73</td>\n",
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" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>17.0</td>\n",
" <td>Winter</td>\n",
" </tr>\n",
" <tr>\n",
" <th>17</th>\n",
" <td>2006-12-16</td>\n",
" <td>17:41:00</td>\n",
" <td>3.430</td>\n",
" <td>0.156</td>\n",
" <td>237.06</td>\n",
" <td>14.4</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>17.0</td>\n",
" <td>Winter</td>\n",
" </tr>\n",
" <tr>\n",
" <th>18</th>\n",
" <td>2006-12-16</td>\n",
" <td>17:42:00</td>\n",
" <td>3.266</td>\n",
" <td>0.000</td>\n",
" <td>237.13</td>\n",
" <td>13.8</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>18.0</td>\n",
" <td>Winter</td>\n",
" </tr>\n",
" <tr>\n",
" <th>19</th>\n",
" <td>2006-12-16</td>\n",
" <td>17:43:00</td>\n",
" <td>3.728</td>\n",
" <td>0.000</td>\n",
" <td>235.84</td>\n",
" <td>16.4</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>17.0</td>\n",
" <td>Winter</td>\n",
" </tr>\n",
" <tr>\n",
" <th>20</th>\n",
" <td>2006-12-16</td>\n",
" <td>17:44:00</td>\n",
" <td>5.894</td>\n",
" <td>0.000</td>\n",
" <td>232.69</td>\n",
" <td>25.4</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>16.0</td>\n",
" <td>Winter</td>\n",
" </tr>\n",
" <tr>\n",
" <th>21</th>\n",
" <td>2006-12-16</td>\n",
" <td>17:45:00</td>\n",
" <td>7.706</td>\n",
" <td>0.000</td>\n",
" <td>230.98</td>\n",
" <td>33.2</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>17.0</td>\n",
" <td>Winter</td>\n",
" </tr>\n",
" <tr>\n",
" <th>22</th>\n",
" <td>2006-12-16</td>\n",
" <td>17:46:00</td>\n",
" <td>7.026</td>\n",
" <td>0.000</td>\n",
" <td>232.21</td>\n",
" <td>30.6</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>16.0</td>\n",
" <td>Winter</td>\n",
" </tr>\n",
" <tr>\n",
" <th>23</th>\n",
" <td>2006-12-16</td>\n",
" <td>17:47:00</td>\n",
" <td>5.174</td>\n",
" <td>0.000</td>\n",
" <td>234.19</td>\n",
" <td>22.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>17.0</td>\n",
" <td>Winter</td>\n",
" </tr>\n",
" <tr>\n",
" <th>24</th>\n",
" <td>2006-12-16</td>\n",
" <td>17:48:00</td>\n",
" <td>4.474</td>\n",
" <td>0.000</td>\n",
" <td>234.96</td>\n",
" <td>19.4</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>17.0</td>\n",
" <td>Winter</td>\n",
" </tr>\n",
" <tr>\n",
" <th>25</th>\n",
" <td>2006-12-16</td>\n",
" <td>17:49:00</td>\n",
" <td>3.248</td>\n",
" <td>0.000</td>\n",
" <td>236.66</td>\n",
" <td>13.6</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>17.0</td>\n",
" <td>Winter</td>\n",
" </tr>\n",
" <tr>\n",
" <th>26</th>\n",
" <td>2006-12-16</td>\n",
" <td>17:50:00</td>\n",
" <td>3.236</td>\n",
" <td>0.000</td>\n",
" <td>235.84</td>\n",
" <td>13.6</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>17.0</td>\n",
" <td>Winter</td>\n",
" </tr>\n",
" <tr>\n",
" <th>27</th>\n",
" <td>2006-12-16</td>\n",
" <td>17:51:00</td>\n",
" <td>3.228</td>\n",
" <td>0.000</td>\n",
" <td>235.60</td>\n",
" <td>13.6</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>17.0</td>\n",
" <td>Winter</td>\n",
" </tr>\n",
" <tr>\n",
" <th>28</th>\n",
" <td>2006-12-16</td>\n",
" <td>17:52:00</td>\n",
" <td>3.258</td>\n",
" <td>0.000</td>\n",
" <td>235.49</td>\n",
" <td>13.8</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>17.0</td>\n",
" <td>Winter</td>\n",
" </tr>\n",
" <tr>\n",
" <th>29</th>\n",
" <td>2006-12-16</td>\n",
" <td>17:53:00</td>\n",
" <td>3.178</td>\n",
" <td>0.000</td>\n",
" <td>235.28</td>\n",
" <td>13.4</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>17.0</td>\n",
" <td>Winter</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",
" </tr>\n",
" <tr>\n",
" <th>2075229</th>\n",
" <td>2010-11-26</td>\n",
" <td>20:33:00</td>\n",
" <td>0.978</td>\n",
" <td>0.000</td>\n",
" <td>240.28</td>\n",
" <td>4.0</td>\n",
" <td>0.0</td>\n",
" <td>1.0</td>\n",
" <td>0.0</td>\n",
" <td>Fall</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2075230</th>\n",
" <td>2010-11-26</td>\n",
" <td>20:34:00</td>\n",
" <td>0.968</td>\n",
" <td>0.000</td>\n",
" <td>237.57</td>\n",
" <td>4.0</td>\n",
" <td>0.0</td>\n",
" <td>1.0</td>\n",
" <td>0.0</td>\n",
" <td>Fall</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2075231</th>\n",
" <td>2010-11-26</td>\n",
" <td>20:35:00</td>\n",
" <td>0.960</td>\n",
" <td>0.000</td>\n",
" <td>238.01</td>\n",
" <td>4.0</td>\n",
" <td>0.0</td>\n",
" <td>1.0</td>\n",
" <td>0.0</td>\n",
" <td>Fall</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2075232</th>\n",
" <td>2010-11-26</td>\n",
" <td>20:36:00</td>\n",
" <td>0.964</td>\n",
" <td>0.000</td>\n",
" <td>238.07</td>\n",
" <td>4.0</td>\n",
" <td>0.0</td>\n",
" <td>1.0</td>\n",
" <td>0.0</td>\n",
" <td>Fall</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2075233</th>\n",
" <td>2010-11-26</td>\n",
" <td>20:37:00</td>\n",
" <td>0.980</td>\n",
" <td>0.000</td>\n",
" <td>237.90</td>\n",
" <td>4.2</td>\n",
" <td>0.0</td>\n",
" <td>1.0</td>\n",
" <td>0.0</td>\n",
" <td>Fall</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2075234</th>\n",
" <td>2010-11-26</td>\n",
" <td>20:38:00</td>\n",
" <td>0.976</td>\n",
" <td>0.096</td>\n",
" <td>236.97</td>\n",
" <td>4.0</td>\n",
" <td>0.0</td>\n",
" <td>2.0</td>\n",
" <td>0.0</td>\n",
" <td>Fall</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2075235</th>\n",
" <td>2010-11-26</td>\n",
" <td>20:39:00</td>\n",
" <td>0.984</td>\n",
" <td>0.100</td>\n",
" <td>238.16</td>\n",
" <td>4.2</td>\n",
" <td>0.0</td>\n",
" <td>1.0</td>\n",
" <td>0.0</td>\n",
" <td>Fall</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2075236</th>\n",
" <td>2010-11-26</td>\n",
" <td>20:40:00</td>\n",
" <td>0.986</td>\n",
" <td>0.102</td>\n",
" <td>238.92</td>\n",
" <td>4.2</td>\n",
" <td>0.0</td>\n",
" <td>1.0</td>\n",
" <td>0.0</td>\n",
" <td>Fall</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2075237</th>\n",
" <td>2010-11-26</td>\n",
" <td>20:41:00</td>\n",
" <td>0.990</td>\n",
" <td>0.106</td>\n",
" <td>239.57</td>\n",
" <td>4.2</td>\n",
" <td>0.0</td>\n",
" <td>1.0</td>\n",
" <td>0.0</td>\n",
" <td>Fall</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2075238</th>\n",
" <td>2010-11-26</td>\n",
" <td>20:42:00</td>\n",
" <td>0.988</td>\n",
" <td>0.106</td>\n",
" <td>239.60</td>\n",
" <td>4.2</td>\n",
" <td>0.0</td>\n",
" <td>1.0</td>\n",
" <td>0.0</td>\n",
" <td>Fall</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2075239</th>\n",
" <td>2010-11-26</td>\n",
" <td>20:43:00</td>\n",
" <td>0.988</td>\n",
" <td>0.106</td>\n",
" <td>239.64</td>\n",
" <td>4.2</td>\n",
" <td>0.0</td>\n",
" <td>1.0</td>\n",
" <td>0.0</td>\n",
" <td>Fall</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2075240</th>\n",
" <td>2010-11-26</td>\n",
" <td>20:44:00</td>\n",
" <td>0.982</td>\n",
" <td>0.102</td>\n",
" <td>238.69</td>\n",
" <td>4.0</td>\n",
" <td>0.0</td>\n",
" <td>1.0</td>\n",
" <td>0.0</td>\n",
" <td>Fall</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2075241</th>\n",
" <td>2010-11-26</td>\n",
" <td>20:45:00</td>\n",
" <td>0.972</td>\n",
" <td>0.092</td>\n",
" <td>238.32</td>\n",
" <td>4.0</td>\n",
" <td>0.0</td>\n",
" <td>2.0</td>\n",
" <td>0.0</td>\n",
" <td>Fall</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2075242</th>\n",
" <td>2010-11-26</td>\n",
" <td>20:46:00</td>\n",
" <td>0.908</td>\n",
" <td>0.000</td>\n",
" <td>238.53</td>\n",
" <td>3.8</td>\n",
" <td>0.0</td>\n",
" <td>1.0</td>\n",
" <td>0.0</td>\n",
" <td>Fall</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2075243</th>\n",
" <td>2010-11-26</td>\n",
" <td>20:47:00</td>\n",
" <td>0.910</td>\n",
" <td>0.000</td>\n",
" <td>238.71</td>\n",
" <td>3.8</td>\n",
" <td>0.0</td>\n",
" <td>1.0</td>\n",
" <td>0.0</td>\n",
" <td>Fall</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2075244</th>\n",
" <td>2010-11-26</td>\n",
" <td>20:48:00</td>\n",
" <td>0.912</td>\n",
" <td>0.000</td>\n",
" <td>239.25</td>\n",
" <td>3.8</td>\n",
" <td>0.0</td>\n",
" <td>1.0</td>\n",
" <td>0.0</td>\n",
" <td>Fall</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2075245</th>\n",
" <td>2010-11-26</td>\n",
" <td>20:49:00</td>\n",
" <td>0.948</td>\n",
" <td>0.000</td>\n",
" <td>238.16</td>\n",
" <td>4.0</td>\n",
" <td>0.0</td>\n",
" <td>1.0</td>\n",
" <td>0.0</td>\n",
" <td>Fall</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2075246</th>\n",
" <td>2010-11-26</td>\n",
" <td>20:50:00</td>\n",
" <td>1.198</td>\n",
" <td>0.128</td>\n",
" <td>238.11</td>\n",
" <td>5.0</td>\n",
" <td>0.0</td>\n",
" <td>1.0</td>\n",
" <td>0.0</td>\n",
" <td>Fall</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2075247</th>\n",
" <td>2010-11-26</td>\n",
" <td>20:51:00</td>\n",
" <td>1.024</td>\n",
" <td>0.106</td>\n",
" <td>238.84</td>\n",
" <td>4.2</td>\n",
" <td>0.0</td>\n",
" <td>1.0</td>\n",
" <td>0.0</td>\n",
" <td>Fall</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2075248</th>\n",
" <td>2010-11-26</td>\n",
" <td>20:52:00</td>\n",
" <td>0.946</td>\n",
" <td>0.000</td>\n",
" <td>239.05</td>\n",
" <td>4.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>Fall</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2075249</th>\n",
" <td>2010-11-26</td>\n",
" <td>20:53:00</td>\n",
" <td>0.944</td>\n",
" <td>0.000</td>\n",
" <td>238.72</td>\n",
" <td>4.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>Fall</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2075250</th>\n",
" <td>2010-11-26</td>\n",
" <td>20:54:00</td>\n",
" <td>0.946</td>\n",
" <td>0.000</td>\n",
" <td>239.31</td>\n",
" <td>4.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>Fall</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2075251</th>\n",
" <td>2010-11-26</td>\n",
" <td>20:55:00</td>\n",
" <td>0.946</td>\n",
" <td>0.000</td>\n",
" <td>239.74</td>\n",
" <td>4.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>Fall</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2075252</th>\n",
" <td>2010-11-26</td>\n",
" <td>20:56:00</td>\n",
" <td>0.942</td>\n",
" <td>0.000</td>\n",
" <td>239.41</td>\n",
" <td>4.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>Fall</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2075253</th>\n",
" <td>2010-11-26</td>\n",
" <td>20:57:00</td>\n",
" <td>0.946</td>\n",
" <td>0.000</td>\n",
" <td>240.33</td>\n",
" <td>4.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>Fall</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2075254</th>\n",
" <td>2010-11-26</td>\n",
" <td>20:58:00</td>\n",
" <td>0.946</td>\n",
" <td>0.000</td>\n",
" <td>240.43</td>\n",
" <td>4.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>Fall</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2075255</th>\n",
" <td>2010-11-26</td>\n",
" <td>20:59:00</td>\n",
" <td>0.944</td>\n",
" <td>0.000</td>\n",
" <td>240.00</td>\n",
" <td>4.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>Fall</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2075256</th>\n",
" <td>2010-11-26</td>\n",
" <td>21:00:00</td>\n",
" <td>0.938</td>\n",
" <td>0.000</td>\n",
" <td>239.82</td>\n",
" <td>3.8</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>Fall</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2075257</th>\n",
" <td>2010-11-26</td>\n",
" <td>21:01:00</td>\n",
" <td>0.934</td>\n",
" <td>0.000</td>\n",
" <td>239.70</td>\n",
" <td>3.8</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>Fall</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2075258</th>\n",
" <td>2010-11-26</td>\n",
" <td>21:02:00</td>\n",
" <td>0.932</td>\n",
" <td>0.000</td>\n",
" <td>239.55</td>\n",
" <td>3.8</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>Fall</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"<p>2075259 rows × 10 columns</p>\n",
"</div>"
],
"text/plain": [
" Date Time Global_active_power Global_reactive_power \\\n",
"0 2006-12-16 17:24:00 4.216 0.418 \n",
"1 2006-12-16 17:25:00 5.360 0.436 \n",
"2 2006-12-16 17:26:00 5.374 0.498 \n",
"3 2006-12-16 17:27:00 5.388 0.502 \n",
"4 2006-12-16 17:28:00 3.666 0.528 \n",
"5 2006-12-16 17:29:00 3.520 0.522 \n",
"6 2006-12-16 17:30:00 3.702 0.520 \n",
"7 2006-12-16 17:31:00 3.700 0.520 \n",
"8 2006-12-16 17:32:00 3.668 0.510 \n",
"9 2006-12-16 17:33:00 3.662 0.510 \n",
"10 2006-12-16 17:34:00 4.448 0.498 \n",
"11 2006-12-16 17:35:00 5.412 0.470 \n",
"12 2006-12-16 17:36:00 5.224 0.478 \n",
"13 2006-12-16 17:37:00 5.268 0.398 \n",
"14 2006-12-16 17:38:00 4.054 0.422 \n",
"15 2006-12-16 17:39:00 3.384 0.282 \n",
"16 2006-12-16 17:40:00 3.270 0.152 \n",
"17 2006-12-16 17:41:00 3.430 0.156 \n",
"18 2006-12-16 17:42:00 3.266 0.000 \n",
"19 2006-12-16 17:43:00 3.728 0.000 \n",
"20 2006-12-16 17:44:00 5.894 0.000 \n",
"21 2006-12-16 17:45:00 7.706 0.000 \n",
"22 2006-12-16 17:46:00 7.026 0.000 \n",
"23 2006-12-16 17:47:00 5.174 0.000 \n",
"24 2006-12-16 17:48:00 4.474 0.000 \n",
"25 2006-12-16 17:49:00 3.248 0.000 \n",
"26 2006-12-16 17:50:00 3.236 0.000 \n",
"27 2006-12-16 17:51:00 3.228 0.000 \n",
"28 2006-12-16 17:52:00 3.258 0.000 \n",
"29 2006-12-16 17:53:00 3.178 0.000 \n",
"... ... ... ... ... \n",
"2075229 2010-11-26 20:33:00 0.978 0.000 \n",
"2075230 2010-11-26 20:34:00 0.968 0.000 \n",
"2075231 2010-11-26 20:35:00 0.960 0.000 \n",
"2075232 2010-11-26 20:36:00 0.964 0.000 \n",
"2075233 2010-11-26 20:37:00 0.980 0.000 \n",
"2075234 2010-11-26 20:38:00 0.976 0.096 \n",
"2075235 2010-11-26 20:39:00 0.984 0.100 \n",
"2075236 2010-11-26 20:40:00 0.986 0.102 \n",
"2075237 2010-11-26 20:41:00 0.990 0.106 \n",
"2075238 2010-11-26 20:42:00 0.988 0.106 \n",
"2075239 2010-11-26 20:43:00 0.988 0.106 \n",
"2075240 2010-11-26 20:44:00 0.982 0.102 \n",
"2075241 2010-11-26 20:45:00 0.972 0.092 \n",
"2075242 2010-11-26 20:46:00 0.908 0.000 \n",
"2075243 2010-11-26 20:47:00 0.910 0.000 \n",
"2075244 2010-11-26 20:48:00 0.912 0.000 \n",
"2075245 2010-11-26 20:49:00 0.948 0.000 \n",
"2075246 2010-11-26 20:50:00 1.198 0.128 \n",
"2075247 2010-11-26 20:51:00 1.024 0.106 \n",
"2075248 2010-11-26 20:52:00 0.946 0.000 \n",
"2075249 2010-11-26 20:53:00 0.944 0.000 \n",
"2075250 2010-11-26 20:54:00 0.946 0.000 \n",
"2075251 2010-11-26 20:55:00 0.946 0.000 \n",
"2075252 2010-11-26 20:56:00 0.942 0.000 \n",
"2075253 2010-11-26 20:57:00 0.946 0.000 \n",
"2075254 2010-11-26 20:58:00 0.946 0.000 \n",
"2075255 2010-11-26 20:59:00 0.944 0.000 \n",
"2075256 2010-11-26 21:00:00 0.938 0.000 \n",
"2075257 2010-11-26 21:01:00 0.934 0.000 \n",
"2075258 2010-11-26 21:02:00 0.932 0.000 \n",
"\n",
" Voltage Global_intensity Sub_metering_1 Sub_metering_2 \\\n",
"0 234.84 18.4 0.0 1.0 \n",
"1 233.63 23.0 0.0 1.0 \n",
"2 233.29 23.0 0.0 2.0 \n",
"3 233.74 23.0 0.0 1.0 \n",
"4 235.68 15.8 0.0 1.0 \n",
"5 235.02 15.0 0.0 2.0 \n",
"6 235.09 15.8 0.0 1.0 \n",
"7 235.22 15.8 0.0 1.0 \n",
"8 233.99 15.8 0.0 1.0 \n",
"9 233.86 15.8 0.0 2.0 \n",
"10 232.86 19.6 0.0 1.0 \n",
"11 232.78 23.2 0.0 1.0 \n",
"12 232.99 22.4 0.0 1.0 \n",
"13 232.91 22.6 0.0 2.0 \n",
"14 235.24 17.6 0.0 1.0 \n",
"15 237.14 14.2 0.0 0.0 \n",
"16 236.73 13.8 0.0 0.0 \n",
"17 237.06 14.4 0.0 0.0 \n",
"18 237.13 13.8 0.0 0.0 \n",
"19 235.84 16.4 0.0 0.0 \n",
"20 232.69 25.4 0.0 0.0 \n",
"21 230.98 33.2 0.0 0.0 \n",
"22 232.21 30.6 0.0 0.0 \n",
"23 234.19 22.0 0.0 0.0 \n",
"24 234.96 19.4 0.0 0.0 \n",
"25 236.66 13.6 0.0 0.0 \n",
"26 235.84 13.6 0.0 0.0 \n",
"27 235.60 13.6 0.0 0.0 \n",
"28 235.49 13.8 0.0 0.0 \n",
"29 235.28 13.4 0.0 0.0 \n",
"... ... ... ... ... \n",
"2075229 240.28 4.0 0.0 1.0 \n",
"2075230 237.57 4.0 0.0 1.0 \n",
"2075231 238.01 4.0 0.0 1.0 \n",
"2075232 238.07 4.0 0.0 1.0 \n",
"2075233 237.90 4.2 0.0 1.0 \n",
"2075234 236.97 4.0 0.0 2.0 \n",
"2075235 238.16 4.2 0.0 1.0 \n",
"2075236 238.92 4.2 0.0 1.0 \n",
"2075237 239.57 4.2 0.0 1.0 \n",
"2075238 239.60 4.2 0.0 1.0 \n",
"2075239 239.64 4.2 0.0 1.0 \n",
"2075240 238.69 4.0 0.0 1.0 \n",
"2075241 238.32 4.0 0.0 2.0 \n",
"2075242 238.53 3.8 0.0 1.0 \n",
"2075243 238.71 3.8 0.0 1.0 \n",
"2075244 239.25 3.8 0.0 1.0 \n",
"2075245 238.16 4.0 0.0 1.0 \n",
"2075246 238.11 5.0 0.0 1.0 \n",
"2075247 238.84 4.2 0.0 1.0 \n",
"2075248 239.05 4.0 0.0 0.0 \n",
"2075249 238.72 4.0 0.0 0.0 \n",
"2075250 239.31 4.0 0.0 0.0 \n",
"2075251 239.74 4.0 0.0 0.0 \n",
"2075252 239.41 4.0 0.0 0.0 \n",
"2075253 240.33 4.0 0.0 0.0 \n",
"2075254 240.43 4.0 0.0 0.0 \n",
"2075255 240.00 4.0 0.0 0.0 \n",
"2075256 239.82 3.8 0.0 0.0 \n",
"2075257 239.70 3.8 0.0 0.0 \n",
"2075258 239.55 3.8 0.0 0.0 \n",
"\n",
" Sub_metering_3 season \n",
"0 17.0 Winter \n",
"1 16.0 Winter \n",
"2 17.0 Winter \n",
"3 17.0 Winter \n",
"4 17.0 Winter \n",
"5 17.0 Winter \n",
"6 17.0 Winter \n",
"7 17.0 Winter \n",
"8 17.0 Winter \n",
"9 16.0 Winter \n",
"10 17.0 Winter \n",
"11 17.0 Winter \n",
"12 16.0 Winter \n",
"13 17.0 Winter \n",
"14 17.0 Winter \n",
"15 17.0 Winter \n",
"16 17.0 Winter \n",
"17 17.0 Winter \n",
"18 18.0 Winter \n",
"19 17.0 Winter \n",
"20 16.0 Winter \n",
"21 17.0 Winter \n",
"22 16.0 Winter \n",
"23 17.0 Winter \n",
"24 17.0 Winter \n",
"25 17.0 Winter \n",
"26 17.0 Winter \n",
"27 17.0 Winter \n",
"28 17.0 Winter \n",
"29 17.0 Winter \n",
"... ... ... \n",
"2075229 0.0 Fall \n",
"2075230 0.0 Fall \n",
"2075231 0.0 Fall \n",
"2075232 0.0 Fall \n",
"2075233 0.0 Fall \n",
"2075234 0.0 Fall \n",
"2075235 0.0 Fall \n",
"2075236 0.0 Fall \n",
"2075237 0.0 Fall \n",
"2075238 0.0 Fall \n",
"2075239 0.0 Fall \n",
"2075240 0.0 Fall \n",
"2075241 0.0 Fall \n",
"2075242 0.0 Fall \n",
"2075243 0.0 Fall \n",
"2075244 0.0 Fall \n",
"2075245 0.0 Fall \n",
"2075246 0.0 Fall \n",
"2075247 0.0 Fall \n",
"2075248 0.0 Fall \n",
"2075249 0.0 Fall \n",
"2075250 0.0 Fall \n",
"2075251 0.0 Fall \n",
"2075252 0.0 Fall \n",
"2075253 0.0 Fall \n",
"2075254 0.0 Fall \n",
"2075255 0.0 Fall \n",
"2075256 0.0 Fall \n",
"2075257 0.0 Fall \n",
"2075258 0.0 Fall \n",
"\n",
"[2075259 rows x 10 columns]"
]
},
"execution_count": 67,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"dataset1"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": []
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": []
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"collapsed": false
},
"outputs": [],
"source": []
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"collapsed": false,
"scrolled": true
},
"outputs": [],
"source": []
},
{
"cell_type": "code",
"execution_count": 37,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": [
"sns.set(style='darkgrid')"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"collapsed": false,
"scrolled": true
},
"outputs": [],
"source": []
},
{
"cell_type": "code",
"execution_count": 69,
"metadata": {
"collapsed": false
},
"outputs": [],
"source": [
"year_group = dataset1.groupby(dataset1['Date'].map(lambda x: x.year))"
]
},
{
"cell_type": "code",
"execution_count": 49,
"metadata": {
"collapsed": false
},
"outputs": [
{
"data": {
"text/plain": [
"<pandas.core.groupby.DataFrameGroupBy object at 0x295F7850>"
]
},
"execution_count": 49,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"year_group"
]
},
{
"cell_type": "code",
"execution_count": 52,
"metadata": {
"collapsed": false
},
"outputs": [],
"source": [
"year_group.tail();"
]
},
{
"cell_type": "code",
"execution_count": 64,
"metadata": {
"collapsed": false
},
"outputs": [],
"source": [
"dataset1.Date;"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"collapsed": false
},
"outputs": [],
"source": []
},
{
"cell_type": "code",
"execution_count": 8,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": [
"seasons_dict = {12: 'Winter', 1: 'Winter', 2: 'Winter', 3: 'Spring', 4: 'Spring', 5: 'Spring', 6: 'Summer', 7: 'Summer', \n",
" 8: 'Summer', 9: 'Fall', 10: 'Fall', 11: 'Fall'}"
]
},
{
"cell_type": "code",
"execution_count": 70,
"metadata": {
"collapsed": false
},
"outputs": [],
"source": [
"dataset1['season'] = dataset1.Date.apply(lambda x: seasons_dict[x.month])"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"collapsed": false
},
"outputs": [],
"source": []
},
{
"cell_type": "code",
"execution_count": 98,
"metadata": {
"collapsed": false
},
"outputs": [
{
"data": {
"text/plain": [
"<seaborn.axisgrid.FacetGrid at 0xcfc1a50>"
]
},
"execution_count": 98,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
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K+0+KwDDA73HXqEE20QrVnv507doVAHDkyBH07dtX5ef3339n/SVVtUeYN28eSktLsX79\netbPvkgkEmRkZKj8xMbGsq5Dl1Q0yK4Qn5SNR7nPNVgRIeWqPVL55ptvcPfuXVy9ehXXrlWet5eV\nlaGggP18NBWnTjExMZBKpejSpQv27duHXr16ISAgAAKBAIGBgRg0aFAdd6NhGtjbGruOpuNpfrGy\nQfb/jXpb02WRBq7aeX+ys7Nx7949fPvtt5g3b57yiEMkEsHOzg6Wlpq/46Br8/7U1oGTNxB54CoA\nwEBPiMi5XrAyM9JwVaQhq/b0x9raGv369cPOnTuRmZmJvn37wsbGBqdPn6a7NVqCGmQTbcN6gvZH\njx4BAExNTaFQKDBz5kxeCyPsUINsom1YhUpOTg6Cg4MBAGKxGMHBwbhz5w6vhRH2qEE20SasQkUg\nECAjI0P5+saNG9DTY/UwLlEDapBNtAmrZJg1axYmTpyI5s3Lh9nn5eVh5cqVvBZGamekux3+PJUF\nWZlC2SDb29VO02WRBohVqDg7OyMuLg6ZmZnQ09NDu3btqK+KlqlokH3wv1Of6LjreM+pLfT1qO0n\nUS9WoZKVlYWdO3fi+fPnYBgGCoUC2dnZ2LFjB9/1kVoY5dEehxNuQa5glA2yX+zET4g6sPo1Fhwc\nDHNzc6SlpaFTp054+vQp7O3ta34jUStqkE20AatQUSgUmDp1KlxdXdG5c2esX78eV65c4bs2UgfU\nIJtoGqtQMTY2hkwmg62tLVJSUmBgYICSkhK+ayN1UNEgu0JUbCZNTUvUilWoeHt749NPP4WHhwe2\nb9+OSZMmKe8EEe3j51l5alrRIJsQdWEVKv7+/li3bh0aNWqEbdu2YcyYMcoWBNSnVvtQg2yiSazv\nN4rFYgBAixYt4OXlBRMTEwDAunXr+KmMvBG/QR2U/13RIJsQdXjjhxjofF07UYNsoilvHCo0Q552\nqmiQXaGiQTYhfKPHLXUYNcgmmkChosMqGmRXqGiQTQif6JqKjnPu3gotm5TPu1TRIJsQPlU79mf/\n/v3VvtnHxwd79uzhtCDCLZFQAN+B9gjbexlAeYPs8e86oFkjEw1XRnRVtaFS00TsPj4+1FayHhjQ\nqw12HqEG2UQ9qg2VZcuWvXZdcXEx58UQfujrCfG+R3tlg+yj529jtFcHapBNeMGq9cGRI0cQERGh\n0vqguLgYCQkJfNdHODK4nw32/JWJgucyZYPsCcM6a7osooNYXagNDQ3FnDlzYGdnh1WrVmHUqFF4\n7733+K6NcIgaZBN1YRUq5ubm6N+/P7p3746CggJIJBJcvnyZ79oIx6hBNlEHVqFiZGSEmzdvws7O\nDomJiZDJZLWaoZBoB2qQrVvkcgVOXb6HRZHnMH7e/zAi5AC+jjiF58WaPQJlFSrTp0/HmjVrMGDA\nACQkJMDFxYWmKK2nRrrbweC/vrUVDbJJ/VMoLcXs9WewcttFXEx7iILn5UGSkpWLz0OP497jQo3V\nVu20p6+Tn58PCwsLPuqptYY+7WldbNh3Rdkgu4mFETbO8aIG2fXM0l/O43zKg9eub9nYFBEzB0Bf\nT6TGqsqx+pv04MEDfPHFF+jbty9cXFywZMkS5Obm8l0b4ckoj/YQCcsHglY0yCb1x92HBdUGCgDc\nf1qEM1fuq6kiVaxCZc6cOXB2dsbx48dx5MgRdO3aFbNnz+a7NsITapBdv9UUKBXOXdXiUMnNzcX4\n8eMhFoshFosRFBSEBw/Y7VhycjICAgKqXCeVSjFu3DjcvEl3IdSNGmTXX9ISdhfX2W7HNVah8vbb\nb+PgwYPK13FxcejatWuN74uMjMTcuXNRWvrq1eirV6/C398fd+/SobcmUIPs+qvVfwNEudqOa9WG\nioODAzp16oS9e/ciJCQEjo6O6NmzJ6ZMmYJjx47V+OE2NjaIiIiocl1paSnWr1+Pdu3aVbme8O/l\nBtl/nMpC+u1ceihOyxWx/PN5V0MTyVX7mH56evobfbiXlxfu3btX5boePXoAoNYJmmTfxgqO9k1x\n+dpjAFCODdLXE8KtR2tMGNaZxgdpEYWCweaDqYiOv17jtu852aJtK83coWU19kcqlSI8PBwJCQmQ\ny+Xo378/pk2bpmx+rS5hYWHKLv7kzcnliirPu0vLFIi9cBepWblYIXmHgkULFMvKsHrnJST8U3nx\n1cRQDyKRQPmMSgUfNzsEjeii7hKVWF1TWbx4MaRSKb777jusWLECpaWlWLBgAesv4epoRCKRICMj\nQ+UnNjaWk89uiI5duIOMO3mvXX//aRG2HkxTY0WkKnnPijFn/RmVQGnT3AzrZgzAlgVDMCuwt3K5\nQACMH+KgfGRAE1gdqaSkpOCPP/5Qvp4/fz6GDh3K+ksqmmPHxMRAKpXCz8/vlXVE/Q4l3Kpxm5N/\nZ+PjkV0hNtbnvR7yqtsPnmFx5Dk8ypMql3W3b4KvJ/RV/pm80701rro8xcEzNzHUuXJ8l6aw+naG\nYfDs2TOYm5c3UX727BlEInZP6rVu3Rq7d+8GAAwfPvyV9Vu3bmVbK+GQQsHg5r38GreTlSmQ/agA\nDjaNatyWcOty5iMs23IBz4srT1G9+r6Fz3y7Q0+kepLx6ai38amWNN5iFSpBQUHw9fXFwIEDwTAM\n4uLiMHnyZL5rIzwSCAChUAiFXFHjtnpCeoRf3Y6cu40ff09WeSgxcGin/54v0u6je1ah8sEHH6Bb\nt264cOECFAoFwsLC0LFjR75rIzwSCAR4u30TXMqofp5loQAoU9QcPIQbCgWDbYfS8Nvxygbl+npC\nBI/rCVfH1hqsjL1aNb42NS1/mCYtLQ1paWnw8fHhrzLCO2+3djWGioIBZkecxoRhneHtagehBi8A\n6rqSUjl+2HUJZ5Irn242NzXAvIn94GBbf04/37jxNam/ejk0x7h3O2LX0YxqtyuTM9j0Rwr+zniM\n6eN60C1mHvxbUIKlv55Hxu3Ku3HWzcRYMKk/WjTWzJOxdVVj64MdO3agWbNm8PLygq+vL3Jzc6Gn\np4eff/4ZNjaaeWLvRdT64M0lpT/EHyezcOX6EygUCrRtbYH3nNqikbkh1u25jH8LS5TbWooNMX1c\nD/RyaK7BinXL3YcFWBR5Dg9znyuXdbNrgjlBfSA2MdBgZXVTbahs3LgRCQkJmD9/Ptq2bQtvb2/8\n+OOPiIuLQ2pqKr777jt11lolChXuMAwDhoHKKU5eQTHW7P4bl9JVT5O83dohaFhnjfTr0CXJ1x5j\n2eZEFL1wh2dg7zb4ws+x3va4qbbq6OhohIeHo23btuUbC4Vo3bo1xo8fj+TkZLUUSNRHIBC8cs3E\nyswICz7uj4+9u0JPVLnuj5NZCFl7kqZRfQPHEm9jwcYElUDxH+KA6WN71NtAAWoIFZFIpLw4CwBT\npkwpf5NQCAOD+ndYRupGKBTAx90Oq6a6oXVTsXL5zZxnmP7DCRw5d4vGcNVCxR2etXsuK28Z64mE\nCPmwF8Z4ddT6W8Y1qTZUFAoFCgsre10OHjwYAKjpdQNlZ22JNcHuKqNfZaVyhEclY8XWiyh8LtNg\ndfWDrFSO73ckYe+xTOUyMxMDLP3UGR49deP0vdpQGTFiBGbNmqUSLEVFRZgzZw68vb15L45oHyND\nPUhGO+LrwD4wfeHR/TNXciD5Ph4pWU81WJ12yy8swdwNZ3HycuXI/VZNTLFqqiu6tGuswcq4VW2o\nTJ48GY0aNYKrqyt8fX3h5+eHd955B40bN8ZHH32krhqJFnLp3grrQjxU/jE8+VeKOetPY/vhNMhZ\nPKnbkGQ/KsBX604h7VZlb+cu7RojdKobWr1wSqkLWHXTf/jwIa5cuQIA6NKlC1q1asV7YWzR3R/N\nkssV2Bt7DbuPpuPFNredbBsh5MNeaN5Ive0xtNE/N57gu18TVZpfefS0xtQxjjp596xOU3RoEwoV\n7ZB68ym+35GkMprW1EgPn/s6wrVH/Xi8nA/HL95F2N6/USav/Gc27t2OGPdu/b8g+zr1974V0Sqd\n2zbG2pABKuNTiorLsHL7RazZfUljTZg1hWEY7Dicjh92XVIGip5IgOBxPTF+sIPOBgpAoUI4JDbW\nx1f+vTBtjCOMDCoP62Mv3MX01fG4dvf1DaF0SWmZHKt3XsLuvyqHP4iN9bH4/5wxsHcbDVamHhQq\nhFMCgQCD+tpgzZcesLOu7JGa86QIM8NOYV/cNSh0eI6hZ0UyzPspAfGXspXLWjY2RehUV3Sza6LB\nytSHQoXwonVTMUIlbvBxt1MuK5Mz+DUmFQt+TkDus2INVsePnCeF+GrdSZXb6p1sGyF0qiusm5lp\nsDL1olAhvNHXE+Jj765YNNkJlmaGyuWXMx9DsioOF1LZTUhXH6RkPcWMtaeQ86RIuczNsTWWfuoM\nC7FhNe/UPRQqhHc9OzZDWMgA9O5UObL5WZEMizedx0/RVyArlWuwujd34lI25m44i4IXnigeM6gD\nQj7sBQN93btlXBMKFaIWlmaGmP9xP3wysqtKf9WY0zcRsvYk7jx4psHq6oZhGOz5KwOrdiSh7L+H\n/URCAaaN6QH/9zo12IZWFCpEbQQCAbzd7LB6uhusm1U+RXrr/jMErzmJQwn1Z2BiaZkCa3b/je2H\nKyfcMzXWx6LJThjU9y0NVqZ5FCpE7dq2ssAPwe4Y3F91YOL635KxbMsFPCvS7oGJhc9lWLAxAccv\nVs4D3ryRCUIlruhu31SDlWkHChWiEUYGevjCzxGzJ/RRmVMo4Z/7mPp9HP65/kSD1b3eg6dFmLHu\nFP65UVlfRxsrrJrqhjbNG84dnupQqBCNcn67FdaFDFAZmPg0vxjfbDiDrf9LVV6r0AZpN3MRsvYk\n7j2uHLXv0r0Vvp3ionJ3q6GjUCEa19TKGN9OcYH/EAflxU2GAaJir+HriNN48LSohk/g36m/7+Gb\nDWdUTs38PO0x0783DBvgHZ7qUKgQrSASCjDGqyNWfP4Omr0wsjnjdh6mfh+v8oSqOjEMg6jYTKzc\nfhGlZZV3eCSjHRE4tHODvcNTHQoVolUcbBth3ZcecHthZLO0pAzf70jC6p1JeF5cWs27uVUmVyBs\n72Vs/V/lJPUmRnpY+El/le53RBWFCtE6psb6mPFhL0wf20NlYGJcUjamrz6BzDv8D0wslJZi4c8J\n+CvxjnJZMytjrJS4wrFDM96/vz6jUCFaSSAQwLPPW1j7pQfat7FULr//tHxg4m/H+RuY+OBpEWaG\nnUTytco7PB3essSqaW6waWHOy3fqEt5DJTk5GQEBAa8sP378OHx9fTF27FhERUXxXQapp1o1FWPl\nF674YEB75TK5gsGWg6mY99NZPM2XVvPu2su4nYuv1p3C3YeVd3icurXEt1NcaGZGllhN0F5XkZGR\nOHDggMo0HwBQVlaG5cuXY9++fTA0NMS4cePg6emJRo3qz3yxRH309YQIGt4Fjh2aYvXOS8grKJ8x\n8cr1J5Csise0MY7o17XlG3/PmSs5WL0jCbKyytvYozzaY8IwuiBbG7weqdjY2CAiIuKV5Tdu3ICN\njQ3EYjH09fXRq1cvXLhwgc9SiA5w7NAMYTMGoE/nyoGJBc9lWPprIjbsu4KSOg5MZBgG++KuYfmW\nC8pAEQoF+My3Oz4a0YUCpZZ4DRUvLy+IRK/ewy8sLISZWeXTh6ampjSXEGHFQmyIeRP74f/e76Yy\ni9/BMzcRsuYEbt+v3cDEMrkCEb8l49eYVOUyY0M9LPi4P95zsuWq7AaF19Of1xGLxa/MJWRuXvMF\nsLCwMISHh/NZGqkHBAIBhr/TrnyKi+1JyqlXbz8owJdrTmCid1cMdbatsQ9skbQUy7dewOXMx8pl\nTSyNsWBSf9i2pAuydaWWuz8vjzy1s7PD7du38ezZM8hkMly4cAGOjo41fo5EIkFGRobKT2xsLF9l\nEy3XtpUFVk93UzmikJUpsGHfFXz7ayLyC8uvvRTLypCY+gDxSXeRkvUUCgWDR7nPMTP8lEqgtLe2\nwPfT3ChQ3pBajlQqfmPExMRAKpXCz88Ps2fPxsSJE8EwDPz8/NCsGd37J7VnZKCHz3y7o0fHZgjb\n+zcKnpc/HHc+5QGufR8Pxw5Ncf7qfZVJ0JtYGEEqk6PohXl4+nVpgRkf9oKRoUYO3nUKzftDdMaT\nf6VYvfNA92kPAAAMZUlEQVSSyghiNnzc7RA0vAtEdEGWE/TwG9EZTSyNseRTZwS81wls82GyTzd8\n7N2VAoVDFCpEp4iEAowe1AF9OrdgtX0TS2OeK2p4KFSITnpx3uLqZD+iRxm4RqFCdJKhAbseJ2y3\nI+xRqBCd1OeF6UCq347daRJhj0KF6KQBvdrAsoZJvJy6tUTLJqbVbkNqj0KF6CRTY33M+7gfzEwM\nqlzf0cYKU8f0UHNVDQM96UN0Voe3rLB+5kAcOXcLB07eQMHzUjQyN8SEYZ3h6mitMnaIcIdCheg0\nSzNDjPHqiDFeHTVdSoNBUU0I4RSFCiGEUxQqhBBOUagQQjhFoUII4RSFCiGEUxQqhBBOUagQQjhF\noUII4RSFCiGEUxQqhBBOUagQQjhFoUII4RSFCiGEUxQqhBBOUagQQjhFoUII4RSFCiGEUxQqhBBO\nUagQQjjFa6gwDIMFCxZg7NixCAwMxN27d1XW79+/H97e3vD398dvv/3GZymEEDXhNVSOHTsGmUyG\n3bt3IyQkBMuWLVOuy8vLw7p167Bjxw5s27YNf/75J3JycvgshxCiBryGSlJSElxdXQEA3bt3x9Wr\nV5Xr7t69i06dOsHMzAwCgQDdunXD5cuX+SyHEKIGvM77U1hYCDMzs8ov09ODQqGAUCiEra0trl+/\njtzcXBgbGyMhIQFt27at9XfI5XIAwIMHDzirmxBSsxYtWkBP79UI4TVUxGIxioqKlK8rAgUAzM3N\n8fXXX0MikcDS0hJdunSBlZVVtZ8XFhaG8PDwKtd9+OGH3BVOCKlRbGwsrK2tX1nOa6j07NkTcXFx\nGDJkCC5fvowOHToo18nlcqSkpGDHjh2QyWT4+OOP8eWXX1b7eRKJBBKJRGVZcXExrl69iqZNm0Ik\nEvGyHy/z9PREbGysWr5L3Wjf6i9171+LFi2qXM5rqHh5eeHMmTMYO3YsAGDZsmWIiYmBVCqFn58f\nAOD999+HoaEhJk6cCEtLy1p/h5GREXr37s1p3WxUldC6gvat/tKG/RMwDMNouoj6pmPHjsjIyNB0\nGbygfau/tGX/6OE3QginKFQIIZwSLVy4cKGmi6iP+vXrp+kSeEP7Vn9pw/7RNRVCCKfo9IcQwikK\nFUIIpyhUCCGcolAhhHCKQoUQwqkGGypBQUH4559/AAClpaXo3bs3fvnlF+X6gIAAfPLJJygrK3vt\nZxw7dgyPHz/mvda62rhxIz766CMEBARgwoQJSElJYfW+kJCQavdbE+q6L7rk3r176NWrFwIDAxEQ\nEIDAwECsX7++ym1nz56N06dPIzo6Gt9//71a6+R17I82c3FxQVJSErp164aLFy/C1dUVJ06cwMSJ\nEyGTyXD//n0cO3as2s/YsmULFi9ejKZNm6qpavZu3LiB48ePY/fu3QCA9PR0fP3119i/f3+N71X3\nX8KavMm+6Bp7e3ts3bq1Vu8RCAQ8VVO1Bhsqzs7O+PHHHxEUFISTJ0/Cz88Pq1atQmFhIVJSUtCn\nTx8MHDgQhw8fxoIFC6Cvr4979+7hyZMnWL58OR49eoT09HTMmjULO3fuxK5du3Dw4EEIBAIMGzYM\n/v7+mD17NvLy8pCfn4+NGzeq9Jbhm1gsxoMHD/Dbb7/B1dUVDg4O2Lt3LwICAtCuXTtkZWUBANas\nWYMbN25g1apVMDAwgJ+fH9auXfva/e7UqROioqKwc+dOWFpaQk9PD8OGDYOPj49G9mXx4sVo27Yt\ndu/ejSdPnuD9999HcHAwWrRogZycHAwdOhTXrl1DamoqPDw8EBwcjICAADg4OODatWswMTFB7969\ncfr0aRQUFOCXX36BsbExFixYgDt37kChUGD69Ono06cPRowYAVtbWxgYGGgseF9+rEyhUGD+/Pl4\n8OABHj9+jIEDB2LatGkaqa1Cgz396dy5s/If1oULF9CnTx84OTnh7NmzSExMhKurq0rCW1tbY9Om\nTfD398eePXvg7u4OBwcHrFy5Erdv38ahQ4ewa9cu7NixA3/99Rdu3rwJAHBycsKuXbvUGigA0Lx5\nc/z444+4dOkSxo4di6FDhyI+Ph5AeUuKbdu2YejQofjxxx8BADKZDNu3b8fIkSOr3e+8vDxERkZi\nz5492LRpE6RSqcb25XW/gbOzs7Fs2TJs2LABa9euxZw5cxAVFYXff/9duY2joyM2b94MmUwGY2Nj\n/PLLL2jfvj0SExMRFRWFRo0aYdu2bYiIiMCiRYsAAEVFRfj88881eiR3/fp1ldOf5ORkODo6IjIy\nElFRUdi1a5fGaqvQYI9UBAIBHBwccPLkSTRt2hT6+vpwdXVFfHw8MjIyEBgYqPKXp1OnTgDKe0hc\nunRJuZxhGGRmZiInJwcTJkwAwzAoKCjAnTt3AKBO3ey4cOfOHZiamuK7774DAKSkpGDSpElo1qwZ\n+vfvDwDo0aOHsv/G6+p8eb/v3LkDe3t7GBgYKD+Db9XtS4UXf4O3adMGpqam0NfXR5MmTaoM9Ir9\nMjc3R/v27QEAZmZmKCkpQWZmJpKSkpCcnAyGYSCXy5GXlwdAc3+eFV4+/SksLER0dDTOnz8PU1NT\nlJaWarC6cg32SAUoP4r46aef4ObmBgDo1asXUlJSoFAoYGFhofIXtarfikKhEAqFAm3btlX+YW/b\ntg3vv/8+OnbsqNxGEzIyMrB48WLlXzIbGxuYm5tDJBIpL3ImJSXB3t4egOr+Vbffb731FrKysiCT\nyaBQKHDlyhW+d+W1+2JpaYlHjx4BAFJTU6t87+tGoVR3ncHOzg7Dhw/H1q1bERkZiSFDhih7/aj7\n+sTLXt6f6OhoWFhYIDQ0FB999BGKi4s1VFmlBnukApRfrJ0/fz5CQ0MBAPr6+rCwsFD+FqvpL1CP\nHj0wa9Ys/PLLL+jfvz/GjRsHmUyG7t27q/wW1QQvLy9kZWXB19cXJiYmYBgGM2fOxObNmxEdHY1f\nf/0VJiYmWLlyJTIyMlT2tbr9trKywqRJkzB+/HhYWFigpKSkyj6lfO2LqakpFAoFZs6cCX19fSxa\ntAitWrVC8+bNq6y/qn153fqK/x4zZgzmzp2LgIAAFBUVYdy4cRAIBBoPFODV/XFyckJISAguX74M\nfX192NraKoNWU2hAYQPz4sXNupDL5fj555/x6aefAijvDRwcHKyR7ntEOzXoI5WG6E1/24pEIkil\nUowaNQoGBgZ4++23KVCICjpSIYRwqkFfqCWEcI9ChRDCKQoVQginKFQIIZyiUCGEcIpChRDCKXpO\nhdTJw4cPMWPGDEilUgiFQsydOxcCgQDLli1DcXExrKyssHjxYrRu3RqJiYlYs2YNiouL8ezZM3z1\n1VcYPHgw/vzzT2zatAkikQjW1tYIDQ2FgYEBNmzYgD///BMikQguLi6YOXMmcnJy8MUXX8De3h5p\naWlo0qQJ1q5dC3Nzc03/ryAvYwipg7CwMGbTpk0MwzBMYmIi8/PPPzPe3t7M/fv3GYZhmFOnTjFB\nQUEMwzDM1KlTmaysLIZhGCYhIYEZMWIEwzAM4+npyTx9+pRhGIZZs2YNk5aWxsTHxzNjxoxhSkpK\nGLlczkyZMoXZsWMHk52dzTg4ODBpaWkMwzCMRCJhtm/frtZ9JuzQkQqpE2dnZ0ydOhUpKSnw8PCA\nu7s7IiIiMGXKFOWgt+fPnwMAQkNDERcXh0OHDiE5OVm5fODAgRg3bhw8PT0xZMgQODg44MCBAxg2\nbJhyFPQHH3yAAwcOwN3dHY0bN4aDgwOA8tG6//77rwb2nNSEQoXUSc+ePXHw4EFlWERFReGtt95C\ndHQ0gPLRtE+ePAEAjBs3Dk5OTujbty+cnJwwY8YMAMCcOXPg6+uL+Ph4fPXVV/j8889fGYXLMIyy\ntaWhoaFyuUAgeO0IZKJZdKGW1EloaCj2798PHx8fzJs3D+np6cjPz8fFixcBAFFRUQgJCUF+fj7u\n3LmDqVOnws3NDadPn4ZCoYBcLsfgwYNhZWWFyZMnw9vbG2lpaXBycsLBgwdRUlKCsrIy7Nu3T9n/\nhUKkfqAjFVInAQEBCAkJQXR0NEQiEZYsWYIWLVpg6dKlkMlkEIvFWLFiBSwsLODr64thw4bBzMwM\njo6OkEqlKC0txbRp0xAUFAQjIyNYWFhg+fLlaNasGdLS0vDBBx9ALpfD1dUV/v7+uH//vla0HiA1\nowGFhBBO0ekPIYRTFCqEEE5RqBBCOEWhQgjhFIUKIYRTFCqEEE5RqBBCOEWhQgjh1P8DnGhAbmZx\nEo4AAAAASUVORK5CYII=\n",
"text/plain": [
"<matplotlib.figure.Figure at 0xcfc1ed0>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"sns.factorplot(data=dataset1, x=\"season\", y=\"Global_active_power\")"
]
},
{
"cell_type": "code",
"execution_count": 11,
"metadata": {
"collapsed": false
},
"outputs": [],
"source": [
"tod_dict = {0: 'Night', 1: 'Night', 2: 'Night', 3: 'Night', 4: 'Night', 5: 'Night', 6: 'Morning', 7: 'Morning', \n",
" 8: 'Morning', 9: 'Morning', 10: 'Morning', 11: 'Morning', 12: 'Afternoon', 13: 'Afternoon',\n",
" 14: 'Afternoon', 15: 'Afternoon', 16: 'Afternoon', 17: 'Afternoon', 18: 'Evening', 19: 'Evening',\n",
" 20: 'Evening', 21: 'Evening', 22:'Evening', 23:'Evening'}"
]
},
{
"cell_type": "code",
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"source": []
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{
"cell_type": "code",
"execution_count": 144,
"metadata": {
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{
"data": {
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"<div>\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>Date</th>\n",
" <th>Time</th>\n",
" <th>Global_active_power</th>\n",
" <th>Global_reactive_power</th>\n",
" <th>Voltage</th>\n",
" <th>Global_intensity</th>\n",
" <th>Sub_metering_1</th>\n",
" <th>Sub_metering_2</th>\n",
" <th>Sub_metering_3</th>\n",
" <th>season</th>\n",
" <th>tod</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>0</th>\n",
" <td>2006-12-16</td>\n",
" <td>17:24:00</td>\n",
" <td>4.216</td>\n",
" <td>0.418</td>\n",
" <td>234.84</td>\n",
" <td>18.4</td>\n",
" <td>0.0</td>\n",
" <td>1.0</td>\n",
" <td>17.0</td>\n",
" <td>Winter</td>\n",
" <td>17:24:00</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1</th>\n",
" <td>2006-12-16</td>\n",
" <td>17:25:00</td>\n",
" <td>5.360</td>\n",
" <td>0.436</td>\n",
" <td>233.63</td>\n",
" <td>23.0</td>\n",
" <td>0.0</td>\n",
" <td>1.0</td>\n",
" <td>16.0</td>\n",
" <td>Winter</td>\n",
" <td>17:25:00</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2</th>\n",
" <td>2006-12-16</td>\n",
" <td>17:26:00</td>\n",
" <td>5.374</td>\n",
" <td>0.498</td>\n",
" <td>233.29</td>\n",
" <td>23.0</td>\n",
" <td>0.0</td>\n",
" <td>2.0</td>\n",
" <td>17.0</td>\n",
" <td>Winter</td>\n",
" <td>17:26:00</td>\n",
" </tr>\n",
" <tr>\n",
" <th>3</th>\n",
" <td>2006-12-16</td>\n",
" <td>17:27:00</td>\n",
" <td>5.388</td>\n",
" <td>0.502</td>\n",
" <td>233.74</td>\n",
" <td>23.0</td>\n",
" <td>0.0</td>\n",
" <td>1.0</td>\n",
" <td>17.0</td>\n",
" <td>Winter</td>\n",
" <td>17:27:00</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4</th>\n",
" <td>2006-12-16</td>\n",
" <td>17:28:00</td>\n",
" <td>3.666</td>\n",
" <td>0.528</td>\n",
" <td>235.68</td>\n",
" <td>15.8</td>\n",
" <td>0.0</td>\n",
" <td>1.0</td>\n",
" <td>17.0</td>\n",
" <td>Winter</td>\n",
" <td>17:28:00</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" Date Time Global_active_power Global_reactive_power Voltage \\\n",
"0 2006-12-16 17:24:00 4.216 0.418 234.84 \n",
"1 2006-12-16 17:25:00 5.360 0.436 233.63 \n",
"2 2006-12-16 17:26:00 5.374 0.498 233.29 \n",
"3 2006-12-16 17:27:00 5.388 0.502 233.74 \n",
"4 2006-12-16 17:28:00 3.666 0.528 235.68 \n",
"\n",
" Global_intensity Sub_metering_1 Sub_metering_2 Sub_metering_3 season \\\n",
"0 18.4 0.0 1.0 17.0 Winter \n",
"1 23.0 0.0 1.0 16.0 Winter \n",
"2 23.0 0.0 2.0 17.0 Winter \n",
"3 23.0 0.0 1.0 17.0 Winter \n",
"4 15.8 0.0 1.0 17.0 Winter \n",
"\n",
" tod \n",
"0 17:24:00 \n",
"1 17:25:00 \n",
"2 17:26:00 \n",
"3 17:27:00 \n",
"4 17:28:00 "
]
},
"execution_count": 144,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"dataset1.head()"
]
},
{
"cell_type": "code",
"execution_count": null,
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"collapsed": false
},
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"source": []
},
{
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{
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{
"cell_type": "code",
"execution_count": null,
"metadata": {
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},
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},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
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},
"outputs": [],
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},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"collapsed": false,
"scrolled": true
},
"outputs": [],
"source": []
},
{
"cell_type": "code",
"execution_count": 127,
"metadata": {
"collapsed": false
},
"outputs": [],
"source": [
"dataset1.head();"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"collapsed": false,
"scrolled": false
},
"outputs": [],
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},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"collapsed": false
},
"outputs": [],
"source": []
},
{
"cell_type": "code",
"execution_count": 115,
"metadata": {
"collapsed": false,
"scrolled": true
},
"outputs": [],
"source": [
"dataset1['tod'] = dataset1['Time'].apply(lambda x: tod_dict[int(x.split(':')[0])])"
]
},
{
"cell_type": "code",
"execution_count": 116,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": [
"date_means_tod = dataset1.groupby(\"tod\").mean()"
]
},
{
"cell_type": "code",
"execution_count": 117,
"metadata": {
"collapsed": false
},
"outputs": [
{
"data": {
"text/html": [
"<div>\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>Global_active_power</th>\n",
" <th>Global_reactive_power</th>\n",
" <th>Voltage</th>\n",
" <th>Global_intensity</th>\n",
" <th>kitchen</th>\n",
" <th>laundry</th>\n",
" <th>Heater - AC</th>\n",
" <th>month</th>\n",
" </tr>\n",
" <tr>\n",
" <th>tod</th>\n",
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" <th></th>\n",
" <th></th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>Afternoon</th>\n",
" <td>1.042171</td>\n",
" <td>0.134376</td>\n",
" <td>237.090414</td>\n",
" <td>4.453436</td>\n",
" <td>1.342076</td>\n",
" <td>2.249479</td>\n",
" <td>5.958524</td>\n",
" <td>5.334935</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Evening</th>\n",
" <td>1.778293</td>\n",
" <td>0.153937</td>\n",
" <td>235.947418</td>\n",
" <td>7.582858</td>\n",
" <td>2.591241</td>\n",
" <td>2.748166</td>\n",
" <td>7.241827</td>\n",
" <td>5.363636</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Morning</th>\n",
" <td>1.289001</td>\n",
" <td>0.106459</td>\n",
" <td>235.074423</td>\n",
" <td>5.476680</td>\n",
" <td>1.042161</td>\n",
" <td>1.258827</td>\n",
" <td>8.532875</td>\n",
" <td>5.331731</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Night</th>\n",
" <td>0.602831</td>\n",
" <td>0.099221</td>\n",
" <td>237.624838</td>\n",
" <td>2.599656</td>\n",
" <td>0.167747</td>\n",
" <td>0.480724</td>\n",
" <td>1.601042</td>\n",
" <td>5.333600</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" Global_active_power Global_reactive_power Voltage \\\n",
"tod \n",
"Afternoon 1.042171 0.134376 237.090414 \n",
"Evening 1.778293 0.153937 235.947418 \n",
"Morning 1.289001 0.106459 235.074423 \n",
"Night 0.602831 0.099221 237.624838 \n",
"\n",
" Global_intensity kitchen laundry Heater - AC month \n",
"tod \n",
"Afternoon 4.453436 1.342076 2.249479 5.958524 5.334935 \n",
"Evening 7.582858 2.591241 2.748166 7.241827 5.363636 \n",
"Morning 5.476680 1.042161 1.258827 8.532875 5.331731 \n",
"Night 2.599656 0.167747 0.480724 1.601042 5.333600 "
]
},
"execution_count": 117,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"date_means_tod"
]
},
{
"cell_type": "code",
"execution_count": 74,
"metadata": {
"collapsed": false
},
"outputs": [
{
"data": {
"text/plain": [
"386120.0"
]
},
"execution_count": 74,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"dataset1['Sub_metering_1'].sum()"
]
},
{
"cell_type": "code",
"execution_count": 75,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": [
"date_means_season = dataset1.groupby(\"season\").mean()"
]
},
{
"cell_type": "code",
"execution_count": 76,
"metadata": {
"collapsed": false
},
"outputs": [
{
"data": {
"text/html": [
"<div>\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>Global_active_power</th>\n",
" <th>Global_reactive_power</th>\n",
" <th>Voltage</th>\n",
" <th>Global_intensity</th>\n",
" <th>Sub_metering_1</th>\n",
" <th>Sub_metering_2</th>\n",
" <th>Sub_metering_3</th>\n",
" </tr>\n",
" <tr>\n",
" <th>season</th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
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" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>Fall</th>\n",
" <td>1.109868</td>\n",
" <td>0.129150</td>\n",
" <td>239.559843</td>\n",
" <td>4.743651</td>\n",
" <td>1.196958</td>\n",
" <td>1.528439</td>\n",
" <td>5.589630</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Spring</th>\n",
" <td>1.089312</td>\n",
" <td>0.117351</td>\n",
" <td>230.297759</td>\n",
" <td>4.667754</td>\n",
" <td>1.460615</td>\n",
" <td>1.731025</td>\n",
" <td>5.547520</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Summer</th>\n",
" <td>0.981350</td>\n",
" <td>0.137204</td>\n",
" <td>239.540856</td>\n",
" <td>4.229006</td>\n",
" <td>1.182651</td>\n",
" <td>1.867221</td>\n",
" <td>5.128041</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Winter</th>\n",
" <td>1.403453</td>\n",
" <td>0.121053</td>\n",
" <td>240.439897</td>\n",
" <td>5.946036</td>\n",
" <td>1.183347</td>\n",
" <td>1.582447</td>\n",
" <td>6.595837</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" Global_active_power Global_reactive_power Voltage \\\n",
"season \n",
"Fall 1.109868 0.129150 239.559843 \n",
"Spring 1.089312 0.117351 230.297759 \n",
"Summer 0.981350 0.137204 239.540856 \n",
"Winter 1.403453 0.121053 240.439897 \n",
"\n",
" Global_intensity Sub_metering_1 Sub_metering_2 Sub_metering_3 \n",
"season \n",
"Fall 4.743651 1.196958 1.528439 5.589630 \n",
"Spring 4.667754 1.460615 1.731025 5.547520 \n",
"Summer 4.229006 1.182651 1.867221 5.128041 \n",
"Winter 5.946036 1.183347 1.582447 6.595837 "
]
},
"execution_count": 76,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"date_means_season"
]
},
{
"cell_type": "code",
"execution_count": 77,
"metadata": {
"collapsed": false
},
"outputs": [],
"source": [
"dataset1['month'] = dataset1['Date'].apply(lambda x: int(str(x).split('-')[1]))"
]
},
{
"cell_type": "code",
"execution_count": 111,
"metadata": {
"collapsed": false
},
"outputs": [],
"source": [
"date_means_month = dataset1.groupby('month').mean()"
]
},
{
"cell_type": "code",
"execution_count": 112,
"metadata": {
"collapsed": false
},
"outputs": [
{
"data": {
"text/html": [
"<div>\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>Global_active_power</th>\n",
" <th>Global_reactive_power</th>\n",
" <th>Voltage</th>\n",
" <th>Global_intensity</th>\n",
" <th>kitchen</th>\n",
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" <tr>\n",
" <th>month</th>\n",
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" <tbody>\n",
" <tr>\n",
" <th>1</th>\n",
" <td>1.487228</td>\n",
" <td>0.123047</td>\n",
" <td>240.356117</td>\n",
" <td>6.304140</td>\n",
" <td>1.536111</td>\n",
" <td>1.563702</td>\n",
" <td>7.419371</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2</th>\n",
" <td>1.125981</td>\n",
" <td>0.110972</td>\n",
" <td>240.112532</td>\n",
" <td>4.768219</td>\n",
" <td>0.836171</td>\n",
" <td>1.414221</td>\n",
" <td>5.480766</td>\n",
" </tr>\n",
" <tr>\n",
" <th>3</th>\n",
" <td>1.325860</td>\n",
" <td>0.118473</td>\n",
" <td>240.138419</td>\n",
" <td>5.618953</td>\n",
" <td>1.458547</td>\n",
" <td>2.131384</td>\n",
" <td>6.670798</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4</th>\n",
" <td>0.856658</td>\n",
" <td>0.112428</td>\n",
" <td>213.869333</td>\n",
" <td>3.694611</td>\n",
" <td>1.085167</td>\n",
" <td>1.090361</td>\n",
" <td>4.674474</td>\n",
" </tr>\n",
" <tr>\n",
" <th>5</th>\n",
" <td>1.076469</td>\n",
" <td>0.120963</td>\n",
" <td>236.253662</td>\n",
" <td>4.652270</td>\n",
" <td>1.823691</td>\n",
" <td>1.946688</td>\n",
" <td>5.176923</td>\n",
" </tr>\n",
" <tr>\n",
" <th>6</th>\n",
" <td>0.839696</td>\n",
" <td>0.142619</td>\n",
" <td>239.858553</td>\n",
" <td>3.649833</td>\n",
" <td>1.180250</td>\n",
" <td>1.547722</td>\n",
" <td>4.313313</td>\n",
" </tr>\n",
" <tr>\n",
" <th>7</th>\n",
" <td>1.251068</td>\n",
" <td>0.128354</td>\n",
" <td>238.834190</td>\n",
" <td>5.334573</td>\n",
" <td>1.024892</td>\n",
" <td>2.786009</td>\n",
" <td>6.867473</td>\n",
" </tr>\n",
" <tr>\n",
" <th>8</th>\n",
" <td>1.215292</td>\n",
" <td>0.126787</td>\n",
" <td>239.118777</td>\n",
" <td>5.182698</td>\n",
" <td>1.350298</td>\n",
" <td>2.081845</td>\n",
" <td>6.283532</td>\n",
" </tr>\n",
" <tr>\n",
" <th>9</th>\n",
" <td>0.959176</td>\n",
" <td>0.121748</td>\n",
" <td>239.073113</td>\n",
" <td>4.099544</td>\n",
" <td>1.015972</td>\n",
" <td>1.487302</td>\n",
" <td>5.720175</td>\n",
" </tr>\n",
" <tr>\n",
" <th>10</th>\n",
" <td>1.111431</td>\n",
" <td>0.138645</td>\n",
" <td>239.757773</td>\n",
" <td>4.764206</td>\n",
" <td>1.527381</td>\n",
" <td>1.799206</td>\n",
" <td>5.242361</td>\n",
" </tr>\n",
" <tr>\n",
" <th>11</th>\n",
" <td>1.258998</td>\n",
" <td>0.127058</td>\n",
" <td>239.848642</td>\n",
" <td>5.367202</td>\n",
" <td>1.047520</td>\n",
" <td>1.298810</td>\n",
" <td>5.806845</td>\n",
" </tr>\n",
" <tr>\n",
" <th>12</th>\n",
" <td>1.592171</td>\n",
" <td>0.129137</td>\n",
" <td>240.875709</td>\n",
" <td>6.744201</td>\n",
" <td>1.130066</td>\n",
" <td>1.778027</td>\n",
" <td>6.785982</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" Global_active_power Global_reactive_power Voltage \\\n",
"month \n",
"1 1.487228 0.123047 240.356117 \n",
"2 1.125981 0.110972 240.112532 \n",
"3 1.325860 0.118473 240.138419 \n",
"4 0.856658 0.112428 213.869333 \n",
"5 1.076469 0.120963 236.253662 \n",
"6 0.839696 0.142619 239.858553 \n",
"7 1.251068 0.128354 238.834190 \n",
"8 1.215292 0.126787 239.118777 \n",
"9 0.959176 0.121748 239.073113 \n",
"10 1.111431 0.138645 239.757773 \n",
"11 1.258998 0.127058 239.848642 \n",
"12 1.592171 0.129137 240.875709 \n",
"\n",
" Global_intensity kitchen laundry Heater - AC \n",
"month \n",
"1 6.304140 1.536111 1.563702 7.419371 \n",
"2 4.768219 0.836171 1.414221 5.480766 \n",
"3 5.618953 1.458547 2.131384 6.670798 \n",
"4 3.694611 1.085167 1.090361 4.674474 \n",
"5 4.652270 1.823691 1.946688 5.176923 \n",
"6 3.649833 1.180250 1.547722 4.313313 \n",
"7 5.334573 1.024892 2.786009 6.867473 \n",
"8 5.182698 1.350298 2.081845 6.283532 \n",
"9 4.099544 1.015972 1.487302 5.720175 \n",
"10 4.764206 1.527381 1.799206 5.242361 \n",
"11 5.367202 1.047520 1.298810 5.806845 \n",
"12 6.744201 1.130066 1.778027 6.785982 "
]
},
"execution_count": 112,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"date_means_month"
]
},
{
"cell_type": "code",
"execution_count": 107,
"metadata": {
"collapsed": false
},
"outputs": [],
"source": [
"dataset1.rename(columns = {'Sub_metering_1':'kitchen'}, inplace = True)"
]
},
{
"cell_type": "code",
"execution_count": 109,
"metadata": {
"collapsed": false
},
"outputs": [],
"source": [
"dataset1.rename(columns = {'Sub_metering_2':'laundry'}, inplace = True)"
]
},
{
"cell_type": "code",
"execution_count": 110,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": [
"dataset1.rename(columns = {'Sub_metering_3':'Heater - AC'}, inplace = True)"
]
},
{
"cell_type": "code",
"execution_count": 83,
"metadata": {
"collapsed": false
},
"outputs": [
{
"data": {
"text/html": [
"<div>\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>Date</th>\n",
" <th>Time</th>\n",
" <th>Global_active_power</th>\n",
" <th>Global_reactive_power</th>\n",
" <th>Voltage</th>\n",
" <th>Global_intensity</th>\n",
" <th>kitchen</th>\n",
" <th>laundry</th>\n",
" <th>Heater - AC</th>\n",
" <th>season</th>\n",
" <th>tod</th>\n",
" <th>month</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>299995</th>\n",
" <td>2007-07-13</td>\n",
" <td>01:19:00</td>\n",
" <td>0.328</td>\n",
" <td>0.222</td>\n",
" <td>240.67</td>\n",
" <td>1.6</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>Summer</td>\n",
" <td>Night</td>\n",
" <td>7</td>\n",
" </tr>\n",
" <tr>\n",
" <th>299996</th>\n",
" <td>2007-07-13</td>\n",
" <td>01:20:00</td>\n",
" <td>0.328</td>\n",
" <td>0.220</td>\n",
" <td>240.34</td>\n",
" <td>1.6</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>Summer</td>\n",
" <td>Night</td>\n",
" <td>7</td>\n",
" </tr>\n",
" <tr>\n",
" <th>299997</th>\n",
" <td>2007-07-13</td>\n",
" <td>01:21:00</td>\n",
" <td>0.326</td>\n",
" <td>0.224</td>\n",
" <td>240.82</td>\n",
" <td>1.6</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>Summer</td>\n",
" <td>Night</td>\n",
" <td>7</td>\n",
" </tr>\n",
" <tr>\n",
" <th>299998</th>\n",
" <td>2007-07-13</td>\n",
" <td>01:22:00</td>\n",
" <td>0.324</td>\n",
" <td>0.222</td>\n",
" <td>240.74</td>\n",
" <td>1.6</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>Summer</td>\n",
" <td>Night</td>\n",
" <td>7</td>\n",
" </tr>\n",
" <tr>\n",
" <th>299999</th>\n",
" <td>2007-07-13</td>\n",
" <td>01:23:00</td>\n",
" <td>0.324</td>\n",
" <td>0.226</td>\n",
" <td>241.24</td>\n",
" <td>1.6</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>Summer</td>\n",
" <td>Night</td>\n",
" <td>7</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" Date Time Global_active_power Global_reactive_power \\\n",
"299995 2007-07-13 01:19:00 0.328 0.222 \n",
"299996 2007-07-13 01:20:00 0.328 0.220 \n",
"299997 2007-07-13 01:21:00 0.326 0.224 \n",
"299998 2007-07-13 01:22:00 0.324 0.222 \n",
"299999 2007-07-13 01:23:00 0.324 0.226 \n",
"\n",
" Voltage Global_intensity kitchen laundry Heater - AC season \\\n",
"299995 240.67 1.6 0.0 0.0 0.0 Summer \n",
"299996 240.34 1.6 0.0 0.0 0.0 Summer \n",
"299997 240.82 1.6 0.0 0.0 0.0 Summer \n",
"299998 240.74 1.6 0.0 0.0 0.0 Summer \n",
"299999 241.24 1.6 0.0 0.0 0.0 Summer \n",
"\n",
" tod month \n",
"299995 Night 7 \n",
"299996 Night 7 \n",
"299997 Night 7 \n",
"299998 Night 7 \n",
"299999 Night 7 "
]
},
"execution_count": 83,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"dataset1.tail()"
]
},
{
"cell_type": "code",
"execution_count": 89,
"metadata": {
"collapsed": false
},
"outputs": [
{
"data": {
"text/plain": [
"<seaborn.axisgrid.JointGrid at 0x8043430>"
]
},
"execution_count": 89,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
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CwB4nj58YGTOhqqEPqfERSIiVfg5navWckxWAVY39EEUgy4VzXFY6rRqZyTo0dA47vG7J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\nzmeffcbSpUs5cuQIpaWltLe3qw7LECkpKcyePZv4+HgmTJj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"text/plain": [
"<matplotlib.figure.Figure at 0x10d4c4f0>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"sns.jointplot(x=\"month\", y=\"Heater - AC\", data=dataset1, kind='kde')"
]
},
{
"cell_type": "code",
"execution_count": 86,
"metadata": {
"collapsed": false
},
"outputs": [
{
"data": {
"text/html": [
"<div>\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>Global_active_power</th>\n",
" <th>Global_reactive_power</th>\n",
" <th>Voltage</th>\n",
" <th>Global_intensity</th>\n",
" <th>kitchen</th>\n",
" <th>laundry</th>\n",
" <th>Heater - AC</th>\n",
" <th>month</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>count</th>\n",
" <td>300000.000000</td>\n",
" <td>300000.000000</td>\n",
" <td>300000.000000</td>\n",
" <td>300000.000000</td>\n",
" <td>300000.000000</td>\n",
" <td>300000.000000</td>\n",
" <td>296225.000000</td>\n",
" <td>300000.000000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>mean</th>\n",
" <td>1.178617</td>\n",
" <td>0.123529</td>\n",
" <td>236.434101</td>\n",
" <td>5.030474</td>\n",
" <td>1.287067</td>\n",
" <td>1.685307</td>\n",
" <td>5.835362</td>\n",
" <td>5.341000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>std</th>\n",
" <td>1.206879</td>\n",
" <td>0.112693</td>\n",
" <td>26.928825</td>\n",
" <td>5.096950</td>\n",
" <td>6.605558</td>\n",
" <td>6.701319</td>\n",
" <td>8.197138</td>\n",
" <td>3.446383</td>\n",
" </tr>\n",
" <tr>\n",
" <th>min</th>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>1.000000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>25%</th>\n",
" <td>0.292000</td>\n",
" <td>0.000000</td>\n",
" <td>236.830000</td>\n",
" <td>1.200000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>3.000000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>50%</th>\n",
" <td>0.562000</td>\n",
" <td>0.104000</td>\n",
" <td>239.790000</td>\n",
" <td>2.600000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>5.000000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>75%</th>\n",
" <td>1.648000</td>\n",
" <td>0.194000</td>\n",
" <td>241.940000</td>\n",
" <td>7.000000</td>\n",
" <td>0.000000</td>\n",
" <td>1.000000</td>\n",
" <td>17.000000</td>\n",
" <td>7.000000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>max</th>\n",
" <td>10.670000</td>\n",
" <td>1.148000</td>\n",
" <td>251.700000</td>\n",
" <td>46.400000</td>\n",
" <td>78.000000</td>\n",
" <td>78.000000</td>\n",
" <td>20.000000</td>\n",
" <td>12.000000</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" Global_active_power Global_reactive_power Voltage \\\n",
"count 300000.000000 300000.000000 300000.000000 \n",
"mean 1.178617 0.123529 236.434101 \n",
"std 1.206879 0.112693 26.928825 \n",
"min 0.000000 0.000000 0.000000 \n",
"25% 0.292000 0.000000 236.830000 \n",
"50% 0.562000 0.104000 239.790000 \n",
"75% 1.648000 0.194000 241.940000 \n",
"max 10.670000 1.148000 251.700000 \n",
"\n",
" Global_intensity kitchen laundry Heater - AC \\\n",
"count 300000.000000 300000.000000 300000.000000 296225.000000 \n",
"mean 5.030474 1.287067 1.685307 5.835362 \n",
"std 5.096950 6.605558 6.701319 8.197138 \n",
"min 0.000000 0.000000 0.000000 0.000000 \n",
"25% 1.200000 0.000000 0.000000 0.000000 \n",
"50% 2.600000 0.000000 0.000000 0.000000 \n",
"75% 7.000000 0.000000 1.000000 17.000000 \n",
"max 46.400000 78.000000 78.000000 20.000000 \n",
"\n",
" month \n",
"count 300000.000000 \n",
"mean 5.341000 \n",
"std 3.446383 \n",
"min 1.000000 \n",
"25% 3.000000 \n",
"50% 5.000000 \n",
"75% 7.000000 \n",
"max 12.000000 "
]
},
"execution_count": 86,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"dataset1.describe()"
]
},
{
"cell_type": "code",
"execution_count": 93,
"metadata": {
"collapsed": false
},
"outputs": [
{
"data": {
"text/plain": [
"<matplotlib.text.Text at 0xc915870>"
]
},
"execution_count": 93,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
"image/png": 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nIYDA8isQhIeH6x//+Ifv4kTvvvuuHA5HQAsD2vJtw5cqqTykiO4Hgl3KadXv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\n",
"text/plain": [
"<matplotlib.figure.Figure at 0xd21c050>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"dataset1['month'].plot(kind='hist')\n",
"plt.title('Histogram of months')\n",
"plt.xlabel('Months')"
]
},
{
"cell_type": "code",
"execution_count": 94,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": [
"sns.set(style='ticks')"
]
},
{
"cell_type": "code",
"execution_count": 96,
"metadata": {
"collapsed": false
},
"outputs": [
{
"data": {
"text/plain": [
"<seaborn.axisgrid.JointGrid at 0xd1f4990>"
]
},
"execution_count": 96,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
"image/png": 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IAIhhtQaRJA0bNkx33HGHvv/+e3k8HnXq1Enx8fEqKChQamqqWzUCAGLYEYNI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\nYII=\n",
"text/plain": [
"<matplotlib.figure.Figure at 0xd1f4170>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"x = dataset1['month']\n",
"y = dataset1['Heater - AC']\n",
"sns.jointplot(x,y, kind='hex', color=\"#4CB391\")"
]
},
{
"cell_type": "code",
"execution_count": 97,
"metadata": {
"collapsed": false
},
"outputs": [
{
"data": {
"text/plain": [
"<seaborn.axisgrid.JointGrid at 0xc915cf0>"
]
},
"execution_count": 97,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
"image/png": 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B9yr3ol2rQZRMgbToOMilMlT2tAIAcqMTcG3hGUiIcu1akrXWwV68fXI3mgZ7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\ndP3LyaKXjQAAAABJRU5ErkJggg==\n",
"text/plain": [
"<matplotlib.figure.Figure at 0x11020b70>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"sns.jointplot(x,y, kind='kde', color=\"#4CB391\")"
]
},
{
"cell_type": "code",
"execution_count": 99,
"metadata": {
"collapsed": false
},
"outputs": [
{
"data": {
"text/plain": [
"<seaborn.axisgrid.FacetGrid at 0xd088ab0>"
]
},
"execution_count": 99,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
"image/png": 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YNaG3We0xBkGi4urqiubmZkRGRuLy5ctwcnJCU5N15E4Yy5krJfjntvMddir8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\n",
"text/plain": [
"<matplotlib.figure.Figure at 0xcfddb30>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"sns.factorplot(data=dataset1, x=\"month\", y=\"Global_active_power\")"
]
},
{
"cell_type": "code",
"execution_count": 100,
"metadata": {
"collapsed": false
},
"outputs": [
{
"data": {
"text/plain": [
"<seaborn.axisgrid.FacetGrid at 0xd038db0>"
]
},
"execution_count": 100,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
"image/png": 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etgbX9Qn0VTh1Ww5CZFFJSkpCRUUFUlNTsWjRIrbt6fbt2yGTybBk\nyRLMnj0bKSkpmDJlCkJCQsQ0x2kwNQLEMAw+3ZEN1SO3x13uhr9Pbe72cBneLwzuj8KcldX1OH7+\nrtn2OmtDdqJlRHV/DLU9TUhIQEJCgpgmOCVN0/UNcfTsnzhxoZA9TnumG9oH6+/rq/SU44le7XH4\nTAEA4MCpW2Y3TuOJCuWoOD3Ok3HjQjTdWKgvAlRaUYv1O3VuT7fIQKNDxE9yFmzPXrvPEwdTcPWS\nB64GiYoDYkoEaP3Oc2wCm7tMipeT+xrdU6ZndDBPBA6cMi+8TDkqrgWJigPSGAFqpLV1lWPZfyLz\nnK6V5rQx3dChjX63h4tUKuHNVg5k3TKrIDbf/aE1FWeHRMUBMSYCVKaqZRt/A0BMRAAmDI82+VmJ\nj3Vk96gUl1Yj+9p9k+5XVdWxeTEAuT+uAImKgxJuIAKU/v15dkOgXCbFy1ONd3u4tAnwRN+uuqic\nqS4Qt3eyzE1idE4N4biQqDgo+kpLHj9/B7+e/ZM9Th0dyxMhUxk1QOcCHT9/16gylI1wXZ82AV4O\n3SOYMA4SFQeltQhQeWUdPt2hc3u6hPtjohluD5cB3duydVzUDdpNhsbiqr2TXRkSFQeFO1PhRoA+\n330epRXaDncyN4nW7XGz7L9ZLnPDiHhdjsr+UzeN3sjoqr2TXRkSFQfF36d5BOhUTiEOn9bNIpKf\nikFEO/37qYyFGwXKu1OO60Z20XP1CvquiPNUhnExJBIJQgK9UFGl/XAvSz8OOWdG0qmDHyaP6CLY\n86La+6FzuD9yb2t3LO8/eROdjdhkSO6P60EzFQekQaPdy3O9gD9bqH9Urd5NKsEryX0hs9DtacpT\nnNnKkTMFqDWwyVCjYVy+K6ErQqLigGTsvYiff8tv9by3pxxhIcYnuRnL0L6cTYY1aoObDB9W8Nty\nkPvjGpCoOBjllXX48egNg9ccy76j9xpzUHrK8UTv9uzx/pM39V7PLXngqZDx1oAI54VExcE4lVOI\nOrXG4HW//vGnwWvMgVsV7lxuMW+zYFOaFrumthyuAYmKg2Fs4plQVfCb0qNTMNpyyhccyGo9w5a7\nSNuWSh64DCQqDkaQn4dR1wX6GnedqUilEjz5uG628kvW7VY3GRZScSaXhETFwRjQvS28PAxnAiQ+\nFm7wGnNJfLzJJsOrLW8ypMiPa0Ki4mB4KGRIHR2r95runYLwWFxb0WwI9vdE3xjdJsP9p1pesC3i\nrLeQ++M6kKg4IOOHdsKssXEttsrs27UN3po9QPSNe09xCmOfuFDYbK2nXt2AEmrL4ZKQqDggEokE\nk0d2waZlozH72TjO68CSWf3h7Sl+6LZ/97bw9dZtMjx8+jbv/L2H1bzm7yEkKi6D6KJSUlKChIQE\n5OXl8V7ftGkTxo0bx/ZZzs/PF9sUp8PX2x0TE7qwPZCfsWJPXrlMigTeJsNbvE2G3MhPgI8CHu60\nI8RVEPV/Wq1WY/ny5fDwaB6JyMnJwfvvv4+4uLgW7iRMwVY9eZ/qH4EfftUm4uXfLUduQSm6hAcA\noIbsroyoM5U1a9YgJSWlxX4+OTk52LBhA1JTU5Geni6mGYRIRLTzRZdw3abC/ZyqcLzeyRROdilE\nE5WdO3ciKCgIgwcPbrH2xtixY7Fy5Ups3rwZp0+fxpEjR8QyhRCRUQN0C7a/cjYZ8kse0EzFlRBV\nVDIzMzFjxgxcvnwZb7zxBkpKStjzM2fOhL+/P2QyGYYPH46LFy8aHHPt2rWIiYnh/UtMTBTrVyCM\nYFifDmwb08oaNY4/qt5P7o/rIpqofPXVV8jIyEBGRgZiY2OxZs0aBAUFAQBUKhXGjRuH6upqMAyD\nEydOoHv37gbHpF7K9oe3pxyDe7VjjxtdIJ77QzMVl8IqS/KNG8n27NmD6upqTJkyBQsXLsSMGTOg\nUCgwaNAgDBs2zBqmECIwqn8EDj2qOHcutxjXC0rZvs0A0JbWVFwKq4jK5s2bAQBRUVHsa+PHj8f4\n8eOt8XhCZHpEB6FdkDfuPsqg3bLvMnvOTSpBkD+15XAlKPmNsBiJRILE/rq9RlkXi9if2wR4UlsO\nF4NEhRCEJx/viJa0w8fL3ejK+4RzQKJCCIKXh5ztDcTl2u1SrNp4EtW1ahtYRdgCEhVCED7Ychpl\nrRSQ+v1SET7YctrKFhG2gkSFsJjc26U4mVOo95qTOYXILSi1kkWELSFRISzm6Fnj6uEeFaluLmFf\nkKgQFmPrurmEfUGiQlhMoI3r5hL2BYkKYTHc5u36SDDyOsKxIVEhLCYsxIfXD6glnhoQgbAQHytZ\nRNgSEhVCEF5I6o0xgyJbPDdmUCTmT7Z+ESnCNlCNP0IQZG5SvJjUG+OGROGl/+8QAEACYO1rIxDR\n1te2xhFWhWYqhKBEtPXV1cwdHEWC4oLQTIUQHFvVzCXsA5qpEAQhKCQqBEEICokKQRCCQqJCEISg\nkKgQBCEoJCoEQQiKzXopHzx4EElJSUhOTsb27dvFNoMgCCthk17KarUaq1evxs6dO6FQKJCSkoLE\nxEQEBgaKaQ5BEFbAJr2Ur1+/joiICCiVSsjlcsTHxyMrK0tMUwiCsBKizVS4vZTXr1/PO6dSqeDj\no9ux6u3tjYqKCrOe09Cg7d1bWKi/nCFBEMLStm1byGTNJURUUZFIJMjMzGR7KX/22WcICgqCUqmE\nSqVir62srISvr+E9ImvXrsW6detaPDdt2jTBbCcIwjC//PILwsKa18iRMFZoyjJjxgysWrWK7VCo\nVqsxduxYbN++HR4eHkhOTsb69eubuUnGUFNTgwsXLqBNmzZwc3Nr9brExETB+i4LNZYz2+TMv5uQ\nYzmyTVafqXBpqZfykiVLMHv2bDAMgylTppglKADg4eGBxx57zKhrW1JVcxFqLGe2yZl/NyHHcjab\nbNZLOSEhAQkJCdZ4PEEQVoSS3wiCEBQSFYIgBMVtxYoVK2xthLUYMGCA3Y3lzDY58+8m5FjOZpNV\noj8EQbgO5P4QBCEoJCoEQQgKiQpBEIJCokIQhKCQqBAEISguIyrZ2dmYMWOG2fer1Wq8/vrrmDZt\nGp5//nkcPHjQ7LE0Gg2WLl2KlJQUTJs2Dbm5uWaPBbReCMtUJk2ahLS0NKSlpWHp0qVmj5Oeno7k\n5GRMnjwZO3bsMHuc77//HjNmzEBaWhqmTp2K3r178zaiGotarcaiRYuQnJyM6dOnm/13qqurw6JF\nizB16lTMmTMHt27dMmsc7nvx1q1bSE1NxfTp07Fy5Uqzx2nkvffew7Zt2yyy6dKlS5g2bRrS0tIw\nd+5cPHjwwLTBGBfg888/Z8aNG8dMnTrV7DF27NjBvPvuuwzDMExpaSmTkJBg9lj79+9nli5dyjAM\nw5w8eZKZP3++2WPV19czL774IjN69Gjmxo0bZo9TW1vLTJw40ez7Gzl58iQzb948hmEYprKyklm7\ndq3FYzIMw6xcuZL59ttvzbr3wIEDzCuvvMIwDMNkZmYyCxYsMGucr776innrrbcYhmGYGzduMLNn\nzzZ5jKbvxXnz5jFZWVkMwzDMsmXLmP3795s1TklJCTN37lxm1KhRzNatWy2yafr06czly5cZhmGY\nrVu3Mu+9955J47nETCUiIgKffPKJRWM8/fTTePnllwFoZxot7c40lieffBJvv/02AODPP/+En5+f\n2WO1VgjLVC5fvoyqqirMmTMHs2bNQnZ2tlnjHDt2DF27dsULL7yA+fPnY8SIERbZBQDnz59Hbm4u\npkyZYtb9kZGRaGhoAMMwqKiogFwuN2uc3NxcDBs2DIB2H9uNGzdMHqPpezEnJ4fdEDts2DAcP37c\nrHGqqqqwYMECjB8/3mKbPvzwQ8TExADQzvIUCoVJ47mEqIwaNUpvWQRj8PT0hJeXF1QqFV5++WW8\n+uqrFo0nlUrxj3/8A++88w6effZZs8bgFsJiLMxh9PDwwJw5c7Bx40asWLECixcvhkajMXmchw8f\n4sKFC/j444+xYsUKLFq0yCK7AK079dJLL5l9v7e3NwoKCjBmzBgsW7bMbDe4W7duOHz4MADg7Nmz\nuHfvnsl/96bvRe79phQrazpOWFgYevUyr9Vs07GCg4MBAGfOnMHXX3+NWbNmmTSeS4iKUNy9excz\nZ87ExIkT8cwzz1g83urVq7Fv3z68+eabqKmpMfn+nTt3IjMzEzNmzGALYZWUlJhlS2RkJPstFxkZ\nCX9/f9y/f9/kcfz9/TF06FDIZDJERUVBoVCY7pNzqKioQH5+Pvr372/2GJs2bcLQoUOxb98+/PDD\nD3jjjTdQV1dn8jiTJ0+Gt7c3pk2bhl9++QXdu3dny3qYi1Sq+wgaW6zMGuzduxcrV65Eeno6AgIC\nTLrXpUTFkm/z4uJizJkzB6+99homTpxokR27d+9Geno6AEChUEAqlfLeXMby1VdfISMjAxkZGYiN\njcWaNWsQFBRklk07duzA6tWrAQBFRUWorKxEmzZtTB4nPj4eR48eZcepqakx+U3JJSsrCwMHDjT7\nfgDw8/ODUqkEAPj4+ECtVps1Czt//jwGDRqELVu2YPTo0QgPD7fILgCIi4tj6zP/+uuviI+PN+l+\nS2eoLbF7925s2bIFGRkZ6NChg8n3W6Weir1gybfKhg0bUF5ejk8//RSffPIJJBIJvvjiC7i7u5s8\n1lNPPYUlS5Zg+vTpUKvV+O///m+zxuFi6TdmUlISlixZgtTUVEilUrz77rtmCV1CQgJ+//13JCUl\ngWEYLF++3CLb8vLyLP7wzpw5E0uXLsW0adPYSFDTDg/GEBERgY8++gjr16+Hr68v3nnnHYvsAoA3\n3ngDb731Furr6xEdHY0xY8aYdL+l/+9N0Wg0ePfdd9G+fXu8+OKLkEgk6N+/v0nuJ20oJAhCUFzK\n/SEIQnxIVAiCEBQSFYIgBIVEhSAIQSFRIQhCUEhUCIIQFBIVwi759ttvsXfvXgDAkiVLsGvXLhtb\nRBgLiQphl/zxxx9mpdITtselMmoJcTh16hTWr18PhmFw+/ZtPPXUU/Dx8cGBAwcAAJ9//jmys7Px\n0UcfgWEYhIeHY9WqVQgMDMTIkSMxYcIEHDt2DDU1NVizZg3Kyspw8OBBnDx5kt0qcOjQIWzZsgUl\nJSWYN28enn/+eVv+yoQeaKZCCMK5c+ewevVq7NmzB9988w2Cg4OxY8cOxMTE4Ouvv8by5cvx2Wef\nYffu3ejbty9WrVrF3hsYGIjt27dj6tSpWL9+PQYNGoSRI0fi73//OwYPHgxAWyBp+/bt2LBhAz78\n8ENb/ZqEEZCoEILQpUsXhIaGwsPDAwEBAewmwPbt2+PQoUPo3bs32rVrBwCYOnUqr27IkCFD2DHK\nyspaHD8xMZG9prS0VMxfhbAQEhVCEJoWPmqtZgig3bTW0NDAHjcWAZJIJK3uurWkKBZhXUhUCNHp\n1asXzp49izt37gAAtm3bZrCcgZubG9RqdYvnaA+sfUPyTwhO0+34wcHBePvtt/Hiiy9CrVajffv2\nbNmA1rbuP/HEE/jwww9bLFok9HZ/Qlio9AFBEIJC7g9BEIJCokIQhKCQqBAEISgkKgRBCAqJCkEQ\ngkKiQhCEoJCoEAQhKCQqBEEIyv8PKR4nL5e3TzsAAAAASUVORK5CYII=\n",
"text/plain": [
"<matplotlib.figure.Figure at 0xbfa1790>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"sns.factorplot(data=dataset1, x=\"month\", y=\"Heater - AC\")"
]
},
{
"cell_type": "code",
"execution_count": 118,
"metadata": {
"collapsed": false
},
"outputs": [
{
"data": {
"text/plain": [
"<seaborn.axisgrid.FacetGrid at 0xc75d0f0>"
]
},
"execution_count": 118,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
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D34hKkL+9fDWlkFmdXlXID3izszSEh6NFJ0drNwoVohJG+fSD5V8bcEmkMpxN\nUK3by1cUmj5016czFCpEJeiIhJgY5Mw8PhOfDYlUNYYclFbW43ZWGfOYmj6do1AhKmNKsCtaLwCK\ny+uRlF7Mb0F/kd990MbcAJ5OljxWo/ooVIjKsLcyQsDgtlHWqrLpWOwjTR9VvN2tSihUiEqR77BN\nvF2E0sr6jg/mQHlVA1IzS5nHtLh11yhUiEoZ6W0Pa/OWiaZSqQxnrubwWk9cygO0Dg+1MtOHt6v6\nrv7PFQoVolJEIiEmBbVt6H4mPgsSiZS3euSXOQjxo6ZPd1CoEJUzeZQLWn92H1Y24I80fjpsK2sa\nkSK3HAOtndI9FCpE5dhaGiLQux/z+Je4LF7qiE95gNa72uYmehiiZuvo8oVChaik8JC2JtCfaUUo\nLq/r5GjlkL+VHOLXHyJq+nQLhQpRSQFe9sxm51IZcOYqtyNsq+uaFCY2jqF9fbqNQoWoJJFQgMmj\n2q5Wzl7NhpjDDturKYXMiF5TIz34utt08QrSikKFqKxJQc7M3ZayqkYkphZydm75AW/Bvv2gI6If\nle6i/1NEZVmbG2KUT1uHLVdr2NbWN+P6nbY7TjTXp2coVIhKk1/DNulOMQpLazs+mCUJqYUQS1qa\nPsaGuvD3sO3iFUQehQpRacM8bWFvZQQAkHHUYSs/4G2UTz/o6tCPSU9w/n9LKpVi7dq1mDdvHiIj\nI5GRkcF1CUSNCIUCTAmW67BNyFFqh21dQzP+TKemT19wHioXLlyAQCDA999/jxUrVuDf//431yUQ\nNTNxpDMzRqSiuhFXU5TXYXvtdhGaxS2hZaivg+Ge1PTpKc5DZeLEidiyZQsAID8/H+bm5lyXQNSM\npZkBgn3bxon8Eqe8rXLl7/oEDekHXR2R0s6lqXhpLAqFQvzzn//E1q1bMW3aND5KIGpmqtySCMl3\nH6LgYQ3r52hoFOPabfmmDw146w3ONxNr9d5776G0tBSzZ8/GyZMnO9xXmTYTIwDg52EDBxtjPHjY\ncvfndFw2Fk3zYfUcf6QVo6lZAgAw0BMhwMue1ffXFpxfqRw7dgy7du0CAOjr60MoFEIo7LiM6Oho\npKenK/w5f/48V+USFSEUChAu12F7LjEHzWIJq+eQb/oEettDX5eaPr3BeahMnjwZqampWLBgAV58\n8UWsW7cOenp6XJdB1FDYSGdmZGtVbRPi5LbN6KvGZonCiF2669N7nDd/DA0N8dFHH3F9WqIBzE30\nMdrPAZf3ElcYAAAPo0lEQVSu5wNoGWE7bjg7297+mVaMhqaWKx89XRFGUNOn12hUD1Er8mvY3rz3\nELlF1ay8r/y+PiO87GCoz1t3o9qjUCFqxdfdGgNsTZjHp+P7PsK2WSzB1VtyTR9a4a1PKFSIWhEI\nBApXKxeu5TB3bHor6U4J6hvFAABdHSFGDqGmT19QqBC1EzbSiZmPU13XrHDXpjfk5/oEDLaDkYFu\nn95P21GoELVjaqSncHemL5uONYulCk0f2ten7yhUiFqSXxIhNbMM2YVVvXqfGxklqK1vBgDoiAQI\nklu/hfQOhQpRS0PcrOBkb8o87u3VinzTZ5inHUwMqenTVxQqRC0JBAKF+UC/XstFQ5O4R+8hkUgR\nnyJ/14fm+rCBQoWordBAJ+j9NZS+tkGM36/3rMM25V4pquuaALQstD3Kl0KFDRQqRG2ZGOpi7DC5\nDtv4rB69Xv6ukb+HDUyNaLoIGyhUiFqTH7OSnl2OzILKbr1OIpUpzB2iuT7soVAham2wsyVcHcyY\nx93tsE3NLEVFTSMAQCiAwiJQpG8oVIhae3SE7a9/5DGjYztzRe6uj6+7DcxN9JVRnlaiUCFqL3SE\nIwz0Wjps6xvFuJSU3+nxUqkMV262hQo1fdhFoULUnpGBrsISCF112KZll6GsqqXpIxAAIdT0YRWF\nCtEI4SFtq8Jl5FYgI6+iw2Pl7/oMcbOGpVn7S5mS3uE8VMRiMd544w1ERkbi+eefx4ULF7gugWig\nQU6WcHds25mhow5bqVSm0J8ymga8sY7zUDl+/DgsLS3x3Xff4YsvvmC26yCkr+TnA11KykNdQ/Nj\nx9zNLcfDygbm8Wg/6k9hG+ehMnXqVKxYsQJAy26FOjq0whZhx7jhA2Co39phK8HFP/MeOyb2RtvY\nFC8XS9hYGHJWn7bgPFQMDQ1hZGSEmpoarFixAitXruS6BKKhjAx0MT7AiXl8Ki4bMpmMeSyTyRT6\nU+iuj3Lwcpnw4MEDLF++HAsWLEBERESnx9K+P6QnwkNc8UtcFgDgfkEl7uZWwNPZEgBwL68SxWV1\nzLHU9FEOzq9UHj58iMWLF2PVqlWYOXNml8fTvj+kJwYOMIenswXzWL7DVv4qZZCTBeysjDisTHtw\nHiqff/45qqqq8Mknn2DhwoWIiopCU1MT12UQDabQYXs9H7X1zY83fWiFN6XhvPmzbt06rFu3juvT\nEi0ydtgA7D6egroGMRqbJPjtj1wMGWjNbJkK0LKRykSD34jGMdDXQeiItg7bn69k4szVtq08Bg4w\nh4ONMR+laQUKFaKR5CcZ5hbV4KffM5nHwwbZ8lCR9qBQIRrpTk55h187m5CNvGJ2djYkj6NQIRqn\nsLQWn/yY3OHXq+uase1/fyqMYSHsoVAhGud0fDYk0s4DIyO3otOrGdJ7FCpE49zOKuvmcRQqykCh\nQghhFYUK0TheLpbdO861e8eRnqFQIRonPMQVIqGg02M8HM0x2JlCRRkoVIjG6WdtjJef8+/w6+Ym\nenht/ggIBJ0HD+kdWsyEaKQpwa6wszTCjxfu4kbGQwCAnq4ITw4fgLmTBtNkQiWiUCEaa/hgOwwf\nbIeauibUNYhhYarPbJNKlIdChWg8EyM9mNCWppyhPhVCCKsoVAghrKJQIYSwikKFEMIq3kIlOTkZ\nCxcu5Ov0hBAl4eXuz+7du3Hs2DEYG9PqW4RoGl6uVFxcXPDxxx/zcWpCiJLxcqUyadIk5Ofn9/r1\nEokEAFBYWMhWSYSQHurXr1+7O4yq/OC3zjYTi4yM5LgaQkir8+fPw9HR8bHneQ2V7iznFx0djejo\naIXnGhoakJKSAltbW4hE3Ay7DgsL0+hNzOjzqTc+Pl+/fv3afZ7XUOntLFEDAwMEBgayXE3X2ktl\nTUKfT72pyufj7ZbygAEDsH//fr5OTwhREhr8RghhFYUKIYRVok2bNm3iuwh1MWrUKL5LUCr6fOpN\nVT6fQEY7KhFCWETNH0IIqyhUCCGsolAhhLCKQoUQwioKFUIIqzQ+VL744gs88cQTaGpqAgDcuHED\nkydPxvbt23Ht2jXcuXOH5wr7LiEhAaNHj0ZUVBQWLlyIhQsX4tVXX+3z++7atQs3b95koULlSEhI\nQGBgIIqKipjntm3bhl27dmHz5s2dvu6111577Pk7d+7g2rVrSqm1MwkJCfDy8sLJkycVnp82bRrW\nrFnT6/e9fPkyDh482NfyekzlZyn31YkTJ/D000/j559/xsyZM3H58mW88MILiIyMxJo1axAREQFP\nT0++y+yzkJAQbNu2jdX3XLp0Kavvpwx6enpYs2YNvvrqK+Y5Ozu7Lmtvb97ZmTNnYGNjw8u8soED\nB+LkyZOIiIgA0BJwDQ0NfXrPsWPHslFaj2l0qCQkJMDFxQVz585FTEwM3N3dcejQIejp6aGpqQmX\nL19GamoqBg0ahKSkJHzzzTcQiUQYMWIEXnvtNezcuRNJSUmoq6vD22+/jXXr1sHBwQHZ2dnw9/fH\npk2bUF1djVWrVqGmpgYSiQQrVqxAcHAwYmNj8Z///Af6+vqwtLTEO++8g9TUVHzxxRfQ1dVFXl4e\nIiIi8I9//IOVz/rocKOysjIsWLCA+e23ZcsWhISEwNnZGW+//TYAwMLCot26nnrqKbz00ktYs2YN\nnnrqKZSUlODixYtoaGhAbm4ulixZghkzZuDGjRvYvHkzTExMYGVlBX19fbz77rusfJ7uCg4Ohkwm\nw3fffccshSGTyTBnzhwcOHAAv/76K3bs2AFTU1OYmZlh8ODBCAoKQmZmJpYuXYrS0lKEhoZi9uzZ\nOHz4MPT09ODj4wM/Pz9OP4eXlxeysrJQU1MDExMTHD9+HNOnT0dBQQFOnDiBb775Bvr6+nBxccHm\nzZtx4sQJHDp0CDKZDMuXL8emTZsQEBCAzMxM2NjYYMeOHTh69Cju37+PuXPn4vXXX3/se7e8vBwx\nMTFoamqCm5sb4uPjcebMmT5/Fo0OlYMHD2LWrFlwdXWFnl7LZlLPPvssbG1tMWfOHNy5cwdPPfUU\nDA0NsXPnThw+fBj6+vp44403cOXKFQCAu7s71q5di/z8fGRlZWHPnj3Q19fHxIkTUVpait27d2PM\nmDFYuHAhioqKMH/+fJw/fx4bNmzA/v37YWtri3379uHjjz9GaGgoHjx4gBMnTqChoQFjx45lLVTi\n4+MRFRUFmUwGgUCA8ePHw8vLC9euXYO/vz8SEhKwbt06zJs3D++88w7c3d3x448/4osvvsCYMWMe\nq+ull15SeP+amhrs3r0b2dnZePnllzFjxgxs2rQJH3zwAdzd3bF9+3YUFxez8ll6QiAQYOPGjZg9\ne7bCb2aBQACpVIqtW7fihx9+gJWVFWJiYpivNzc345NPPoFYLMb48eOxfPly5nuD60BpNXnyZJw9\nexYzZ87EjRs3sHTpUty6dQs7d+7E0aNHYWhoiPfeew8HDhyAkZERzM3NmRUUc3NzsXfvXtjb22P+\n/PlMs7X1iqy9791du3Zh4sSJmDdvHq5cuYLY2FhWPofGhkpVVRUuXbqEsrIy7Nu3DzU1Nfj222/h\n7Oz82LHZ2dkoKyvDkiVLIJPJUFdXh9zcXACAm5sbc5yLiwsMDQ0BtFxiNzY24v79+3jmmWcAAPb2\n9jA1NUVpaSlMTExga2sLAAgMDMT27dsRGhoKT09PCAQCGBoawsDAgLXP217zJy4uDkeOHEFJSQkm\nTJgAoVCIe/fu4a233gIAiMViuLi4AECXdXl7ewMAHBwc0NjYCAAoLi6Gu7s78xkf7RPgirm5Odas\nWYPVq1djxIgRzPNlZWXMVVRrjQ8ftuyrPGjQIOjo6DB/+CYQCPD0009j48aNcHR0xMiRIyGTySCT\nyeDh4cF83wUGBiI2Nhb+/v4K35tWVlawt7cH0LLOSeu/Uav2vnfv3buHmTNnMu/LFo3tqD127Bhm\nzZqFL7/8Ert378YPP/yA2NhYlJWVMce0/jZzdHSEg4MD9uzZg3379mHBggUYOnQoAEAobP9/UWtz\nw93dHYmJiQCAoqIiVFVVwcLCArW1tcw3cEJCAlxdXZX4adtf8CokJAS3b9/G4cOHMWvWLAAtbfd/\n/etf2Lt3L2JiYhAaGgqg67Vt2vu6g4MD7t27B6BldwQ+hYaGws3NDYcPH2aes7a2Rl1dHcrLywF0\nXaNAIGCWKuWDo6Mj6uvrsW/fPkyfPp2pKSMjA/X19QAUv5c6+t7sSuv3iqenJ5KSkgCA+S8b+I9o\nJTl06BD+9a9/MY8NDAwwefJkHDx4EOvXrwcADB06FNu2bcP27duxaNEiREZGMiHT2mEmT/4Hq/Xv\nL730EtauXYvTp0+jsbERW7ZsgUgkwpYtW7B8+XIIhUKYmZnhvffew507d3q9MFVXrl69iqioKABg\nmkC7d+/GlClTEBcXBycnJwDAxo0bsWrVKkgkEgiFQmzdulXh7klPbNiwAWvXroWxsTF0dXWZ35R8\nWbt2LeLj45n/xwKBAOvXr8fSpUthamoKqVTK/EC29+/g6+uLDz74AB4eHggKCuKydEZERASOHz8O\nFxcX5OTkwNLSEtOmTUNUVBREIhGcnZ0RExODn3/+ucP3aO+ztfe9u2TJErzxxhs4deoUbG1tWbti\nowmFpNe+++47REREwNLSEh999BH09PSwbNkyvstSsGvXLixatAi6urpYtWoVnnjiCaa5qu0uXrwI\na2tr+Pr6Ii4uDp9//jm+/vrrPr+vxl6pEOWzsbHB3//+dxgZGcHU1BTvv/8+3yU9xtjYGM8//zwM\nDAw6vALVVo6Ojli3bh1EIhGkUilzBd9XdKVCCGGVxnbUEkL4QaFCCGEVhQohhFUUKoQQVlGoEKWp\nqanB//3f/3X7+CNHjvRpVi5RDRQqRGkqKiqQlpbGdxmEYzROhSjN1q1bUVxcjOjoaISGhmLPnj0Q\nCATw8fHBhg0bYGhoiKNHj+Kzzz6DqakpHBwcYGxszHfZpI/oSoUozfr162FnZ4dXXnkFn332Gb77\n7jscP36cmRVeXFyMDz/8EP/73/9w4MAB1NbW8l0yYQGFClEqmUyGhIQETJgwAWZmZgCA559/HnFx\ncUhKSkJAQACsrKwgFAqZSXREvVGoEKVrncIvr3VCo1QqZZ5ThSUISN9RqBCl0dHRgVQqxciRI/Hr\nr7+iqqoKAPDDDz8gODgYAQEBSE5ORnFxMaRSKW/rsRB20a8GojTW1tZwcHDAO++8g6VLlyIyMhIS\niQQ+Pj546623YGRkhDfffBN/+9vfYGRkBA8PD75LJiygCYWEEFZR84cQwioKFUIIqyhUCCGsolAh\nhLCKQoUQwioKFUIIqyhUCCGsolAhhLDq/wHkc/Z5MtK2+AAAAABJRU5ErkJggg==\n",
"text/plain": [
"<matplotlib.figure.Figure at 0xc5b8f90>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"sns.factorplot(data=dataset1,x=\"tod\", y='Heater - AC')"
]
},
{
"cell_type": "code",
"execution_count": 119,
"metadata": {
"collapsed": false
},
"outputs": [
{
"data": {
"text/plain": [
"<seaborn.axisgrid.FacetGrid at 0x1784ddf0>"
]
},
"execution_count": 119,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
"image/png": 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A82+lcLigDg83K7ddMYULZgaxdX9Jn93UokK8CfXuoLnd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\nAAAAAElFTkSuQmCC\n",
"text/plain": [
"<matplotlib.figure.Figure at 0x1784d030>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"g = sns.FacetGrid(dataset1, col=\"month\")\n",
"g.map(sns.distplot, \"Heater - AC\")"
]
},
{
"cell_type": "code",
"execution_count": 122,
"metadata": {
"collapsed": false
},
"outputs": [
{
"data": {
"text/plain": [
"<seaborn.axisgrid.FacetGrid at 0x17800950>"
]
},
"execution_count": 122,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
"image/png": 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CIAgiCmhSRRAEQRAEQRAEEQU0qSIIgiAIgiAIgogCVTwbdzqdWL58OU6fPg2Hw4G5c+fi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\n",
"text/plain": [
"<matplotlib.figure.Figure at 0x18bef370>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"g = sns.FacetGrid(dataset1, col=\"season\")\n",
"g.map(plt.scatter, \"Global_active_power\", \"Heater - AC\")"
]
},
{
"cell_type": "code",
"execution_count": 123,
"metadata": {
"collapsed": false
},
"outputs": [
{
"data": {
"text/plain": [
"<seaborn.axisgrid.FacetGrid at 0xd61aa70>"
]
},
"execution_count": 123,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
"image/png": 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djIwM0tLSLvkcQjSXUor92WdY9PURtu0v9PosNNDMTUNiuX1cL0KC/HxUQyGu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\nGf4f5nG/ba7E1MYAAAAASUVORK5CYII=\n",
"text/plain": [
"<matplotlib.figure.Figure at 0x17aee030>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"g = sns.FacetGrid(dataset1, col=\"season\")\n",
"g.map(sns.regplot, \"Global_active_power\", \"Heater - AC\")"
]
},
{
"cell_type": "code",
"execution_count": 124,
"metadata": {
"collapsed": false,
"scrolled": false
},
"outputs": [
{
"data": {
"text/plain": [
"<seaborn.axisgrid.FacetGrid at 0x193dcdb0>"
]
},
"execution_count": 124,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
"image/png": 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A8vPz1bNnz9tqBwAAAADKiyIv/3vttdf06KOP6ocffpC3t7fuuecejRs3TosW\nLSpWB7Vr19aKFSskSfXr11dMTIx9EQMAAABAOVLkTFViYqKee+45OTk5yc3NTaNHj9aZM2dKIzYA\nAAAAKPeKLKqcnZ2VlpYmi8UiSTpx4sQ1D5wAAAAAgDtZkZf/RUREKCwsTKdPn9af//xn7dmzR7Nm\nzSqN2AAAAACg3CuyqOrcubNatGihH374QQUFBZo+fXqxHoUOAAAAAHeCIq/je+655+Tn56fHH39c\nwcHB8vPzU79+/UojNgAAAAAo9wqdqQoPD1dCQoIkyd/f33ZPlbOzs4KCgkonOgAAAAAo5wotqpYu\nXSpJmjlzpqZMmVJqAQEAAABARVLkPVXjx4/Xhg0blJGRIUkqKChQYmKiRo0a5fDgAAAAAKC8K9bT\n/7KysnTy5Em1bdtWO3fu1EMPPVQasQEAAABAuVfkgyqOHz+upUuXqlu3bnrxxRf1+eef69y5c6UR\nGwAAAACUe0UWVXfddZcsFosaNGigQ4cOqWbNmsrNzS2N2AAAAACg3Cvy8r/GjRtrxowZev755zVu\n3DidO3dOeXl5pREbAAAAAJR7Rc5Uvf766+rVq5caNWqkiIgInTt3Tm+//XZpxAYAAAAA5V6RM1XO\nzs6yWCxavny5+vXrJx8fHz3wwAOlERsAAAAAlHtFzlT9/e9/17vvvqslS5YoIyNDU6dO1UcffVQa\nsQEAAABAuVdkURUbG6uPPvpInp6eql69ulatWqXVq1eXRmwAAAAAUO4VWVQ5OTnJzc3N9trd3V3O\nzs4ODQoAAAAAKooi76lq166d3nzzTWVlZWnjxo1auXKlAgMDSyM2AAAAACj3ipypmjBhgurVq6cm\nTZpozZo1euyxx/TKK6+URmwAAAAAUO4VOVPl5OSkAQMGaMCAAaURDwAAAABUKIUWVf7+/rJYLNct\nN8bIYrHop59+cmhgAAAAAFARFFpUHTx40PbvkJAQrVmzplQCAgAAAICKpMh7qiTdcMYKAAAAAFDM\nosoY4+g4AAAAAKBCYqYKAAAAAOxQ6D1VQUFBtmLq7NmzCg4OlvTfB1XExcXddqd9+/ZVlSpVJEl1\n6tTRrFmzbrstAAAAAChLhRZVMTExDukwNzdXkrR06VKHtA8AAAAApanQoqp27doO6fDgwYPKzMzU\n0KFDVVBQoNGjR6tVq1YO6QsAAAAAHK3IL/8taR4eHho6dKieffZZnThxQsOGDdPXX38tJ6di3d4F\nAAAAAOVjtGmQAAAgAElEQVRKqRdV9evXV7169Wz/9vX11fnz51WzZs0brh8dHa0FCxaUZohAhUW+\nAMVDrgDFQ64AxWMxpfy89OXLl+vnn3/WtGnTdPbsWf3hD3/QP/7xj1uaqUpMTFRwcLDi4uJUp04d\nB0YLVHzkC1A85ApQPOQKcL1Sn6l65plnNGnSJA0cOFBOTk6aNWsWl/4BAAAAqLBKvahydXXVW2+9\nVdrdAgAAAIBDMEUEAAAAAHagqAIAAAAAO1BUAQAAAIAdKKoAAAAAwA4UVQAAAABgB4oqAAAAALAD\nRRUAAAAA2IGiCgAAAADsQFEFAAAAAHagqAIAAAAAO1BUAQAAAIAdKKoAAAAAwA4uZR1AaTl//rz+\n/e9/KykpSU2aNFGnTp3k4nLH7D4AAAAAB7kjqoqNGzdqxowZysjIsC275557NH36dLVt27YMIwMA\nAABQ0VX6y/9WrlypiRMnqqCgQCNGjNA777yjZ599VhcvXtTLL7+sLVu2lHWIAAAAACqwSl1UnTp1\nSvPnz5efn5/Chw/Rtp//ozn/Z76STYZemTJJFotFEyZM0L59+8o6VAAAAAAVVKUuqt59913l5OSo\nRYeH9bfPl+rHg/uVb83Xpu2bNeej99T/hYEqKCjQ+PHjdenSpbIOFwAAAEAFVGmLqhMnTig+Pl73\nNbpfW77/t6rVvls+je/T5SoFqv1gQ3lW9dbKr9eo73PP6Pz583rnnXdkjCnrsAEAAABUMJW2qPr0\n008li5RizZTbXVWU6pSjPDfpnnq1dCozWVk+FuW7SZv3JahJU3+tX79e69evL+uwAQAAAFQwlbKo\nys/PV1xcnLxr+CpLecrzdpLLfT7K9DY6b0mXpYaXnKt7yvWeqjqfkqzGDzeXu7u73nvvPWVmZpZ1\n+AAAAAAqkEpZVO3fv18pKSlyqeYhSzUPWap7qKCai1zr+shyr7dca/mooKqL8rws8rzXV+s3b1DI\nM32VnJysqKgoLgMEAAAAUGyVsqj66aefJCeLUnMzJR9XydddbtWr6G7vu1W3Wh1V8fKRU01vOfl5\nKNulQFZnydOvipo2bap169Zp1apVZb0LAAAAACqISllUHTlyRPJwlrxcJG83WXw9dLf33fJ09VZV\n96ry8/KTj1c1GR93qaqbXKp7aV3cPzVr1iz5+vrq3Xff1Y8//ljWuwEAAACgAqiURdXp06clN2fJ\n3VnydVPVKj662/su3Vv1HlXz8NE93nfLz7O6PKtWkZOPu+Thooupl7T/2CFNmzZN+fn5ioiIuFKc\nOcCxY8cUHh6u3//+9woNDdWvv/7qkH4AAAAAOF6lLKrOnz8vZw9XWaq4yeLpKh93H1V1r6J7vO/S\n/b615edVXb6evvJ295bxclGBqyQ3Z8Vv36xOnTopMjJS6enpmjx5srKysko0ttzcXE2ePFkHDhxQ\ndna2Dh48qMjISFmt1hLtBwAAAEDpKPWiyhijadOmacCAAQoPDy/xWRpjjE6dPi3jYpHcneXi6S4f\n96q628tP7q4eMpKquHvLx72KfD2qyeLhInm4qIqvj77fv1fGGPXs2VPPPvusjh49qrlz55ZofEuW\nLNHhw4fVp08fxcXFKSgoSHv27NGXX35Zov0AAAAAKB2lXlRt3LhRubm5WrFihcaOHavZs2eXaPsZ\nGRnKzs6ScZbk7CQ3d3e5u1z5z9fdW0386quKWxV5uXnJ3cVdLu5ukouTfKpV0+XUFKWkpUqSxowZ\no9/97nf66quvdOHChRKJzRijtWvXqkqVKvrLX/4iSRo3bpycnJy0bt26EukDAAAAQOkq9aJq9+7d\n6tSpkySpVatW2rdvX4m2n5KSIlkskpOT5OIkV2dXebl6yWKxyNejujIL8uXrUU0eLu5ydXaVq6ur\n5GKRk+uVoTh74ZwkydXVVf369VNBQYE2bNhQIrElJSXp7NmzeuSRR+Tt7S1Juueee+Tv76/9+/cr\nPz+/RPoBAAAAUHpKvahKT09X1apVba9dXFxK9H6ivLw8yaIr/zlJFotFLk5XdrPgN+s5WZzlJIss\nFifJ6eoGUk5urm2dZs2aSZLOnTtXIrGlpKRIkmrWrHnNcl9fX+Xn51+JHQAAAECF4lLaHVapUkUZ\nGRm211arVU5Ohdd20dHRWrBgQYnGYLFYirXe1YdUlPQM0v+2d/XLhvnSYdjLEfkCVEbkClA85ApQ\nPKU+U/Xwww/r22+/lSTt2bNHDzzwwE3Xj4iI0KFDh675Ly4urtD1vb29JWMkq5EKrCqwFig7/8rs\nk+v/n6vKzs9RXkGu8k2BCgoKpIL/v76k6tWq2drasmWLJCkwMPD2d/g36tevL4vFokOHDtmWGWN0\n/Phx+fn5ycvLq0T6wZ3rVvMFuFORK0DxkCtA8ZR6UdWtWze5ublpwIABmjNnjiZNmlSi7fv4+EhW\nXSmS8o3y8vOUnZ8lq9WqYymn5aUCnc84r+z8HOUX5CsvL1fKtyo3J0dOTk6q4Xe3pCtfIPzFF1+o\nevXqateuXYnE5u3trQcffFB79uyx3Uu2efNmnTlzRm3atCmRPgAAAACUrlK//M9isSgyMtJh7bu7\nu6tGjRpKzs+W8qzKycpSZl62zmVc0L1V79GhlNMyxqq0nHSl5qSpIDtXyi3QpQsX9bu69eXh7qGM\njAy9+uqrysnJ0axZs648zKKEREREaNiwYXr55Zc1evRoffjhh3J2dtZLL71UYn0AAAAAKD2V8st/\na9SoIeUVSNn5Mjn5SslOUVZelk6nnlVefq4uZFxSak6a0nPTpewCKbtAeZk5atuytXJzczV+/Hgd\nO3ZMzz33nB577LESja1169bq27evUlNTFRkZqbNnz2rQoEFq0KBBifYDAAAAoHSU+kxVabjnnnt0\nIPGILBl5UlqOUqun6Gz6ed3tdZfyrfnKyc/V5azLSs9KkyUtT+7GRVn5Vj0Z1FNvvvmmEhIS1Llz\nZ40ePdoh8U2YMEF9+/bVjh075OfnpyeeeMIh/QAAAABwvEpZVNWtW1fafmWmSql5yk7N0EXni7Ia\nq5wtziowBbqQkaz81CyZtBxlXUxXS/8W+uXIca1du1b+/v6aNWuWXFwcMzwuLi7y9/eXv7+/Q9oH\nAAAAUHoqZVHVqFEjKadATrlGJj1XupyjTPd05RTkyMPFQzn5OcpNz5Tlcp6csqzKT89Vx9btNWPG\nDHl6emrWrFny8PAo690AAAAAUAFUyqLq6pP0qrtVUXJKtuThogJJBT5ucvdxUk5KuiypebJezJTT\n5Wzdd3dN7d66Q1lZWZo9e7buv//+st0BAAAAABVGpXxQxb333qtGjRrp0qnzUmquXLKMdD5LbmlG\nab8myzvDIuvZdHnlu6ggNVvtmrbWv7f/WwEBAeratWtZhw8AAACgAqmURZUkPfPMMyrIyFXNancr\n73SKfJw8lXPyoszpdKX/ckF+rlWVkZis9q3a6Ksv1snHx0dTp06VxWIp69ABAAAAVCCVtqh68skn\n5evrq5Rfzqmqm5cu/3xKdavU0EN1/dXQ5z4l/5yoOvfU0oUjp5Sbk6MJEybovvvuK+uwAQAAAFQw\nlbao8vDw0ODBg5WVlqFHHmitpo2a6OTBY/r+uwQdOfCzHmrWUvW8a+rIz4fVu3dv9ezZs6xDBgAA\nAFABVcoHVVz17LPPKjY2Vl//Y73++Mc/auDTz+rM+bNqUPt+xa5cre++26xWrVpp/PjxZR0qAAAA\ngAqqUhdV7u7umjt3rl5++WUtXLhQktStWzf9n+hFysjIULt27fT222/z+HQAAAAAt63SXv53VcOG\nDbVs2TL94Q9/kLu7uzZs2CAPDw+NHDlS8+bNk6enZ1mHCAAAAKACq9QzVVf5+vpqxIgRGjZsmM6d\nO6caNWrI3d29rMMCAAAAUAncEUXVVW5ubqpTp05ZhwEAAACgEqn0l/8BAAAAgCNRVAEAAACAHSiq\nAAAAAMAOFFUAAAAAYAeKKgAAAACwA0UVAAAAANiBogoAAAAA7EBRBQAAAAB2oKgCAAAAADu4lHUA\nt6OgoECSdObMmTKOBCgb9957r1xcipe+5AvuZOQKUDzkClA8heVKhSyqzp8/L0kaNGhQGUcClI24\nuDjVqVOnWOuSL7iTkStA8ZArQPEUlisWY4wpg3jskp2drX379qlGjRpydnYudL3g4GDFxcWVYmTE\nQAylE8OtnFEsTr5UprEhBmL4rZLOlZKMzR7EQAwlHQO5QgzEUDyVaqbKw8NDbdu2Lda6xT3r4kjE\nQAxlGUNx8+VOHBtiIIbf4rOFGIiheMgVYiCG6/GgCgAAAACwA0UVAAAAANiBogoAAAAA7OD8+uuv\nv17WQThS+/btyzoEYiCGchfDjZSHuIiBGMpbDIUpD7ERAzGUtxhupDzERQzEUBoxVMin/wEAAABA\necHlfwAAAABgB4oqAAAAALADRRUAAAAA2IGiCgAAAADsQFFVhj777DN99dVXkqRJkyZpzZo1JdLu\nypUr9dRTT+npp5/Wq6++qvz8/OvWCQsL06lTp0qkv/IgPz9fDz/8sFJTU23L+vXrp6FDh9peHz9+\nXEFBQTp//rz++Mc/3rS9H374QW+99ZbD4sWtIVdKXnR0tJ5++mn17t1b/fv315YtW25p+3379um1\n115zUHQoDvKi5NmbF6gcyK2SFRsbq/bt26tPnz4KCQlRSEiIXnzxxZtuExYWpp07dyohIUFhYWGl\nFKl9KKrK0Pfff6/c3NwSbfPEiRP6+OOPtXLlSn355ZeyWq1atmzZdetZLJYS7besubi4qE2bNvr+\n++8lSRcvXpQxRsePH1dOTo4kadeuXerYsaNq1KihhQsX3rS9o0ePKjk52eFxo3jIlZL11Vdfaf/+\n/Vq7dq3Wrl2ruXPn6pVXXtHFixeL3UaLFi00Y8YMB0aJopAXJask8gKVA7lV8oKCghQbG6s1a9Zo\nzZo1Wrx4cbG3rShj4lLWAVQECQkJ+vDDD2WM0a+//qru3buratWq2rhxoyTpb3/7m/z8/LRp0ya9\n9957Msaobt26mj59uvz8/BQUFKTevXvru+++U3Z2tt58802lpKQoPj5eO3bsUI0aNSRJmzZt0rJl\ny5ScnKzhw4erf//+18Qxb948bd68+ZplTz31lIYMGWJ77ebmptdff11eXl6SpAceeECnT5++bp9u\n9CT99PR0jR07VhcuXJAkjRw5Ul26dNHJkyf1+uuv6/Lly/L09NSUKVPUtGlTHT58WDNmzFBWVpaS\nk5M1ZMgQhYaGavv27YqKipKTk5OqVaumt99+W76+vlq9erWWLFkii8Wi5s2ba+rUqfL09FTHjh3V\ns2dP7d69Wy4uLnr33XdVu3ZtW1xWq1V9+/a9LqnmzZun+vXr2163b99e//nPf/TYY49p27Zt6tCh\ng06fPq2EhAR16tRJu3fv1uOPP66kpCSFhYUpPj5ekyZNUpUqVbR//36dPXtWI0eOVNeuXTV//nxl\nZmZq4cKFGjZsmObOnauEhARZrVb16dNHL7zwghISEhQVFSWr1aoHHnhAs2fPLvJnqbIjVypGrly4\ncEFWq1XZ2dny9PRU/fr1NX/+fLm6uiopKUnDhw/X/fffr19++UW1a9dWVFSUfHx8FBgYqBYtWig5\nOVnjx4/XBx98oJiYGIWFhally5bavXu3Ll26pClTpqhTp046e/asxo0bp9TUVDVu3Fg7d+7Ut99+\nW+TPUWVDXlSOvLj6uSFJCxYssO1jx44d1aVLF+3atUs1atTQwIEDFRMTo7Nnz2rOnDlq27atwsLC\n1KxZM23btk25ubmaPHmyYmJidPToUYWHh2vw4MHKzMzU9OnTdfjwYVmtVg0bNkxPPPGEYmNjFRsb\nq8uXL6tLly4aPXr0TX7a7izkVsXIrZtZv369lixZopycHGVnZ2vmzJlq27ZtsbYtdwyKtGPHDtOm\nTRtz5swZk5WVZR566CHz2WefGWOMmThxolm6dKlJTk42nTp1MqdOnTLGGLN48WIzatQoY4wxXbp0\nMUuXLjXGGBMTE2MiIiJs28bGxtr+PXz4cGOMMT///LMJDAy0O+7k5GTTpUsXs3PnzuveCw0NNUlJ\nSdcsi42NNdOnTzfGGHPkyBEzd+5cY4wxAwYMMD/99JNteY8ePYwxxrzxxhtm+/btxhhjTp48aVq3\nbm2MMSYsLMz8+OOPtv3dunWrOXTokOnWrZtJSUkxxhgTGRlpa79JkyYmLi7OGGPMnDlzzJw5c25r\nf/ft22dCQ0ONMca88sorZvv27Wb16tVm1qxZxhhj6z8xMdEEBQUZY66M+9XjcejQIdOuXTtjjDFf\nfPGFmThxojHGmOXLl9tiysnJMaGhoWbXrl1mx44dJiAgwKSnp99WvJURuVIxciUlJcUMGDDAPPTQ\nQ2bIkCFm0aJF5vz588YYYxITE02TJk1sYzFnzhwzc+ZMW/9Xl+/YscOEhYXZxuhqnsXHx5u+ffsa\nY4yJiIgwy5cvN8YYs2HDBuPv739b8VZ05EXlyIurnxvGGBMdHW2io6Nt/cfHx9tiHzt2rG08Ro4c\naRuv2bNn27bt3r27ycnJMUlJSSYgIMAYY8xbb71lYmJijDHGpKWlmSeffNL8+uuv5osvvjDdu3c3\nVqv1tvarMiO3KkZuffHFF6Zdu3YmJCTE9O7d24SEhJgdO3YYq9VqBg8ebC5dumSMMWbVqlW2sQ4N\nDTUJCQnXfNaUd8xUFVPjxo1Vs2ZNSVL16tUVGBgoSapdu7ZSUlL0ww8/qFWrVrrvvvskSc8995wW\nLVpk275jx462djZs2HDDPoKDg23rXL58+br3582bd81ZXovFct2ZkKvOnj2rYcOGqX///sWu+Fu3\nbq158+bpzJkzevzxx/XnP/9ZmZmZ+vHHHzVp0iTb2ZPs7GylpKRo4sSJ2rJlixYtWqRDhw4pKytL\n0pUp3hEjRqhr167q2rWrHnnkES1btkxBQUHy8fGRJPXv31+vvvrqDcdn165d18T12zMhV2OwWCzX\nnQlp1qyZTp48qby8PO3evVszZsxQgwYNbGcMfX195ePjo7S0tGvaf/TRRyVdOWv023uyrtq2bZsO\nHTqk7du3S5KysrL0888/q2HDhmrQoIG8vb2LNb53CnKl/OeKj4+Pli9frsOHD2vr1q2Kj4/XRx99\npFWrVslisahBgwa2sQgJCdG4ceNs27Zs2fKGY9KpUydbXCkpKZKkrVu3as6cOZKkrl272vbpTkRe\nVPy8uJmrP/+1a9dWmzZtJEm1atWy5YIkde7c2bZOq1at5Obmplq1atk+k7Zt26acnBytWrXKNk5H\njhyRJDVv3rzCXAJV2sit8p9bV/u+0RU90dHR2rRpk44fP66EhAQ5OzsXa0zKI4qqYnJ1db3m9f8e\ndKvVes2UrdVqVUFBge21u7u7JF3zg/e/XFxufjhGjx5drGn/o0ePatiwYbZLCoqrXr16Wr9+vbZs\n2aL4+Hh9/PHH+vzzz+Xu7q7Y2FjbemfPnlW1atUUEREhX19fdenSRU888YTtps7BgwcrODhYmzZt\nUlRUlLp37y5vb+/r9vu34+Pm5ibpxuPj5ORUrJtELRaLWrVqpbVr16pBgwZydXVVzZo1VVBQoM2b\nN6tDhw433O7qsSmM1WrV+PHj1bVrV0nSpUuX5O3trT179hS57Z2IXCn/ubJkyRIFBgbK399fjRs3\n1uDBgzVu3Dh988036tGjxzXHzBhzzXhf7f9/3ei4OTs7y2q1XtPWnYq8qNh50bNnz2vazcvLu+aY\n/nbsCzsOv13/Rn84Wq1WRUVFqWnTppKk5ORkVatWTevWreOz5ibIrfKfW4XJzMzUM888o5CQEAUE\nBKhJkyY3vM+souBBFSWkVatW2rt3r+2JLStXrrSdLSmMs7PzDZ/8It3+Hx8ZGRl68cUXNXr06FtK\nWElatmyZ5s+frx49emjq1Km2m3Pr16+vL7/8UtKVM8+hoaGSrpxVe/nllxUUFKSEhARJV35Z9e/f\nX+np6QoPD1d4eLgOHDig9u3ba9OmTbaZoM8++6zI8bkd7du315IlS2yzT1eXLV269JplhfntH4NX\nf6kEBgZq5cqVys/PV0ZGhgYOHKi9e/eWeOx3CnKl7HMlLS3Ndt+gdGX2NTEx0fbH3PHjx3Xw4EFJ\n0urVq21n2G/Vo48+qnXr1kmSvv322+tmifFf5EX5zgsfHx+lpqbq0qVLys3NLdGnAl49VoGBgfr0\n008lSefOndPTTz99w3tucGvIrbLPrcKcOHFCzs7OGj58uAIDA7V58+ZrTsRVNMxU3YYbTcHfdddd\nmjFjhkaMGKH8/HzVqlVLb7zxRqHrS1KHDh00b968G14Sc7vT/J9//rmSk5P18ccf66OPPpLFYlFQ\nUJAiIiKK3LZ3794aO3asnnrqKbm6uurll19WlSpVFBUVpWnTpmnx4sVyc3PTu+++K0mKiIjQ888/\nLx8fHzVo0EC1a9dWUlKSxowZo4kTJ8rZ2Vmenp6KjIxUo0aN9NJLL2nQoEEqKChQ8+bNFRkZade+\n3khgYKBmzpxpm66Wrkxdr169Wq1bty5y+6uxtGzZUu+//77eeecdjRo1SidOnFCfPn1UUFCgZ555\nRgEBAbZfVCgcuVI+c2XEiBF655139PTTT8vDw0MWi0VhYWF65JFHlJSUpGrVqik6Olq//PKLmjRp\norFjx960/8KWT5o0Sa+88oo+//xzNWnS5I6+/O+3yIuKlxeSNHToUPXr10+1atVSq1atbNsVp/+b\nrXP1vREjRigyMlJPPfWUrFarJkyYoLp16153yRUKR26Vz9wqjL+/v/z9/dWjRw95eXkpICDAVvxW\nxMtdLeZOvh7jDhYWFqY333xTtWrVKutQgHLtTsuV/33KmT1iYmLUoUMHNWzYUAcOHNBrr72m1atX\nl0CUKGt3Wl4ApYXcqriYqbpDVcQzAEBZuBNzpaT2uV69ehozZoycnJzk7u6umTNnlki7KHt3Yl4A\npYHcqriYqQIAAAAAO/CgCgAAAACwQ4UsqvLz85WYmFjok1kA/Bf5AhQPuQIUD7kCXK9CFlVnzpxR\ncHCwzpw5U9ahAOUe+QIUD7kCFA+5AlyvQhZVAAAAAFBeUFQBAAAAgB0oqgAAAADADhRVAAAAAGAH\niioAAAAAsANFFQAAAADYgaIKAAAAAOxAUQUAAAAAdqCoAgAAAAA7UFQBAAAAgB0oqgAAAADADhRV\nAAAAAGAHiioAAAAAsANFFQAAAADYgaIKAAAAAOxAUQUAAAAAdqCoAgAAAAA7UFQBAAAAgB0oqgAA\nAADADhRVAAAAAGAHiioAAAAAsANFFQAAAADYgaIKAAAAAOzg4qiG8/Pz9eqrryopKUl5eXkaPny4\nGjVqpIkTJ8rJyUmNGzfWtGnTHNU9AAAAAJQKhxVVX375papXr665c+cqNTVVvXv3lr+/v8aMGaO2\nbdtq2rRp2rhxo7p27eqoEAAAAADA4Rx2+V+vXr00atQoSVJBQYGcnZ114MABtW3bVpLUuXNnbd++\n3VHdAwAAAECpcFhR5enpKS8vL6Wnp2vUqFEaPXq0jDG29729vZWWluao7gEAAACgVDjs8j9JOn36\ntEaOHKnQ0FD9/ve/V1RUlO29jIwM+fj4FNlGdHS0FixY4MgwgUqDfAGKh1wBiodcAYrHYn47fVSC\nLly4oPDwcE2dOlWBgYGSpD/96U8aMmSIAgICNG3aNAUGBqpXr1633HZiYqKCg4MVFxenOnXqlHTo\nQKVCvgDFQ64AxUOuANdz2EzVwoULlZqaqr/+9a96//33ZbFYNHnyZM2cOVN5eXlq2LChevbs6aju\nAQAAAKBUOKyomjx5siZPnnzd8piYGEd1CQAAAAClzqH3VFVGR48e1Zw5c5SVlaV69eppwoQJqlat\nWlmHBQAAAKCMUFTdgtzcXE2aNEnHjh2TJB08eFAXL15UdHS0XFwYSgAAAOBO5LBHqldGS5Ys0bFj\nx9S3b18lJCToscce086dO/X++++XdWgAAAAAyghFVTFlZ2frk08+0d13362XX35ZTk5OioyMVJ06\ndfTpp5/q119/LesQAQAAAJSB/8fencdHVd/7H3+fmcm+kAWIkiigsogIyCJUBCUBAZeCoGySqKgt\nLpTLokJlB0GLVq/BWhX9IUETVAqoV/FKoGKVgiCLgKxCMZEAhhCyLzPn9wdlKhdCBiazJHk97+M+\nypzMnPPOhA/xPd8zZyhVLtqwYYOKi4t15513Kjw8XJIUHh6uxx9/XHa7XW+//baPEwIAAADwBUqV\ni7Zu3SpJzs/cOiMpKUlNmjTRmjVrVFZW5otoAAAAAHyIUuWiXbt2yTAMRURF6rejhmr05LFavupj\nGYahxMREFRUVacuWLb6OCQAAAMDLKFUu+umnnxQXF6fP12XqyLEcbf5+q+YueEHbdn2vjh07ShKl\nCgAAAKiHKFUusNvtOn78uC6//HJ9t2ObbDabpv7hKUnShq2bnKXqzCmCAAAAAOoPSpULTp06JdM0\n1aBBAx3410E1S7hS3bv8RpK098f9Cg8PV3x8vA4ePOjjpAAAAAC8jVLlgtLSUklSYFCQSstK1Ti2\nkWKjY2S1WJVfcEqSFBsbq/z8fF/GBAAAAOADlCoXVFZWSpIs1tNPV2BAgEzTlMVicX7NarXKbrfL\n4XD4LCcAAAAA76NUucBqtUqSLIYhwzCUX1ig/FP5qqisUMOYWEnSiRMnFBUVJYuFpxQAAACoT2gA\nLggODpYklZaUqlFsQx3O/km7D+yTJF3ZJEGlpaXKzs5WfHy8L2MCAAAA8AFKlQsiIyMlSSdPnlS7\n1tcpN++ExkybKEnq2rGLtm/frsrKSudVAAEAAADUH5QqF9hsNjVs2FBHjx5VYvdbnNt73dRTndp2\n0KZNmyRJN9xwg68iAgAAAPARm68D1BZXXnmltm7dqh5dbtKajE9UUFSoJnGXyzRNffnll7JarerU\nqUNvlakAACAASURBVJOvYwIAAADwMlaqXNSmTRs5HA7t2LFDEeERahJ3uSTpu+++04EDB5SYmKiw\nsDAfpwQAAADgbZQqF515v9TXX3/t3OZwOPTqq69KkoYNG+aTXAAAAAB8i1Lloq5duyo8PFwfffSR\njh8/Lkl6//33tX37diUmJqp9+/Y+TggAAADAFyhVLgoKCtKjjz6q/Px83XPPPXr99df10ksvKTo6\nWk8++aSv4wEAAADwEUrVRRgyZIj69eunoqIivfnmm7LZbJo/f74aNWrk62gAAAAAfISr/10EwzA0\nZcoUPfzww9q/f786dOighg0b+joWAAAAAB+iVF2k4OBgNWvWTM2aNfN1FAAAAAB+wOOn/23btk3J\nycmSpB9++EE9e/ZUSkqKUlJS9Nlnn3n68AAAAADgUR5dqVq4cKFWrlzp/PymHTt2aNSoUXrggQc8\neVgAAAAA8BqPrlQ1bdrU+TlOkrRz5079/e9/18iRI/XMM8+ouLjYk4cHAAAAAI/zaKnq06ePrFar\n83b79u311FNPacmSJbriiiuUmprqycMDAAAAgMd59UIVvXv3VkREhKTThWvOnDnVPiY1NVULFizw\ndDSgTmBeANcwK4BrmBXANYZpmqYnD5Cdna0JEyYoIyNDQ4YM0dSpU3X99ddryZIlysnJ0cSJEy96\nn1lZWUpKSlJmZqYSEhI8kBqoO5gXwDXMCuAaZgU4l1dXqmbMmKHZs2crICBAjRo10qxZs7x5eAAA\nAACocR4vVfHx8crIyJAktWnTRunp6Z4+JAAAAAB4jcc/pwoAAAAA6jJKFQAAAAC44YKlav369Tpw\n4IDzdlpamr755huPhwIAAACA2qLKUvXpp59q+vTpKikpcW6LjY3VtGnT9Pnnn3slHAAAAAD4uypL\n1cKFC5WWlqa2bds6t91+++1atGiRXn/9da+EAwAAAAB/V2WpMk1TcXFx52xPSEiQw+HwaCgAAAAA\nqC0uWKqKiorO2V5YWKiKigqPhgIAAACA2qLKUjVgwACNGzdOR44ccW7LycnRxIkT1bdvX6+EAwAA\nAAB/V+WH/z744IPKy8tT//79FR4eLtM0VVJSovvuu09PPPGENzMCAAAAgN+qslRJ0vjx4zV69Gj9\n+OOPslgsuvrqqxUUFKSCggJFRER4KyMAAAAA+K0LlipJCg0NdV4BcNu2bcrIyNCqVau0ZcsWj4cD\nAAAAAH93wQ//laSioiKlp6drwIABGjFihCQpIyPD48EAAAAAoDaocqVq165dSk9P16pVq3T99ddr\n5MiR+stf/qJ58+Z5Mx8AAAAA+LUqV6oGDRqkgoICrVy5Um+//bbuvfdeWSzVLmwBAAAAQL1SZUt6\n7bXX5HA4NHDgQI0fP16rV6+WaZrezAYAAAAAfq/KUtWrVy+98sor+vzzz9WhQwctWLBAOTk5mjlz\npvbt2+fNjAAAAADgt6o9ny86OlopKSlasWKFli1bJqvVqpSUFG9kAwAAAAC/d1Fvkrr22ms1ZcoU\nrVu3zlN5AAAAAKBWuaQrTwQEBNR0DgAAAAColbicHwAAAAC44aJK1dKlSz2VAwAAAABqpYsqVRkZ\nGZ7KAQAAAAC10kWVKj6nCgAAAADOdlGlatiwYZ7KAQAAAAC1EqUKAAAAANzg8av/bdu2TcnJyZKk\nw4cPa8SIERo5cqRmzpzp6UMDAAAAgMdVW6pOnDhxyTtfuHChpkyZooqKCknSvHnzNH78eC1ZskQO\nh0OrV6++5H0DAAAAgD+otlTdd999l7zzpk2b6tVXX3Xe3rlzpzp37ixJ6tmzp9avX3/J+wYAAAAA\nf2Cr7g6tW7fWihUr1K5dOwUHBzu3N2nSpNqd9+nTR9nZ2c7bv756YFhYmAoKCi42LwAAAAD4lWpL\n1bZt27Rt27azthmGoczMzIs+mMXyn4WxoqIiRUZGVvuY1NRULViw4KKPBdRHzAvgGmYFcA2zArjG\nMD384VPZ2dmaMGGCMjIy9Oijj2rUqFHq0qWLpk+frm7duql///4Xvc+srCwlJSUpMzNTCQkJHkgN\n1B3MC+AaZgVwDbMCnKva91Tl5+drypQpSklJUV5eniZPnqxTp05d0sGefvppvfLKKxo2bJgqKyvV\nr1+/S9oPAAAAAPiLak//mzp1qrp3767t27crLCxMjRs31sSJE/XGG2+4dID4+HhlZGRIkpo1a6a0\ntDT3EgMAAACAH6l2pSorK0tDhw6VxWJRYGCgxo0bp5ycHG9kAwAAAAC/V22pslqtKigokGEYkqRD\nhw6ddcEJAAAAAKjPqj39b8yYMUpOTtaRI0f02GOPaevWrZo7d643sgEAAACA36u2VPXs2VNt27bV\n9u3bZbfbNWvWLJcuhQ4AAAAA9UG15/ENHTpUMTExuvXWW5WUlKSYmBgNHjzYG9kAAAAAwO9VuVKV\nkpKijRs3SpJat27tfE+V1WpVYmKid9IBAAAAgJ+rslQtXrxYkjRnzhxNmTLFa4EAAAAAoDap9j1V\nTz75pL744gsVFRVJkux2u7KysjR27FiPhwMAAAAAf+fS1f9KSkp0+PBhde7cWd9++606dOjgjWwA\nAAAA4PeqvVDFwYMHtXjxYvXp00cPP/ywPvjgAx07dswb2QAAAADA71VbqmJjY2UYhpo3b649e/Yo\nLi5O5eXl3sgGAAAAAH6v2tP/WrRoodmzZ2v48OGaOHGijh07poqKCm9kAwAAAAC/V+1K1YwZM9S/\nf39dc801GjNmjI4dO6YXX3zRG9kAAAAAwO9Vu1JltVplGIbS09M1ePBgRUZGqmXLlt7IBgAAAAB+\nr9qVqnfeeUcvv/yyFi1apKKiIk2bNk1vvfWWN7IBAAAAgN+rtlQtX75cb731lkJCQhQdHa0PP/xQ\ny5Yt80Y2AAAAAPB71ZYqi8WiwMBA5+2goCBZrVaPhgIAAACA2qLa91TdeOONev7551VSUqLVq1dr\n6dKl6tatmzeyAQAAAIDfq3al6qmnnlLTpk3VqlUrrVixQrfccouefvppb2QDAAAAAL9X7UqVxWLR\nsGHDNGzYMG/kAQAAAIBapcpS1bp1axmGcc520zRlGIZ++OEHjwYDAAAAgNqgylK1e/du558HDhyo\nFStWeCUQAAAAANQm1b6nStJ5V6wAAAAAAC6WKtM0PZ0DAAAAAGolVqoAAAAAwA1VvqcqMTHRWaaO\nHj2qpKQkSf+5UEVmZuYlH3TQoEEKDw+XJCUkJGju3LmXvC8AAAAA8KUqS1VaWppHDlheXi5JWrx4\nsUf2DwAAAADeVGWpio+P98gBd+/ereLiYj300EOy2+0aN26c2rdv75FjAQAAAICnVfvhvzUtODhY\nDz30kO69914dOnRIjzzyiD7//HNZLC69vQsAAAAA/IrXS1WzZs3UtGlT55+joqJ0/PhxxcXFnff+\nqampWrBggTcjArUW8wK4hlkBXMOsAK4xTC9fLz09PV179+7V9OnTdfToUT344IP65JNPLmqlKisr\nS0lJScrMzFRCQoIH0wK1H/MCuIZZAVzDrADn8vpK1T333KPJkydrxIgRslgsmjt3Lqf+AQAAAKi1\nvF6qAgIC9MILL3j7sAAAAADgESwRAQAAAIAbKFUAAAAA4AZKFQAAAAC4gVIFAAAAAG6gVAEAAACA\nGyhVAAAAAOAGShUAAAAAuIFSBQAAAABuoFQBAAAAgBsoVQAAAADgBkoVAAAAALiBUgUAAAAAbrD5\nOoC3nDx5Ut99952Ki4vVsWNHNWnSxNeRAAAAANQB9aJUHT58WI8++qiOHj0qSQoNDdW0adPUu3dv\nHycDAAAAUNvV+dP/jh8/7ixUw4cP1xNPPCHTNDVp0iR99NFHvo4HAAAAoJar86Xqz3/+s44ePape\n/Xtr58/79emGNep3z12KiIzQ888/r/379/s6IgAAAIBarE6XqqysLK1evVrxV12pv29Zr+/37dLB\nnw9rxRf/oxadrlNZWZlefvllX8cEAAAAUIvV6VK1fPlymRbpaFm+bLGhMuLCZDQOVWhCtLbs/l5N\nWjbVP//5T/3jH//wdVQAAAAAtVSdLlXr16+XJTJI9mDJHmFTYONIhTSJUkmQqcDGETpefFKG1aK/\n/vWvMk3T13EBAAAA1EJ1tlTl5+dr3/59MkNtMqKDZTQMVUUDq0ojLDIahqgi1FBlkKGEVs21e/du\nbdmyxdeRAQAAANRCdbZUffXVVzIDLVKoTWoQJDUMVkBsmAJjwmVpHCqjYagsUUHKLcmXJH355Zc+\nTgwAAACgNqqzpWrz5s1SoFWKCJQRE6zQ6AaKaBCtyAbRCm8QJUUFyQwPUIkqFBwVplWrVqmiosLX\nsQEAAADUMnW2VO3atUuW0AAZ4YGyRYcqNqKhGoU1VMPQWDUMb6jgqHApKlgKsSqmSWPl5uayWgUA\nAADgotXJUmWaprKysmSEBEjhgQoOC1Oj0FhdFhGnyyMvU6OwRgoPi5QRZpMlIli5hadPAVy/fr2P\nkwMAAACobWy+DuAJeXl5Kisrk2ENkRFmU0RopKJCohQWGKoAi03BtiDlFkfpZOQJVQQWqtxerpDI\nMC5WAQAAAOCieb1UmaapGTNmaM+ePQoMDNSzzz6rK664okaPcfLkScliSEFWWUMCFREcoZiQKAXZ\ngiRJAdZARQZFKCAwUBXBVinAosaXNVTWgX+psrJSNlud7JoAAAAAPMDrp/+tXr1a5eXlysjI0IQJ\nEzRv3rwaP0ZhYaFkNaQAiyxBNoXYQhRoDVSQNUBxYbEKDQhRaGCYgoKCpSCrZLMoNCJcdrtdx48f\nr/E8AAAAAOour5eqzZs3q0ePHpKk9u3ba8eOHTV+jPLy8tMrVVaLDKtVIQHBCgsMVUxYrCzWAEUE\nhSvEFqQAa4Bks0hWQ9YAq6TTn28FAAAAAK7yeqkqLCxURESE87bNZpPD4ajRY9jt9tN/MCTDkKyG\nVTZrgPPrhmHIYrHIMCyn7yDj9J8lVVZW1mgWAAAAAHWb1988FB4erqKiIudth8Mhi6XqbpeamqoF\nCxa4dUxTpkzTdN42ZDi/8p//Nf/vw4BapybmBagPmBXANcwK4Bqvr1R17NjR+XlQW7duVcuWLS94\n/zFjxmjPnj1n/X9mZuYFHxMYGCiZpmQ3ZdodKqsoU1F5kez2clkk5Zfmq6yy/PSKlt0hOSSH/fRq\nWXh4eI18n4AvXMq8APURswK4hlkBXOP1lao+ffro66+/1rBhwyTJIxeqCAkJkRymZHfIUWFXqb1M\n5fZyHSs6Ien0FQiLy0tUVlEmVTgku0PlpWWSpJiYmBrPAwAAAKDu8nqpMgxDM2fO9OgxGjRoINlN\nqcwue2mFCsoKdLwoV43CYmWz2FRSWarCikKVl5dKJZVSpUMnfzmhqKgoRUZGejQbAAAAgLqlTn4g\nU0xMjGRKRqUps6RChaWFOlVWIFOmLIZF5fZynSzJV2VxmYxyu8wKh47nHFW3rt18HR0AAABALVMn\nS1VQUJAaNWqkE+VlMgvKVVh0SidCT6jSXiGrxaaSyhKdKs6Xo7BMKq5UwwYxOn6kSF26dPF1dAAA\nAAC1jNcvVOEtLVq0kL2wTGZRhSryi3W88Lh+Kc5VbnGufinKVUlBocyTZXIUlcssqZTFYlHfvn19\nHRsAAABALVNnS1W7du2kcod0qkyOk6UqPJmv3IJc5RXlKf/UCdnziqWCchmldv2SlaPu3bvrsssu\n83VsAAAAALVMnS1VPXr0kMoqpaJK6USpzF+KVZJ3SqfyTqgst0BmbonM/DI1iWos2U0lJib6OjIA\nAACAWqhOvqdKklq2bKmoiAYqKLXLzC+XabPIViHZTYdU6ZBxqkJmQbnyS3MVGhqqnj17+joyAAAA\ngFqozq5UGYahTh07yZ5fIjOvVNbCSlUeLZD5S7GM3FI5jhfpsgaNVPDLSQ0fPvz0ZdgBAAAA4CLV\n2VIlSf3795dKK3VZg4aqPFaouIAGinGEyJ5TqIiAUJ04lKPY2FglJyf7OioAAACAWqpOl6oePXoo\nPj5ex/dn66omTZVzMFt5P/+iq+KbqnmDy1VWVKJHHnlE4eHhvo4KAAAAoJaq06XKarXqv/7rv1RZ\nUaHCw7/o+adnKXXmfCWENNS277aqe/fuGjRokK9jAgAAAKjF6uyFKs7o1auXxowZo9TUVD01boKs\nVqvsdru6dOmi2bNny2Kp070SAAAAgIfV+VIlSffff7+uv/56vf/++8rOzlaPHj00atQo2Wz14tsH\nAAAA4EH1plV07NhRHTt29HUMAAAAAHUM574BAAAAgBsoVQAAAADgBkoVAAAAALiBUgUAAAAAbqBU\nAQAAAIAbKFUAAAAA4AZKFQAAAAC4gVIFAAAAAG6gVAEAAACAGyhVAAAAAOAGm68DXAq73S5JysnJ\n8XESwDcuu+wy2WyujS/zgvqMWQFcw6wArqlqVmplqTp+/Lgk6b777vNxEsA3MjMzlZCQ4NJ9mRfU\nZ8wK4BpmBXBNVbNimKZp+iCPW0pLS7Vjxw41atRIVqu1yvslJSUpMzPTi8nIQAbvZLiYVxRdmZe6\n9NyQgQy/VtOzUpPZ3EEGMtR0BmaFDGRwTZ1aqQoODlbnzp1duq+rr7p4EhnI4MsMrs5LfXxuyECG\nX+N3CxnI4BpmhQxkOBcXqgAAAAAAN1CqAAAAAMANlCoAAAAAcIN1xowZM3wdwpO6du3q6whkIIPf\nZTgff8hFBjL4W4aq+EM2MpDB3zKcjz/kIgMZvJGhVl79DwAAAAD8Baf/AQAAAIAbKFUAAAAA4AZK\nFQAAAAC4gVIFAAAAAG6gVPnQ+++/r08//VSSNHnyZK1YsaJG9vvee+/pjjvu0J133qn58+ef9z7J\nycn6+eefa+R4/qCyslIdO3bUqVOnnNsGDx6shx56yHn74MGDSkxM1PHjx/X73//+gvvbvn27Xnjh\nBY/lxcVhVmpeamqqfvvb32rAgAEaMmSIvvrqq4t6/I4dOzR16lQPpYMrmIua5+5coG5gtmrW8uXL\n1bVrV919990aOHCgBg4cqIcffviCj0lOTta3336rjRs3Kjk52UtJ3WPzdYD6bMuWLTV+WcesrCy9\n8847WrlypYKCgjRixAh98803uummm866n2EYNXpcX7PZbOrUqZO2bNmiW265RSdOnJBpmjp48KDK\nysoUFBSkTZs26eabb1ajRo30+uuvX3B/Bw4cUG5urpfSozrMSs369NNPtXPnTq1cuVKGYejQoUMa\nMWKEPvnkE8XExLi0j7Zt26pt27YeTooLYS5qVk3MBeoGZqvmJSYmat68eZf02NrynFCqXLBx40b9\n9a9/lWma+umnn3TbbbcpIiJCq1evliS9+eabiomJ0dq1a/Xf//3fMk1TV1xxhWbNmqWYmBglJiZq\nwIAB+sc//qHS0lI9//zzys/P15o1a7RhwwY1atRIkrR27Vq9++67ys3N1ejRozVkyJCzcrz00kta\nt27dWdvuuusujRo1ynk7ISFBn376qaxWq/Ly8lRYWKiIiIhzvqfzXUm/sLBQEyZM0C+//CJJeuKJ\nJ9SrVy8dPnxYM2bM0MmTJxUSEqIpU6bo2muv1b59+zR79myVlJQoNzdXo0aN0siRI7V+/XrNnz9f\nFotFDRo00IsvvqioqCgtW7ZMixYtkmEYuu666zRt2jSFhITo5ptvVr9+/bR582bZbDa9/PLLio+P\nd+ZyOBwaNGjQOUP10ksvqVmzZs7bXbt21XfffadbbrnF+Q/VkSNHtHHjRvXo0UObN2/Wrbfequzs\nbCUnJ2vNmjWaPHmywsPDtXPnTh09elRPPPGEevfurVdeeUXFxcV6/fXX9cgjj+hPf/qTNm7cKIfD\nobvvvlv333+/Nm7cqPnz58vhcKhly5aX/I9FXcKs1I5Z+eWXX+RwOFRaWqqQkBA1a9ZMr7zyigIC\nApSdna3Ro0fryiuv1L/+9S/Fx8dr/vz5ioyMVLdu3dS2bVvl5ubqySef1Guvvaa0tDQlJyerXbt2\n2rx5s/Ly8jRlyhT16NFDR48e1cSJE3Xq1Cm1aNFC3377rb788ktX/irVKcxF3ZiLM783JGnBggXO\n7/Hmm29Wr169tGnTJjVq1EgjRoxQWlqajh49queee06dO3dWcnKy2rRpo2+++Ubl5eV65plnlJaW\npgMHDiglJUUPPPCAiouLNWvWLO3bt08Oh0OPPPKIbr/9di1fvlzLly/XyZMn1atXL40bN+7Cf+Hq\nEWardszWhXz22WdatGiRysrKVFpaqjlz5qhz584uPdbvmKjWhg0bzE6dOpk5OTlmSUmJ2aFDB/P9\n9983TdM0J02aZC5evNjMzc01e/ToYf7888+maZrmwoULzbFjx5qmaZq9evUyFy9ebJqmaaalpZlj\nxoxxPnb58uXOP48ePdo0TdPcu3ev2a1bN7cyv//++2anTp3MUaNGmRUVFed8feTIkWZ2dvZZ25Yv\nX27OmjXLNE3T3L9/v/mnP/3JNE3THDZsmPnDDz84t/ft29c0TdN89tlnzfXr15umaZqHDx82b7jh\nBtM0TTM5Odn8/vvvnd/v119/be7Zs8fs06ePmZ+fb5qmac6cOdO5/1atWpmZmZmmaZrmc889Zz73\n3HOX9D3v2LHDHDlypGmapvn000+b69evN5ctW2bOnTvXNE3TefysrCwzMTHRNM3Tz/uZn8eePXvM\nG2+80TRN0/zb3/5mTpo0yTRN00xPT3dmKisrM0eOHGlu2rTJ3LBhg9mlSxezsLDwkvLWRcxK7ZiV\n/Px8c9iwYWaHDh3MUaNGmW+88YZ5/Phx0zRNMysry2zVqpX57bffOo8zZ84c5/HPbN+wYYOZnJzs\nfI7OzNmaNWvMQYMGmaZpmmPGjDHT09NN0zTNL774wmzduvUl5a3tmIu6MRdnfm+Ypmmmpqaaqamp\nzuOvWbPGmX3ChAnO5+OJJ55wPl/z5s1zPva2224zy8rKzOzsbLNLly6maZrmCy+8YKalpZmmaZoF\nBQXmnXfeaf7000/m3/72N/O2224zHQ7HJX1fdRmzVTtm629/+5t54403mgMHDjQHDBhgDhw40Nyw\nYYPpcDjMBx54wMzLyzNN0zQ//PBD53M9cuRIc+PGjWf9rvF3rFS5qEWLFoqLi5MkRUdHq1u3bpKk\n+Ph45efna/v27Wrfvr0uv/xySdLQoUP1xhtvOB9/8803O/fzxRdfnPcYSUlJzvucPHnynK+/9NJL\nZ73KaxjGOa+EnHHvvfdq8ODBmjRpklJTU116ZeuGG27QSy+9pJycHN1666167LHHVFxcrO+//16T\nJ092vnpSWlqq/Px8TZo0SV999ZXeeOMN7dmzRyUlJZJOL/E+/vjj6t27t3r37q3f/OY3evfdd5WY\nmKjIyEhJ0pAhQ/THP/7xvM/Ppk2bzsr161dCzmQwDOOcV0LatGmjw4cPq6KiQps3b9bs2bPVvHlz\n5yuGUVFRioyMVEFBwVn77969uySpZcuWZ70n64xvvvlGe/bs0fr16yVJJSUl2rt3r66++mo1b95c\nYWFh1T639Qmz4v+zEhkZqfT0dO3bt09ff/211qxZo7feeksffvihDMNQ8+bNna8UDhw4UBMnTnQ+\ntl27dud9Tnr06OHMlZ+fL0n6+uuv9dxzz0mSevfu7fye6iPmovbPxYWc+fsfHx+vTp06SZKaNGni\nnAVJ6tmzp/M+7du3V2BgoJo0aeL8nfTNN9+orKxMH374ofN52r9/vyTpuuuuqzWnQHkbs+X/s3Xm\n2Oc7oyc1NVVr167VwYMHtXHjRlmt1mqfD39FqXJRQEDAWbf/7w/d4XCctWTrcDhkt9udt4OCgiTp\nrL94/5fNduEfx7hx46odvpycHP3888/q2LGjLBaL7rjjDqWnp1/wMWc0bdpUn332mb766iutWbNG\nb7/9tj744AMFBQVp+fLlzvsdPXpUDRo00JgxYxQVFaVevXrp9ttvd76p84EHHlBSUpLWrl2r+fPn\n67bbblNYWNg53/evn5/AwEBJ539+LBaLS28SNQxD7du318qVK9W8eXMFBAQoLi5Odrtd69atO+e8\n5TPO/Gyq4nA49OSTT6p3796SpLy8PIWFhWnr1q3VPrY+Ylb8f1YWLVqkbt26qXXr1mrRooUeeOAB\nTZw4Uf/7v/+rvn37nvUzM03zrOf7zPH/r/P93KxWqxwOx1n7qq+Yi9o9F/369TtrvxUVFWf9TH/9\n3Ff1c/j1/c/3H44Oh0Pz58/XtddeK0nKzc1VgwYN9PHHH/O75gKYLf+fraoUFxfrnnvu0cCBA9Wl\nSxe1atVK77777iXvz9e4+l8Nad++vbZt2+a8YsvSpUudr5ZUxWq1qrKy8rxfu9T/+CgoKNDEiRNV\nWFgo0zS1atUq56tm1Xn33Xf1yiuvqG/fvpo2bZpOnDghSWrWrJk++ugjSadfeR45cqSk06+q/eEP\nf1BiYqI2btwo6fQ/VkOGDFFhYaFSUlKUkpKiXbt2qWvXrlq7dq1zJej999+v9vm5FF27dtWiRYuc\nq09nti1evPisbVX59X8MnvlHpVu3blq6dKkqKytVVFSkESNGaNu2bTWevb5gVnw/KwUFBc73DUqn\nV1+zsrKc/zF38OBB7d69W5K0bNky5yvsF6t79+76+OOPJUlffvnlOavE+A/mwr/nIjIyUqdOnVJe\nXp7Ky8tr9KqAZ35W3bp103vvvSdJOnbsmH7729/qyJEjNXac+orZ8v1sVeXQoUOyWq0aPXq0unXr\npnXr1p31Qlxtw0rVJTjfEnxsbKxmz56txx9/XJWVlWrSpImeffbZKu8vSTfddJNeeuml854Sc6nL\n/C1atNDo0aM1dOhQ2Ww2de7c+bzLz+czYMAATZgwQXfddZcCAgL0hz/8QeHh4Zo/f76mT5+uhQsX\nKjAwUC+//LIkacyYMRo+fLgiIyPVvHlzxcfHKzs7W+PHj9ekSZNktVoVEhKimTNn6pprrtHvpWJS\nvAAAIABJREFUfvc73XfffbLb7bruuus0c+ZMt77X8+nWrZvmzJnjXK6WTi9dL1u2TDfccEO1jz+T\npV27dnr11Vf15z//WWPHjtWhQ4d09913y26365577lGXLl2c/1ChasyKf87K448/rj//+c/67W9/\nq+DgYBmGoeTkZP3mN79Rdna2GjRooNTUVP3rX/9Sq1atNGHChAsev6rtkydP1tNPP60PPvhArVq1\nqten//0ac1H75kKSHnroIQ0ePFhNmjRR+/btnY9z5fgXus+Zrz3++OOaOXOm7rrrLjkcDj311FO6\n4oorzjnlClVjtvxztqrSunVrtW7dWn379lVoaKi6dOniLL+18XRXw6zP52PUY8nJyXr++efVpEkT\nX0cB/Fp9m5X/e5Uzd6Slpemmm27S1VdfrV27dmnq1KlatmxZDaSEr9W3uQC8hdmqvVipqqdq4ysA\ngC/Ux1mpqe+5adOmGj9+vCwWi4KCgjRnzpwa2S98rz7OBeANzFbtxUoVAAAAALiBC1UAAAAAgBtq\nZamqrKxUVlZWlVdmAfAfzAvgGmYFcA2zApyrVpaqnJwcJSUlKScnx9dRAL/HvACuYVYA1zArwLlq\nZakCAAAAAH9BqQIAAAAAN1CqAAAAAMANlCoAAAAAcAOlCgAAAADcQKkCAAAAADdQqgAAAADADZQq\nAAAAAHADpQoAAAAA3ECpAgAAAAA3UKoAAAAAwA2UKgAAAABwA6UKAAAAANxAqQIAAAAAN1CqAAAA\nAMANlCoAAAAAcAOlCgAAAADcQKkCAAAAADdQqgAAAADADZQqAAAAAHADpQoAAAAA3ECpAgAAAAA3\n2Dy148rKSv3xj39Udna2KioqNHr0aF1zzTWaNGmSLBaLWrRooenTp3vq8AAAAADgFR4rVR999JGi\no6P1pz/9SadOndKAAQPUunVrjR8/Xp07d9b06dO1evVq9e7d21MRAAAAAMDjPHb6X//+/TV27FhJ\nkt1ul9Vq1a5du9S5c2dJUs+ePbV+/XpPHR4AAAAAvMJjpSokJEShoaEqLCzU2LFjNW7cOJmm6fx6\nWFiYCgoKPHV4AAAAAPAKj16o4siRI7r//vt1991364477pDF8p/DFRUVKTIy0pOHBwAAAACP89h7\nqn755Rc99NBDmjZtmrp16yZJuvbaa/Xtt9+qS5cuWrdunXP7haSmpmrBggWeignUKcwL4BpmBXAN\nswK4xjB/fU5eDXr22Wf12Wef6aqrrpJpmjIMQ88884zmzJmjiooKXX311ZozZ44Mw7jofWdlZSkp\nKUmZmZlKSEjwQHqg7mBeANcwK4BrmBXgXB5bqXrmmWf0zDPPnLM9LS3NU4cE4EcqKir0P//zP/ru\nu+8UHR2t4cOH67LLLvN1LAAAgBrnsVIFoP4yTVMzZ87UqlWrnNuWLl2qmTNnqm/fvj5MBgAAUPM8\neqEKAPXTokWLtGrVKrVp00ZLlizRtGnTFBQUpKlTp2rNmjW+jgcAAFCjWKkCUKPy8/P11ltvqVGj\nRnr55ZcVExOj1q1b66qrrtJjjz2madOmKT4+Xq1atfJ1VAAAgBrBShWAGvXxxx+rtLRU9913n2Ji\nYpSXf1KlZWVq27atZs2apdLSUj311FMqLi72dVQAAIAaQakCUKPWrFkji8WiG3/TVY9OHa++DwzS\nXY8M1eYdW3Xrrbfq/vvvV3Z2tqZPny6Hw+HruAAAAG6jVAGoMYWFhfr+++/Vrl07vbMiQ5u+36IW\nza5WYXGRxs56Wnt+3KdHH31UnTp10tq1a/XRRx/5OjIAAIDbKFUAasyuXbtkmqaaXXOVvvjHWrVs\nfo2W/PkNPffUDJWVl+ult/8im82mWbNmKSwsTC+88IIOHDjg69gAAABuoVQBqDG7d++WJBU6SmWa\nppIHDpVhGLrlxu7qdkMXbd6xVT/+dEhxcXGaPn26SktLNX/+fHnoM8gBAAC8glIFoMacWXU6eOQn\nBdgC1OPGm5xfG9D7dknS5+syJUmJiYm6+eabtWnTJv3973/3elYAAICaQqkCUGNycnIkSdlHj+iq\nK5spNDhEy/+xSl9s/kq/6XijDMPQth92OO8/duxYSVJ6erpP8gIAANQEPqcKQI3Jzc1VZHQDFZSX\nKT7ucm3e973mpb8qSVqfukLN4q/U7gN7nfdv3ry5brzxRm3cuFHHjh1T48aNfRUdAADgkrFSBaDG\nFBcXKzg0RJLUICJSy/+xyvm14ydz1Ti2kYpKilVaVubcfsMNN0iS9u7dKwAAgNqIUgWgxpSXlysg\nIECSFGAL0PGTJ5xfKykvc36tsrLCub1Ro0aSpLy8PC8mBQAAqDmUKgA1xjAM6d9X8quorFBSx+7O\nr10e01gnT52U1WpVWGiYc/upU6ckSREREd4NCwAAUEN4TxWAGhMUFKSKsgrJJuWdytcdXZP0c+5R\n3diqg2xWm/b/66Caxl9xunz924YNGyRJLVu29FVsAAAAt1CqANSYiIgIZf/8s4LignXkWI7CQ0I1\nbvDDkqSde39QaVmprm/Zxnn/ffv2adOmTbruuuvUpEkTX8UGAABwC6f/AagxjRs3VnFRka5pepX2\nHzqgU4UFzq99tm61JOmWrjdLkhwOh+bPny+73a7f/e53PskLAABQEyhVAGpMQkKCJOna5i1ldzj0\nceZnkqRf8k7oo9WfKjY6Rr+5oYsk6fXXX9d3332nW265Rd27d69ynwAAAP6O0/8A1Jhrr71WknRZ\nRKxCg0P08v97Tc2vaKY30v+fSkpLNfaBR2Wz2fTPf/5Tb731luLj4zV16lQfpwYAAHAPK1UAasz1\n118vSfph5y6lDBouq8WisbOe1s59u3VHr766+7Y7dfjwYU2ePFkBAQF69tlnFRUV5ePUAAAA7mGl\nCkCNufLKKxUXF6eNGzdq5syZatuqjdauX6fmCU015I67VVpaqkmTJqmgoEAzZsxQ27ZtfR0ZAADA\nbZQqADXGMAz169dP77zzjr744gvdeeed6tq+kyTJbrdrxowZ2rt3rwYNGqQ777zTx2kBAABqBqf/\nAahRgwcPltVq1ZtvvqkTJ05IOl2o5syZo8zMTHXs2FFPPvmkj1MCAADUHEoVgBrVpEkTpaSkKDs7\nW7fddpsWLVqkBx98UB9//LHatGmjF198UQEBAb6OCQAAUGM4/Q9AjXvsscdUWlqqL7/8UgsWLJAk\n3XbbbZo0aZIiIiJ8nA4AAKBmebxUbdu2TS+88ILS0tL0ww8/6Pe//72aNWsmSRo+fLj69+/v6QgA\nvMwwDE2YMEFDhw7V3r17lZCQoJYtW/o6FgAAgEd4tFQtXLhQK1euVFhYmCRpx44dGjVqlB544AFP\nHhaAn0hISHB+IDAAAEBd5dH3VDVt2lSvvvqq8/bOnTv197//XSNHjtQzzzyj4uJiTx4eAAAAADzO\no6WqT58+slqtztvt27fXU089pSVLluiKK65QamqqJw8PAAAAAB7n1QtV9O7d2/km9T59+mjOnDnV\nPiY1NdX5RncAF8a8AK5hVgDXMCuAawzTNE1PHiA7O1sTJkxQRkaGhgwZoqlTp+r666/XkiVLlJOT\no4kTJ170PrOyspSUlKTMzEzerwFUg3kBXMOsAK5hVoBzeXWlasaMGZo9e7YCAgLUqFEjzZo1y5uH\nBwAAAIAa5/FSFR8fr4yMDElSmzZtlJ6e7ulDAgAAAIDXePRCFQAAAABQ11GqAAAAAMANFyxV69ev\n14EDB5y309LS9M0333g8FAAAAADUFlWWqk8//VTTp09XSUmJc1tsbKymTZumzz//3CvhAAAAAMDf\nVVmqFi5cqLS0NLVt29a57fbbb9eiRYv0+uuveyUcAAAAAPi7KkuVaZqKi4s7Z3tCQoIcDodHQwEA\nAABAbXHBUlVUVHTO9sLCQlVUVHg0FAAAAADUFlWWqgEDBmjcuHE6cuSIc1tOTo4mTpyovn37eiUc\nAAAAAPi7Kj/898EHH1ReXp769++v8PBwmaapkpIS3XfffXriiSe8mREAAAAA/FaVpUqSxo8fr9Gj\nR+vHH3+UxWLR1VdfraCgIBUUFCgiIsJbGQEAAADAb12wVElSaGio8wqA27ZtU0ZGhlatWqUtW7Z4\nPBwAAAAA+LsLfvivJBUVFSk9PV0DBgzQiBEjJEkZGRkeDwYAAAAAtUGVK1W7du1Senq6Vq1apeuv\nv14jR47UX/7yF82bN8+b+QAAAADAr1W5UjVo0CAVFBRo5cqVevvtt3XvvffKYql2YQsAAAAA6pUq\nW9Jrr70mh8OhgQMHavz48Vq9erVM0/RmNgAAAADwe1WWql69eumVV17R559/rg4dOmjBggXKycnR\nzJkztW/fPm9mBAAAAAC/Ve35fNHR0UpJSdGKFSu0bNkyWa1WpaSkeCMbAAAAAPi9i3qT1LXXXqsp\nU6Zo3bp1nsoDAAAAALXKJV15IiAgoKZzAAAAAECtxOX8AAAAAMANF1Wqli5d6qkcAAAAAFArXVSp\nysjI8FQOAAAAAKiVLqpU8TlVAAAAAHC2iypVw4YN81QOAAAAAKiVKFUAAAAA4AaPX/1v27ZtSk5O\nliQdPnxYI0aM0MiRIzVz5kxPHxoAAAAAPK7aUnXixIlL3vnChQs1ZcoUVVRUSJLmzZun8ePHa8mS\nJXI4HFq9evUl7xsAAAAA/EG1peq+++675J03bdpUr776qvP2zp071blzZ0lSz549tX79+kveNwAA\nAAD4A1t1d2jdurVWrFihdu3aKTg42Lm9SZMm1e68T58+ys7Odt7+9dUDw8LCVFBQcLF5AQAAAMCv\nVFuqtm3bpm3btp21zTAMZWZmXvTBLJb/LIwVFRUpMjKy2sekpqZqwYIFF30soD5iXgDXMCuAa5gV\nwDWG6eEPn8rOztaECROUkZGhRx99VKNGjVKXLl00ffp0devWTf3797/ofWZlZSkpKUmZmZlKSEjw\nQGqg7mBeANcwK4BrmBXgXNW+pyo/P19TpkxRSkqK8vLyNHnyZJ06deqSDvb000/rlVde0bBhw1RZ\nWal+/fpd0n4AAAAAwF9Ue/rf1KlT1b17d23fvl1hYWFq3LixJk6cqDfeeMOlA8THxysjI0OS1KxZ\nM6WlpbmXGAAAAAD8SLUrVVlZWRo6dKgsFosCAwM1btw45eTkeCMbAAAAAPi9akuV1WpVQUGBDMOQ\nJB06dOisC04AAAAAQH1W7el/Y8aMUXJyso4cOaLHHntMW7du1dy5c72RDQAAAAD8XrWlqmfPnmrb\ntq22b98uu92uWbNmuXQpdAAAAACoD6o9j2/o0KGKiYnRrbfeqqSkJMXExGjw4MHeyAYAAAAAfq/K\nlaqUlBRt3LhRktS6dWvne6qsVqsSExO9kw4AAAAA/FyVpWrx4sWSpDlz5mjKlCleCwQAAAAAtUm1\n76l68skn9cUXX6ioqEiSZLfblZWVpbFjx3o8HAAAAAD4O5eu/ldSUqLDhw+rc+fO+vbbb9WhQwdv\nZAMAAAAAv1fthSoOHjyoxYsXq0+fPnr44Yf1wQcf6NixY97IBgAAAAB+r9pSFRsbK8Mw1Lx5c+3Z\ns0dxcXEqLy/3RjYAAAAA8HvVnv7XokULzZ49W8OHD9fEiRN17NgxVVRUeCMbAAAAAPi9aleqZsyY\nof79++uaa67RmDFjdOzYMb344oveyAYAAAAAfq/alSqr1SrDMJSenq7BgwcrMjJSLVu29EY2AAAA\nAPB71a5UvfPOO3r55Ze1aNEiFRUVadq0aXrrrbe8kQ0AAAAA/F61pWr58uV66623FBISoujoaH34\n4YdatmyZN7IBAAAAgN+rtlRZLBYFBgY6bwcFBclqtXo0FAAAAADUFtW+p+rGG2/U888/r5KSEq1e\nvVpLly5Vt27dvJENAAAAAPxetStVTz31lJo2bapWrVppxYoVuuWWW/T00097IxsAAAAA+L1qV6os\nFouGDRumYcOGeSMPAAAAANQqVZaq1q1byzCMc7abpinDMPTDDz94NBgAAAAA1AZVlqrdu3c7/zxw\n4ECtWLHCK4EAAAAAoDap9j1Vks67YgUAAAAAcLFUmabp6RwAAAAAUCuxUgUAAAAAbqjyPVWJiYnO\nMnX06FElJSVJ+s+FKjIzMy/5oIMGDVJ4eLgkKSEhQXPnzr3kfQEAAACAL1VZqtLS0jxywPLycknS\n4sWLPbJ/AAAAAPCmKktVfHy8Rw64e/duFRcX66GHHpLdbte4cePUvn17jxwLAAAAADyt2g//rWnB\nwcF66KGHdO+99+rQoUN65JFH9Pnnn8ticentXQAAAADgV7xeqpo1a6amTZs6/xwVFaXjx48rLi7u\nvPdPTU3VggULvBkRqLWYF8A1zArgGmYFcI1hevl66enp6dq7d6+mT5+uo0eP6sEHH9Qnn3xyUStV\nWVlZSkpKUmZmphISEjyYFqj9mBfANcwK4BpmBTiX11eq7rnnHk2ePFkjRoyQxWLR3LlzOfUPAAAA\nQK3l9VIVEBCgF154wduHBQAAAACPYIkIAAAAANxAqQIAAAAAN1CqAAAAAMANlCoAAAAAcAOlCgAA\nAADcQKkCAAAAADdQqgAAAADADZQqAAAAAHADpQoAAAAA3ECpAgAAAAA3UKoAAAAAwA2UKgAAAABw\ng83XAQD4F4fDoXXr1iknJ0fx8fG66aabZLVafR0LAADAb1GqADhlZ2dr8uTJ2rVrl3Nb586dNWfO\nHDVs2NCHyQAAAPwXp/8BkCSVl5frySef1K5du9SnTx/NnTtXPXv21KZNm/S73/1OBQUFvo4IAADg\nlyhVACRJr732mvbu3avb+vdVRYRViz59X6EJMRowaKAOHz6sZ555Rg6Hw9cxAQAA/A6n/wFQTk6O\n3nvvPTWMj9OXuzepvKJckrTv0AFFRTZQ207t9c0332jp0qUaPny4j9MCAAD4F1aqACgtLU12h13l\nYRZVWk1Ftbhc1oRINWp9hU6VFelw4TFFREVqwYIFOnLkiK/jAgAA+BVKFVDPORwOrV69WiGNGqjA\nXiI1DNYpS6kim8ToF3uBAi6LUEF5sVp2aquysjK9+eabvo4MAADgVyhVQD23f/9+5ebmyhFqkyU6\nWIoJkmJDlB9cIaNhiCoirLI1DteWvTt05VXN9NFHH2nr1q2+jg0AAOA3KFVAPffPf/5TCrKq3GaX\n2SBQig6W5fJwGY3DZGkSIcUGyx5qkRlq0+WtmkqS/vrXv/o4NQAAgP+gVAH13IYNG6QQmxQaIEUH\nyRIbqsbhjdW0wRWKCY2RNTZMRkywbFEh2rRzqzp16axNmzZp/fr1vo4OAADgFyhVQD1mmqZ27dql\ngPAQGQ0CZUQFKyYsRg3DYtUoLFYxIdGKCouWok6vVjmsUuce3WS1WvXcc8+pvLzc198CAACAz1Gq\ngHosNzdXBQUFsgdKCrEpKCJMMaHRig2NVlhgmBqFN1TD0FgFRIScXs0KsSnr2M+65557lJ2drTVr\n1vj6WwAAAPA5r5cq0zQ1ffp0DRs2TCkpKfrpp5+8HQHAvx05ckSyGjIDLFJ4gMKCwhQTEq248Ma6\nLCJOjcMaKjqkgcKDI2REBckaFqSvvl2ve4cMkcVi0XvvvefrbwEAAMDnvF6qVq9erfLycmVkZGjC\nhAmaN2+etyMA+Le8vDzJYkhWQwoNUGRQpBoERyrIGiSbxaYgW5CighsoPCBcCrLJDDBUUFSoCrNS\nN910k3bt2qXDhw/7+tsAAADwKa+Xqs2bN6tHjx6SpPbt22vHjh3ejgDg3woKCk6XKpshI8Cq0MAQ\nhQQEq1F4Q10WEadAa4CCbUEKDwqVEWiVaTtdwPYe3K9evXpJEhesAAAA9Z7XS1VhYaEiIiKct202\nmxwOh7djAJBOX2jCkGSzyGK1ymaxKcQWLItx+p+GhmENFWQLktVildVmO72iZTH0S94JtWjRQpI4\nhRcAANR7Xi9V4eHhKioqct52OByyWLheBuALdrtd0umiZFgMGTJkswQ4v24xLAq0BcpiWGRYLJJh\nSIah4pISRUdHS5JOnTrlo/QAAAD+webtA3bs2FFr165Vv379tHXrVrVs2fKC909NTdWCBQu8lA6o\n3S52XgzDOP0HUzL//X8O8+yV47LKMkmmTNPUmTsH2GwqKSmRJAUFBdVAcsC7+N0CuIZZAVzj9VLV\np08fff311xo2bJgkVXuhijFjxmjMmDFnbcvKylJSUpLHMgK11cXOS1BQkGSakt0hR6VddoddJRWl\nMk1ThmGooKxAFfYKVTrsclRUSnaH5DAVGx2jH3/8UZKUkJDg8e8LqGn8bgFcw6wArvF6qTIMQzNn\nzvT2YQGcR2ho6OlSVWHKrHSozF6u0spSZZ/6WSHWQJXYy09vqyiVo9IuVZqS3dSVlyfos5Wf6P+z\nd+fhUZV3/8c/M5OVQMIqSkCgLIlAWQqRSAElYdMWCWKRQkIpLuUpID8WFWRfBBQrlmBbqVokUnDB\ngFqXyvKIBUoAFUUUEUFMICwh+56Z+/cHD1NTCAnMTGZC3q/r4rqYM3PO/Zkz+WbyPfeZM5LUqVMn\nLz8LAAAA7+LDTEAt1qBBA8l+YaZKBWXKKsxSTnGuJKnQXiKHcSi3KFfZxblScZlsZVKgf4BahbfQ\n+++/r2bNmqlr165efhYAAADeVe0zVQB8R5MmTS40VaUOKb9EhaVFyirKlpFRkF+QisuKlVWUrYKS\nfJncUpUVFOvWTt309ltvq6ioSPfcc49sNpu3nwYAAIBX0VQBtdhNN90kf39/qdQie4Fd+TnZygg8\nL7vDrrCgUBWUFupcfoYK8/Kk/FKpsEydIzpo3QtJCgkJ0fDhw739FAAAALyOpgqoxWw2m9q3b69D\n6d9JOf6y5JYoI+S8ZJHySvJljEOZhZlSdomshXbZi+z67tARZWZmauLEieW+cw4AAKC2oqkCarnu\n3bvryzcOy1JQJnO+SCUBuUo3pfKz+qnMUSaTVSSTWSSTVaRbftJe/7tlm2666SbFx8d7OzoAAIBP\n4EIVQC3Xq1cvqbBM1iK7LJklUmaRzKk8ObIKZc4WyJpVKktOqUxuiZRXouLiYv3P//yP/Pw4JgMA\nACDRVAG1XqdOnRQYEKhgh78cmYWynCtSQJEUVhKgoDwj++k8Oc4XqGXTcB365AtFRUXpzjvv9HZs\nAAAAn0FTBdRyQUFB6tu3r/LSMhRot8mRWaSS07nKOJKmwvRsBRdZ5FcsWXNKJUmTJ0+WxWLxcmoA\nAADfQVMFQHFxcZLDKLxuY9Wx+8s/s1QdG/9EgZl2FZzNUXRkN313+FsNHjxYkZGR3o4LAADgU2iq\nAOjWW29VVFSUjn7+tfr36K1Ai78OHvhcfrJqXNwo7frwI91www165JFHvB0VAADA59BUAZDFYtGs\nWbMUGhqqf7y+WWMH/0qvPL1a4+68T6/8dY2sVquWLl2qsLAwb0cFAADwOVy+C4AkqXnz5lqyZIke\neeQR/fHZP0r6oySpfv36mjdvnrp06eLdgAAAAD6KpgqAU3R0tDZt2qS9e/dq+/btCg8P1+jRo9Wo\nUSNvRwMAAPBZNFUAymnUqJEGDx6swYMHezsKAABAjcBnqgAAAADABTRVAAAAAOACmioAAAAAcAFN\nFQAAAAC4gKYKAAAAAFxAUwUAAAAALqCpAgAAAAAX0FQBAAAAgAtoqgAAAADABTRVAAAAAOACP28H\nuBZ2u12SlJ6e7uUkgHfceOON8vOrWvlSL6jNqBWgaqgVoGoqqpUa2VSdPXtWkjR69GgvJwG8Y+vW\nrWrevHmVHku9oDajVoCqoVaAqqmoVizGGOOFPC4pKirSwYMH1aRJE9lstgofFxsbq61bt1ZjMjKQ\noXoyXM0RxarUy/W0b8hAhh9zd624M5sryEAGd2egVshAhqq5rmaqgoKC1KNHjyo9tqpHXTyJDGTw\nZoaq1ktt3DdkIMOP8d5CBjJUDbVCBjJcigtVAAAAAIALaKoAAAAAwAU0VQAAAADgAtv8+fPnezuE\nJ/Xs2dPbEchABp/LcDm+kIsMZPC1DBXxhWxkIIOvZbgcX8hFBjJUR4YaefU/AAAAAPAVnP4HAAAA\nAC6gqQIAAAAAF9BUAQAAAIALaKoAAAAAwAU0VV702muv6d1335UkzZw5U5s2bXLr9tetW6eEhITL\n3peQkKCTJ0+6dTxvKisr089+9jPl5OQ4lw0fPlz333+/8/axY8cUExOjs2fP6ne/+90Vt/f555/r\n6aef9lheXB1qxf0SExN19913a+jQoRoxYoQ+/vjjq1r/4MGDmjNnjofSoSqoC/dztS5wfaC23Cs5\nOVk9e/bUsGHDFBcXp7i4OD3wwANXXCchIUF79+5VSkpKhfvK1/h5O0Bt9umnn3rsso7ffvutVq9e\nrZYtW172fovF4pFxvcXPz0/du3fXp59+qttvv13nz5+XMUbHjh1TcXGxAgMDtW/fPvXu3VtNmjTR\n888/f8XtHT16VBkZGdWUHpWhVtzr3Xff1ZdffqnNmzfLYrHo+PHjGjVqlN555x01bNiwStvo1KmT\nOnXq5OGkuBLqwr3cURe4PlBb7hcTE6OlS5de07o1ZZ/QVFVBSkqK/vKXv8gYox9++EEDBw5UvXr1\ntGXLFknSX//6VzVs2FDbt2/XH//4Rxlj1KJFCy1cuFANGzZUTEyMhg4dqn/9618qKirSk08+qezs\nbG3btk179uxRkyZNJEnbt2/XunXrlJGRofHjx2vEiBHlcqxYsUI7duwot2zIkCEaN25cuWUlJSWa\nN2+e/t//+39KTk6+7HO63JX08/LyNG3aNJ07d06SNHHiRPXr108nTpzQ/PnzlZWVpeDgYM2ePVu3\n3HKLjhw5okWLFqmwsFAZGRkaN26c4uPjtXv3bi1fvlxWq1VhYWH6wx/+oPr162vjxo1as2aNLBaL\nOnbsqLlz5yo4OFi9e/fW4MGDtX//fvn5+enZZ59VeHi4M5fD4dA999xzSVGtWLFCrVoN0p5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JLUunXrcsv9/PzUuHFjnTlzxgupAAAAPIumCoDbXGyamjZtesl9QUFBfF8VAAC4LtFUAXCb7Oxs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\ndeooPj5eP/30k9q0aaMJEyZc9fjlbZ8yZYomTZqkj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692TXfq1CmFhYVpxIgR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\nlSS5XC7ZbDZ988036tixoySpW7du2rZtW1XtHgAAAAB8osqaqtDQUNWoUUP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XuVwuXXvt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WtXSdLWrVtLrV5UbIQqAAAAlDm//PKLoqKilFuYrx/3/KQOLdupaYPGkqSgwEA9+uDDsjsc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\nAAAAADdYnnvuuedKuwhP6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AIAAAAANxCqAAAAAMANhCoAAAAAcAOhCgAAAADcQKgCAAAA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\nNHPmTB04cMCXGQEAAACgwarzfL7IyEilpqZq9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GpfgF8rugK4h64A7vH5UJWYmKgtW7Yo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\nAAAA8ABDFQAAAAB44P8BOoVo1JYgy6oAAAAASUVORK5CYII=\n",
"text/plain": [
"<matplotlib.figure.Figure at 0x17d8bb50>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"g = sns.FacetGrid(dataset1, col=\"season\", row=\"month\")\n",
"g.map(sns.kdeplot, \"Global_active_power\", \"Heater - AC\")"
]
},
{
"cell_type": "code",
"execution_count": 132,
"metadata": {
"collapsed": false,
"scrolled": false
},
"outputs": [
{
"data": {
"text/plain": [
"<seaborn.axisgrid.PairGrid at 0x21a5eab0>"
]
},
"execution_count": 132,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
"image/png": 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FrmYpFCcNcWch7JPFF3cWctG83DygXJMmul58iant3ewqnjpqXAD5g5UMlrWli8c2j37e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Gq1EhYWhsFgKHes8ePHk5iYyM6dO8nOzqZ9+/blinUjFf2BByguLsZisZT7PbpKVVX+/e9/s3//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\nRK5CYII=\n",
"text/plain": [
"<matplotlib.figure.Figure at 0x21a5e770>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"g = sns.PairGrid(dataset1[[\"Global_active_power\",\"kitchen\",\"season\"]], hue=\"season\")\n",
"g.map_upper(sns.regplot)\n",
"g.map_lower(sns.residplot)\n",
"g.map_diag(plt.hist)\n",
"for ax in g.axes.flat:\n",
" plt.setp(ax.get_xticklabels(), rotation=45)\n",
"g.add_legend()\n",
"g.set(alpha=0.5)"
]
},
{
"cell_type": "code",
"execution_count": 134,
"metadata": {
"collapsed": false
},
"outputs": [
{
"data": {
"text/plain": [
"<seaborn.axisgrid.JointGrid at 0x1da22b70>"
]
},
"execution_count": 134,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
"image/png": 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6x/jFviBtcKvtSZpmT4pFZIgvvt9f1FOZlFa34MGX9+BEbg3GJAbi+gVjrXad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\nISIIgiC4QkJEEARBcIWEiCAIguDK/wMgfta8gd8N8gAAAABJRU5ErkJggg==\n",
"text/plain": [
"<matplotlib.figure.Figure at 0x24074dd0>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"sns.jointplot(\"month\",\"Global_active_power\", data=dataset1, kind=\"kde\")"
]
},
{
"cell_type": "code",
"execution_count": 137,
"metadata": {
"collapsed": false
},
"outputs": [
{
"data": {
"text/plain": [
"<seaborn.axisgrid.JointGrid at 0x21e5db90>"
]
},
"execution_count": 137,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
"image/png": 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F07j9atcXd3grOSMSQggvFhzox67MEnz0nKFPZPm2EEJ4sTGpYRzKr+Pw8UKG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\nTkSuQmCC\n",
"text/plain": [
"<matplotlib.figure.Figure at 0x21e45e90>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"g = sns.JointGrid(x = \"month\", y = \"Heater - AC\", data=dataset1)\n",
"g.plot_joint(sns.regplot, order=2)\n",
"g.plot_marginals(sns.distplot)"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": []
}
],
"metadata": {
"kernelspec": {
"display_name": "Python 2",
"language": "python",
"name": "python2"
},
"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 2
},
"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython2",
"version": "2.7.11"
}
},
"nbformat": 4,
"nbformat_minor": 0
}
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