Part1_Samsung_Health_Pedometer_data.ipynb

{
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  {
   "attachments": {
    "Samsung_health_iconography.png": {
     "image/png": 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"
    }
   },
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Introduction <a class=\"anchor\" id=\"0\"></a>\n",
    "![Samsung_health_iconography.png](attachment:Samsung_health_iconography.png)\n",
    "\n",
    "_\"If you are in a bad mood, go for a walk. If you are still in a bad mood, go for another walk.\"_  Hippocrates.\n",
    "    \n",
    "In 2016, I have purchased a Samsung Galaxy S6 smartphone. Thanks to the preinstalled app \"Samsung Health\", I was able to track my daily number of steps and burned calories. This was very helpful because I was a very active student then. Seven years later, in 2023, I am still using the app but my daily life has significantly changed as I am now working as a data analyst, sitting at my desk almost all day long. This made me wonder :\n",
    "\n",
    "* In 7 years, how many steps did I make in total ? \n",
    "* What year was I the most active ?\n",
    "* How did my exercice habits change over time in terms of frequency and intensity of workouts ?\n",
    "\n",
    "Let's find out!\n",
    "\n",
    "# Table of contents\n",
    "* [0. Introduction](#0)\n",
    "* [1. Importing my pedometer data into a Pandas dataframe](#1)\n",
    " * [1.1. Preliminary remarks about the data source](#1.1)\n",
    " * [1.2. The import process](#1.2)\n",
    " * [1.3. A quick glance at the original dataset](#1.3)\n",
    "* [2. Performing some quality checks](#2)\n",
    " * [2.1. Completion rate check](#2.1)\n",
    " * [2.2. Duplicates check](#2.2)\n",
    " * [2.3. Outliers check](#2.3)\n",
    "* [3. Quick data preparation](#3)\n",
    "* [4. Insights derived from data visualization](#4)\n",
    " * [4.1. I walked ca. 12,000 km walked over 6 years. This is the distance between Paris (France) and Vladivostok (Russia)!](#4.1)\n",
    " * [4.2. I was most active when working in Japan and at the end of the Covid19 French lockdown](#4.2)\n",
    " * [4.3. Reaching 10,000 steps a day is an everyday challenge!](#4.3)\n",
    "* [5. Conclusion](#5)\n",
    " * [5.1. Summary of the insights and how to go further](#5.1) \n",
    " * [5.2. Technical challenges encountered](#5.2) \n",
    " * [5.3. What I learnt as a data analyst](#5.3) "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<div style=\"background-color: RGB(0,150,250);\" >\n",
    "<h2 style=\"margin: auto; padding: 20px; color:#fff; \">1. Import my pedometer data into a Pandas dataframe</h2> <a class=\"anchor\" id=\"1\"></a>\n",
    "</div>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 1.1. Preliminary remarks about the data source <a class=\"anchor\" id=\"1.1\"></a>\n",
    "*Data source* : To retrieve my pedometer data from the Samsung Health app, I had to download a csv file entitled \"com.samsung.shealth.tracker.pedometer_day_summary.20230806172745\".  \n",
    "\n",
    "*Data structure* : The original dataset has 19 variables (more about them below). The first row of the csv file holds the title of the file. The 2nd row contains the names of the different variables. The rows below contain the observation values. \n",
    "\n",
    "*Information in the dataset* : The dataset provides information about the daily number of steps and calories burned. The information are summarized for each day in the dataset.\n",
    "\n",
    "*To find out more* : Samsung provides a technical documentation for developers as well as the meaning of some variables here: https://developer.samsung.com/health/android/data/api-reference/com/samsung/android/sdk/healthdata/HealthConstants.StepCount.html\n",
    "\n",
    "## 1.2. The import process <a class=\"anchor\" id=\"1.2\"></a>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Import the relevant Python packages for the case study\n",
    "import pandas as pd\n",
    "from datetime import datetime\n",
    "\n",
    "    # Data viz focus\n",
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns\n",
    "\n",
    "    # Notebook format\n",
    "from IPython.display import Image\n",
    "from IPython.core.display import HTML"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Import the data in a Pandas dataframe\n",
    "    ## Since the csv file contains the names of the variables only in the 2nd row, 1st row is skipped\n",
    "    ## Moreover, the values in the 1st column should not be considered as an index\n",
    "pedometer = pd.read_csv('C:/Users/margo/Documents/Documents/Quotidien/Samsung_Health/samsunghealth_margot.2m_20230806172745/com.samsung.shealth.tracker.pedometer_day_summary.20230806172745.csv',\n",
    "                skiprows = 1,\n",
    "                index_col = False)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 1.3. A quick glance at the original dataset <a class=\"anchor\" id=\"1.3\"></a>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(4906, 19)\n"
     ]
    },
    {
     "data": {
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       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>step_count</th>\n",
       "      <th>binning_data</th>\n",
       "      <th>active_time</th>\n",
       "      <th>recommendation</th>\n",
       "      <th>run_step_count</th>\n",
       "      <th>update_time</th>\n",
       "      <th>source_package_name</th>\n",
       "      <th>create_time</th>\n",
       "      <th>source_info</th>\n",
       "      <th>speed</th>\n",
       "      <th>distance</th>\n",
       "      <th>calorie</th>\n",
       "      <th>walk_step_count</th>\n",
       "      <th>deviceuuid</th>\n",
       "      <th>pkg_name</th>\n",
       "      <th>healthy_step</th>\n",
       "      <th>achievement</th>\n",
       "      <th>datauuid</th>\n",
       "      <th>day_time</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
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       "      <th>0</th>\n",
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       "      <td>2016-12-20 08:10:19.980</td>\n",
       "      <td>com.sec.android.app.shealth</td>\n",
       "      <td>2016-12-20 08:10:19.980</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.536459</td>\n",
       "      <td>4994.66000</td>\n",
       "      <td>214.590000</td>\n",
       "      <td>6786</td>\n",
       "      <td>fzT18hJDCE</td>\n",
       "      <td>com.sec.android.app.shealth</td>\n",
       "      <td>4000</td>\n",
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       "      <td>1482105600000</td>\n",
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       "      <th>1</th>\n",
       "      <td>8697</td>\n",
       "      <td>6cc5d795-b6e6-434e-9b02-2c08e7e906cf.binning_d...</td>\n",
       "      <td>4652693</td>\n",
       "      <td>6000</td>\n",
       "      <td>18</td>\n",
       "      <td>2017-03-19 15:56:14.218</td>\n",
       "      <td>com.sec.android.app.shealth</td>\n",
       "      <td>2017-03-18 16:23:44.103</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.356969</td>\n",
       "      <td>6313.56000</td>\n",
       "      <td>262.939970</td>\n",
       "      <td>8679</td>\n",
       "      <td>VfS0qUERdZ</td>\n",
       "      <td>com.sec.android.app.shealth</td>\n",
       "      <td>0</td>\n",
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       "      <td>6cc5d795-b6e6-434e-9b02-2c08e7e906cf</td>\n",
       "      <td>1489881600000</td>\n",
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       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>852</td>\n",
       "      <td>d794ba61-21cc-4882-8797-024a257229eb.binning_d...</td>\n",
       "      <td>350197</td>\n",
       "      <td>6000</td>\n",
       "      <td>42</td>\n",
       "      <td>2016-12-06 23:00:02.906</td>\n",
       "      <td>com.sec.android.app.shealth</td>\n",
       "      <td>2016-12-06 23:00:02.906</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.444444</td>\n",
       "      <td>687.26996</td>\n",
       "      <td>32.699997</td>\n",
       "      <td>810</td>\n",
       "      <td>fzT18hJDCE</td>\n",
       "      <td>com.sec.android.app.shealth</td>\n",
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       "      <td>1480982400000</td>\n",
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       "      <th>3</th>\n",
       "      <td>11428</td>\n",
       "      <td>4730f039-2fa8-466a-a947-5dd0af347e7c.binning_d...</td>\n",
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       "      <td>2017-03-24 00:29:27.150</td>\n",
       "      <td>com.sec.android.app.shealth</td>\n",
       "      <td>2017-03-08 16:00:02.148</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.934353</td>\n",
       "      <td>8313.46000</td>\n",
       "      <td>354.810000</td>\n",
       "      <td>11389</td>\n",
       "      <td>fzT18hJDCE</td>\n",
       "      <td>com.sec.android.app.shealth</td>\n",
       "      <td>5116</td>\n",
       "      <td>4730f039-2fa8-466a-a947-5dd0af347e7c.achieveme...</td>\n",
       "      <td>4730f039-2fa8-466a-a947-5dd0af347e7c</td>\n",
       "      <td>1488931200000</td>\n",
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       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>5388</td>\n",
       "      <td>b1fdc6d6-57bd-4084-82db-4139f027f9c9.binning_d...</td>\n",
       "      <td>2757604</td>\n",
       "      <td>6000</td>\n",
       "      <td>0</td>\n",
       "      <td>2017-02-16 12:02:51.094</td>\n",
       "      <td>com.sec.android.app.shealth</td>\n",
       "      <td>2017-02-15 23:59:20.263</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.416400</td>\n",
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       "      <td>165.170000</td>\n",
       "      <td>5388</td>\n",
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       "      <td>com.sec.android.app.shealth</td>\n",
       "      <td>0</td>\n",
       "      <td>b1fdc6d6-57bd-4084-82db-4139f027f9c9.achieveme...</td>\n",
       "      <td>b1fdc6d6-57bd-4084-82db-4139f027f9c9</td>\n",
       "      <td>1487203200000</td>\n",
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       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>15366</td>\n",
       "      <td>4308a8b1-3117-4e32-9890-2d4a8f208cde.binning_d...</td>\n",
       "      <td>6302277</td>\n",
       "      <td>6000</td>\n",
       "      <td>8950</td>\n",
       "      <td>2017-02-02 16:00:58.357</td>\n",
       "      <td>com.sec.android.app.shealth</td>\n",
       "      <td>2017-02-02 16:00:58.357</td>\n",
       "      <td>NaN</td>\n",
       "      <td>4.305555</td>\n",
       "      <td>14289.79000</td>\n",
       "      <td>870.130000</td>\n",
       "      <td>6416</td>\n",
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       "      <td>com.sec.android.app.shealth</td>\n",
       "      <td>8405</td>\n",
       "      <td>4308a8b1-3117-4e32-9890-2d4a8f208cde.achieveme...</td>\n",
       "      <td>4308a8b1-3117-4e32-9890-2d4a8f208cde</td>\n",
       "      <td>1485993600000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   step_count                                       binning_data  active_time  \\\n",
       "0        6807  02fda250-e056-4773-bd10-f72e1828a737.binning_d...      3322088   \n",
       "1        8697  6cc5d795-b6e6-434e-9b02-2c08e7e906cf.binning_d...      4652693   \n",
       "2         852  d794ba61-21cc-4882-8797-024a257229eb.binning_d...       350197   \n",
       "3       11428  4730f039-2fa8-466a-a947-5dd0af347e7c.binning_d...      5794265   \n",
       "4        5388  b1fdc6d6-57bd-4084-82db-4139f027f9c9.binning_d...      2757604   \n",
       "5       15366  4308a8b1-3117-4e32-9890-2d4a8f208cde.binning_d...      6302277   \n",
       "\n",
       "   recommendation  run_step_count              update_time  \\\n",
       "0            6000              21  2016-12-20 08:10:19.980   \n",
       "1            6000              18  2017-03-19 15:56:14.218   \n",
       "2            6000              42  2016-12-06 23:00:02.906   \n",
       "3           10000              39  2017-03-24 00:29:27.150   \n",
       "4            6000               0  2017-02-16 12:02:51.094   \n",
       "5            6000            8950  2017-02-02 16:00:58.357   \n",
       "\n",
       "           source_package_name              create_time source_info     speed  \\\n",
       "0  com.sec.android.app.shealth  2016-12-20 08:10:19.980         NaN  2.536459   \n",
       "1  com.sec.android.app.shealth  2017-03-18 16:23:44.103         NaN  1.356969   \n",
       "2  com.sec.android.app.shealth  2016-12-06 23:00:02.906         NaN  2.444444   \n",
       "3  com.sec.android.app.shealth  2017-03-08 16:00:02.148         NaN  2.934353   \n",
       "4  com.sec.android.app.shealth  2017-02-15 23:59:20.263         NaN  1.416400   \n",
       "5  com.sec.android.app.shealth  2017-02-02 16:00:58.357         NaN  4.305555   \n",
       "\n",
       "      distance     calorie  walk_step_count  deviceuuid  \\\n",
       "0   4994.66000  214.590000             6786  fzT18hJDCE   \n",
       "1   6313.56000  262.939970             8679  VfS0qUERdZ   \n",
       "2    687.26996   32.699997              810  fzT18hJDCE   \n",
       "3   8313.46000  354.810000            11389  fzT18hJDCE   \n",
       "4   3905.87000  165.170000             5388  VfS0qUERdZ   \n",
       "5  14289.79000  870.130000             6416  fzT18hJDCE   \n",
       "\n",
       "                      pkg_name  healthy_step  \\\n",
       "0  com.sec.android.app.shealth          4000   \n",
       "1  com.sec.android.app.shealth             0   \n",
       "2  com.sec.android.app.shealth             0   \n",
       "3  com.sec.android.app.shealth          5116   \n",
       "4  com.sec.android.app.shealth             0   \n",
       "5  com.sec.android.app.shealth          8405   \n",
       "\n",
       "                                         achievement  \\\n",
       "0  02fda250-e056-4773-bd10-f72e1828a737.achieveme...   \n",
       "1  6cc5d795-b6e6-434e-9b02-2c08e7e906cf.achieveme...   \n",
       "2  d794ba61-21cc-4882-8797-024a257229eb.achieveme...   \n",
       "3  4730f039-2fa8-466a-a947-5dd0af347e7c.achieveme...   \n",
       "4  b1fdc6d6-57bd-4084-82db-4139f027f9c9.achieveme...   \n",
       "5  4308a8b1-3117-4e32-9890-2d4a8f208cde.achieveme...   \n",
       "\n",
       "                               datauuid       day_time  \n",
       "0  02fda250-e056-4773-bd10-f72e1828a737  1482105600000  \n",
       "1  6cc5d795-b6e6-434e-9b02-2c08e7e906cf  1489881600000  \n",
       "2  d794ba61-21cc-4882-8797-024a257229eb  1480982400000  \n",
       "3  4730f039-2fa8-466a-a947-5dd0af347e7c  1488931200000  \n",
       "4  b1fdc6d6-57bd-4084-82db-4139f027f9c9  1487203200000  \n",
       "5  4308a8b1-3117-4e32-9890-2d4a8f208cde  1485993600000  "
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# The data set contains 19 columns and 4,304 rows\n",
    "print(pedometer.shape) \n",
    "\n",
    "# Have a glance at the first values of the original dataset\n",
    "pedometer.head(6)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<div style=\"background-color: RGB(0,150,250);\" >\n",
    "<h2 style=\"margin: auto; padding: 20px; color:#fff; \">2. Perform some quality checks</h2><a class=\"anchor\" id=\"2\"></a>\n",
    "</div>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Before analyzing the pedometer data in depth, one needs to first confirm that the data quality of the underlying dataset is good enough. To do so, 3 different quality checks were performed:\n",
    "\n",
    "* _Completion rate check_ : Does the dataset have lots of Null values in specific columns?\n",
    "* _Duplicates check_ : Does the dataset have indeed 1 row per day of observation ?\n",
    "* _Outliers check_ : Do the columns contain values that make sense ?"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 2.1. Completion rate check <a class=\"anchor\" id=\"2.1\"></a>\n",
    "\n",
    "_Check n°1 : What is the percentage of null values in each column of the dataframe ?_"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "step_count              0.000000\n",
       "binning_data            0.000000\n",
       "active_time             0.000000\n",
       "recommendation          0.000000\n",
       "run_step_count          0.000000\n",
       "update_time             0.000000\n",
       "source_package_name     0.000000\n",
       "create_time             0.000000\n",
       "source_info            59.845088\n",
       "speed                   0.000000\n",
       "distance                0.000000\n",
       "calorie                 0.000000\n",
       "walk_step_count         0.000000\n",
       "deviceuuid              0.000000\n",
       "pkg_name                0.000000\n",
       "healthy_step            0.000000\n",
       "achievement             0.000000\n",
       "datauuid                0.000000\n",
       "day_time                0.000000\n",
       "dtype: float64"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Methodology : \n",
    "# For each column in the dataframe, I counted the number of Null values and divided it by the total number of rows.\n",
    "# To obtain a percentage format, I multipled the end result by 100.\n",
    "pedometer.isna().sum() / pedometer.shape[0] * 100"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<div class=\"alert alert-block alert-success\">\n",
    "<b>Success:</b> All columns seem very well completed except one single column, \"source_info\" (more than half of the observations are Null). The latter will be dropped since it does not add value to the case study. Indeed, my health info come from a single data source: the app on my smartphone (I do not own a smart watch).\n",
    "</div>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 2.2 Duplicates check <a class=\"anchor\" id=\"2.2\"></a>\n",
    "\n",
    "_Check n°2 : What is the granularity of the dataset ? Is it really one value per day or are there duplicates in the dataset?_"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "#Step 1 : Create dates from the timestamp variables\n",
    "format1 =\"%Y-%m-%d %H:%M:%S.%f\"\n",
    "format2 = \"%Y-%m-%d\"\n",
    "pedometer[\"create_date\"] = pedometer[\"create_time\"].apply(lambda x: datetime.strptime(x, format1).strftime(format2))\n",
    "pedometer[\"update_date\"] = pedometer[\"update_time\"].apply(lambda x: datetime.strptime(x, format1).strftime(format2))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
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       "    <tr>\n",
       "      <th>2022-01-22</th>\n",
       "      <td>30</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-10-30</th>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-07-15</th>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-06-24</th>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-03-16</th>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-12-07</th>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-12-04</th>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-12-03</th>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-11-30</th>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-11-28</th>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>2102 rows × 1 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "             counts\n",
       "create_date        \n",
       "2022-01-22       30\n",
       "2019-10-30        5\n",
       "2023-07-15        4\n",
       "2023-06-24        4\n",
       "2023-03-16        4\n",
       "...             ...\n",
       "2016-12-07        2\n",
       "2016-12-04        2\n",
       "2016-12-03        2\n",
       "2016-11-30        2\n",
       "2016-11-28        2\n",
       "\n",
       "[2102 rows x 1 columns]"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Step 2: Compute the number of rows per creation date, and returning the dates for which there are more than 1 row\n",
    "date_counts = pedometer[\"create_date\"].value_counts(ascending = False).rename_axis(\"create_date\").to_frame(\"counts\")\n",
    "date_counts[date_counts[\"counts\"] > 1].sort_values([\"counts\", \"create_date\"], ascending = False)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<div class=\"alert alert-block alert-danger\">\n",
    "<b>Danger:</b> The original dataset has some duplicated values ! Indeed, many creation dates have more than 2 rows associated (in the extreme case, the creation date \"2022-01-22\" has up to 30 rows associated!). This seems to happen for no specific period (different years are represented). Let's investigate further on a small sample of observations to understand where the duplicates come from.\n",
    "</div>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <td>com.sec.android.app.shealth</td>\n",
       "      <td>2023-08-05 22:00:02.552</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.398914</td>\n",
       "      <td>...</td>\n",
       "      <td>210.39998</td>\n",
       "      <td>6909</td>\n",
       "      <td>xDq4cMfd7l</td>\n",
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       "      <td>1691193600000</td>\n",
       "      <td>2023-08-05</td>\n",
       "      <td>2023-08-05</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4775</th>\n",
       "      <td>5393</td>\n",
       "      <td>879bb9e8-41bb-4e40-a0f5-aab114b79f0e.binning_d...</td>\n",
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       "      <td>2023-08-06 15:17:45.681</td>\n",
       "      <td>com.sec.android.app.shealth</td>\n",
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       "      <td>879bb9e8-41bb-4e40-a0f5-aab114b79f0e.source_in...</td>\n",
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       "      <td>1691280000000</td>\n",
       "      <td>2023-08-06</td>\n",
       "      <td>2023-08-06</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>609 rows × 21 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "      step_count                                       binning_data  \\\n",
       "4334        7939  e183f42f-9c35-4b24-abe0-a4b586a7b98c.binning_d...   \n",
       "4339        7939  cdc6fc50-ac4c-40eb-b828-12e9daedc009.binning_d...   \n",
       "4346       15038  32fcc169-0653-4848-a4ed-f7778bc8430d.binning_d...   \n",
       "4350       15038  881694d7-78ce-4ce2-b9fa-e0a203587968.binning_d...   \n",
       "4356        9310  d3f46757-a7d6-49a9-b76d-8a0e29649b5d.binning_d...   \n",
       "...          ...                                                ...   \n",
       "4753        5712  15785417-57b3-4c35-97d7-c01d269418a3.binning_d...   \n",
       "4759        5712  4d34234c-f0f6-4d47-b6cc-c4bb18dcefd1.binning_d...   \n",
       "4766        6909  e0f0b68b-8eab-4511-abd1-db212f6cd273.binning_d...   \n",
       "4770        6909  7d022eb4-acb5-4efc-a632-9f187dff9fe2.binning_d...   \n",
       "4775        5393  879bb9e8-41bb-4e40-a0f5-aab114b79f0e.binning_d...   \n",
       "\n",
       "      active_time  recommendation  run_step_count              update_time  \\\n",
       "4334      4184406            7000              10  2022-10-06 19:50:08.905   \n",
       "4339      4184406            7000              10  2022-10-06 22:00:04.971   \n",
       "4346      7911939            7000               0  2022-10-07 20:35:46.424   \n",
       "4350      7911939            7000               0  2022-10-07 22:00:03.539   \n",
       "4356      5015033            7000               6  2022-10-08 20:02:20.286   \n",
       "...           ...             ...             ...                      ...   \n",
       "4753      2965304            7000               0  2023-08-04 20:48:57.023   \n",
       "4759      2965304            7000               0  2023-08-04 22:00:01.573   \n",
       "4766      3598025            7000               0  2023-08-05 17:56:56.172   \n",
       "4770      3598025            7000               0  2023-08-05 22:00:02.552   \n",
       "4775      2790622            7000               0  2023-08-06 15:17:45.681   \n",
       "\n",
       "              source_package_name              create_time  \\\n",
       "4334  com.sec.android.app.shealth  2022-10-06 06:44:04.474   \n",
       "4339  com.sec.android.app.shealth  2022-10-06 22:00:04.971   \n",
       "4346  com.sec.android.app.shealth  2022-10-07 05:52:46.705   \n",
       "4350  com.sec.android.app.shealth  2022-10-07 22:00:03.539   \n",
       "4356  com.sec.android.app.shealth  2022-10-08 07:54:05.233   \n",
       "...                           ...                      ...   \n",
       "4753  com.sec.android.app.shealth  2023-08-04 03:46:20.774   \n",
       "4759  com.sec.android.app.shealth  2023-08-04 22:00:01.573   \n",
       "4766  com.sec.android.app.shealth  2023-08-05 09:39:39.607   \n",
       "4770  com.sec.android.app.shealth  2023-08-05 22:00:02.552   \n",
       "4775  com.sec.android.app.shealth  2023-08-06 05:13:21.658   \n",
       "\n",
       "                                            source_info     speed  ...  \\\n",
       "4334  e183f42f-9c35-4b24-abe0-a4b586a7b98c.source_in...  1.385384  ...   \n",
       "4339                                                NaN  1.385384  ...   \n",
       "4346  32fcc169-0653-4848-a4ed-f7778bc8430d.source_in...  1.386041  ...   \n",
       "4350                                                NaN  1.386041  ...   \n",
       "4356  d3f46757-a7d6-49a9-b76d-8a0e29649b5d.source_in...  1.346731  ...   \n",
       "...                                                 ...       ...  ...   \n",
       "4753  15785417-57b3-4c35-97d7-c01d269418a3.source_in...  1.405056  ...   \n",
       "4759                                                NaN  1.405056  ...   \n",
       "4766  e0f0b68b-8eab-4511-abd1-db212f6cd273.source_in...  1.398914  ...   \n",
       "4770                                                NaN  1.398914  ...   \n",
       "4775  879bb9e8-41bb-4e40-a0f5-aab114b79f0e.source_in...  1.405625  ...   \n",
       "\n",
       "        calorie  walk_step_count  deviceuuid                     pkg_name  \\\n",
       "4334  246.01991             7929  VfS0qUERdZ  com.sec.android.app.shealth   \n",
       "4339  246.01991             7929  xDq4cMfd7l  com.sec.android.app.shealth   \n",
       "4346  460.59998            15038  VfS0qUERdZ  com.sec.android.app.shealth   \n",
       "4350  460.59998            15038  xDq4cMfd7l  com.sec.android.app.shealth   \n",
       "4356  289.83997             9304  VfS0qUERdZ  com.sec.android.app.shealth   \n",
       "...         ...              ...         ...                          ...   \n",
       "4753  174.86996             5712  VfS0qUERdZ  com.sec.android.app.shealth   \n",
       "4759  174.86996             5712  xDq4cMfd7l  com.sec.android.app.shealth   \n",
       "4766  210.39998             6909  VfS0qUERdZ  com.sec.android.app.shealth   \n",
       "4770  210.39998             6909  xDq4cMfd7l  com.sec.android.app.shealth   \n",
       "4775  163.22998             5393  VfS0qUERdZ  com.sec.android.app.shealth   \n",
       "\n",
       "     healthy_step                                        achievement  \\\n",
       "4334            0  e183f42f-9c35-4b24-abe0-a4b586a7b98c.achieveme...   \n",
       "4339            0  cdc6fc50-ac4c-40eb-b828-12e9daedc009.achieveme...   \n",
       "4346            0  32fcc169-0653-4848-a4ed-f7778bc8430d.achieveme...   \n",
       "4350            0  881694d7-78ce-4ce2-b9fa-e0a203587968.achieveme...   \n",
       "4356            0  d3f46757-a7d6-49a9-b76d-8a0e29649b5d.achieveme...   \n",
       "...           ...                                                ...   \n",
       "4753            0  15785417-57b3-4c35-97d7-c01d269418a3.achieveme...   \n",
       "4759            0  4d34234c-f0f6-4d47-b6cc-c4bb18dcefd1.achieveme...   \n",
       "4766            0  e0f0b68b-8eab-4511-abd1-db212f6cd273.achieveme...   \n",
       "4770            0  7d022eb4-acb5-4efc-a632-9f187dff9fe2.achieveme...   \n",
       "4775            0  879bb9e8-41bb-4e40-a0f5-aab114b79f0e.achieveme...   \n",
       "\n",
       "                                  datauuid       day_time  create_date  \\\n",
       "4334  e183f42f-9c35-4b24-abe0-a4b586a7b98c  1665014400000   2022-10-06   \n",
       "4339  cdc6fc50-ac4c-40eb-b828-12e9daedc009  1665014400000   2022-10-06   \n",
       "4346  32fcc169-0653-4848-a4ed-f7778bc8430d  1665100800000   2022-10-07   \n",
       "4350  881694d7-78ce-4ce2-b9fa-e0a203587968  1665100800000   2022-10-07   \n",
       "4356  d3f46757-a7d6-49a9-b76d-8a0e29649b5d  1665187200000   2022-10-08   \n",
       "...                                    ...            ...          ...   \n",
       "4753  15785417-57b3-4c35-97d7-c01d269418a3  1691107200000   2023-08-04   \n",
       "4759  4d34234c-f0f6-4d47-b6cc-c4bb18dcefd1  1691107200000   2023-08-04   \n",
       "4766  e0f0b68b-8eab-4511-abd1-db212f6cd273  1691193600000   2023-08-05   \n",
       "4770  7d022eb4-acb5-4efc-a632-9f187dff9fe2  1691193600000   2023-08-05   \n",
       "4775  879bb9e8-41bb-4e40-a0f5-aab114b79f0e  1691280000000   2023-08-06   \n",
       "\n",
       "     update_date  \n",
       "4334  2022-10-06  \n",
       "4339  2022-10-06  \n",
       "4346  2022-10-07  \n",
       "4350  2022-10-07  \n",
       "4356  2022-10-08  \n",
       "...          ...  \n",
       "4753  2023-08-04  \n",
       "4759  2023-08-04  \n",
       "4766  2023-08-05  \n",
       "4770  2023-08-05  \n",
       "4775  2023-08-06  \n",
       "\n",
       "[609 rows x 21 columns]"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Step 3: Confirm the existence of duplicated values thanks to a small sample\n",
    "pedometer[pedometer[\"create_date\"]>'2022-10-05'].sort_values(\"create_time\", ascending = True)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<div class=\"alert alert-block alert-warning\">\n",
    "<b>Learnings:</b> Rows seem to be completely identical as far as the step counts and calories are considered. However, 2 differences are to be noticed: <br> i) The duplicates seem to occur due to the 'binning data', 'source info' and 'deviceuuid' columns ; <br> ii) For some unknown reason, the create time and update time are exactly identical as far as the deviceuuid \"xDq4cMfd7l\" is considered. \n",
    "</div>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead tr th {\n",
       "        text-align: left;\n",
       "    }\n",
       "\n",
       "    .dataframe thead tr:last-of-type th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <th colspan=\"2\" halign=\"left\">create_date</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <th>min</th>\n",
       "      <th>max</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>deviceuuid</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>VfS0qUERdZ</th>\n",
       "      <td>2016-11-25</td>\n",
       "      <td>2023-08-06</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>fzT18hJDCE</th>\n",
       "      <td>2016-11-26</td>\n",
       "      <td>2019-09-17</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>t/q+ToT9P9</th>\n",
       "      <td>2019-09-19</td>\n",
       "      <td>2022-01-22</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>xDq4cMfd7l</th>\n",
       "      <td>2022-01-22</td>\n",
       "      <td>2023-08-05</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "           create_date            \n",
       "                   min         max\n",
       "deviceuuid                        \n",
       "VfS0qUERdZ  2016-11-25  2023-08-06\n",
       "fzT18hJDCE  2016-11-26  2019-09-17\n",
       "t/q+ToT9P9  2019-09-19  2022-01-22\n",
       "xDq4cMfd7l  2022-01-22  2023-08-05"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Step 4: Investigate the differences between deviceuuid\n",
    "pedometer.groupby(\"deviceuuid\").agg({'create_date': [min, max]})"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<div class=\"alert alert-block alert-warning\">\n",
    "<b>Learnings:</b> There are 4 deviceuuids in the dataset, but only \"VfS0qUERdZ\" seems to cover the whole period. Other deviceuuids like 't/q+ToT9P9' cover a much shorter period of time.\n",
    "</div>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>step_count</th>\n",
       "      <th>binning_data</th>\n",
       "      <th>active_time</th>\n",
       "      <th>recommendation</th>\n",
       "      <th>run_step_count</th>\n",
       "      <th>update_time</th>\n",
       "      <th>source_package_name</th>\n",
       "      <th>create_time</th>\n",
       "      <th>source_info</th>\n",
       "      <th>speed</th>\n",
       "      <th>...</th>\n",
       "      <th>calorie</th>\n",
       "      <th>walk_step_count</th>\n",
       "      <th>deviceuuid</th>\n",
       "      <th>pkg_name</th>\n",
       "      <th>healthy_step</th>\n",
       "      <th>achievement</th>\n",
       "      <th>datauuid</th>\n",
       "      <th>day_time</th>\n",
       "      <th>create_date</th>\n",
       "      <th>update_date</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>178</th>\n",
       "      <td>385</td>\n",
       "      <td>a93bfe30-f6c4-4d21-9ea6-24f041f4fd26.binning_d...</td>\n",
       "      <td>167688</td>\n",
       "      <td>6000</td>\n",
       "      <td>6</td>\n",
       "      <td>2016-11-25 19:04:33.444</td>\n",
       "      <td>com.sec.android.app.shealth</td>\n",
       "      <td>2016-11-25 13:13:03.287</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.631118</td>\n",
       "      <td>...</td>\n",
       "      <td>14.47000</td>\n",
       "      <td>379</td>\n",
       "      <td>VfS0qUERdZ</td>\n",
       "      <td>com.sec.android.app.shealth</td>\n",
       "      <td>0</td>\n",
       "      <td>a93bfe30-f6c4-4d21-9ea6-24f041f4fd26.achieveme...</td>\n",
       "      <td>a93bfe30-f6c4-4d21-9ea6-24f041f4fd26</td>\n",
       "      <td>1480032000000</td>\n",
       "      <td>2016-11-25</td>\n",
       "      <td>2016-11-25</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>7088</td>\n",
       "      <td>9f320dff-0957-4b70-86ae-2a882263139d.binning_d...</td>\n",
       "      <td>2595080</td>\n",
       "      <td>6000</td>\n",
       "      <td>6083</td>\n",
       "      <td>2016-11-27 18:03:05.574</td>\n",
       "      <td>com.sec.android.app.shealth</td>\n",
       "      <td>2016-11-27 17:15:01.242</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.849973</td>\n",
       "      <td>...</td>\n",
       "      <td>492.03000</td>\n",
       "      <td>1005</td>\n",
       "      <td>VfS0qUERdZ</td>\n",
       "      <td>com.sec.android.app.shealth</td>\n",
       "      <td>0</td>\n",
       "      <td>9f320dff-0957-4b70-86ae-2a882263139d.achieveme...</td>\n",
       "      <td>9f320dff-0957-4b70-86ae-2a882263139d</td>\n",
       "      <td>1480204800000</td>\n",
       "      <td>2016-11-27</td>\n",
       "      <td>2016-11-27</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>2014</td>\n",
       "      <td>20a4ce2d-5bcc-442d-a80e-fc3f442087ba.binning_d...</td>\n",
       "      <td>936206</td>\n",
       "      <td>6000</td>\n",
       "      <td>7</td>\n",
       "      <td>2016-11-28 19:04:31.036</td>\n",
       "      <td>com.sec.android.app.shealth</td>\n",
       "      <td>2016-11-28 07:38:07.812</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.550908</td>\n",
       "      <td>...</td>\n",
       "      <td>67.25000</td>\n",
       "      <td>2007</td>\n",
       "      <td>VfS0qUERdZ</td>\n",
       "      <td>com.sec.android.app.shealth</td>\n",
       "      <td>0</td>\n",
       "      <td>20a4ce2d-5bcc-442d-a80e-fc3f442087ba.achieveme...</td>\n",
       "      <td>20a4ce2d-5bcc-442d-a80e-fc3f442087ba</td>\n",
       "      <td>1480291200000</td>\n",
       "      <td>2016-11-28</td>\n",
       "      <td>2016-11-28</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>79</th>\n",
       "      <td>9626</td>\n",
       "      <td>42d66b02-3de3-418b-8b1a-a8e918b29889.binning_d...</td>\n",
       "      <td>3499741</td>\n",
       "      <td>6000</td>\n",
       "      <td>8986</td>\n",
       "      <td>2016-11-29 17:11:49.441</td>\n",
       "      <td>com.sec.android.app.shealth</td>\n",
       "      <td>2016-11-29 09:22:50.469</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.906311</td>\n",
       "      <td>...</td>\n",
       "      <td>687.09000</td>\n",
       "      <td>640</td>\n",
       "      <td>VfS0qUERdZ</td>\n",
       "      <td>com.sec.android.app.shealth</td>\n",
       "      <td>0</td>\n",
       "      <td>42d66b02-3de3-418b-8b1a-a8e918b29889.achieveme...</td>\n",
       "      <td>42d66b02-3de3-418b-8b1a-a8e918b29889</td>\n",
       "      <td>1480377600000</td>\n",
       "      <td>2016-11-29</td>\n",
       "      <td>2016-11-29</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>161</th>\n",
       "      <td>1051</td>\n",
       "      <td>9f63422a-45db-4a68-9afe-2b17db629d3d.binning_d...</td>\n",
       "      <td>499284</td>\n",
       "      <td>6000</td>\n",
       "      <td>4</td>\n",
       "      <td>2016-11-30 21:51:08.121</td>\n",
       "      <td>com.sec.android.app.shealth</td>\n",
       "      <td>2016-11-30 11:14:33.504</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.512105</td>\n",
       "      <td>...</td>\n",
       "      <td>34.97000</td>\n",
       "      <td>1047</td>\n",
       "      <td>VfS0qUERdZ</td>\n",
       "      <td>com.sec.android.app.shealth</td>\n",
       "      <td>0</td>\n",
       "      <td>9f63422a-45db-4a68-9afe-2b17db629d3d.achieveme...</td>\n",
       "      <td>9f63422a-45db-4a68-9afe-2b17db629d3d</td>\n",
       "      <td>1480464000000</td>\n",
       "      <td>2016-11-30</td>\n",
       "      <td>2016-11-30</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>33</th>\n",
       "      <td>1937</td>\n",
       "      <td>b13e9292-d0c1-44cf-89b6-ea3ae6e9aa87.binning_d...</td>\n",
       "      <td>945463</td>\n",
       "      <td>6000</td>\n",
       "      <td>4</td>\n",
       "      <td>2016-12-01 16:36:23.994</td>\n",
       "      <td>com.sec.android.app.shealth</td>\n",
       "      <td>2016-12-01 05:48:27.735</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.471807</td>\n",
       "      <td>...</td>\n",
       "      <td>63.34000</td>\n",
       "      <td>1933</td>\n",
       "      <td>VfS0qUERdZ</td>\n",
       "      <td>com.sec.android.app.shealth</td>\n",
       "      <td>0</td>\n",
       "      <td>b13e9292-d0c1-44cf-89b6-ea3ae6e9aa87.achieveme...</td>\n",
       "      <td>b13e9292-d0c1-44cf-89b6-ea3ae6e9aa87</td>\n",
       "      <td>1480550400000</td>\n",
       "      <td>2016-12-01</td>\n",
       "      <td>2016-12-01</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>166</th>\n",
       "      <td>24</td>\n",
       "      <td>2c9a0767-1055-41c7-95cf-c0a2b897437f.binning_d...</td>\n",
       "      <td>14945</td>\n",
       "      <td>6000</td>\n",
       "      <td>0</td>\n",
       "      <td>2016-12-02 10:55:01.785</td>\n",
       "      <td>com.sec.android.app.shealth</td>\n",
       "      <td>2016-12-02 10:54:01.186</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.114074</td>\n",
       "      <td>...</td>\n",
       "      <td>0.76000</td>\n",
       "      <td>24</td>\n",
       "      <td>VfS0qUERdZ</td>\n",
       "      <td>com.sec.android.app.shealth</td>\n",
       "      <td>0</td>\n",
       "      <td>2c9a0767-1055-41c7-95cf-c0a2b897437f.achieveme...</td>\n",
       "      <td>2c9a0767-1055-41c7-95cf-c0a2b897437f</td>\n",
       "      <td>1480636800000</td>\n",
       "      <td>2016-12-02</td>\n",
       "      <td>2016-12-02</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>165</th>\n",
       "      <td>2553</td>\n",
       "      <td>4fb78b1b-f88f-4afc-8a0e-def28eaf01b9.binning_d...</td>\n",
       "      <td>1192879</td>\n",
       "      <td>6000</td>\n",
       "      <td>3</td>\n",
       "      <td>2016-12-03 18:32:53.136</td>\n",
       "      <td>com.sec.android.app.shealth</td>\n",
       "      <td>2016-12-03 07:35:01.642</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.545311</td>\n",
       "      <td>...</td>\n",
       "      <td>83.10999</td>\n",
       "      <td>2550</td>\n",
       "      <td>VfS0qUERdZ</td>\n",
       "      <td>com.sec.android.app.shealth</td>\n",
       "      <td>0</td>\n",
       "      <td>4fb78b1b-f88f-4afc-8a0e-def28eaf01b9.achieveme...</td>\n",
       "      <td>4fb78b1b-f88f-4afc-8a0e-def28eaf01b9</td>\n",
       "      <td>1480723200000</td>\n",
       "      <td>2016-12-03</td>\n",
       "      <td>2016-12-03</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>8 rows × 21 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "     step_count                                       binning_data  \\\n",
       "178         385  a93bfe30-f6c4-4d21-9ea6-24f041f4fd26.binning_d...   \n",
       "13         7088  9f320dff-0957-4b70-86ae-2a882263139d.binning_d...   \n",
       "18         2014  20a4ce2d-5bcc-442d-a80e-fc3f442087ba.binning_d...   \n",
       "79         9626  42d66b02-3de3-418b-8b1a-a8e918b29889.binning_d...   \n",
       "161        1051  9f63422a-45db-4a68-9afe-2b17db629d3d.binning_d...   \n",
       "33         1937  b13e9292-d0c1-44cf-89b6-ea3ae6e9aa87.binning_d...   \n",
       "166          24  2c9a0767-1055-41c7-95cf-c0a2b897437f.binning_d...   \n",
       "165        2553  4fb78b1b-f88f-4afc-8a0e-def28eaf01b9.binning_d...   \n",
       "\n",
       "     active_time  recommendation  run_step_count              update_time  \\\n",
       "178       167688            6000               6  2016-11-25 19:04:33.444   \n",
       "13       2595080            6000            6083  2016-11-27 18:03:05.574   \n",
       "18        936206            6000               7  2016-11-28 19:04:31.036   \n",
       "79       3499741            6000            8986  2016-11-29 17:11:49.441   \n",
       "161       499284            6000               4  2016-11-30 21:51:08.121   \n",
       "33        945463            6000               4  2016-12-01 16:36:23.994   \n",
       "166        14945            6000               0  2016-12-02 10:55:01.785   \n",
       "165      1192879            6000               3  2016-12-03 18:32:53.136   \n",
       "\n",
       "             source_package_name              create_time source_info  \\\n",
       "178  com.sec.android.app.shealth  2016-11-25 13:13:03.287         NaN   \n",
       "13   com.sec.android.app.shealth  2016-11-27 17:15:01.242         NaN   \n",
       "18   com.sec.android.app.shealth  2016-11-28 07:38:07.812         NaN   \n",
       "79   com.sec.android.app.shealth  2016-11-29 09:22:50.469         NaN   \n",
       "161  com.sec.android.app.shealth  2016-11-30 11:14:33.504         NaN   \n",
       "33   com.sec.android.app.shealth  2016-12-01 05:48:27.735         NaN   \n",
       "166  com.sec.android.app.shealth  2016-12-02 10:54:01.186         NaN   \n",
       "165  com.sec.android.app.shealth  2016-12-03 07:35:01.642         NaN   \n",
       "\n",
       "        speed  ...    calorie  walk_step_count  deviceuuid  \\\n",
       "178  1.631118  ...   14.47000              379  VfS0qUERdZ   \n",
       "13   2.849973  ...  492.03000             1005  VfS0qUERdZ   \n",
       "18   1.550908  ...   67.25000             2007  VfS0qUERdZ   \n",
       "79   2.906311  ...  687.09000              640  VfS0qUERdZ   \n",
       "161  1.512105  ...   34.97000             1047  VfS0qUERdZ   \n",
       "33   1.471807  ...   63.34000             1933  VfS0qUERdZ   \n",
       "166  1.114074  ...    0.76000               24  VfS0qUERdZ   \n",
       "165  1.545311  ...   83.10999             2550  VfS0qUERdZ   \n",
       "\n",
       "                        pkg_name healthy_step  \\\n",
       "178  com.sec.android.app.shealth            0   \n",
       "13   com.sec.android.app.shealth            0   \n",
       "18   com.sec.android.app.shealth            0   \n",
       "79   com.sec.android.app.shealth            0   \n",
       "161  com.sec.android.app.shealth            0   \n",
       "33   com.sec.android.app.shealth            0   \n",
       "166  com.sec.android.app.shealth            0   \n",
       "165  com.sec.android.app.shealth            0   \n",
       "\n",
       "                                           achievement  \\\n",
       "178  a93bfe30-f6c4-4d21-9ea6-24f041f4fd26.achieveme...   \n",
       "13   9f320dff-0957-4b70-86ae-2a882263139d.achieveme...   \n",
       "18   20a4ce2d-5bcc-442d-a80e-fc3f442087ba.achieveme...   \n",
       "79   42d66b02-3de3-418b-8b1a-a8e918b29889.achieveme...   \n",
       "161  9f63422a-45db-4a68-9afe-2b17db629d3d.achieveme...   \n",
       "33   b13e9292-d0c1-44cf-89b6-ea3ae6e9aa87.achieveme...   \n",
       "166  2c9a0767-1055-41c7-95cf-c0a2b897437f.achieveme...   \n",
       "165  4fb78b1b-f88f-4afc-8a0e-def28eaf01b9.achieveme...   \n",
       "\n",
       "                                 datauuid       day_time  create_date  \\\n",
       "178  a93bfe30-f6c4-4d21-9ea6-24f041f4fd26  1480032000000   2016-11-25   \n",
       "13   9f320dff-0957-4b70-86ae-2a882263139d  1480204800000   2016-11-27   \n",
       "18   20a4ce2d-5bcc-442d-a80e-fc3f442087ba  1480291200000   2016-11-28   \n",
       "79   42d66b02-3de3-418b-8b1a-a8e918b29889  1480377600000   2016-11-29   \n",
       "161  9f63422a-45db-4a68-9afe-2b17db629d3d  1480464000000   2016-11-30   \n",
       "33   b13e9292-d0c1-44cf-89b6-ea3ae6e9aa87  1480550400000   2016-12-01   \n",
       "166  2c9a0767-1055-41c7-95cf-c0a2b897437f  1480636800000   2016-12-02   \n",
       "165  4fb78b1b-f88f-4afc-8a0e-def28eaf01b9  1480723200000   2016-12-03   \n",
       "\n",
       "    update_date  \n",
       "178  2016-11-25  \n",
       "13   2016-11-27  \n",
       "18   2016-11-28  \n",
       "79   2016-11-29  \n",
       "161  2016-11-30  \n",
       "33   2016-12-01  \n",
       "166  2016-12-02  \n",
       "165  2016-12-03  \n",
       "\n",
       "[8 rows x 21 columns]"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Step 5 : Keep only the data associated to the deviceuuid \"VfS0qUERdZ\"\n",
    "pedometer = pedometer[pedometer[\"deviceuuid\"]==\"VfS0qUERdZ\"]\n",
    "pedometer.sort_values(\"create_date\", ascending = True).head(8)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Step 6: One chooses to remove variables that: \n",
    "    # i) cause duplicates,\n",
    "    # ii) are no use for the case study, \n",
    "    #iii) cannot be understood due to the lack of documentation\n",
    "pedometer = pedometer.drop([\"binning_data\", \"source_package_name\", \"source_info\", \n",
    "                            \"pkg_name\", \"achievement\", \"deviceuuid\", \"datauuid\",\n",
    "                           \"healthy_step\", \"speed\" , \"active_time\",\n",
    "                            #\"create_time\", \"update_time\"\n",
    "                           ], axis =1 )"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <th></th>\n",
       "      <th>create_date</th>\n",
       "      <th>update_date</th>\n",
       "      <th>recommendation</th>\n",
       "      <th>step_count</th>\n",
       "      <th>walk_step_count</th>\n",
       "      <th>run_step_count</th>\n",
       "      <th>distance</th>\n",
       "      <th>calorie</th>\n",
       "      <th>day_time</th>\n",
       "      <th>create_time</th>\n",
       "      <th>update_time</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>4775</th>\n",
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       "      <th>4766</th>\n",
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       "    <tr>\n",
       "      <th>4753</th>\n",
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       "      <td>2023-08-04</td>\n",
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       "      <td>2023-08-04 03:46:20.774</td>\n",
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       "      <th>4743</th>\n",
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       "      <td>2023-08-03 05:03:10.777</td>\n",
       "      <td>2023-08-03 19:52:18.967</td>\n",
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       "      <th>4735</th>\n",
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       "      <td>6.799999</td>\n",
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       "      <td>2023-08-02 06:03:03.855</td>\n",
       "      <td>2023-08-02 20:38:48.852</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4905</th>\n",
       "      <td>2023-08-01</td>\n",
       "      <td>2023-08-01</td>\n",
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       "      <td>2023-08-01 06:33:00.342</td>\n",
       "      <td>2023-08-01 18:15:13.458</td>\n",
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       "    <tr>\n",
       "      <th>4903</th>\n",
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       "      <td>2023-07-30 22:45:26.487</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4899</th>\n",
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       "      <td>2023-07-29</td>\n",
       "      <td>7000</td>\n",
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       "      <td>2023-07-29 07:22:22.695</td>\n",
       "      <td>2023-07-29 21:15:11.853</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "     create_date update_date  recommendation  step_count  walk_step_count  \\\n",
       "4775  2023-08-06  2023-08-06            7000        5393             5393   \n",
       "4766  2023-08-05  2023-08-05            7000        6909             6909   \n",
       "4753  2023-08-04  2023-08-04            7000        5712             5712   \n",
       "4743  2023-08-03  2023-08-03            7000        5875             5875   \n",
       "4735  2023-08-02  2023-08-02            7000         201              201   \n",
       "4905  2023-08-01  2023-08-01            7000        3893             3893   \n",
       "4903  2023-07-30  2023-07-30            7000          18               18   \n",
       "4899  2023-07-29  2023-07-29            7000        4287             4287   \n",
       "\n",
       "      run_step_count    distance     calorie       day_time  \\\n",
       "4775               0  3922.57030  163.229980  1691280000000   \n",
       "4766               0  5033.33000  210.399980  1691193600000   \n",
       "4753               0  4166.42040  174.869960  1691107200000   \n",
       "4743               0  4293.95000  179.279970  1691020800000   \n",
       "4735               0   140.04999    6.799999  1690934400000   \n",
       "4905               0  2822.49000  119.369990  1690848000000   \n",
       "4903               0    12.50000    0.580000  1690761600000   \n",
       "4899               0  3079.18000  131.040000  1690588800000   \n",
       "\n",
       "                  create_time              update_time  \n",
       "4775  2023-08-06 05:13:21.658  2023-08-06 15:17:45.681  \n",
       "4766  2023-08-05 09:39:39.607  2023-08-05 17:56:56.172  \n",
       "4753  2023-08-04 03:46:20.774  2023-08-04 20:48:57.023  \n",
       "4743  2023-08-03 05:03:10.777  2023-08-03 19:52:18.967  \n",
       "4735  2023-08-02 06:03:03.855  2023-08-02 20:38:48.852  \n",
       "4905  2023-08-01 06:33:00.342  2023-08-01 18:15:13.458  \n",
       "4903  2023-07-30 22:44:22.646  2023-07-30 22:45:26.487  \n",
       "4899  2023-07-29 07:22:22.695  2023-07-29 21:15:11.853  "
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Step 7 : Rearrange the order of columns to improve readability\n",
    "cols = ['create_date','update_date','recommendation',\n",
    "        'step_count','walk_step_count','run_step_count','distance',\n",
    "        'calorie', 'day_time','create_time','update_time'\n",
    "]\n",
    "pedometer = pedometer[cols]\n",
    "pedometer.sort_values(\"create_date\", ascending = False).head(8)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<div class=\"alert alert-block alert-success\">\n",
    "<b>Success:</b> In the sample rows above, duplicates have been correctly eliminated (e.g. only 1 row per create_date).\n",
    "</div>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>counts</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>create_date</th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2023-07-29</th>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-07-19</th>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-07-15</th>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-06-28</th>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-06-24</th>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-01-09</th>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-01-07</th>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-01-02</th>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-12-20</th>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-12-13</th>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>228 rows × 1 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "             counts\n",
       "create_date        \n",
       "2023-07-29        2\n",
       "2023-07-19        2\n",
       "2023-07-15        2\n",
       "2023-06-28        2\n",
       "2023-06-24        2\n",
       "...             ...\n",
       "2017-01-09        2\n",
       "2017-01-07        2\n",
       "2017-01-02        2\n",
       "2016-12-20        2\n",
       "2016-12-13        2\n",
       "\n",
       "[228 rows x 1 columns]"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Step 8 : Ensure there are no more duplicates\n",
    "date_counts = pedometer[\"create_date\"].value_counts(ascending = False).rename_axis(\"create_date\").to_frame(\"counts\")\n",
    "date_counts[date_counts[\"counts\"] > 1].sort_values(\"create_date\", ascending = False)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<div class=\"alert alert-block alert-danger\">\n",
    "<b>Danger:</b> There are still duplicates in the dataset !\n",
    "</div>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>create_date</th>\n",
       "      <th>update_date</th>\n",
       "      <th>recommendation</th>\n",
       "      <th>step_count</th>\n",
       "      <th>walk_step_count</th>\n",
       "      <th>run_step_count</th>\n",
       "      <th>distance</th>\n",
       "      <th>calorie</th>\n",
       "      <th>day_time</th>\n",
       "      <th>create_time</th>\n",
       "      <th>update_time</th>\n",
       "    </tr>\n",
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       "  <tbody>\n",
       "    <tr>\n",
       "      <th>4074</th>\n",
       "      <td>2022-09-14</td>\n",
       "      <td>2022-09-14</td>\n",
       "      <td>7000</td>\n",
       "      <td>26575</td>\n",
       "      <td>26528</td>\n",
       "      <td>47</td>\n",
       "      <td>18841.6300</td>\n",
       "      <td>1017.57996</td>\n",
       "      <td>1663113600000</td>\n",
       "      <td>2022-09-14 06:15:40.190</td>\n",
       "      <td>2022-09-14 20:51:22.522</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4084</th>\n",
       "      <td>2022-09-14</td>\n",
       "      <td>2022-09-15</td>\n",
       "      <td>7000</td>\n",
       "      <td>32481</td>\n",
       "      <td>32481</td>\n",
       "      <td>0</td>\n",
       "      <td>22865.4000</td>\n",
       "      <td>1236.21000</td>\n",
       "      <td>1663200000000</td>\n",
       "      <td>2022-09-14 23:23:31.277</td>\n",
       "      <td>2022-09-15 20:02:44.497</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4092</th>\n",
       "      <td>2022-09-16</td>\n",
       "      <td>2022-09-16</td>\n",
       "      <td>7000</td>\n",
       "      <td>25937</td>\n",
       "      <td>25916</td>\n",
       "      <td>21</td>\n",
       "      <td>18275.8000</td>\n",
       "      <td>971.73000</td>\n",
       "      <td>1663286400000</td>\n",
       "      <td>2022-09-16 06:55:10.384</td>\n",
       "      <td>2022-09-16 21:31:03.990</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4106</th>\n",
       "      <td>2022-09-17</td>\n",
       "      <td>2022-09-17</td>\n",
       "      <td>7000</td>\n",
       "      <td>16893</td>\n",
       "      <td>16893</td>\n",
       "      <td>0</td>\n",
       "      <td>12084.1200</td>\n",
       "      <td>597.49994</td>\n",
       "      <td>1663372800000</td>\n",
       "      <td>2022-09-17 02:35:02.947</td>\n",
       "      <td>2022-09-17 22:00:06.087</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4127</th>\n",
       "      <td>2022-09-17</td>\n",
       "      <td>2022-09-18</td>\n",
       "      <td>7000</td>\n",
       "      <td>7814</td>\n",
       "      <td>7797</td>\n",
       "      <td>17</td>\n",
       "      <td>5792.9995</td>\n",
       "      <td>254.11989</td>\n",
       "      <td>1663459200000</td>\n",
       "      <td>2022-09-17 22:00:05.866</td>\n",
       "      <td>2022-09-18 20:55:44.726</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "     create_date update_date  recommendation  step_count  walk_step_count  \\\n",
       "4074  2022-09-14  2022-09-14            7000       26575            26528   \n",
       "4084  2022-09-14  2022-09-15            7000       32481            32481   \n",
       "4092  2022-09-16  2022-09-16            7000       25937            25916   \n",
       "4106  2022-09-17  2022-09-17            7000       16893            16893   \n",
       "4127  2022-09-17  2022-09-18            7000        7814             7797   \n",
       "\n",
       "      run_step_count    distance     calorie       day_time  \\\n",
       "4074              47  18841.6300  1017.57996  1663113600000   \n",
       "4084               0  22865.4000  1236.21000  1663200000000   \n",
       "4092              21  18275.8000   971.73000  1663286400000   \n",
       "4106               0  12084.1200   597.49994  1663372800000   \n",
       "4127              17   5792.9995   254.11989  1663459200000   \n",
       "\n",
       "                  create_time              update_time  \n",
       "4074  2022-09-14 06:15:40.190  2022-09-14 20:51:22.522  \n",
       "4084  2022-09-14 23:23:31.277  2022-09-15 20:02:44.497  \n",
       "4092  2022-09-16 06:55:10.384  2022-09-16 21:31:03.990  \n",
       "4106  2022-09-17 02:35:02.947  2022-09-17 22:00:06.087  \n",
       "4127  2022-09-17 22:00:05.866  2022-09-18 20:55:44.726  "
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Investigate further and focusing on some examples that still have duplicate values based on step 6 results\n",
    "pedometer[(pedometer[\"create_date\"]>='2022-09-14')\n",
    "          & (pedometer[\"create_date\"]<='2022-09-18')\n",
    "         ].sort_values(\"create_date\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<div class=\"alert alert-block alert-warning\">\n",
    "<b>Learnings:</b> Remaining duplicates seem to occur because there is a problem with the 'create_date' variable in the original dataset. Indeed, as you can see, there is no \"create_date\" record for the dates '2022-09-15' or '2022-09-18'. The values are in fact to be derived from the update_date, not the create_date! To confirm this way of interpretating the data, I checked the values of \"step_count\" and \"calorie\" in my Samsung Health app: they are aligned.\n",
    "</div>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <td>2022-09-14</td>\n",
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       "      <td>False</td>\n",
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       "      <td>True</td>\n",
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       "      <td>2022-09-26 05:14:48.437</td>\n",
       "      <td>2022-09-27 22:00:04.547</td>\n",
       "      <td>True</td>\n",
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       "      <td>2022-09-27</td>\n",
       "      <td>2022-09-26</td>\n",
       "      <td>2022-09-27</td>\n",
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       "      <td>2022-09-27 18:33:08.273</td>\n",
       "      <td>True</td>\n",
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      ],
      "text/plain": [
       "      clean_date create_date update_date  recommendation  step_count  \\\n",
       "212   2017-01-07  2017-01-07  2017-01-07            6000        8476   \n",
       "110   2017-01-08  2017-01-07  2017-01-08            6000        7229   \n",
       "62    2017-01-09  2017-01-09  2017-01-09            6000        6596   \n",
       "91    2017-01-10  2017-01-09  2017-01-10            6000       11165   \n",
       "4074  2022-09-14  2022-09-14  2022-09-14            7000       26575   \n",
       "4084  2022-09-15  2022-09-14  2022-09-15            7000       32481   \n",
       "4092  2022-09-16  2022-09-16  2022-09-16            7000       25937   \n",
       "4106  2022-09-17  2022-09-17  2022-09-17            7000       16893   \n",
       "4127  2022-09-18  2022-09-17  2022-09-18            7000        7814   \n",
       "4215  2022-09-26  2022-09-26  2022-09-27            7000        9184   \n",
       "4225  2022-09-27  2022-09-26  2022-09-27            7000        1590   \n",
       "\n",
       "      walk_step_count  run_step_count    distance      calorie       day_time  \\\n",
       "212              8458              18   6144.3300   263.900000  1483747200000   \n",
       "110              7176              53   5357.5000   225.970000  1483833600000   \n",
       "62               6586              10   4764.3800   211.010000  1483920000000   \n",
       "91               6073            5092   9963.6200   574.029970  1484006400000   \n",
       "4074            26528              47  18841.6300  1017.579960  1663113600000   \n",
       "4084            32481               0  22865.4000  1236.210000  1663200000000   \n",
       "4092            25916              21  18275.8000   971.730000  1663286400000   \n",
       "4106            16893               0  12084.1200   597.499940  1663372800000   \n",
       "4127             7797              17   5792.9995   254.119890  1663459200000   \n",
       "4215             9141              43   6750.3500   289.429930  1664150400000   \n",
       "4225             1590               0   1129.7700    56.159996  1664236800000   \n",
       "\n",
       "                  create_time              update_time  is_duplicate  \\\n",
       "212   2017-01-07 09:41:41.605  2017-01-07 15:53:43.490          True   \n",
       "110   2017-01-07 16:31:00.685  2017-01-08 14:17:00.797          True   \n",
       "62    2017-01-09 00:09:01.712  2017-01-09 13:34:42.569          True   \n",
       "91    2017-01-09 23:08:00.260  2017-01-10 13:43:47.388          True   \n",
       "4074  2022-09-14 06:15:40.190  2022-09-14 20:51:22.522          True   \n",
       "4084  2022-09-14 23:23:31.277  2022-09-15 20:02:44.497          True   \n",
       "4092  2022-09-16 06:55:10.384  2022-09-16 21:31:03.990         False   \n",
       "4106  2022-09-17 02:35:02.947  2022-09-17 22:00:06.087          True   \n",
       "4127  2022-09-17 22:00:05.866  2022-09-18 20:55:44.726          True   \n",
       "4215  2022-09-26 05:14:48.437  2022-09-27 22:00:04.547          True   \n",
       "4225  2022-09-26 22:02:55.888  2022-09-27 18:33:08.273          True   \n",
       "\n",
       "      rank_create_time  \n",
       "212                1.0  \n",
       "110                2.0  \n",
       "62                 1.0  \n",
       "91                 2.0  \n",
       "4074               1.0  \n",
       "4084               2.0  \n",
       "4092               1.0  \n",
       "4106               1.0  \n",
       "4127               2.0  \n",
       "4215               1.0  \n",
       "4225               2.0  "
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Step 9 : Create a \"clean_date\" variable. 3 rules are used to populate the variable:\n",
    "    # i) When there is no duplicate of the 'create_date' variable, simply take the 'create_date' (e.g. create_date = '2022-09-16')\n",
    "    # ii) When there are duplicates of the create_date variable:\n",
    "        # ii.a) Case 1 : The values of the couple (\"create_date\", \"update_date\") are different \n",
    "            #-> Take the \"update_date\" instead (eg. create_date = '2022-09-17')\n",
    "        # ii.b) Case 2 : The values of the couple (\"create_date\", \"update_date\") are identical\n",
    "            #-> One orders the create_time in ascending order\n",
    "            # -> Then one assigns the create_date to rank=1 and update_date for all the other ranks\n",
    "            # (e.g. create_date '2022-09-26')\n",
    "            \n",
    "# Identify duplicates\n",
    "pedometer[\"is_duplicate\"] = pedometer.duplicated(subset = \"create_date\", keep = False)\n",
    "#pedometer[\"is_duplicate2\"] = pedometer.duplicated(subset = [\"create_date\", \"update_date\"], keep = False)\n",
    "\n",
    "# Compute the rank of each observation that shares the same create_date\n",
    "pedometer[\"rank_create_time\"] = pedometer.groupby(\"create_date\")[\"day_time\"].rank(ascending = True)\n",
    "\n",
    "# Create the \"clean_date\" variable based on conditions\n",
    "pedometer.loc[pedometer[\"is_duplicate\"] == 0, \"clean_date\"] = pedometer[\"create_date\"] # rule i)\n",
    "pedometer.loc[(pedometer[\"is_duplicate\"] == 1) & \n",
    "              (pedometer[\"rank_create_time\"]==1), \"clean_date\"] = pedometer[\"create_date\"] # rule ii.a)\n",
    "pedometer.loc[(pedometer[\"is_duplicate\"] == 1) & \n",
    "              (pedometer[\"rank_create_time\"]!=1), \"clean_date\"] = pedometer[\"update_date\"] # rule ii.b)\n",
    "\n",
    "#Rearrange the columns\n",
    "cols = pedometer.columns.tolist()\n",
    "cols = cols[-1:] + cols[:-1]\n",
    "pedometer = pedometer[cols] \n",
    "\n",
    "# Test on a sample\n",
    "pedometer[((pedometer[\"create_date\"]>=\"2022-09-14\") & (pedometer[\"create_date\"]<=\"2022-09-18\"))\n",
    "          | ((pedometer[\"create_date\"]>=\"2017-01-07\") & (pedometer[\"create_date\"]<=\"2017-01-09\"))\n",
    "          | (pedometer[\"create_date\"]=='2022-09-26')\n",
    "         ].sort_values(\"create_time\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<div class=\"alert alert-block alert-success\">\n",
    "<b>Success:</b> Duplicates have been removed ! Final remark: The process of removing duplicates has been quite tedious. It would have been much cleaner and quicker if the online documentation was more exhaustive (e.g. explaining why there may be different deviceuuids, why update_time and create_time may be mixed up, etc).\n",
    "</div>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 2.3. Outliers check <a class=\"anchor\" id=\"2.3\"></a>\n",
    "\n",
    "_Check n°3 : Are there any values in the dataset that do not seem to make any sense ?_"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>recommendation</th>\n",
       "      <th>step_count</th>\n",
       "      <th>walk_step_count</th>\n",
       "      <th>run_step_count</th>\n",
       "      <th>distance</th>\n",
       "      <th>calorie</th>\n",
       "      <th>day_time</th>\n",
       "      <th>rank_create_time</th>\n",
       "      <th>distance_km</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>2440.000000</td>\n",
       "      <td>2440.00000</td>\n",
       "      <td>2440.000000</td>\n",
       "      <td>2440.000000</td>\n",
       "      <td>2440.000000</td>\n",
       "      <td>2440.000000</td>\n",
       "      <td>2.440000e+03</td>\n",
       "      <td>2440.000000</td>\n",
       "      <td>2440.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>7013.524590</td>\n",
       "      <td>7376.30000</td>\n",
       "      <td>7027.740984</td>\n",
       "      <td>348.559016</td>\n",
       "      <td>5531.551459</td>\n",
       "      <td>254.671187</td>\n",
       "      <td>1.585887e+12</td>\n",
       "      <td>1.093443</td>\n",
       "      <td>5.531551</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>481.964039</td>\n",
       "      <td>5831.74738</td>\n",
       "      <td>5788.119321</td>\n",
       "      <td>984.001887</td>\n",
       "      <td>4269.367250</td>\n",
       "      <td>201.476133</td>\n",
       "      <td>6.095753e+10</td>\n",
       "      <td>0.291111</td>\n",
       "      <td>4.269367</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>6000.000000</td>\n",
       "      <td>13.00000</td>\n",
       "      <td>13.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>9.770000</td>\n",
       "      <td>0.360000</td>\n",
       "      <td>1.480032e+12</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.009770</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>7000.000000</td>\n",
       "      <td>3463.50000</td>\n",
       "      <td>2959.750000</td>\n",
       "      <td>9.000000</td>\n",
       "      <td>2639.557275</td>\n",
       "      <td>120.559975</td>\n",
       "      <td>1.533233e+12</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>2.639557</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>7000.000000</td>\n",
       "      <td>6601.50000</td>\n",
       "      <td>6288.000000</td>\n",
       "      <td>54.000000</td>\n",
       "      <td>4915.990000</td>\n",
       "      <td>220.065000</td>\n",
       "      <td>1.586002e+12</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>4.915990</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>7000.000000</td>\n",
       "      <td>9496.50000</td>\n",
       "      <td>9014.000000</td>\n",
       "      <td>186.000000</td>\n",
       "      <td>7230.450000</td>\n",
       "      <td>327.924970</td>\n",
       "      <td>1.638684e+12</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>7.230450</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>10000.000000</td>\n",
       "      <td>40607.00000</td>\n",
       "      <td>40565.000000</td>\n",
       "      <td>9069.000000</td>\n",
       "      <td>29208.210000</td>\n",
       "      <td>1350.090000</td>\n",
       "      <td>1.691280e+12</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>29.208210</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       recommendation   step_count  walk_step_count  run_step_count  \\\n",
       "count     2440.000000   2440.00000      2440.000000     2440.000000   \n",
       "mean      7013.524590   7376.30000      7027.740984      348.559016   \n",
       "std        481.964039   5831.74738      5788.119321      984.001887   \n",
       "min       6000.000000     13.00000        13.000000        0.000000   \n",
       "25%       7000.000000   3463.50000      2959.750000        9.000000   \n",
       "50%       7000.000000   6601.50000      6288.000000       54.000000   \n",
       "75%       7000.000000   9496.50000      9014.000000      186.000000   \n",
       "max      10000.000000  40607.00000     40565.000000     9069.000000   \n",
       "\n",
       "           distance      calorie      day_time  rank_create_time  distance_km  \n",
       "count   2440.000000  2440.000000  2.440000e+03       2440.000000  2440.000000  \n",
       "mean    5531.551459   254.671187  1.585887e+12          1.093443     5.531551  \n",
       "std     4269.367250   201.476133  6.095753e+10          0.291111     4.269367  \n",
       "min        9.770000     0.360000  1.480032e+12          1.000000     0.009770  \n",
       "25%     2639.557275   120.559975  1.533233e+12          1.000000     2.639557  \n",
       "50%     4915.990000   220.065000  1.586002e+12          1.000000     4.915990  \n",
       "75%     7230.450000   327.924970  1.638684e+12          1.000000     7.230450  \n",
       "max    29208.210000  1350.090000  1.691280e+12          2.000000    29.208210  "
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Summarize the data\n",
    "pedometer[\"distance_km\"]= pedometer[\"distance\"]/1000\n",
    "pedometer.describe()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<div class=\"alert alert-block alert-success\">\n",
    "<b>Success:</b> The values seem to be coherent:\n",
    "    <br>i) There are no negative values for the distance, number of steps or calories burned ;\n",
    "    <br>ii) Maximal values seem to be aligned with what I have in mind: I know that I can walk easily more than 25 kms / day when I am hiking.\n",
    "</div>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<div style=\"background-color: RGB(0,150,250);\" >\n",
    "<h2 style=\"margin: auto; padding: 20px; color:#fff; \">3. Data preparation</h2><a class=\"anchor\" id=\"3\"></a>\n",
    "</div>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>clean_date</th>\n",
       "      <th>recommendation</th>\n",
       "      <th>step_count</th>\n",
       "      <th>walk_step_count</th>\n",
       "      <th>run_step_count</th>\n",
       "      <th>distance</th>\n",
       "      <th>calorie</th>\n",
       "      <th>distance_km</th>\n",
       "      <th>year</th>\n",
       "      <th>month</th>\n",
       "      <th>week</th>\n",
       "      <th>month_number</th>\n",
       "      <th>week_number</th>\n",
       "      <th>day_number</th>\n",
       "      <th>weekday</th>\n",
       "      <th>steps_thousand</th>\n",
       "      <th>walk_steps_thousand</th>\n",
       "      <th>run_steps_thousand</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2017-03-19</td>\n",
       "      <td>6000</td>\n",
       "      <td>8697</td>\n",
       "      <td>8679</td>\n",
       "      <td>18</td>\n",
       "      <td>6313.56</td>\n",
       "      <td>262.93997</td>\n",
       "      <td>6.31356</td>\n",
       "      <td>2017</td>\n",
       "      <td>2017-03</td>\n",
       "      <td>2017-11</td>\n",
       "      <td>03</td>\n",
       "      <td>11</td>\n",
       "      <td>19</td>\n",
       "      <td>Sunday</td>\n",
       "      <td>8.697</td>\n",
       "      <td>8.679</td>\n",
       "      <td>0.018</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2017-02-15</td>\n",
       "      <td>6000</td>\n",
       "      <td>5388</td>\n",
       "      <td>5388</td>\n",
       "      <td>0</td>\n",
       "      <td>3905.87</td>\n",
       "      <td>165.17000</td>\n",
       "      <td>3.90587</td>\n",
       "      <td>2017</td>\n",
       "      <td>2017-02</td>\n",
       "      <td>2017-07</td>\n",
       "      <td>02</td>\n",
       "      <td>07</td>\n",
       "      <td>15</td>\n",
       "      <td>Wednesday</td>\n",
       "      <td>5.388</td>\n",
       "      <td>5.388</td>\n",
       "      <td>0.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>2017-02-09</td>\n",
       "      <td>6000</td>\n",
       "      <td>5402</td>\n",
       "      <td>5392</td>\n",
       "      <td>10</td>\n",
       "      <td>3919.18</td>\n",
       "      <td>167.84999</td>\n",
       "      <td>3.91918</td>\n",
       "      <td>2017</td>\n",
       "      <td>2017-02</td>\n",
       "      <td>2017-06</td>\n",
       "      <td>02</td>\n",
       "      <td>06</td>\n",
       "      <td>09</td>\n",
       "      <td>Thursday</td>\n",
       "      <td>5.402</td>\n",
       "      <td>5.392</td>\n",
       "      <td>0.010</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>2017-01-30</td>\n",
       "      <td>6000</td>\n",
       "      <td>15350</td>\n",
       "      <td>15286</td>\n",
       "      <td>64</td>\n",
       "      <td>11175.10</td>\n",
       "      <td>472.72995</td>\n",
       "      <td>11.17510</td>\n",
       "      <td>2017</td>\n",
       "      <td>2017-01</td>\n",
       "      <td>2017-05</td>\n",
       "      <td>01</td>\n",
       "      <td>05</td>\n",
       "      <td>30</td>\n",
       "      <td>Monday</td>\n",
       "      <td>15.350</td>\n",
       "      <td>15.286</td>\n",
       "      <td>0.064</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>2016-12-17</td>\n",
       "      <td>6000</td>\n",
       "      <td>9854</td>\n",
       "      <td>785</td>\n",
       "      <td>9069</td>\n",
       "      <td>10431.82</td>\n",
       "      <td>712.87000</td>\n",
       "      <td>10.43182</td>\n",
       "      <td>2016</td>\n",
       "      <td>2016-12</td>\n",
       "      <td>2016-50</td>\n",
       "      <td>12</td>\n",
       "      <td>50</td>\n",
       "      <td>17</td>\n",
       "      <td>Saturday</td>\n",
       "      <td>9.854</td>\n",
       "      <td>0.785</td>\n",
       "      <td>9.069</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    clean_date  recommendation  step_count  walk_step_count  run_step_count  \\\n",
       "1   2017-03-19            6000        8697             8679              18   \n",
       "4   2017-02-15            6000        5388             5388               0   \n",
       "7   2017-02-09            6000        5402             5392              10   \n",
       "8   2017-01-30            6000       15350            15286              64   \n",
       "10  2016-12-17            6000        9854              785            9069   \n",
       "\n",
       "    distance    calorie  distance_km  year    month     week month_number  \\\n",
       "1    6313.56  262.93997      6.31356  2017  2017-03  2017-11           03   \n",
       "4    3905.87  165.17000      3.90587  2017  2017-02  2017-07           02   \n",
       "7    3919.18  167.84999      3.91918  2017  2017-02  2017-06           02   \n",
       "8   11175.10  472.72995     11.17510  2017  2017-01  2017-05           01   \n",
       "10  10431.82  712.87000     10.43182  2016  2016-12  2016-50           12   \n",
       "\n",
       "   week_number day_number    weekday  steps_thousand  walk_steps_thousand  \\\n",
       "1           11         19     Sunday           8.697                8.679   \n",
       "4           07         15  Wednesday           5.388                5.388   \n",
       "7           06         09   Thursday           5.402                5.392   \n",
       "8           05         30     Monday          15.350               15.286   \n",
       "10          50         17   Saturday           9.854                0.785   \n",
       "\n",
       "    run_steps_thousand  \n",
       "1                0.018  \n",
       "4                0.000  \n",
       "7                0.010  \n",
       "8                0.064  \n",
       "10               9.069  "
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Step 1 : Remove columns that were useful for duplicates check (see above)\n",
    "pedometer = pedometer.drop(columns = [\"is_duplicate\", \"rank_create_time\", \n",
    "                                      \"create_date\", \"update_date\", \"create_time\", \"update_time\",\n",
    "                                      \"day_time\"])\n",
    "\n",
    "# Step 2 : Create some additional date variables (year, month, week)\n",
    "# Date abbreviations\n",
    "pedometer[\"year\"] = pedometer[\"clean_date\"].apply(lambda x: datetime.strptime(x, \"%Y-%m-%d\").strftime(\"%Y\"))\n",
    "pedometer[\"month\"] = pedometer[\"clean_date\"].apply(lambda x: datetime.strptime(x, \"%Y-%m-%d\").strftime(\"%Y-%m\"))\n",
    "pedometer[\"week\"] = pedometer[\"clean_date\"].apply(lambda x: datetime.strptime(x, \"%Y-%m-%d\").strftime(\"%Y-%W\"))\n",
    "# Date numbers\n",
    "pedometer[\"month_number\"] = pedometer[\"clean_date\"].apply(lambda x: datetime.strptime(x, \"%Y-%m-%d\").strftime(\"%m\"))\n",
    "pedometer[\"week_number\"] = pedometer[\"clean_date\"].apply(lambda x: datetime.strptime(x, \"%Y-%m-%d\").strftime(\"%W\"))\n",
    "pedometer[\"day_number\"] = pedometer[\"clean_date\"].apply(lambda x: datetime.strptime(x, \"%Y-%m-%d\").strftime(\"%d\"))\n",
    "# Date labels\n",
    "pedometer[\"weekday\"] = pedometer[\"clean_date\"].apply(lambda x: datetime.strptime(x, \"%Y-%m-%d\").strftime(\"%A\"))\n",
    "# Some numeric variables that will be useful for data visualization\n",
    "pedometer[\"steps_thousand\"] = pedometer[\"step_count\"]/1000\n",
    "pedometer[\"walk_steps_thousand\"] = pedometer[\"walk_step_count\"]/1000\n",
    "pedometer[\"run_steps_thousand\"] = pedometer[\"run_step_count\"]/1000\n",
    "\n",
    "pedometer.head(5)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Export the cleaned data to Excel\n",
    "pedometer.to_csv(\"pedometer_data.csv\", sep = \";\", index = False)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<div style=\"background-color: RGB(0,150,250);\" >\n",
    "<h2 style=\"margin: auto; padding: 20px; color:#fff; \">4. Insights from data exploration</h2><a class=\"anchor\" id=\"4\"></a>\n",
    "</div>\n",
    "\n",
    "## 4.1. I walked ca. 13,500 km walked over 7 years. This is the distance between Paris (France) and Vladivostok (Russia)!  <a class=\"anchor\" id=\"4.1\"></a>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Between 2016 and 2023, I walked in total: \u001b[1m 17998172 \u001b[0m steps, i.e. \u001b[1m 13496 km. \u001b[0m\n",
      "Equivalently, per day, I walked on average: \u001b[1m 7613 \u001b[0m steps, i.e. \u001b[1m 5 km. \u001b[0m\n"
     ]
    }
   ],
   "source": [
    "# Some descriptive statitics\n",
    "total_activity = pedometer[[\"step_count\", \"distance_km\"]].sum()\n",
    "avg_activity = pedometer[[\"step_count\", \"distance_km\"]].sum() / pedometer[\"clean_date\"].nunique()\n",
    "\n",
    "print(\"Between 2016 and 2023, I walked in total:\", '\\033[1m', int(total_activity[0]),  '\\033[0m', \"steps, i.e.\", \n",
    "      '\\033[1m', int(total_activity[1]), \"km.\", '\\033[0m',)\n",
    "\n",
    "print(\"Equivalently, per day, I walked on average:\", '\\033[1m', int(avg_activity[0]),  '\\033[0m', \"steps, i.e.\", \n",
    "      '\\033[1m', int(avg_activity[1]), \"km.\", '\\033[0m',)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Graph n°1: Cumulative sum of my steps and distance traveled\n",
    "g1 = pedometer.set_index(\"clean_date\")[[\"steps_thousand\", \"run_steps_thousand\", \n",
    "                                        \"walk_steps_thousand\", \"distance_km\"]].cumsum().plot()\n",
    "\n",
    "g1.set_title(\"Cumulative sum of steps (in thousand) and kilometers (2016-2023)\")\n",
    "g1.set(xlabel = \"Time\", ylabel= 'Cumulative sum')\n",
    "plt.show()\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<div class=\"alert alert-block alert-warning\">\n",
    "<b>Learnings:</b> \n",
    "<br>\n",
    "    <br><b>Most of my steps are derived from walking, not running</b> (cf steep green line vs flat orange line). Furthermore, over 7 years, I was able to walk ca. 18 million steps, i.e. 13,500 km (~8,300 miles). This represents 7,600 steps/day, or put it differently 5 kms/day. \n",
    "<br>\n",
    "    <br><b>I tend to walk more in my daily life in the recent years</b> (cf. steeper slope from 2020 onwards).\n",
    "</div>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 4.2. I was most active when working in Japan and at the end of the Covid19 French lockdown <a class=\"anchor\" id=\"4.2\"></a>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1600x827 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Graph n°2 a) : Total distance (in kilometers) walked every year (2016-2023)\n",
    "sns.set(rc={'figure.figsize':(16,8.27)})\n",
    "sns.set_style(\"white\")\n",
    "\n",
    "data_year = pedometer.groupby(\"year\")[[\"step_count\", \"distance_km\"]].sum().reset_index()\n",
    "g2 = sns.barplot(data = data_year, x= \"year\", y = \"distance_km\" , color = \"blue\", alpha = 0.7)\n",
    "g2.set_title(\"Total distance walked per year (2016-2023), in kilometers\")\n",
    "g2.set(xlabel = \"year\", ylabel= \"Total number of kilometers\")\n",
    "\n",
    "for i in g2.containers:\n",
    "    g2.bar_label(i,)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<div class=\"alert alert-block alert-warning\">\n",
    "<b>Learnings:</b> \n",
    "<br>\n",
    "\n",
    "<br> <b>From a very broad perspective, it seems that I used to walk ca. 1,700 kilometers/year for the period 2017-2021.</b> However, there are some \"outliers\" years.\n",
    "<br> 2019 was the year I was the least active (1,400 km) as I was busy preparing for my final exams and data analyst job search.\n",
    "<br>On the contrary, 2021 was my record-breaking year (2,900 km). I was so excited that the Covid19 was (temporarily) over that I went out as much as possible. Every weekend, I was hiking, going to the swimming pool, etc. In 2022, I walked less than in 2021 but still more than pre-pandemic.\n",
    "<br> Note: I ignored 2016 and 2023 since I do not have complete data for these years. <br>\n",
    "\n",
    "</div>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1600x827 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Graph n°2b) : Average daily number of steps, aggregated per month (2016-2023)\n",
    "sns.set(rc={'figure.figsize':(16,8.27)})\n",
    "sns.set_style(\"white\")\n",
    "\n",
    "g2 = sns.lineplot(data = pedometer.sort_values(\"month\"), x= \"month\", y = \"step_count\", color = \"blue\")\n",
    "g2.set_title(\"Average daily number of steps, aggregated per month (2016-2023)\")\n",
    "g2.set(xlabel = \"Month\", ylabel= \"Total number of steps\")\n",
    "\n",
    "locs, labels = plt.xticks()\n",
    "plt.setp(labels, rotation=90)\n",
    "\n",
    "g2.vlines(x='2017-01', ymin=0, ymax=20000, color='b', linestyles = \"dashed\", label='2017')\n",
    "g2.vlines(x='2018-01', ymin=0, ymax=20000, color='b', linestyles = \"dashed\", label='2018')\n",
    "g2.vlines(x='2019-01', ymin=0, ymax=20000, color='b', linestyles = \"dashed\", label='2019')\n",
    "g2.vlines(x='2020-01', ymin=0, ymax=20000, color='b', linestyles = \"dashed\", label='2020')\n",
    "g2.vlines(x='2021-01', ymin=0, ymax=20000, color='b', linestyles = \"dashed\", label='2021')\n",
    "g2.vlines(x='2022-01', ymin=0, ymax=20000, color='b', linestyles = \"dashed\", label='2022')\n",
    "g2.vlines(x='2023-01', ymin=0, ymax=20000, color='b', linestyles = \"dashed\", label='2023')\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<div class=\"alert alert-block alert-warning\">\n",
    "<b>Learnings:</b> \n",
    "<br>\n",
    "<br> <b>The graph above shows that my walking habits were not consistent over the last 7 years (i.e. I did not walk exactly 7,600 steps every day).</b> For instance, the years 2017 and 2019 were quite below average, whereas 2018 and 2021 were above average. More specifically, my lowest point was reached in March / April 2020 , when France enforced its first lockdown due to the Covid19 pandemic crisis. This explains why I was walking only 2,500 steps a day. On the contrary, my peak was achieved in June / July 2021, i.e. when the French government allowed again social activities (e.g. hiking in groups, going to the swimming pool, etc). At that time, I was walking about 14,000 steps a day.<br>\n",
    "<br>\n",
    "<b>Some seasonality seems also to be at play. My busiest periods often take place in summer (July to September)</b>. Indeed:  \n",
    "    <br> i) 2018 2nd semester: This corresponds to the period I was working in Japan. I had to walk a lot in my daily life for going to work and grocery shopping (my apartment was located 20 minutes away from the nearest train station). In summer, I also enjoyed \"Obon\" holidays by traveling to Hokkaido.\n",
    "    <br> ii) 2019 August: This refers to my trip in the Netherlands before starting my first full time job. I walked a lot to discover cities Amsterdam or The Hague.\n",
    "    <br> iii) 2020 August and 2021 August: Covid was (temporarily) over in France and I joined hiking groups to walk in the woods every weekend.<br>\n",
    "    <br> \n",
    "<b> It seems that I became more active since the beginning of the Covid19 crisis (cf. positive slope for several consecutive months from March 2020 onwards) </b>. In 2022 however, I walked less than in 2021 but the daily average number of steps is still above that of the other years.<br> \n",
    "<br>\n",
    "<b>Finally, the confidence intervals in light blue become more spread over time.</b> This suggests that the daily average number of steps displayed with the dark blue line does not perfectly reflect the reality: there may be days I walk far less or far more than the average number in the recent period.\n",
    "   \n",
    "</div>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[Text(0.5, 0, 'Month number'), Text(0, 0.5, 'Distance (km)')]"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
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\n",
      "text/plain": [
       "<Figure size 1600x827 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Graph n°3 : Let's compare the distribution of steps on a small sample of data\n",
    "    # Monthly comparison, 2019 vs 2022\n",
    "sample = pedometer[((pedometer[\"year\"]==\"2022\") & (pedometer[\"month_number\"]<=\"06\"))\n",
    "                   | ((pedometer[\"year\"]==\"2019\") & (pedometer[\"month_number\"]<=\"06\"))\n",
    "                  ].sort_values(\"clean_date\")\n",
    "\n",
    "g3 = sns.boxplot(data = sample, x= \"month_number\", y = \"distance_km\", hue = \"year\", palette = \"Blues\")\n",
    "g3.set_title(\"Distance in kilometers: Comparison month by month between 2019 and 2022\")\n",
    "g3.set(xlabel = \"Month number\", ylabel= \"Distance (km)\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<div class=\"alert alert-block alert-warning\">\n",
    "<b>Learnings:</b> The boxplot above shows the distribution of kilometers traveled in a day. It is computed by month, with a comparison between 2019 and 2022 (1st semester only considered in the sample for readibility purposes).\n",
    "<br>\n",
    "    <br> <b>It shows that I am systematically more active in 2022 than in 2019</b> (the median in the dark blue box is always above that of the light blue box).\n",
    "    <br>\n",
    "    <br> <b> More importantly, it shows that the distance I travel daily varies much more in 2022 than in 2019 </b>. Indeed, the whiskers are much more spead out in 2022. There are also much more outliers that lie very far from the median line. The variation is mostly driven by high values (right skewed distribution). Indeed, the first quartile (Q1) value stays very consistent on the contrary (close to zero) : there are some days I am not active at all, whatever the month or the year considered.\n",
    " \n",
    "</div>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 4.3. Reaching 10,000 steps a day is an everyday challenge!   <a class=\"anchor\" id=\"4.3\"></a>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>clean_date</th>\n",
       "      <th>recommendation</th>\n",
       "      <th>step_count</th>\n",
       "      <th>walk_step_count</th>\n",
       "      <th>run_step_count</th>\n",
       "      <th>distance</th>\n",
       "      <th>calorie</th>\n",
       "      <th>distance_km</th>\n",
       "      <th>year</th>\n",
       "      <th>month</th>\n",
       "      <th>week</th>\n",
       "      <th>month_number</th>\n",
       "      <th>week_number</th>\n",
       "      <th>day_number</th>\n",
       "      <th>weekday</th>\n",
       "      <th>steps_thousand</th>\n",
       "      <th>walk_steps_thousand</th>\n",
       "      <th>run_steps_thousand</th>\n",
       "      <th>goal_10000</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2017-03-19</td>\n",
       "      <td>6000</td>\n",
       "      <td>8697</td>\n",
       "      <td>8679</td>\n",
       "      <td>18</td>\n",
       "      <td>6313.56</td>\n",
       "      <td>262.93997</td>\n",
       "      <td>6.31356</td>\n",
       "      <td>2017</td>\n",
       "      <td>2017-03</td>\n",
       "      <td>2017-11</td>\n",
       "      <td>03</td>\n",
       "      <td>11</td>\n",
       "      <td>19</td>\n",
       "      <td>Sunday</td>\n",
       "      <td>8.697</td>\n",
       "      <td>8.679</td>\n",
       "      <td>0.018</td>\n",
       "      <td>0.8697</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2017-02-15</td>\n",
       "      <td>6000</td>\n",
       "      <td>5388</td>\n",
       "      <td>5388</td>\n",
       "      <td>0</td>\n",
       "      <td>3905.87</td>\n",
       "      <td>165.17000</td>\n",
       "      <td>3.90587</td>\n",
       "      <td>2017</td>\n",
       "      <td>2017-02</td>\n",
       "      <td>2017-07</td>\n",
       "      <td>02</td>\n",
       "      <td>07</td>\n",
       "      <td>15</td>\n",
       "      <td>Wednesday</td>\n",
       "      <td>5.388</td>\n",
       "      <td>5.388</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.5388</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>2017-02-09</td>\n",
       "      <td>6000</td>\n",
       "      <td>5402</td>\n",
       "      <td>5392</td>\n",
       "      <td>10</td>\n",
       "      <td>3919.18</td>\n",
       "      <td>167.84999</td>\n",
       "      <td>3.91918</td>\n",
       "      <td>2017</td>\n",
       "      <td>2017-02</td>\n",
       "      <td>2017-06</td>\n",
       "      <td>02</td>\n",
       "      <td>06</td>\n",
       "      <td>09</td>\n",
       "      <td>Thursday</td>\n",
       "      <td>5.402</td>\n",
       "      <td>5.392</td>\n",
       "      <td>0.010</td>\n",
       "      <td>0.5402</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>2017-01-30</td>\n",
       "      <td>6000</td>\n",
       "      <td>15350</td>\n",
       "      <td>15286</td>\n",
       "      <td>64</td>\n",
       "      <td>11175.10</td>\n",
       "      <td>472.72995</td>\n",
       "      <td>11.17510</td>\n",
       "      <td>2017</td>\n",
       "      <td>2017-01</td>\n",
       "      <td>2017-05</td>\n",
       "      <td>01</td>\n",
       "      <td>05</td>\n",
       "      <td>30</td>\n",
       "      <td>Monday</td>\n",
       "      <td>15.350</td>\n",
       "      <td>15.286</td>\n",
       "      <td>0.064</td>\n",
       "      <td>1.0000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>2016-12-17</td>\n",
       "      <td>6000</td>\n",
       "      <td>9854</td>\n",
       "      <td>785</td>\n",
       "      <td>9069</td>\n",
       "      <td>10431.82</td>\n",
       "      <td>712.87000</td>\n",
       "      <td>10.43182</td>\n",
       "      <td>2016</td>\n",
       "      <td>2016-12</td>\n",
       "      <td>2016-50</td>\n",
       "      <td>12</td>\n",
       "      <td>50</td>\n",
       "      <td>17</td>\n",
       "      <td>Saturday</td>\n",
       "      <td>9.854</td>\n",
       "      <td>0.785</td>\n",
       "      <td>9.069</td>\n",
       "      <td>0.9854</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    clean_date  recommendation  step_count  walk_step_count  run_step_count  \\\n",
       "1   2017-03-19            6000        8697             8679              18   \n",
       "4   2017-02-15            6000        5388             5388               0   \n",
       "7   2017-02-09            6000        5402             5392              10   \n",
       "8   2017-01-30            6000       15350            15286              64   \n",
       "10  2016-12-17            6000        9854              785            9069   \n",
       "\n",
       "    distance    calorie  distance_km  year    month     week month_number  \\\n",
       "1    6313.56  262.93997      6.31356  2017  2017-03  2017-11           03   \n",
       "4    3905.87  165.17000      3.90587  2017  2017-02  2017-07           02   \n",
       "7    3919.18  167.84999      3.91918  2017  2017-02  2017-06           02   \n",
       "8   11175.10  472.72995     11.17510  2017  2017-01  2017-05           01   \n",
       "10  10431.82  712.87000     10.43182  2016  2016-12  2016-50           12   \n",
       "\n",
       "   week_number day_number    weekday  steps_thousand  walk_steps_thousand  \\\n",
       "1           11         19     Sunday           8.697                8.679   \n",
       "4           07         15  Wednesday           5.388                5.388   \n",
       "7           06         09   Thursday           5.402                5.392   \n",
       "8           05         30     Monday          15.350               15.286   \n",
       "10          50         17   Saturday           9.854                0.785   \n",
       "\n",
       "    run_steps_thousand  goal_10000  \n",
       "1                0.018      0.8697  \n",
       "4                0.000      0.5388  \n",
       "7                0.010      0.5402  \n",
       "8                0.064      1.0000  \n",
       "10               9.069      0.9854  "
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Create a new variable \"goal_10000\": It returns 1 if I walked more than 10 000 steps a day\n",
    "pedometer.loc[pedometer[\"step_count\"]>=10000, \"goal_10000\"] = 1\n",
    "pedometer.loc[pedometer[\"step_count\"]<10000, \"goal_10000\"] = pedometer[\"step_count\"]/10000\n",
    "pedometer.head(5)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[Text(0.5, 58.219999999999985, 'Day of week'),\n",
       " Text(167.25, 0.5, 'Week number')]"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1600x827 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "## Graph n°4: Heatmap \n",
    "\n",
    "# Prepare the data for the heatmap\n",
    "sample2 = pedometer[(pedometer[\"year\"]==\"2022\") \n",
    "                    & ((pedometer[\"month_number\"]==\"09\")\n",
    "                      | (pedometer[\"month_number\"]==\"10\"))][[\"week_number\", \"weekday\",\"goal_10000\"]]\n",
    "\n",
    "sample2 = sample2.pivot(index= \"week_number\", columns = \"weekday\", values = \"goal_10000\")\n",
    "cols_order = [\"Monday\", \"Tuesday\", \"Wednesday\", \"Thursday\", \"Friday\", \"Saturday\", \"Sunday\"]\n",
    "sample2 = sample2[cols_order]\n",
    "\n",
    "# Heatmap\n",
    "g5 = sns.heatmap(sample2, annot=True, cmap=\"GnBu\")\n",
    "g5.set_title(\"September and October 2022: How many days did I reach the objective of walking 10000 steps a day ?\")\n",
    "g5.set(xlabel = \"Day of week\", ylabel= \"Week number\")\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<div class=\"alert alert-block alert-warning\">\n",
    "<b>Learnings:</b> \n",
    "    <br>\n",
    "    <br>\n",
    "     <b>In September and early October 2022, I could pass the \"10000 steps a day\" only every 3 other days (12 days out of 39 days in total).</b> \n",
    "    <br>\n",
    "    <br> The days I was successful were mostly Fridays and Saturdays. Indeed, every Fridays (except holidays) I gather with my coworkers to do a quick hike at lunch time in the woods next to our headquarters. On Saturdays, I usually work out by going to the Olympic swimming pool that is a bit far away from my home or by hiking with some Meetup groups. \n",
    "    <br>\n",
    "    <br> On the contrary, I tend to be not very active on Tuesdays as I am often working remotely.\n",
    "    <br>\n",
    "    <br> Finally, regarding Week 37, I was able to reach the objective everyday (except Sunday) because I was on holiday and could hike in Spain the whole week.\n",
    "</div>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<div style=\"background-color: RGB(0,150,250);\" >\n",
    "<h2 style=\"margin: auto; padding: 20px; color:#fff; \">5. Conclusion</h2><a class=\"anchor\" id=\"5\"></a>\n",
    "</div>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 5.1. Summary of the insights and how to go further  <a class=\"anchor\" id=\"5.1\"></a>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The case study demonstrated that :\n",
    "* **I am a walker, not a runner**\n",
    "* **My performances are mainly driven by my schedule.** Indeed, I tend to walk more during the weekends and when I am on holiday (especially in summer). On the contrary, my step count is low when I am working remotely or when the Covid19 lockdown was enforced in France.\n",
    "* **I do not reach everyday the 10,000 steps a day recommendation made by the World Health Organization.** I try to compensate with long hikes during the weekends or with my coworker group at lunch time.\n",
    "<br>\n",
    "\n",
    "The case study could have been improved in various ways, by:\n",
    "* Developing further the data visualization part with a summary dashboard\n",
    "* Making some time series predictions (e.g. what do I expect my step count to be next month ?)\n",
    "* Joining Samsung health data with other data (e.g. weight data, calendar data, etc)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 5.2. Technical challenges encountered <a class=\"anchor\" id=\"5.2\"></a>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Here are some of the difficulties I faced while making the case study:\n",
    "\n",
    "* **Dataset understanding: I could not find any exhaustive documentation online about the dataset.** Therefore I had to get rid of some variables because I was not sure about their interpretation (e.g. what is a Samsung \"healthy step\" ?) \n",
    "<br>\n",
    "\n",
    "* **Quality of data: It was very hard to understand why my original dataset had so many duplicates (Was it a bug of the Samsung Health app ? A timezone problem ? ...) and how to get rid of them properly.** Data cleaning was thus quite tedious.\n",
    "<br>\n",
    "\n",
    "* **Data source: The data I got from Samsung underestimate my level of activity** because they come from my smartphone, not a smartwatch. Thus I have no record of my dance class lessons and swimming sessions. This may have been a problem if I had tried to get an exhaustive view of my physical activity level.\n",
    "<br>\n",
    "\n",
    "* **Data source: My data cannot be up to date** because I used a flat file as my main data source. Furthermore, I could not make any use of the many Json files that accompanied the csv files. "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 5.3. What I learnt as a data analyst <a class=\"anchor\" id=\"5.3\"></a>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "I aboslutely loved writing this case study ! I learnt a lot because:\n",
    "* **This was the first time I was coding in Python.** In my professional life, I am used to coding in SQL and R, so this was refreshing to learn how to code a new programming language.\n",
    "* **This was also the first time I was using the Jupyter Notebook and Markdown formats.** I found it very convenient to display at the same time code, comments and final outputs to make the case study easier to understand.\n",
    "* **Data cleaning is as always very crucial**. Without getting rid off duplicates, I would have overestimated my total step count by at least 20% !"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Thank you for reading this far and happy hiking !"
   ]
  },
  {
   "attachments": {
    "arthur-hickinbotham-BtCaXJ8BJjY-unsplash.jpg": {
     "image/jpeg": 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"
    }
   },
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "  ![arthur-hickinbotham-BtCaXJ8BJjY-unsplash.jpg](attachment:arthur-hickinbotham-BtCaXJ8BJjY-unsplash.jpg)\n",
    "  \n",
    "  Photo by <a href=\"https://unsplash.com/@arthurhick?utm_source=unsplash&utm_medium=referral&utm_content=creditCopyText\">Arthur Hickinbotham</a> on <a href=\"https://unsplash.com/s/photos/hiking?utm_source=unsplash&utm_medium=referral&utm_content=creditCopyText\">Unsplash</a>\n",
    "  "
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.9.13"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}