{"cells":[{"metadata":{"_uuid":"8f2839f25d086af736a60e9eeb907d3b93b6e0e5","_cell_guid":"b1076dfc-b9ad-4769-8c92-a6c4dae69d19","trusted":true},"cell_type":"code","source":"# This Python 3 environment comes with many helpful analytics libraries installed\n# It is defined by the kaggle/python docker image: https://github.com/kaggle/docker-python\n# For example, here's several helpful packages to load in \n\nimport numpy as np # linear algebra\nimport pandas as pd # data processing, CSV file I/O (e.g. pd.read_csv)\n\n# Input data files are available in the \"../input/\" directory.\n# For example, running this (by clicking run or pressing Shift+Enter) will list the files in the input directory\n\nimport matplotlib.pyplot as plt\n%matplotlib inline\n\nimport seaborn as sns\nsns.set()\n\nfrom IPython.display import HTML\n\nimport os\nprint(os.listdir(\"../input\"))\n\nimport warnings\nwarnings.filterwarnings(\"ignore\", category=DeprecationWarning)\nwarnings.filterwarnings(\"ignore\", category=UserWarning)\nwarnings.filterwarnings(\"ignore\", category=FutureWarning)\n# Any results you write to the current directory are saved as output.","execution_count":1,"outputs":[{"output_type":"stream","text":"['test', 'train.csv', 'sample_submission.csv']\n","name":"stdout"}]},{"metadata":{"_cell_guid":"79c7e3d0-c299-4dcb-8224-4455121ee9b0","_uuid":"d629ff2d2480ee46fbb7e2d37f6b5fab8052498a","trusted":true},"cell_type":"code","source":"#reading data \ntrain = pd.read_csv(\"../input/train.csv\", nrows=10000000,\n                   dtype={'acoustic_data': np.int16, 'time_to_failure': np.float64})\ntrain.head(5)\n\n","execution_count":2,"outputs":[{"output_type":"execute_result","execution_count":2,"data":{"text/plain":"   acoustic_data  time_to_failure\n0             12           1.4691\n1              6           1.4691\n2              8           1.4691\n3              5           1.4691\n4              8           1.4691","text/html":"<div>\n<style scoped>\n    .dataframe tbody tr th:only-of-type {\n        vertical-align: middle;\n    }\n\n    .dataframe tbody tr th {\n        vertical-align: top;\n    }\n\n    .dataframe thead th {\n        text-align: right;\n    }\n</style>\n<table border=\"1\" class=\"dataframe\">\n  <thead>\n    <tr style=\"text-align: right;\">\n      <th></th>\n      <th>acoustic_data</th>\n      <th>time_to_failure</th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th>0</th>\n      <td>12</td>\n      <td>1.4691</td>\n    </tr>\n    <tr>\n      <th>1</th>\n      <td>6</td>\n      <td>1.4691</td>\n    </tr>\n    <tr>\n      <th>2</th>\n      <td>8</td>\n      <td>1.4691</td>\n    </tr>\n    <tr>\n      <th>3</th>\n      <td>5</td>\n      <td>1.4691</td>\n    </tr>\n    <tr>\n      <th>4</th>\n      <td>8</td>\n      <td>1.4691</td>\n    </tr>\n  </tbody>\n</table>\n</div>"},"metadata":{}}]},{"metadata":{"trusted":true},"cell_type":"code","source":"train.rename({\"acoustic_data\": \"signal\",\"time_to_failure\":\"quaktime\"})\n#Exploratory analysis\n","execution_count":4,"outputs":[{"output_type":"execute_result","execution_count":4,"data":{"text/plain":"         acoustic_data  time_to_failure\n0                   12         1.469100\n1                    6         1.469100\n2                    8         1.469100\n3                    5         1.469100\n4                    8         1.469100\n5                    8         1.469100\n6                    9         1.469100\n7                    7         1.469100\n8                   -5         1.469100\n9                    3         1.469100\n10                   5         1.469100\n11                   2         1.469100\n12                   2         1.469100\n13                   3         1.469100\n14                  -1         1.469100\n15                   5         1.469100\n16                   6         1.469100\n17                   4         1.469100\n18                   3         1.469100\n19                   5         1.469100\n20                   4         1.469100\n21                   2         1.469100\n22                   6         1.469100\n23                   7         1.469100\n24                   7         1.469100\n25                   8         1.469100\n26                  14         1.469100\n27                   9         1.469100\n28                   4         1.469100\n29                   7         1.469100\n...                ...              ...\n9999970              2        10.412898\n9999971              8        10.412898\n9999972              6        10.412898\n9999973              7        10.412898\n9999974              5        10.412898\n9999975              6        10.412898\n9999976              4        10.412898\n9999977              6        10.412898\n9999978              4        10.412898\n9999979              3        10.412898\n9999980              4        10.412898\n9999981              6        10.412898\n9999982              6        10.412898\n9999983              7        10.412898\n9999984              6        10.412898\n9999985              6        10.412898\n9999986              8        10.412898\n9999987              8        10.412898\n9999988              9        10.412898\n9999989              3        10.412898\n9999990              4        10.412898\n9999991              6        10.412898\n9999992             11        10.412898\n9999993              2        10.412898\n9999994              7        10.412898\n9999995              4        10.412898\n9999996              6        10.412898\n9999997              6        10.412898\n9999998              4        10.412898\n9999999              1        10.412898\n\n[10000000 rows x 2 columns]","text/html":"<div>\n<style scoped>\n    .dataframe tbody tr th:only-of-type {\n        vertical-align: middle;\n    }\n\n    .dataframe tbody tr th {\n        vertical-align: top;\n    }\n\n    .dataframe thead th {\n        text-align: right;\n    }\n</style>\n<table border=\"1\" class=\"dataframe\">\n  <thead>\n    <tr style=\"text-align: right;\">\n      <th></th>\n      <th>acoustic_data</th>\n      <th>time_to_failure</th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th>0</th>\n      <td>12</td>\n      <td>1.469100</td>\n    </tr>\n    <tr>\n      <th>1</th>\n      <td>6</td>\n      <td>1.469100</td>\n    </tr>\n    <tr>\n      <th>2</th>\n      <td>8</td>\n      <td>1.469100</td>\n    </tr>\n    <tr>\n      <th>3</th>\n      <td>5</td>\n      <td>1.469100</td>\n    </tr>\n    <tr>\n      <th>4</th>\n      <td>8</td>\n      <td>1.469100</td>\n    </tr>\n    <tr>\n      <th>5</th>\n      <td>8</td>\n      <td>1.469100</td>\n    </tr>\n    <tr>\n      <th>6</th>\n      <td>9</td>\n      <td>1.469100</td>\n    </tr>\n    <tr>\n      <th>7</th>\n      <td>7</td>\n      <td>1.469100</td>\n    </tr>\n    <tr>\n      <th>8</th>\n      <td>-5</td>\n      <td>1.469100</td>\n    </tr>\n    <tr>\n      <th>9</th>\n      <td>3</td>\n      <td>1.469100</td>\n    </tr>\n    <tr>\n      <th>10</th>\n      <td>5</td>\n      <td>1.469100</td>\n    </tr>\n    <tr>\n      <th>11</th>\n      <td>2</td>\n      <td>1.469100</td>\n    </tr>\n    <tr>\n      <th>12</th>\n      <td>2</td>\n      <td>1.469100</td>\n    </tr>\n    <tr>\n      <th>13</th>\n      <td>3</td>\n      <td>1.469100</td>\n    </tr>\n    <tr>\n      <th>14</th>\n      <td>-1</td>\n      <td>1.469100</td>\n    </tr>\n    <tr>\n      <th>15</th>\n      <td>5</td>\n      <td>1.469100</td>\n    </tr>\n    <tr>\n      <th>16</th>\n      <td>6</td>\n      <td>1.469100</td>\n    </tr>\n    <tr>\n      <th>17</th>\n      <td>4</td>\n      <td>1.469100</td>\n    </tr>\n    <tr>\n      <th>18</th>\n      <td>3</td>\n      <td>1.469100</td>\n    </tr>\n    <tr>\n      <th>19</th>\n      <td>5</td>\n      <td>1.469100</td>\n    </tr>\n    <tr>\n      <th>20</th>\n      <td>4</td>\n      <td>1.469100</td>\n    </tr>\n    <tr>\n      <th>21</th>\n      <td>2</td>\n      <td>1.469100</td>\n    </tr>\n    <tr>\n      <th>22</th>\n      <td>6</td>\n      <td>1.469100</td>\n    </tr>\n    <tr>\n      <th>23</th>\n      <td>7</td>\n      <td>1.469100</td>\n    </tr>\n    <tr>\n      <th>24</th>\n      <td>7</td>\n      <td>1.469100</td>\n    </tr>\n    <tr>\n      <th>25</th>\n      <td>8</td>\n      <td>1.469100</td>\n    </tr>\n    <tr>\n      <th>26</th>\n      <td>14</td>\n      <td>1.469100</td>\n    </tr>\n    <tr>\n      <th>27</th>\n      <td>9</td>\n      <td>1.469100</td>\n    </tr>\n    <tr>\n      <th>28</th>\n      <td>4</td>\n      <td>1.469100</td>\n    </tr>\n    <tr>\n      <th>29</th>\n      <td>7</td>\n      <td>1.469100</td>\n    </tr>\n    <tr>\n      <th>...</th>\n      <td>...</td>\n      <td>...</td>\n    </tr>\n    <tr>\n      <th>9999970</th>\n      <td>2</td>\n      <td>10.412898</td>\n    </tr>\n    <tr>\n      <th>9999971</th>\n      <td>8</td>\n      <td>10.412898</td>\n    </tr>\n    <tr>\n      <th>9999972</th>\n      <td>6</td>\n      <td>10.412898</td>\n    </tr>\n    <tr>\n      <th>9999973</th>\n      <td>7</td>\n      <td>10.412898</td>\n    </tr>\n    <tr>\n      <th>9999974</th>\n      <td>5</td>\n      <td>10.412898</td>\n    </tr>\n    <tr>\n      <th>9999975</th>\n      <td>6</td>\n      <td>10.412898</td>\n    </tr>\n    <tr>\n      <th>9999976</th>\n      <td>4</td>\n      <td>10.412898</td>\n    </tr>\n    <tr>\n      <th>9999977</th>\n      <td>6</td>\n      <td>10.412898</td>\n    </tr>\n    <tr>\n      <th>9999978</th>\n      <td>4</td>\n      <td>10.412898</td>\n    </tr>\n    <tr>\n      <th>9999979</th>\n      <td>3</td>\n      <td>10.412898</td>\n    </tr>\n    <tr>\n      <th>9999980</th>\n      <td>4</td>\n      <td>10.412898</td>\n    </tr>\n    <tr>\n      <th>9999981</th>\n      <td>6</td>\n      <td>10.412898</td>\n    </tr>\n    <tr>\n      <th>9999982</th>\n      <td>6</td>\n      <td>10.412898</td>\n    </tr>\n    <tr>\n      <th>9999983</th>\n      <td>7</td>\n      <td>10.412898</td>\n    </tr>\n    <tr>\n      <th>9999984</th>\n      <td>6</td>\n      <td>10.412898</td>\n    </tr>\n    <tr>\n      <th>9999985</th>\n      <td>6</td>\n      <td>10.412898</td>\n    </tr>\n    <tr>\n      <th>9999986</th>\n      <td>8</td>\n      <td>10.412898</td>\n    </tr>\n    <tr>\n      <th>9999987</th>\n      <td>8</td>\n      <td>10.412898</td>\n    </tr>\n    <tr>\n      <th>9999988</th>\n      <td>9</td>\n      <td>10.412898</td>\n    </tr>\n    <tr>\n      <th>9999989</th>\n      <td>3</td>\n      <td>10.412898</td>\n    </tr>\n    <tr>\n      <th>9999990</th>\n      <td>4</td>\n      <td>10.412898</td>\n    </tr>\n    <tr>\n      <th>9999991</th>\n      <td>6</td>\n      <td>10.412898</td>\n    </tr>\n    <tr>\n      <th>9999992</th>\n      <td>11</td>\n      <td>10.412898</td>\n    </tr>\n    <tr>\n      <th>9999993</th>\n      <td>2</td>\n      <td>10.412898</td>\n    </tr>\n    <tr>\n      <th>9999994</th>\n      <td>7</td>\n      <td>10.412898</td>\n    </tr>\n    <tr>\n      <th>9999995</th>\n      <td>4</td>\n      <td>10.412898</td>\n    </tr>\n    <tr>\n      <th>9999996</th>\n      <td>6</td>\n      <td>10.412898</td>\n    </tr>\n    <tr>\n      <th>9999997</th>\n      <td>6</td>\n      <td>10.412898</td>\n    </tr>\n    <tr>\n      <th>9999998</th>\n      <td>4</td>\n      <td>10.412898</td>\n    </tr>\n    <tr>\n      <th>9999999</th>\n      <td>1</td>\n      <td>10.412898</td>\n    </tr>\n  </tbody>\n</table>\n<p>10000000 rows × 2 columns</p>\n</div>"},"metadata":{}}]}],"metadata":{"kernelspec":{"display_name":"Python 3","language":"python","name":"python3"},"language_info":{"name":"python","version":"3.6.4","mimetype":"text/x-python","codemirror_mode":{"name":"ipython","version":3},"pygments_lexer":"ipython3","nbconvert_exporter":"python","file_extension":".py"}},"nbformat":4,"nbformat_minor":1}