sealevel_scrub_2_for_visuals_by_day.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Sea Level Data Scrub for a second file of data with day by day points \n",
    "### Source NASA dataset but retaining the datapoints by day and creates a csv for multiple visualizations. \n",
    "* This notebook takes the origianl source from NASA and creates a file that can be used for other visualizations. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [],
   "source": [
    "%matplotlib inline \n",
    "\n",
    "import requests \n",
    "from io import StringIO\n",
    "import numpy as np\n",
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "import datetime as dt\n",
    "import numpy.linalg as lin\n",
    "from sklearn.svm import SVR\n",
    "from sklearn.model_selection import GridSearchCV\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>year_fraction</th>\n",
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       "  <tbody>\n",
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       "      <td>0</td>\n",
       "      <td>1993.011526</td>\n",
       "      <td>92.66</td>\n",
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       "    <tr>\n",
       "      <td>1</td>\n",
       "      <td>1993.038692</td>\n",
       "      <td>95.39</td>\n",
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       "    <tr>\n",
       "      <td>2</td>\n",
       "      <td>1993.065858</td>\n",
       "      <td>92.29</td>\n",
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       "    <tr>\n",
       "      <td>3</td>\n",
       "      <td>1993.093025</td>\n",
       "      <td>96.20</td>\n",
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       "    <tr>\n",
       "      <td>4</td>\n",
       "      <td>1993.120191</td>\n",
       "      <td>94.64</td>\n",
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       "    <tr>\n",
       "      <td>5</td>\n",
       "      <td>1993.147357</td>\n",
       "      <td>93.22</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>6</td>\n",
       "      <td>1993.174523</td>\n",
       "      <td>91.67</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>7</td>\n",
       "      <td>1993.201689</td>\n",
       "      <td>91.95</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>8</td>\n",
       "      <td>1993.228855</td>\n",
       "      <td>91.70</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>9</td>\n",
       "      <td>1993.256021</td>\n",
       "      <td>101.31</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>10</td>\n",
       "      <td>1993.283188</td>\n",
       "      <td>89.84</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>11</td>\n",
       "      <td>1993.310354</td>\n",
       "      <td>89.52</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>12</td>\n",
       "      <td>1993.337520</td>\n",
       "      <td>88.88</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>13</td>\n",
       "      <td>1993.364686</td>\n",
       "      <td>88.73</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>14</td>\n",
       "      <td>1993.391852</td>\n",
       "      <td>89.03</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>15</td>\n",
       "      <td>1993.419018</td>\n",
       "      <td>88.65</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>16</td>\n",
       "      <td>1993.446185</td>\n",
       "      <td>89.34</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>17</td>\n",
       "      <td>1993.473351</td>\n",
       "      <td>88.12</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>18</td>\n",
       "      <td>1993.500517</td>\n",
       "      <td>86.35</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>19</td>\n",
       "      <td>1993.527683</td>\n",
       "      <td>88.23</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    year_fraction    gmsl\n",
       "0     1993.011526   92.66\n",
       "1     1993.038692   95.39\n",
       "2     1993.065858   92.29\n",
       "3     1993.093025   96.20\n",
       "4     1993.120191   94.64\n",
       "5     1993.147357   93.22\n",
       "6     1993.174523   91.67\n",
       "7     1993.201689   91.95\n",
       "8     1993.228855   91.70\n",
       "9     1993.256021  101.31\n",
       "10    1993.283188   89.84\n",
       "11    1993.310354   89.52\n",
       "12    1993.337520   88.88\n",
       "13    1993.364686   88.73\n",
       "14    1993.391852   89.03\n",
       "15    1993.419018   88.65\n",
       "16    1993.446185   89.34\n",
       "17    1993.473351   88.12\n",
       "18    1993.500517   86.35\n",
       "19    1993.527683   88.23"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sea_data = pd.read_csv('data/GMSL_merged_nasa_1993_2020.csv')\n",
    "# sea_data \n",
    "sea_data.head(20)\n",
    "\n",
    "# sea_level = sea_data['GMSL'].values\n",
    "# sea_level"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [],
   "source": [
    "from datetime import timedelta, datetime\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [],
   "source": [
    "def convert_partial_year(number):\n",
    "    year = int(number)\n",
    "    d = timedelta(days=(number - year)*365.25)\n",
    "    day_one = datetime(year,1,1)\n",
    "    date = d + day_one\n",
    "    return date"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [
    {
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       "      <td>1993-01-05 05:02:12.897607</td>\n",
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       "    <tr>\n",
       "      <td>1</td>\n",
       "      <td>1993.038692</td>\n",
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       "      <td>1993-01-15 03:10:26.659203</td>\n",
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       "      <td>2</td>\n",
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       "      <td>1993-01-25 01:18:40.420798</td>\n",
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       "    <tr>\n",
       "      <td>3</td>\n",
       "      <td>1993.093025</td>\n",
       "      <td>96.20</td>\n",
       "      <td>1993-02-03 23:27:25.739997</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>4</td>\n",
       "      <td>1993.120191</td>\n",
       "      <td>94.64</td>\n",
       "      <td>1993-02-13 21:35:39.501599</td>\n",
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       "      <td>...</td>\n",
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       "      <td>991</td>\n",
       "      <td>2019.943911</td>\n",
       "      <td>105.40</td>\n",
       "      <td>2019-12-11 18:19:25.773595</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>992</td>\n",
       "      <td>2019.971077</td>\n",
       "      <td>101.96</td>\n",
       "      <td>2019-12-21 16:27:39.535198</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>993</td>\n",
       "      <td>2019.998243</td>\n",
       "      <td>100.10</td>\n",
       "      <td>2019-12-31 14:35:53.296800</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>994</td>\n",
       "      <td>2020.025340</td>\n",
       "      <td>98.39</td>\n",
       "      <td>2020-01-10 06:07:49.583997</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>995</td>\n",
       "      <td>2020.052432</td>\n",
       "      <td>97.91</td>\n",
       "      <td>2020-01-20 03:37:08.083199</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>996 rows × 3 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "     year_fraction    gmsl                       date\n",
       "0      1993.011526   92.66 1993-01-05 05:02:12.897607\n",
       "1      1993.038692   95.39 1993-01-15 03:10:26.659203\n",
       "2      1993.065858   92.29 1993-01-25 01:18:40.420798\n",
       "3      1993.093025   96.20 1993-02-03 23:27:25.739997\n",
       "4      1993.120191   94.64 1993-02-13 21:35:39.501599\n",
       "..             ...     ...                        ...\n",
       "991    2019.943911  105.40 2019-12-11 18:19:25.773595\n",
       "992    2019.971077  101.96 2019-12-21 16:27:39.535198\n",
       "993    2019.998243  100.10 2019-12-31 14:35:53.296800\n",
       "994    2020.025340   98.39 2020-01-10 06:07:49.583997\n",
       "995    2020.052432   97.91 2020-01-20 03:37:08.083199\n",
       "\n",
       "[996 rows x 3 columns]"
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sea_data['date'] = sea_data['year_fraction'].apply(convert_partial_year)\n",
    "sea_data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [
    {
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       "      <td>2</td>\n",
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       "      <td>1993-01-25 01:18:40.420798</td>\n",
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       "    <tr>\n",
       "      <td>3</td>\n",
       "      <td>96.20</td>\n",
       "      <td>1993-02-03 23:27:25.739997</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>4</td>\n",
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       "      <td>992</td>\n",
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       "      <td>993</td>\n",
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       "      <td>995</td>\n",
       "      <td>97.91</td>\n",
       "      <td>2020-01-20 03:37:08.083199</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>996 rows × 2 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "       gmsl                       date\n",
       "0     92.66 1993-01-05 05:02:12.897607\n",
       "1     95.39 1993-01-15 03:10:26.659203\n",
       "2     92.29 1993-01-25 01:18:40.420798\n",
       "3     96.20 1993-02-03 23:27:25.739997\n",
       "4     94.64 1993-02-13 21:35:39.501599\n",
       "..      ...                        ...\n",
       "991  105.40 2019-12-11 18:19:25.773595\n",
       "992  101.96 2019-12-21 16:27:39.535198\n",
       "993  100.10 2019-12-31 14:35:53.296800\n",
       "994   98.39 2020-01-10 06:07:49.583997\n",
       "995   97.91 2020-01-20 03:37:08.083199\n",
       "\n",
       "[996 rows x 2 columns]"
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sea_data_1 = sea_data.drop(['year_fraction'], axis=1)\n",
    "sea_data_1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <td>1993</td>\n",
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       "    <tr>\n",
       "      <td>2</td>\n",
       "      <td>92.29</td>\n",
       "      <td>1993-01-25 01:18:40.420798</td>\n",
       "      <td>1993</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>3</td>\n",
       "      <td>96.20</td>\n",
       "      <td>1993-02-03 23:27:25.739997</td>\n",
       "      <td>1993</td>\n",
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       "    <tr>\n",
       "      <td>4</td>\n",
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       "      <td>1993-02-13 21:35:39.501599</td>\n",
       "      <td>1993</td>\n",
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       "      <td>991</td>\n",
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       "      <td>2019-12-11 18:19:25.773595</td>\n",
       "      <td>2019</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>992</td>\n",
       "      <td>101.96</td>\n",
       "      <td>2019-12-21 16:27:39.535198</td>\n",
       "      <td>2019</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>993</td>\n",
       "      <td>100.10</td>\n",
       "      <td>2019-12-31 14:35:53.296800</td>\n",
       "      <td>2019</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>994</td>\n",
       "      <td>98.39</td>\n",
       "      <td>2020-01-10 06:07:49.583997</td>\n",
       "      <td>2020</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>995</td>\n",
       "      <td>97.91</td>\n",
       "      <td>2020-01-20 03:37:08.083199</td>\n",
       "      <td>2020</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>996 rows × 3 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "       gmsl                       date  year\n",
       "0     92.66 1993-01-05 05:02:12.897607  1993\n",
       "1     95.39 1993-01-15 03:10:26.659203  1993\n",
       "2     92.29 1993-01-25 01:18:40.420798  1993\n",
       "3     96.20 1993-02-03 23:27:25.739997  1993\n",
       "4     94.64 1993-02-13 21:35:39.501599  1993\n",
       "..      ...                        ...   ...\n",
       "991  105.40 2019-12-11 18:19:25.773595  2019\n",
       "992  101.96 2019-12-21 16:27:39.535198  2019\n",
       "993  100.10 2019-12-31 14:35:53.296800  2019\n",
       "994   98.39 2020-01-10 06:07:49.583997  2020\n",
       "995   97.91 2020-01-20 03:37:08.083199  2020\n",
       "\n",
       "[996 rows x 3 columns]"
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sea_data_1['year'] = sea_data_1['date'].apply(lambda x: x.year)\n",
    "sea_data_1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <th></th>\n",
       "      <th>gmsl</th>\n",
       "      <th>year</th>\n",
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       "  <tbody>\n",
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       "      <td>0</td>\n",
       "      <td>92.66</td>\n",
       "      <td>1993</td>\n",
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       "      <td>95.39</td>\n",
       "      <td>1993</td>\n",
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       "      <td>92.29</td>\n",
       "      <td>1993</td>\n",
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       "      <td>3</td>\n",
       "      <td>96.20</td>\n",
       "      <td>1993</td>\n",
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       "      <td>4</td>\n",
       "      <td>94.64</td>\n",
       "      <td>1993</td>\n",
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       "    <tr>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
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       "      <td>2019</td>\n",
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       "      <td>992</td>\n",
       "      <td>101.96</td>\n",
       "      <td>2019</td>\n",
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       "      <td>993</td>\n",
       "      <td>100.10</td>\n",
       "      <td>2019</td>\n",
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       "      <td>98.39</td>\n",
       "      <td>2020</td>\n",
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       "      <td>995</td>\n",
       "      <td>97.91</td>\n",
       "      <td>2020</td>\n",
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       "</table>\n",
       "<p>996 rows × 2 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "       gmsl  year\n",
       "0     92.66  1993\n",
       "1     95.39  1993\n",
       "2     92.29  1993\n",
       "3     96.20  1993\n",
       "4     94.64  1993\n",
       "..      ...   ...\n",
       "991  105.40  2019\n",
       "992  101.96  2019\n",
       "993  100.10  2019\n",
       "994   98.39  2020\n",
       "995   97.91  2020\n",
       "\n",
       "[996 rows x 2 columns]"
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sea_data_2 = sea_data_1.drop(['date'], axis=1)\n",
    "sea_data_2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <th>Year</th>\n",
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       "  <tbody>\n",
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       "      <td>95.39</td>\n",
       "      <td>1993</td>\n",
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       "      <td>1993</td>\n",
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       "      <td>2019</td>\n",
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       "      <td>995</td>\n",
       "      <td>97.91</td>\n",
       "      <td>2020</td>\n",
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       "</table>\n",
       "<p>996 rows × 2 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "       GMSL  Year\n",
       "0     92.66  1993\n",
       "1     95.39  1993\n",
       "2     92.29  1993\n",
       "3     96.20  1993\n",
       "4     94.64  1993\n",
       "..      ...   ...\n",
       "991  105.40  2019\n",
       "992  101.96  2019\n",
       "993  100.10  2019\n",
       "994   98.39  2020\n",
       "995   97.91  2020\n",
       "\n",
       "[996 rows x 2 columns]"
      ]
     },
     "execution_count": 30,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sea_data_2.columns = ['GMSL', 'Year']\n",
    "sea_data_2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [],
   "source": [
    "#Saving the file that helps make visualizations to represent all of the data by day and all inclusive\n",
    "sea_data_2.to_csv(\"data/sealevel_data__all_1993-2020.csv\", index = False, header = True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
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