etl.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {
    "editable": true
   },
   "source": [
    "# ETL Processes\n",
    "Use this notebook to develop the ETL process for each of your tables before completing the `etl.py` file to load the whole datasets."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "editable": true
   },
   "outputs": [],
   "source": [
    "import os\n",
    "import glob\n",
    "import psycopg2\n",
    "import pandas as pd\n",
    "from sql_queries import *"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "editable": true
   },
   "outputs": [],
   "source": [
    "conn = psycopg2.connect(\"host=127.0.0.1 dbname=sparkifydb user=student password=student\")\n",
    "cur = conn.cursor()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "editable": true
   },
   "outputs": [],
   "source": [
    "def get_files(filepath):\n",
    "    all_files = []\n",
    "    for root, dirs, files in os.walk(filepath):\n",
    "        files = glob.glob(os.path.join(root,'*.json'))\n",
    "        for f in files :\n",
    "            all_files.append(os.path.abspath(f))\n",
    "    \n",
    "    return all_files"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "editable": true
   },
   "source": [
    "# Process `song_data`\n",
    "In this first part, you'll perform ETL on the first dataset, `song_data`, to create the `songs` and `artists` dimensional tables.\n",
    "\n",
    "Let's perform ETL on a single song file and load a single record into each table to start.\n",
    "- Use the `get_files` function provided above to get a list of all song JSON files in `data/song_data`\n",
    "- Select the first song in this list\n",
    "- Read the song file and view the data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "editable": true
   },
   "outputs": [],
   "source": [
    "song_files = get_files('data/song_data')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "editable": true
   },
   "outputs": [],
   "source": [
    "filepath = song_files[0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "editable": true
   },
   "outputs": [
    {
     "data": {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>num_songs</th>\n",
       "      <th>artist_id</th>\n",
       "      <th>artist_latitude</th>\n",
       "      <th>artist_longitude</th>\n",
       "      <th>artist_location</th>\n",
       "      <th>artist_name</th>\n",
       "      <th>song_id</th>\n",
       "      <th>title</th>\n",
       "      <th>duration</th>\n",
       "      <th>year</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>ARDR4AC1187FB371A1</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td></td>\n",
       "      <td>Montserrat Caballé;Placido Domingo;Vicente Sar...</td>\n",
       "      <td>SOBAYLL12A8C138AF9</td>\n",
       "      <td>Sono andati? Fingevo di dormire</td>\n",
       "      <td>511.16363</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   num_songs           artist_id  artist_latitude  artist_longitude  \\\n",
       "0          1  ARDR4AC1187FB371A1              NaN               NaN   \n",
       "\n",
       "  artist_location                                        artist_name  \\\n",
       "0                  Montserrat Caballé;Placido Domingo;Vicente Sar...   \n",
       "\n",
       "              song_id                            title   duration  year  \n",
       "0  SOBAYLL12A8C138AF9  Sono andati? Fingevo di dormire  511.16363     0  "
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df = pd.read_json(filepath, lines=True)\n",
    "df.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "editable": true
   },
   "source": [
    "## #1: `songs` Table\n",
    "#### Extract Data for Songs Table\n",
    "- Select columns for song ID, title, artist ID, year, and duration\n",
    "- Use `df.values` to select just the values from the dataframe\n",
    "- Index to select the first (only) record in the dataframe\n",
    "- Convert the array to a list and set it to `song_data`"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "editable": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['SOBAYLL12A8C138AF9',\n",
       " 'Sono andati? Fingevo di dormire',\n",
       " 'ARDR4AC1187FB371A1',\n",
       " 0,\n",
       " 511.16363]"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "song_data = df.loc[:, ['song_id', 'title', 'artist_id', 'year', 'duration']].values[0].tolist()\n",
    "song_data"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "editable": true
   },
   "source": [
    "#### Insert Record into Song Table\n",
    "Implement the `song_table_insert` query in `sql_queries.py` and run the cell below to insert a record for this song into the `songs` table. Remember to run `create_tables.py` before running the cell below to ensure you've created/resetted the `songs` table in the sparkify database."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "editable": true
   },
   "outputs": [],
   "source": [
    "cur.execute(song_table_insert, song_data)\n",
    "conn.commit()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "editable": true
   },
   "source": [
    "Run `test.ipynb` to see if you've successfully added a record to this table."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "editable": true
   },
   "source": [
    "## #2: `artists` Table\n",
    "#### Extract Data for Artists Table\n",
    "- Select columns for artist ID, name, location, latitude, and longitude\n",
    "- Use `df.values` to select just the values from the dataframe\n",
    "- Index to select the first (only) record in the dataframe\n",
    "- Convert the array to a list and set it to `artist_data`"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "editable": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['ARDR4AC1187FB371A1',\n",
       " 'Montserrat Caballé;Placido Domingo;Vicente Sardinero;Judith Blegen;Sherrill Milnes;Georg Solti',\n",
       " '',\n",
       " nan,\n",
       " nan]"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "artist_data = df.loc[:, ['artist_id', 'artist_name', 'artist_location', 'artist_latitude', 'artist_longitude']].values[0].tolist()\n",
    "artist_data"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "editable": true
   },
   "source": [
    "#### Insert Record into Artist Table\n",
    "Implement the `artist_table_insert` query in `sql_queries.py` and run the cell below to insert a record for this song's artist into the `artists` table. Remember to run `create_tables.py` before running the cell below to ensure you've created/resetted the `artists` table in the sparkify database."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "editable": true
   },
   "outputs": [],
   "source": [
    "cur.execute(artist_table_insert, artist_data)\n",
    "conn.commit()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "editable": true
   },
   "source": [
    "Run `test.ipynb` to see if you've successfully added a record to this table."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "editable": true
   },
   "source": [
    "# Process `log_data`\n",
    "In this part, you'll perform ETL on the second dataset, `log_data`, to create the `time` and `users` dimensional tables, as well as the `songplays` fact table.\n",
    "\n",
    "Let's perform ETL on a single log file and load a single record into each table.\n",
    "- Use the `get_files` function provided above to get a list of all log JSON files in `data/log_data`\n",
    "- Select the first log file in this list\n",
    "- Read the log file and view the data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "editable": true
   },
   "outputs": [],
   "source": [
    "log_files = get_files('data/log_data')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {
    "editable": true
   },
   "outputs": [],
   "source": [
    "filepath = log_files[0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {
    "editable": true
   },
   "outputs": [
    {
     "data": {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>artist</th>\n",
       "      <th>auth</th>\n",
       "      <th>firstName</th>\n",
       "      <th>gender</th>\n",
       "      <th>itemInSession</th>\n",
       "      <th>lastName</th>\n",
       "      <th>length</th>\n",
       "      <th>level</th>\n",
       "      <th>location</th>\n",
       "      <th>method</th>\n",
       "      <th>page</th>\n",
       "      <th>registration</th>\n",
       "      <th>sessionId</th>\n",
       "      <th>song</th>\n",
       "      <th>status</th>\n",
       "      <th>ts</th>\n",
       "      <th>userAgent</th>\n",
       "      <th>userId</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Mitch Ryder &amp; The Detroit Wheels</td>\n",
       "      <td>Logged In</td>\n",
       "      <td>Tegan</td>\n",
       "      <td>F</td>\n",
       "      <td>65</td>\n",
       "      <td>Levine</td>\n",
       "      <td>205.03465</td>\n",
       "      <td>paid</td>\n",
       "      <td>Portland-South Portland, ME</td>\n",
       "      <td>PUT</td>\n",
       "      <td>NextSong</td>\n",
       "      <td>1.540794e+12</td>\n",
       "      <td>992</td>\n",
       "      <td>Jenny Take A Ride (LP Version)</td>\n",
       "      <td>200</td>\n",
       "      <td>1543363215796</td>\n",
       "      <td>\"Mozilla/5.0 (Macintosh; Intel Mac OS X 10_9_4...</td>\n",
       "      <td>80</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>The Spill Canvas</td>\n",
       "      <td>Logged In</td>\n",
       "      <td>Tegan</td>\n",
       "      <td>F</td>\n",
       "      <td>66</td>\n",
       "      <td>Levine</td>\n",
       "      <td>358.03383</td>\n",
       "      <td>paid</td>\n",
       "      <td>Portland-South Portland, ME</td>\n",
       "      <td>PUT</td>\n",
       "      <td>NextSong</td>\n",
       "      <td>1.540794e+12</td>\n",
       "      <td>992</td>\n",
       "      <td>The TIde (LP Version)</td>\n",
       "      <td>200</td>\n",
       "      <td>1543363420796</td>\n",
       "      <td>\"Mozilla/5.0 (Macintosh; Intel Mac OS X 10_9_4...</td>\n",
       "      <td>80</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Mogwai</td>\n",
       "      <td>Logged In</td>\n",
       "      <td>Tegan</td>\n",
       "      <td>F</td>\n",
       "      <td>67</td>\n",
       "      <td>Levine</td>\n",
       "      <td>571.19302</td>\n",
       "      <td>paid</td>\n",
       "      <td>Portland-South Portland, ME</td>\n",
       "      <td>PUT</td>\n",
       "      <td>NextSong</td>\n",
       "      <td>1.540794e+12</td>\n",
       "      <td>992</td>\n",
       "      <td>Two Rights Make One Wrong</td>\n",
       "      <td>200</td>\n",
       "      <td>1543363778796</td>\n",
       "      <td>\"Mozilla/5.0 (Macintosh; Intel Mac OS X 10_9_4...</td>\n",
       "      <td>80</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Spor</td>\n",
       "      <td>Logged In</td>\n",
       "      <td>Tegan</td>\n",
       "      <td>F</td>\n",
       "      <td>68</td>\n",
       "      <td>Levine</td>\n",
       "      <td>380.34240</td>\n",
       "      <td>paid</td>\n",
       "      <td>Portland-South Portland, ME</td>\n",
       "      <td>PUT</td>\n",
       "      <td>NextSong</td>\n",
       "      <td>1.540794e+12</td>\n",
       "      <td>992</td>\n",
       "      <td>Way Of The Samurai</td>\n",
       "      <td>200</td>\n",
       "      <td>1543364349796</td>\n",
       "      <td>\"Mozilla/5.0 (Macintosh; Intel Mac OS X 10_9_4...</td>\n",
       "      <td>80</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>DJ Dizzy</td>\n",
       "      <td>Logged In</td>\n",
       "      <td>Tegan</td>\n",
       "      <td>F</td>\n",
       "      <td>69</td>\n",
       "      <td>Levine</td>\n",
       "      <td>221.15220</td>\n",
       "      <td>paid</td>\n",
       "      <td>Portland-South Portland, ME</td>\n",
       "      <td>PUT</td>\n",
       "      <td>NextSong</td>\n",
       "      <td>1.540794e+12</td>\n",
       "      <td>992</td>\n",
       "      <td>Sexy Bitch</td>\n",
       "      <td>200</td>\n",
       "      <td>1543364729796</td>\n",
       "      <td>\"Mozilla/5.0 (Macintosh; Intel Mac OS X 10_9_4...</td>\n",
       "      <td>80</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                             artist       auth firstName gender  \\\n",
       "0  Mitch Ryder & The Detroit Wheels  Logged In     Tegan      F   \n",
       "1                  The Spill Canvas  Logged In     Tegan      F   \n",
       "2                            Mogwai  Logged In     Tegan      F   \n",
       "3                              Spor  Logged In     Tegan      F   \n",
       "4                          DJ Dizzy  Logged In     Tegan      F   \n",
       "\n",
       "   itemInSession lastName     length level                     location  \\\n",
       "0             65   Levine  205.03465  paid  Portland-South Portland, ME   \n",
       "1             66   Levine  358.03383  paid  Portland-South Portland, ME   \n",
       "2             67   Levine  571.19302  paid  Portland-South Portland, ME   \n",
       "3             68   Levine  380.34240  paid  Portland-South Portland, ME   \n",
       "4             69   Levine  221.15220  paid  Portland-South Portland, ME   \n",
       "\n",
       "  method      page  registration  sessionId                            song  \\\n",
       "0    PUT  NextSong  1.540794e+12        992  Jenny Take A Ride (LP Version)   \n",
       "1    PUT  NextSong  1.540794e+12        992           The TIde (LP Version)   \n",
       "2    PUT  NextSong  1.540794e+12        992       Two Rights Make One Wrong   \n",
       "3    PUT  NextSong  1.540794e+12        992              Way Of The Samurai   \n",
       "4    PUT  NextSong  1.540794e+12        992                      Sexy Bitch   \n",
       "\n",
       "   status             ts                                          userAgent  \\\n",
       "0     200  1543363215796  \"Mozilla/5.0 (Macintosh; Intel Mac OS X 10_9_4...   \n",
       "1     200  1543363420796  \"Mozilla/5.0 (Macintosh; Intel Mac OS X 10_9_4...   \n",
       "2     200  1543363778796  \"Mozilla/5.0 (Macintosh; Intel Mac OS X 10_9_4...   \n",
       "3     200  1543364349796  \"Mozilla/5.0 (Macintosh; Intel Mac OS X 10_9_4...   \n",
       "4     200  1543364729796  \"Mozilla/5.0 (Macintosh; Intel Mac OS X 10_9_4...   \n",
       "\n",
       "  userId  \n",
       "0     80  \n",
       "1     80  \n",
       "2     80  \n",
       "3     80  \n",
       "4     80  "
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df = pd.read_json(filepath, lines=True)\n",
    "df.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "editable": true
   },
   "source": [
    "## #3: `time` Table\n",
    "#### Extract Data for Time Table\n",
    "- Filter records by `NextSong` action\n",
    "- Convert the `ts` timestamp column to datetime\n",
    "  - Hint: the current timestamp is in milliseconds\n",
    "- Extract the timestamp, hour, day, week of year, month, year, and weekday from the `ts` column and set `time_data` to a list containing these values in order\n",
    "  - Hint: use pandas' [`dt` attribute](https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.Series.dt.html) to access easily datetimelike properties.\n",
    "- Specify labels for these columns and set to `column_labels`\n",
    "- Create a dataframe, `time_df,` containing the time data for this file by combining `column_labels` and `time_data` into a dictionary and converting this into a dataframe"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {
    "editable": true
   },
   "outputs": [
    {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>artist</th>\n",
       "      <th>auth</th>\n",
       "      <th>firstName</th>\n",
       "      <th>gender</th>\n",
       "      <th>itemInSession</th>\n",
       "      <th>lastName</th>\n",
       "      <th>length</th>\n",
       "      <th>level</th>\n",
       "      <th>location</th>\n",
       "      <th>method</th>\n",
       "      <th>page</th>\n",
       "      <th>registration</th>\n",
       "      <th>sessionId</th>\n",
       "      <th>song</th>\n",
       "      <th>status</th>\n",
       "      <th>ts</th>\n",
       "      <th>userAgent</th>\n",
       "      <th>userId</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Mitch Ryder &amp; The Detroit Wheels</td>\n",
       "      <td>Logged In</td>\n",
       "      <td>Tegan</td>\n",
       "      <td>F</td>\n",
       "      <td>65</td>\n",
       "      <td>Levine</td>\n",
       "      <td>205.03465</td>\n",
       "      <td>paid</td>\n",
       "      <td>Portland-South Portland, ME</td>\n",
       "      <td>PUT</td>\n",
       "      <td>NextSong</td>\n",
       "      <td>1.540794e+12</td>\n",
       "      <td>992</td>\n",
       "      <td>Jenny Take A Ride (LP Version)</td>\n",
       "      <td>200</td>\n",
       "      <td>1543363215796</td>\n",
       "      <td>\"Mozilla/5.0 (Macintosh; Intel Mac OS X 10_9_4...</td>\n",
       "      <td>80</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>The Spill Canvas</td>\n",
       "      <td>Logged In</td>\n",
       "      <td>Tegan</td>\n",
       "      <td>F</td>\n",
       "      <td>66</td>\n",
       "      <td>Levine</td>\n",
       "      <td>358.03383</td>\n",
       "      <td>paid</td>\n",
       "      <td>Portland-South Portland, ME</td>\n",
       "      <td>PUT</td>\n",
       "      <td>NextSong</td>\n",
       "      <td>1.540794e+12</td>\n",
       "      <td>992</td>\n",
       "      <td>The TIde (LP Version)</td>\n",
       "      <td>200</td>\n",
       "      <td>1543363420796</td>\n",
       "      <td>\"Mozilla/5.0 (Macintosh; Intel Mac OS X 10_9_4...</td>\n",
       "      <td>80</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Mogwai</td>\n",
       "      <td>Logged In</td>\n",
       "      <td>Tegan</td>\n",
       "      <td>F</td>\n",
       "      <td>67</td>\n",
       "      <td>Levine</td>\n",
       "      <td>571.19302</td>\n",
       "      <td>paid</td>\n",
       "      <td>Portland-South Portland, ME</td>\n",
       "      <td>PUT</td>\n",
       "      <td>NextSong</td>\n",
       "      <td>1.540794e+12</td>\n",
       "      <td>992</td>\n",
       "      <td>Two Rights Make One Wrong</td>\n",
       "      <td>200</td>\n",
       "      <td>1543363778796</td>\n",
       "      <td>\"Mozilla/5.0 (Macintosh; Intel Mac OS X 10_9_4...</td>\n",
       "      <td>80</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Spor</td>\n",
       "      <td>Logged In</td>\n",
       "      <td>Tegan</td>\n",
       "      <td>F</td>\n",
       "      <td>68</td>\n",
       "      <td>Levine</td>\n",
       "      <td>380.34240</td>\n",
       "      <td>paid</td>\n",
       "      <td>Portland-South Portland, ME</td>\n",
       "      <td>PUT</td>\n",
       "      <td>NextSong</td>\n",
       "      <td>1.540794e+12</td>\n",
       "      <td>992</td>\n",
       "      <td>Way Of The Samurai</td>\n",
       "      <td>200</td>\n",
       "      <td>1543364349796</td>\n",
       "      <td>\"Mozilla/5.0 (Macintosh; Intel Mac OS X 10_9_4...</td>\n",
       "      <td>80</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>DJ Dizzy</td>\n",
       "      <td>Logged In</td>\n",
       "      <td>Tegan</td>\n",
       "      <td>F</td>\n",
       "      <td>69</td>\n",
       "      <td>Levine</td>\n",
       "      <td>221.15220</td>\n",
       "      <td>paid</td>\n",
       "      <td>Portland-South Portland, ME</td>\n",
       "      <td>PUT</td>\n",
       "      <td>NextSong</td>\n",
       "      <td>1.540794e+12</td>\n",
       "      <td>992</td>\n",
       "      <td>Sexy Bitch</td>\n",
       "      <td>200</td>\n",
       "      <td>1543364729796</td>\n",
       "      <td>\"Mozilla/5.0 (Macintosh; Intel Mac OS X 10_9_4...</td>\n",
       "      <td>80</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                             artist       auth firstName gender  \\\n",
       "0  Mitch Ryder & The Detroit Wheels  Logged In     Tegan      F   \n",
       "1                  The Spill Canvas  Logged In     Tegan      F   \n",
       "2                            Mogwai  Logged In     Tegan      F   \n",
       "3                              Spor  Logged In     Tegan      F   \n",
       "4                          DJ Dizzy  Logged In     Tegan      F   \n",
       "\n",
       "   itemInSession lastName     length level                     location  \\\n",
       "0             65   Levine  205.03465  paid  Portland-South Portland, ME   \n",
       "1             66   Levine  358.03383  paid  Portland-South Portland, ME   \n",
       "2             67   Levine  571.19302  paid  Portland-South Portland, ME   \n",
       "3             68   Levine  380.34240  paid  Portland-South Portland, ME   \n",
       "4             69   Levine  221.15220  paid  Portland-South Portland, ME   \n",
       "\n",
       "  method      page  registration  sessionId                            song  \\\n",
       "0    PUT  NextSong  1.540794e+12        992  Jenny Take A Ride (LP Version)   \n",
       "1    PUT  NextSong  1.540794e+12        992           The TIde (LP Version)   \n",
       "2    PUT  NextSong  1.540794e+12        992       Two Rights Make One Wrong   \n",
       "3    PUT  NextSong  1.540794e+12        992              Way Of The Samurai   \n",
       "4    PUT  NextSong  1.540794e+12        992                      Sexy Bitch   \n",
       "\n",
       "   status             ts                                          userAgent  \\\n",
       "0     200  1543363215796  \"Mozilla/5.0 (Macintosh; Intel Mac OS X 10_9_4...   \n",
       "1     200  1543363420796  \"Mozilla/5.0 (Macintosh; Intel Mac OS X 10_9_4...   \n",
       "2     200  1543363778796  \"Mozilla/5.0 (Macintosh; Intel Mac OS X 10_9_4...   \n",
       "3     200  1543364349796  \"Mozilla/5.0 (Macintosh; Intel Mac OS X 10_9_4...   \n",
       "4     200  1543364729796  \"Mozilla/5.0 (Macintosh; Intel Mac OS X 10_9_4...   \n",
       "\n",
       "  userId  \n",
       "0     80  \n",
       "1     80  \n",
       "2     80  \n",
       "3     80  \n",
       "4     80  "
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df = df.loc[df['page'] == 'NextSong']\n",
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {
    "editable": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0   2018-11-28 00:00:15.796\n",
       "1   2018-11-28 00:03:40.796\n",
       "2   2018-11-28 00:09:38.796\n",
       "3   2018-11-28 00:19:09.796\n",
       "4   2018-11-28 00:25:29.796\n",
       "Name: ts, dtype: datetime64[ns]"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "t = pd.to_datetime(df['ts'], unit='ms')\n",
    "t.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {
    "editable": true
   },
   "outputs": [],
   "source": [
    "time_data = (t, t.dt.hour,  t.dt.day, t.dt.isocalendar().week, t.dt.month, t.dt.isocalendar().year, t.dt.isocalendar().day)\n",
    "column_labels = ('timestamp', 'hour', 'day', 'week of year', 'month', 'year', 'weekday')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {
    "editable": true
   },
   "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>timestamp</th>\n",
       "      <th>hour</th>\n",
       "      <th>day</th>\n",
       "      <th>week of year</th>\n",
       "      <th>month</th>\n",
       "      <th>year</th>\n",
       "      <th>weekday</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2018-11-28 00:00:15.796</td>\n",
       "      <td>0</td>\n",
       "      <td>28</td>\n",
       "      <td>48</td>\n",
       "      <td>11</td>\n",
       "      <td>2018</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2018-11-28 00:03:40.796</td>\n",
       "      <td>0</td>\n",
       "      <td>28</td>\n",
       "      <td>48</td>\n",
       "      <td>11</td>\n",
       "      <td>2018</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2018-11-28 00:09:38.796</td>\n",
       "      <td>0</td>\n",
       "      <td>28</td>\n",
       "      <td>48</td>\n",
       "      <td>11</td>\n",
       "      <td>2018</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2018-11-28 00:19:09.796</td>\n",
       "      <td>0</td>\n",
       "      <td>28</td>\n",
       "      <td>48</td>\n",
       "      <td>11</td>\n",
       "      <td>2018</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2018-11-28 00:25:29.796</td>\n",
       "      <td>0</td>\n",
       "      <td>28</td>\n",
       "      <td>48</td>\n",
       "      <td>11</td>\n",
       "      <td>2018</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                timestamp  hour  day  week of year  month  year  weekday\n",
       "0 2018-11-28 00:00:15.796     0   28            48     11  2018        3\n",
       "1 2018-11-28 00:03:40.796     0   28            48     11  2018        3\n",
       "2 2018-11-28 00:09:38.796     0   28            48     11  2018        3\n",
       "3 2018-11-28 00:19:09.796     0   28            48     11  2018        3\n",
       "4 2018-11-28 00:25:29.796     0   28            48     11  2018        3"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "time_df = pd.DataFrame(dict(zip(column_labels, time_data)))\n",
    "time_df.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "editable": true
   },
   "source": [
    "#### Insert Records into Time Table\n",
    "Implement the `time_table_insert` query in `sql_queries.py` and run the cell below to insert records for the timestamps in this log file into the `time` table. Remember to run `create_tables.py` before running the cell below to ensure you've created/resetted the `time` table in the sparkify database."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {
    "editable": true
   },
   "outputs": [],
   "source": [
    "for i, row in time_df.iterrows():\n",
    "    cur.execute(time_table_insert, list(row))\n",
    "    conn.commit()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "editable": true
   },
   "source": [
    "Run `test.ipynb` to see if you've successfully added records to this table."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "editable": true
   },
   "source": [
    "## #4: `users` Table\n",
    "#### Extract Data for Users Table\n",
    "- Select columns for user ID, first name, last name, gender and level and set to `user_df`"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {
    "editable": true
   },
   "outputs": [],
   "source": [
    "user_df = df.loc[:, ['userId', 'firstName', 'lastName', 'gender', 'level']]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "editable": true
   },
   "source": [
    "#### Insert Records into Users Table\n",
    "Implement the `user_table_insert` query in `sql_queries.py` and run the cell below to insert records for the users in this log file into the `users` table. Remember to run `create_tables.py` before running the cell below to ensure you've created/resetted the `users` table in the sparkify database."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {
    "editable": true
   },
   "outputs": [],
   "source": [
    "for i, row in user_df.iterrows():\n",
    "    cur.execute(user_table_insert, row)\n",
    "    conn.commit()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "editable": true
   },
   "source": [
    "Run `test.ipynb` to see if you've successfully added records to this table."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "editable": true
   },
   "source": [
    "## #5: `songplays` Table\n",
    "#### Extract Data and Songplays Table\n",
    "This one is a little more complicated since information from the songs table, artists table, and original log file are all needed for the `songplays` table. Since the log file does not specify an ID for either the song or the artist, you'll need to get the song ID and artist ID by querying the songs and artists tables to find matches based on song title, artist name, and song duration time.\n",
    "- Implement the `song_select` query in `sql_queries.py` to find the song ID and artist ID based on the title, artist name, and duration of a song.\n",
    "- Select the timestamp, user ID, level, song ID, artist ID, session ID, location, and user agent and set to `songplay_data`\n",
    "\n",
    "#### Insert Records into Songplays Table\n",
    "- Implement the `songplay_table_insert` query and run the cell below to insert records for the songplay actions in this log file into the `songplays` table. Remember to run `create_tables.py` before running the cell below to ensure you've created/resetted the `songplays` table in the sparkify database."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {
    "editable": true
   },
   "outputs": [],
   "source": [
    "for index, row in df.iterrows():\n",
    "\n",
    "    # get songid and artistid from song and artist tables\n",
    "    cur.execute(song_select, (row.song, row.artist, row.length))\n",
    "    results = cur.fetchone()\n",
    "    \n",
    "    if results:\n",
    "        songid, artistid = results\n",
    "    else:\n",
    "        songid, artistid = None, None\n",
    "\n",
    "    # insert songplay record\n",
    "    \n",
    "    songplay_data = (pd.to_datetime(row.ts, unit='ms'), row.userId, row.level, songid, artistid, row.sessionId, row.location, row.userAgent)\n",
    "    cur.execute(songplay_table_insert, songplay_data)\n",
    "    conn.commit()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "editable": true
   },
   "source": [
    "Run `test.ipynb` to see if you've successfully added records to this table."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "editable": true
   },
   "source": [
    "# Close Connection to Sparkify Database"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {
    "editable": true
   },
   "outputs": [],
   "source": [
    "conn.close()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "editable": true
   },
   "source": [
    "# Implement `etl.py`\n",
    "Use what you've completed in this notebook to implement `etl.py`."
   ]
  }
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