1. data.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Data prep"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 227,
   "metadata": {},
   "outputs": [],
   "source": [
    "from spark_session_manager import SparkSessionManager\n",
    "\n",
    "spark = SparkSessionManager.get_spark_session()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 228,
   "metadata": {},
   "outputs": [],
   "source": [
    "# schema for csv file\n",
    "\n",
    "from pyspark.sql.types import StructType, StructField, StringType, IntegerType, BooleanType\n",
    "from pyspark.sql.functions import monotonically_increasing_id\n",
    "\n",
    "schema = StructType([\n",
    "    StructField(\"video_id\", StringType(), True),\n",
    "    StructField(\"title\", StringType(), True),\n",
    "    StructField(\"publishedAt\", StringType(), True),\n",
    "    StructField(\"channelId\", StringType(), True),\n",
    "    StructField(\"channelTitle\", StringType(), True),\n",
    "    StructField(\"categoryId\", StringType(), True),\n",
    "    StructField(\"trending_date\", StringType(), True),\n",
    "    StructField(\"tags\", StringType(), True),\n",
    "    StructField(\"view_count\", IntegerType(), True),\n",
    "    StructField(\"likes\", IntegerType(), True),\n",
    "    StructField(\"dislikes\", IntegerType(), True),\n",
    "    StructField(\"comment_count\", IntegerType(), True),\n",
    "    StructField(\"thumbnail_link\", StringType(), True),\n",
    "    StructField(\"comments_disabled\", BooleanType(), True),\n",
    "    StructField(\"ratings_disabled\", BooleanType(), True),\n",
    "    StructField(\"description\", StringType(), True)\n",
    "])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 229,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "+---+-----------+--------------------+--------------------+--------------------+--------------------+----------+--------------------+--------------------+----------+------+--------+-------------+--------------------+-----------------+----------------+--------------------+\n",
      "| id|   video_id|               title|         publishedAt|           channelId|        channelTitle|categoryId|       trending_date|                tags|view_count| likes|dislikes|comment_count|      thumbnail_link|comments_disabled|ratings_disabled|         description|\n",
      "+---+-----------+--------------------+--------------------+--------------------+--------------------+----------+--------------------+--------------------+----------+------+--------+-------------+--------------------+-----------------+----------------+--------------------+\n",
      "|  0|3C66w5Z0ixs|I ASKED HER TO BE...|2020-08-11T19:20:14Z|UCvtRTOMP2TqYqu51...|            Brawadis|        22|2020-08-12T00:00:00Z|brawadis|prank|ba...|   1514614|156908|    5855|        35313|https://i.ytimg.c...|            false|           false|SUBSCRIBE to BRAW...|\n",
      "|  1|M9Pmf9AB4Mo|Apex Legends | St...|2020-08-11T17:00:10Z|UC0ZV6M2THA81QT9h...|        Apex Legends|        20|2020-08-12T00:00:00Z|Apex Legends|Apex...|   2381688|146739|    2794|        16549|https://i.ytimg.c...|            false|           false|While running her...|\n",
      "|  2|J78aPJ3VyNs|I left youtube fo...|2020-08-11T16:34:06Z|UCYzPXprvl5Y-Sf0g...|       jacksepticeye|        24|2020-08-12T00:00:00Z|jacksepticeye|fun...|   2038853|353787|    2628|        40221|https://i.ytimg.c...|            false|           false|I left youtube fo...|\n",
      "|  3|kXLn3HkpjaA|XXL 2020 Freshman...|2020-08-11T16:38:55Z|UCbg_UMjlHJg_19SZ...|                 XXL|        10|2020-08-12T00:00:00Z|xxl freshman|xxl ...|    496771| 23251|    1856|         7647|https://i.ytimg.c...|            false|           false|Subscribe to XXL ...|\n",
      "|  4|VIUo6yapDbc|Ultimate DIY Home...|2020-08-11T15:10:05Z|UCDVPcEbVLQgLZX0R...|            Mr. Kate|        26|2020-08-12T00:00:00Z|The LaBrant Famil...|   1123889| 45802|     964|         2196|https://i.ytimg.c...|            false|           false|Transforming The ...|\n",
      "|  5|w-aidBdvZo8|I Haven't Been Ho...|2020-08-11T20:00:04Z|UC5zJwsFtEs9WYe3A...|      Professor Live|        24|2020-08-12T00:00:00Z|Professor injury|...|    949491| 77487|     746|         7506|https://i.ytimg.c...|            false|           false|Subscribe To My C...|\n",
      "|  6|uet14uf9NsE|OUR FIRST FAMILY ...|2020-08-12T00:17:41Z|UCDSJCBYqL7VQrlXf...|       Les Do Makeup|        26|2020-08-12T00:00:00Z|              [None]|    470446| 47990|     440|         4558|https://i.ytimg.c...|            false|           false|Hi babygirls!  Th...|\n",
      "|  7|ua4QMFQATco|  CGP Grey was WRONG|2020-08-11T17:15:11Z|UC2C_jShtL725hvbm...|            CGP Grey|        27|2020-08-12T00:00:00Z|cgpgrey|education...|   1050143| 89190|     854|         6455|https://i.ytimg.c...|            false|           false|‣ What Was TEKOI:...|\n",
      "|  8|SnsPZj91R7E|SURPRISING MY DAD...|2020-08-10T22:26:59Z|UCZDdF_p-L88NWVpz...|        Louie's Life|        24|2020-08-12T00:00:00Z|surprising|dad|fa...|   1402687| 95694|    2158|         6613|https://i.ytimg.c...|            false|           false|Since I was littl...|\n",
      "|  9|SsWHMAhshPQ|Ovi x Natanael Ca...|2020-08-11T23:00:10Z|UC648rgJOboZlgcDb...|      Rancho Humilde|        10|2020-08-12T00:00:00Z|Vengo De Nada|Ale...|    741028|113983|    4373|         5618|https://i.ytimg.c...|            false|           false|Vengo De Nada - O...|\n",
      "| 10|49Z6Mv4_WCA|i don't know what...|2020-08-11T20:24:34Z|UCtinbF-Q-fVthA0q...|        CaseyNeistat|        22|2020-08-12T00:00:00Z|              [None]|    940036| 87111|    1860|         7052|https://i.ytimg.c...|            false|           false|ssend love to my ...|\n",
      "| 11|nt3VVyv5pxQ|Try Not To Laugh ...|2020-08-11T17:00:31Z|UCYJPby9DRCteedh5...|           Smosh Pit|        22|2020-08-12T00:00:00Z|smosh|smosh pit|s...|    591837| 44168|     409|         2652|https://i.ytimg.c...|            false|           false|You know what tim...|\n",
      "| 12|I6hswz4rIrU|Rainbow Six Siege...|2020-08-11T17:13:53Z|UCBMvc6jvuTxH6TNo...|Ubisoft North Ame...|        20|2020-08-12T00:00:00Z|R6|R6S|Siege|New ...|    320872| 14288|     774|         2085|https://i.ytimg.c...|            false|           false|“Prepare. Execute...|\n",
      "| 13|W7VK4DUHvKU|Lil Yachty & Futu...|2020-08-11T19:00:10Z|UC1X3TRsCt36QPjF1...|       LilYachtyVEVO|        10|2020-08-12T00:00:00Z|Lil Yachty|Lil Bo...|    413372| 26440|     293|         1495|https://i.ytimg.c...|            false|           false|Watch the officia...|\n",
      "| 14|W9Aen8hG20Y|When Our Generati...|2020-08-10T22:33:48Z|UCR9NuNwCUIhMOLUQ...|           Kyle Exum|        23|2020-08-12T00:00:00Z|When Our Generati...|    921261|124183|    1678|        16460|https://i.ytimg.c...|            false|           false|500,000 Likes and...|\n",
      "| 15|BNeDH6UTmXw|Ten Minutes with ...|2020-08-11T22:00:05Z|UCMw7m-ScQ6jV1FQz...|       Tyler Cameron|        22|2020-08-12T00:00:00Z|the bachelor|the ...|    105955|  4511|      69|          673|https://i.ytimg.c...|            false|           false|Come hang out me ...|\n",
      "| 16|6TIsR_7nrNc|Kylie Jenner Reac...|2020-08-10T18:41:19Z|UC2rJLq19N0dGrxfi...|       HollywoodLife|        24|2020-08-12T00:00:00Z|kylie jenner|kend...|   1007540| 10102|    7932|         2763|https://i.ytimg.c...|            false|           false|Kylie Jenner diss...|\n",
      "| 17|gPdUslndvVI|Our Farm Got Dest...|2020-08-11T23:00:06Z|UCuxlXCfVyV-i5YLL...|   Cole The Cornstar|        22|2020-08-12T00:00:00Z|farming|family fa...|    277338| 37533|     197|         3666|https://i.ytimg.c...|            false|           false|Wind storm, rain,...|\n",
      "| 18|GTp-0S82guE|      Time to Talk..|2020-08-11T12:04:40Z|UCCgLoMYIyP0U56dE...|          Chloe Ting|        26|2020-08-12T00:00:00Z|chloe ting|chloet...|   1648441|130147|    1425|        15773|https://i.ytimg.c...|            false|           false|I talked about so...|\n",
      "| 19|jbGRowa5tIk|ITZY “Not Shy” M/...|2020-08-11T15:00:13Z|UCaO6TYtlC8U5ttz6...|   JYP Entertainment|        10|2020-08-12T00:00:00Z|JYP Entertainment...|   5999732|714287|   15174|        31039|https://i.ytimg.c...|            false|           false|ITZY Not Shy M/V[...|\n",
      "+---+-----------+--------------------+--------------------+--------------------+--------------------+----------+--------------------+--------------------+----------+------+--------+-------------+--------------------+-----------------+----------------+--------------------+\n",
      "only showing top 20 rows\n",
      "\n"
     ]
    }
   ],
   "source": [
    "file_path = 'data/US_youtube_trending_data.csv'  # Adjust the path accordingly\n",
    "\n",
    "# Load your dataset into a Spark DataFrame\n",
    "df = spark.read.csv(file_path, header=True, schema=schema, escape='\"', quote='\"', multiLine=True)\n",
    "\n",
    "# add unique id column (at the beginning of the DataFrame)\n",
    "df = df.withColumn(\"id\", monotonically_increasing_id())\n",
    "\n",
    "# set the id column as the first column and index\n",
    "df = df.select(\"id\", *df.columns[:-1])\n",
    "\n",
    "df.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 230,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "root\n",
      " |-- id: long (nullable = false)\n",
      " |-- video_id: string (nullable = true)\n",
      " |-- title: string (nullable = true)\n",
      " |-- publishedAt: string (nullable = true)\n",
      " |-- channelId: string (nullable = true)\n",
      " |-- channelTitle: string (nullable = true)\n",
      " |-- categoryId: string (nullable = true)\n",
      " |-- trending_date: string (nullable = true)\n",
      " |-- tags: string (nullable = true)\n",
      " |-- view_count: integer (nullable = true)\n",
      " |-- likes: integer (nullable = true)\n",
      " |-- dislikes: integer (nullable = true)\n",
      " |-- comment_count: integer (nullable = true)\n",
      " |-- thumbnail_link: string (nullable = true)\n",
      " |-- comments_disabled: boolean (nullable = true)\n",
      " |-- ratings_disabled: boolean (nullable = true)\n",
      " |-- description: string (nullable = true)\n",
      "\n",
      "+---+-----------+--------------------+--------------------+--------------------+-------------+----------+--------------------+--------------------+----------+------+--------+-------------+--------------------+-----------------+----------------+--------------------+\n",
      "| id|   video_id|               title|         publishedAt|           channelId| channelTitle|categoryId|       trending_date|                tags|view_count| likes|dislikes|comment_count|      thumbnail_link|comments_disabled|ratings_disabled|         description|\n",
      "+---+-----------+--------------------+--------------------+--------------------+-------------+----------+--------------------+--------------------+----------+------+--------+-------------+--------------------+-----------------+----------------+--------------------+\n",
      "|  0|3C66w5Z0ixs|I ASKED HER TO BE...|2020-08-11T19:20:14Z|UCvtRTOMP2TqYqu51...|     Brawadis|        22|2020-08-12T00:00:00Z|brawadis|prank|ba...|   1514614|156908|    5855|        35313|https://i.ytimg.c...|            false|           false|SUBSCRIBE to BRAW...|\n",
      "|  1|M9Pmf9AB4Mo|Apex Legends | St...|2020-08-11T17:00:10Z|UC0ZV6M2THA81QT9h...| Apex Legends|        20|2020-08-12T00:00:00Z|Apex Legends|Apex...|   2381688|146739|    2794|        16549|https://i.ytimg.c...|            false|           false|While running her...|\n",
      "|  2|J78aPJ3VyNs|I left youtube fo...|2020-08-11T16:34:06Z|UCYzPXprvl5Y-Sf0g...|jacksepticeye|        24|2020-08-12T00:00:00Z|jacksepticeye|fun...|   2038853|353787|    2628|        40221|https://i.ytimg.c...|            false|           false|I left youtube fo...|\n",
      "|  3|kXLn3HkpjaA|XXL 2020 Freshman...|2020-08-11T16:38:55Z|UCbg_UMjlHJg_19SZ...|          XXL|        10|2020-08-12T00:00:00Z|xxl freshman|xxl ...|    496771| 23251|    1856|         7647|https://i.ytimg.c...|            false|           false|Subscribe to XXL ...|\n",
      "|  4|VIUo6yapDbc|Ultimate DIY Home...|2020-08-11T15:10:05Z|UCDVPcEbVLQgLZX0R...|     Mr. Kate|        26|2020-08-12T00:00:00Z|The LaBrant Famil...|   1123889| 45802|     964|         2196|https://i.ytimg.c...|            false|           false|Transforming The ...|\n",
      "+---+-----------+--------------------+--------------------+--------------------+-------------+----------+--------------------+--------------------+----------+------+--------+-------------+--------------------+-----------------+----------------+--------------------+\n",
      "only showing top 5 rows\n",
      "\n"
     ]
    }
   ],
   "source": [
    "# Print the schema of the DataFrame\n",
    "df.printSchema()\n",
    "\n",
    "# Show the first few rows of the DataFrame\n",
    "df.show(5)\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Data Type Conversion"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 231,
   "metadata": {},
   "outputs": [],
   "source": [
    "from pyspark.sql.functions import col\n",
    "\n",
    "# List of columns to convert from string to integer\n",
    "columns_to_convert = ['view_count', 'likes', 'dislikes', 'comment_count']\n",
    "\n",
    "# Convert columns\n",
    "for column in columns_to_convert:\n",
    "    df = df.withColumn(column, col(column).cast('int'))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Date Formatting"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 232,
   "metadata": {},
   "outputs": [],
   "source": [
    "# from pyspark.sql.functions import to_date\n",
    "\n",
    "# # Convert date columns to date type\n",
    "# df = df.withColumn(\"publishedAt\", to_date(col(\"publishedAt\"), \"yyyy-MM-dd'T'HH:mm:ss'Z'\"))\n",
    "# df = df.withColumn(\"trending_date\", to_date(col(\"trending_date\"), \"yyyy-MM-dd\"))\n",
    "\n",
    "# # Show the first few rows of the DataFrame\n",
    "# df.show(5)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Handling Missing Values"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 233,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Drop rows with any missing values\n",
    "df_cleaned = df.na.drop()\n",
    "\n",
    "# Or fill missing values with a default value\n",
    "df_filled = df.na.fill({\"likes\": 0, \"dislikes\": 0, \"comment_count\": 0})  # Example for numeric columns\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 234,
   "metadata": {},
   "outputs": [],
   "source": [
    "from style.chart_defaults import *"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Videos data (unique videos)\n",
    "- single video data (to avoid duplicates)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 235,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "[Stage 380:>                                                        (0 + 1) / 1]\r"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "+-----------+----------------------+--------------------+--------------------+--------------------+----------+--------------------+-----------------+----------------+--------------------+\n",
      "|   video_id|                 title|         publishedAt|           channelId|        channelTitle|categoryId|      thumbnail_link|comments_disabled|ratings_disabled|         description|\n",
      "+-----------+----------------------+--------------------+--------------------+--------------------+----------+--------------------+-----------------+----------------+--------------------+\n",
      "|--14w5SOEUs|     Migos - Avalanche|2021-06-10T16:00:00Z|UCGIelM2Dj3zza3xy...|           MigosVEVO|        10|https://i.ytimg.c...|            false|           false|Music video by Mi...|\n",
      "|--2O86Z0hsM|  MY TESLA PAYS FOR...|2022-03-09T23:19:08Z|UCXJEvxZSozjAAqhb...|             jf.okay|        24|https://i.ytimg.c...|            false|           false|                NULL|\n",
      "|--40TEbZ9Is|  Supporting Actres...|2021-09-20T01:03:32Z|UClBKH8yZRcM4AsRj...|  Television Academy|        24|https://i.ytimg.c...|            false|           false|Hannah Waddingham...|\n",
      "|--47FjCWgrU|  San Francisco 49e...|2023-12-18T00:21:58Z|UCDVYQ4Zhbm3S2dlz...|                 NFL|        17|https://i.ytimg.c...|            false|           false|Check out our oth...|\n",
      "|--5-brQiQFg|  Washington Comman...|2022-12-25T00:30:17Z|UCDVYQ4Zhbm3S2dlz...|                 NFL|        17|https://i.ytimg.c...|            false|           false|Check out our oth...|\n",
      "|--DKkzWVh-E|  Why Retaining Wal...|2021-12-07T13:00:00Z|UCMOqf8ab-42UUQId...|Practical Enginee...|        27|https://i.ytimg.c...|            false|           false|One of the most i...|\n",
      "|--FmExEAsM8|IVE 아이브 'ELEVEN' MV|2021-12-01T09:00:03Z|UCYDmx2Sfpnaxg488...|          starshipTV|        10|https://i.ytimg.c...|            false|           false|IVE Twitter: http...|\n",
      "|--SvHNpSvpk|  YoungBoy Never Br...|2020-09-11T15:00:00Z|UClW4jraMKz6Qj69l...|YoungBoy Never Br...|        10|https://i.ytimg.c...|            false|           false|YoungBoy Never Br...|\n",
      "|--gJDs10ShA|  what happens if y...|2022-06-16T01:11:59Z|UC_54BddY_xCboN2k...|   Hydraulic Beanbag|         1|https://i.ytimg.c...|            false|           false|today was suppose...|\n",
      "|--hjHKgm67g|  The Third Attempt...|2022-04-07T19:14:45Z|UC6I0KzAD7uFTL1qz...|    Blacktail Studio|        26|https://i.ytimg.c...|            false|           false|I tried to make t...|\n",
      "+-----------+----------------------+--------------------+--------------------+--------------------+----------+--------------------+-----------------+----------------+--------------------+\n",
      "only showing top 10 rows\n",
      "\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "                                                                                \r"
     ]
    }
   ],
   "source": [
    "unique_columns = [\n",
    "    \"video_id\", \"title\", \"publishedAt\", \"channelId\", \n",
    "    \"channelTitle\", \"categoryId\", \"thumbnail_link\", \n",
    "    \"comments_disabled\", \"ratings_disabled\", \"description\"\n",
    "]\n",
    "\n",
    "# Drop duplicates based on these columns\n",
    "video_data = df.dropDuplicates(subset=['video_id'])\n",
    "\n",
    "# select only the columns of interest\n",
    "video_data = video_data.select(\n",
    "    # columns in unique_columns list\n",
    "    *unique_columns)\n",
    "\n",
    "# show top 10, video_id asc\n",
    "video_data.orderBy(\"video_id\").show(10)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 236,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "24/04/23 22:42:55 WARN MemoryManager: Total allocation exceeds 95.00% (1,020,054,720 bytes) of heap memory\n",
      "Scaling row group sizes to 95.00% for 8 writers\n",
      "24/04/23 22:42:55 WARN MemoryManager: Total allocation exceeds 95.00% (1,020,054,720 bytes) of heap memory\n",
      "Scaling row group sizes to 84.44% for 9 writers\n",
      "24/04/23 22:42:55 WARN MemoryManager: Total allocation exceeds 95.00% (1,020,054,720 bytes) of heap memory\n",
      "Scaling row group sizes to 76.00% for 10 writers\n",
      "24/04/23 22:42:55 WARN MemoryManager: Total allocation exceeds 95.00% (1,020,054,720 bytes) of heap memory\n",
      "Scaling row group sizes to 69.09% for 11 writers\n",
      "24/04/23 22:42:55 WARN MemoryManager: Total allocation exceeds 95.00% (1,020,054,720 bytes) of heap memory\n",
      "Scaling row group sizes to 63.33% for 12 writers\n",
      "24/04/23 22:42:55 WARN MemoryManager: Total allocation exceeds 95.00% (1,020,054,720 bytes) of heap memory\n",
      "Scaling row group sizes to 69.09% for 11 writers\n",
      "24/04/23 22:42:55 WARN MemoryManager: Total allocation exceeds 95.00% (1,020,054,720 bytes) of heap memory\n",
      "Scaling row group sizes to 76.00% for 10 writers\n",
      "24/04/23 22:42:55 WARN MemoryManager: Total allocation exceeds 95.00% (1,020,054,720 bytes) of heap memory\n",
      "Scaling row group sizes to 84.44% for 9 writers\n",
      "24/04/23 22:42:55 WARN MemoryManager: Total allocation exceeds 95.00% (1,020,054,720 bytes) of heap memory\n",
      "Scaling row group sizes to 95.00% for 8 writers\n",
      "                                                                                \r"
     ]
    }
   ],
   "source": [
    "# save metadata\n",
    "video_data.write.mode(\"overwrite\").parquet(\"data/processed/metadata.parquet\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Add category names"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "specify schema"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 237,
   "metadata": {},
   "outputs": [],
   "source": [
    "from pyspark.sql.types import StructType, StructField, StringType, ArrayType\n",
    "from pyspark.sql.functions import explode\n",
    "\n",
    "schema = StructType([\n",
    "    StructField(\"items\", ArrayType(StructType([\n",
    "        StructField(\"id\", StringType(), True),\n",
    "        StructField(\"snippet\", StructType([\n",
    "            StructField(\"title\", StringType(), True),\n",
    "            StructField(\"assignable\", StringType(), True),\n",
    "            StructField(\"channelId\", StringType(), True)\n",
    "        ]), True)\n",
    "    ])), True)\n",
    "])\n",
    "\n",
    "category_json_df = spark.read.schema(schema).json(\"data/US_category_id.json\")\n",
    "category_df = category_json_df.select(explode(\"items\").alias(\"category_item\"))\n",
    "category_df = category_df.select(\n",
    "    \"category_item.id\",\n",
    "    \"category_item.snippet.title\"\n",
    ")\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "read json file"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 238,
   "metadata": {},
   "outputs": [],
   "source": [
    "category_json_df = spark.read.option(\"multiline\", \"true\").json(\"data/US_category_id.json\")\n",
    "\n",
    "category_df = category_json_df.select(explode(\"items\").alias(\"category_item\"))\n",
    "category_df = category_df.select(\n",
    "    col(\"category_item.id\").alias(\"categoryId\"),\n",
    "    col(\"category_item.snippet.title\").alias(\"categoryTitle\")\n",
    ")\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "convert categoryid type"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 239,
   "metadata": {},
   "outputs": [],
   "source": [
    "df = df.withColumn(\"categoryId\", col(\"categoryId\").cast(\"string\"))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "join dfs"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 240,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "+-----------+--------------------+--------------+\n",
      "|   video_id|               title| categoryTitle|\n",
      "+-----------+--------------------+--------------+\n",
      "|3C66w5Z0ixs|I ASKED HER TO BE...|People & Blogs|\n",
      "|M9Pmf9AB4Mo|Apex Legends | St...|        Gaming|\n",
      "|J78aPJ3VyNs|I left youtube fo...| Entertainment|\n",
      "|kXLn3HkpjaA|XXL 2020 Freshman...|         Music|\n",
      "|VIUo6yapDbc|Ultimate DIY Home...| Howto & Style|\n",
      "+-----------+--------------------+--------------+\n",
      "only showing top 5 rows\n",
      "\n"
     ]
    }
   ],
   "source": [
    "# Perform the join\n",
    "df = df.join(category_df, on=\"categoryId\", how=\"left\")\n",
    "\n",
    "# Show some results to verify the join worked as expected\n",
    "df.select(\"video_id\", \"title\", \"categoryTitle\").show(5)\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Engagement"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Engagement data (original variables)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 242,
   "metadata": {},
   "outputs": [],
   "source": [
    "# # subset for engagement variables -> likes, dislikes, comment_count, view_count\n",
    "\n",
    "# engagement_df = df.select(\"video_id\", \"likes\", \"dislikes\", \"comment_count\", \"view_count\")\n",
    "\n",
    "# # save as parquet\n",
    "# engagement_df.write.mode(\"overwrite\").parquet(\"data/processed/engagement_data.parquet\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Engagement metrics"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "a lot of values in column dislikes are '0', thus eng. metrics will not use it"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "- view_to_like_ratio = view_count / likes\n",
    "- like_to_comment_ratio = likes / comment_count\n",
    "- engagement_rate = ((likes + comment_count) / view_count) * 100\n",
    "- comments_per_view = comment_count / view_count"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 243,
   "metadata": {},
   "outputs": [],
   "source": [
    "# introduce engagement metrics\n",
    "\n",
    "from pyspark.sql import functions as F\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### introduce eng. metrics"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 244,
   "metadata": {},
   "outputs": [],
   "source": [
    "df = df.withColumn(\"view_to_like_ratio\", F.col(\"view_count\") / F.col(\"likes\")) \\\n",
    "    .withColumn(\"like_to_comment_ratio\", F.col(\"likes\") / F.col(\"comment_count\")) \\\n",
    "    .withColumn(\"engagement_rate\", ((F.col(\"likes\") + F.col(\"comment_count\")) / F.col(\"view_count\")) * 100) \\\n",
    "    .withColumn(\"comments_per_view\", F.col(\"comment_count\") / F.col(\"view_count\")) \\\n",
    "    .withColumn(\"average_views_per_day\", F.col(\"view_count\") / F.datediff(F.col(\"trending_date\"), F.col(\"publishedAt\")))\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 245,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "+----------+---+-----------+------------------------------------------------------------+--------------------+------------------------+-------------+--------------------+----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+----------+------+--------+-------------+----------------------------------------------+-----------------+----------------+---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+--------------+------------------+---------------------+-----------------+--------------------+---------------------+\n",
      "|categoryId|id |video_id   |title                                                       |publishedAt         |channelId               |channelTitle |trending_date       |tags                                                                                                                                                                                                                                                                                                                                                                                                                                                            |view_count|likes |dislikes|comment_count|thumbnail_link                                |comments_disabled|ratings_disabled|description                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                  |categoryTitle |view_to_like_ratio|like_to_comment_ratio|engagement_rate  |comments_per_view   |average_views_per_day|\n",
      "+----------+---+-----------+------------------------------------------------------------+--------------------+------------------------+-------------+--------------------+----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+----------+------+--------+-------------+----------------------------------------------+-----------------+----------------+---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+--------------+------------------+---------------------+-----------------+--------------------+---------------------+\n",
      "|22        |0  |3C66w5Z0ixs|I ASKED HER TO BE MY GIRLFRIEND...                          |2020-08-11T19:20:14Z|UCvtRTOMP2TqYqu51xNrqAzg|Brawadis     |2020-08-12T00:00:00Z|brawadis|prank|basketball|skits|ghost|funny videos|vlog|vlogging|NBA|browadis|challenges|bmw i8|faze rug|faze rug brother|mama rug and papa rug                                                                                                                                                                                                                                                                                                                 |1514614   |156908|5855    |35313        |https://i.ytimg.com/vi/3C66w5Z0ixs/default.jpg|false            |false           |SUBSCRIBE to BRAWADIS ▶ http://bit.ly/SubscribeToBrawadis\\r\\rFOLLOW ME ON SOCIAL\\r▶ Twitter: https://twitter.com/Brawadis\\r▶ Instagram: https://www.instagram.com/brawadis/\\r▶ Snapchat: brawadis\\r\\rHi! I’m Brandon Awadis and I like to make dope vlogs, pranks, reactions, challenges and basketball videos. Don’t forget to subscribe and come be a part of the BrawadSquad!                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                             |People & Blogs|9.652879394294747 |4.443349474697704    |12.69108829048193|0.023314851176603413|1514614.0            |\n",
      "|20        |1  |M9Pmf9AB4Mo|Apex Legends | Stories from the Outlands – “The Endorsement”|2020-08-11T17:00:10Z|UC0ZV6M2THA81QT9hrVWJG3A|Apex Legends |2020-08-12T00:00:00Z|Apex Legends|Apex Legends characters|new Apex Legend|Apex Legends Rampart|Apex Legends Season 6|Apex Legends Boosted|Battle Pass|Season 6 Battle Pass|Apex Legends new season|Apex Legends game|Respawn Apex Legends|Battle Royale game|Battle Royale|Battle Royale shooter|Apex Games|squad play|multiplayer shooter|Apex Legends PS4|Apex Legends Xbox|Apex Legends PC|Apex Legends Origin|Respawn Entertainment|Electronic Arts|Titanfall 2|fun battle royale|2381688   |146739|2794    |16549        |https://i.ytimg.com/vi/M9Pmf9AB4Mo/default.jpg|false            |false           |While running her own modding shop, Ramya Parekh (aka Rampart) built her rep in underground gauntlet circuits. But success has a way of making enemies. Good thing she knows how to use all those fancy weapons she’s upgraded…  Apex Legends™ is a free-to-play battle royale game where legendary characters battle for glory, fame, and fortune on the fringes of the Frontier. Play for free now on Xbox One, PS4, and Origin for PC. Learn more about Apex Legends Season 6 – Boosted: http://x.ea.com/64060 Check out our YouTube channel: http://x.ea.com/56710.Follow us on Twitter: https://twitter.com/playapex.Follow us on Instagram: https://www.instagram.com/playapex/.#MeetRampart #ApexSeason6 #ApexSeasonSix #ApexLegends                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                  |Gaming        |16.230777094024084|8.866940600640522    |6.855977777105986|0.006948433212074797|2381688.0            |\n",
      "|24        |2  |J78aPJ3VyNs|I left youtube for a month and THIS is what happened.       |2020-08-11T16:34:06Z|UCYzPXprvl5Y-Sf0g4vX-m6g|jacksepticeye|2020-08-12T00:00:00Z|jacksepticeye|funny|funny meme|memes|jacksepticeye memes|reddit|subreddit|community|community memes|community subreddit|jacksepticeye subreddit|reddit memes|fan submitted|spicy memes|funny pics|reaction|react|green screen|funny memes|funny green screen|dank memes|memes compilation|try not to laugh|meme|fresh memes|meme review|funny moments|bell memes|bell of meme|jacksepticeye bell                                                                |2038853   |353787|2628    |40221        |https://i.ytimg.com/vi/J78aPJ3VyNs/default.jpg|false            |false           |I left youtube for a month and this is what happenedMY COFFEE COMPANY: https://twitter.com/TOTMCoffeeJoin the subreddit: https://www.reddit.com/r/jacksepticeye/MORE MEMES ► https://www.youtube.com/watch?v=wGdn6ldQTTg&list=PLMBYlcH3smRxmCZzsUyrxB0IyKSQAU0pPJacksepticeye's Funniest Home Videos: https://www.youtube.com/watch?v=VqfLcdpBasY&list=PLMBYlcH3smRxOk7Cp_V2ar3QDfvljWvSyEdited by: https://twitter.com/DaveDelirious►Twitter : https://twitter.com/Jack_Septic_Eye►Instagram: http://instagram.com/jacksepticeye                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                            |Entertainment |5.762939282675735 |8.796076676363095    |19.32498321360098|0.01972726822384939 |2038853.0            |\n",
      "|10        |3  |kXLn3HkpjaA|XXL 2020 Freshman Class Revealed - Official Announcement    |2020-08-11T16:38:55Z|UCbg_UMjlHJg_19SZckaKajg|XXL          |2020-08-12T00:00:00Z|xxl freshman|xxl freshmen|2020 xxl freshman|2020 freshman|2020 freshmen|xxl freshman class|2020 xxl freshman class|NLE Choppa|Polo G|Chika|Baby Keem|Mulatto|Jack Harlow|Rod Wave|Lil Tjay|Calboy|Fivio Foreign|Lil Keed|24kGoldn|rapper|rap|hip-hop|music                                                                                                                                                                                                      |496771    |23251 |1856    |7647         |https://i.ytimg.com/vi/kXLn3HkpjaA/default.jpg|false            |false           |Subscribe to XXL → http://bit.ly/subscribe-xxl \\rXXL presents the 2020 XXL Freshman Class featuring NLE Choppa, Polo G, Chika, Baby Keem, Mulatto, Jack Harlow, Rod Wave, Lil Tjay, Calboy, Fivio Foreign, Lil Keed and 10th Spot winner 24kGoldn. Visit the 2020 XXL Freshman Class website → https://www.xxlmag.com/freshman/Credits:Directed by @travissattenProduced by @ritemediagroupMagazine cover shot by Travis ShinnCover collage and lettering created by @rich_tuBeat for video produced by Jetsonmade, Neeko Baby and 1st Class#XXLFreshman #XXLFreshman #HipHop #XXLFreshmanClass #XXLFreshmanCover\\rGo here → http://www.xxlmag.com/\\rXXL on Facebook → https://www.facebook.com/xxlmag\\rXXL on Twitter → https://twitter.com/XXL\\rXXL on Instagram → https://instagram.com/xxl/                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                              |Music         |21.365575674164553|3.0405387733751796   |6.219767256945353|0.015393410645951556|496771.0             |\n",
      "|26        |4  |VIUo6yapDbc|Ultimate DIY Home Movie Theater for The LaBrant Family!     |2020-08-11T15:10:05Z|UCDVPcEbVLQgLZX0Rt6jo34A|Mr. Kate     |2020-08-12T00:00:00Z|The LaBrant Family|DIY|Interior Design|Makeover|Decorating|DIY Movie Theater|Home Movie Theater|Movie Theater|Stay Home|Cole LaBrant|Savannah LaBrant|Kate Albrecht|Joey Zehr|mr. Kate|mr kate|luxurious|red|beautiful|LifeLock Norton 360|Norton|LifeLock|Real estate scams|Home title scams|Identity Theft|Cyber Security|Cyber Safety|lux|collab|omg we're coming over|youtubers|home makeover|nursery makeover|home theater                                 |1123889   |45802 |964     |2196         |https://i.ytimg.com/vi/VIUo6yapDbc/default.jpg|false            |false           |Transforming The LaBrant Family's empty white room into a dramatic custom home movie theater. A portion of this video was sponsored by NortonLifeLock. Time to help protect your home title with Norton 360 with LifeLock Ultimate Plus. #NoPryingEyes Go to https://bit.ly/3iio4um to learn more or visit http://www.facebook.com/LifeLock & http://www.youtube.com/LifeLock    + SUBSCRIBE to our channel!: http://bit.ly/mrkateyoutube+ FOLLOW us on Instagram!: http://www.instagram.com/mrkate and http://www.instagram.com/joeyzehr+ SUBSCRIBE to the LaBrant Fam's channel: https://www.youtube.com/channel/UC4-CH0epzZpD_ARhxCx6LaQWATCH The LaBrant Fam's Nursery Makeover Here: https://www.youtube.com/watch?v=ZhoRLt42AmsWATCH how this collab all started here: https://youtu.be/Xi_F4TKJE5Y#INTERIORDESIGN #HOMETHEATER #MAKEOVER #MRKATE #THELABRANTFAMPIN PICS FROM OUR BLOG!: https://mrkate.com/2020/08/11/ultimate-diy-home-movie-theater-for-the-labrant-family/_________________________Instagram: http://www.instagram.com/mrkate and http://www.instagram.com/joeyzehrTik Tok: @mrkate Snapchat: MrKateTwitter: http://www.twitter.com/mrkateFacebook: http://www.facebook.com/mrkatedotcomPinterest: http://www.pinterest.com/mrkate/Become a member for exclusive VLOGS, LIVE CHATS, EMOJIS, BADGES and DISCOUNT CODES: https://www.youtube.com/channel/UCDVPcEbVLQgLZX0Rt6jo34A/join  _________________________Shop the entire video!: Chaise Lounge: https://bit.ly/3kzL1vlSofa: https://bit.ly/3fNAMQrSideboard: https://bit.ly/33R36yT Wallpaper: https://bit.ly/2DWAdpWWoven Poufs: https://bit.ly/39muMwe Curtains: https://amzn.to/3fIUf4B Nesting Black Tables: https://amzn.to/3fNje70 Sconces (similar): https://amzn.to/3fFPTeE Popcorn Machine (similar): https://bit.ly/2PGUS47 Drink Table: https://bit.ly/3gXUj1G Throw Blanket: https://bit.ly/3gOgV4N Terracotta Pillow: https://bit.ly/3eSXiGZ Jam Velvet Pillows: https://amzn.to/3ktNlnD Burgundy Velvet Pillows: https://amzn.to/3aekTRE Taupe Velvet Pillows: https://amzn.to/3kzIW2b Movie Clap Board: https://amzn.to/33Q1mpA Ticket Shadow Box: https://amzn.to/2XPHijs Popcorn Bags: https://amzn.to/3iymKDN _________________________Creative Credit: Audio Tracks - Epidemic Sound: http://share.epidemicsound.com/rGjgCA Mr. Kate ProductionExecutive Producers: Kate Albrecht and Joey ZehrSupervising Producer: AJ TeslerProducer: Annie O'RourkeCamera: Marco BottiglieriArt Department: Leo Martinez, Gabriel Gonzalez, Kenny NogueiraPA: Amy PattersonEdited by: Vianne Robitaille|Howto & Style |24.537989607440725|20.85701275045537    |4.270706448768517|0.001953929614045515|1123889.0            |\n",
      "+----------+---+-----------+------------------------------------------------------------+--------------------+------------------------+-------------+--------------------+----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+----------+------+--------+-------------+----------------------------------------------+-----------------+----------------+---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+--------------+------------------+---------------------+-----------------+--------------------+---------------------+\n",
      "only showing top 5 rows\n",
      "\n"
     ]
    }
   ],
   "source": [
    "# Show the first few rows of the DataFrame (dont truncate)\n",
    "df.show(5, truncate=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 246,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "[Stage 400:>                                                        (0 + 1) / 1]\r"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "+----------+------+-----------+----------------------+--------------------+--------------------+--------------------+--------------------+--------------------+----------+------+--------+-------------+--------------------+-----------------+----------------+--------------------+----------------+------------------+---------------------+------------------+--------------------+---------------------+\n",
      "|categoryId|    id|   video_id|                 title|         publishedAt|           channelId|        channelTitle|       trending_date|                tags|view_count| likes|dislikes|comment_count|      thumbnail_link|comments_disabled|ratings_disabled|         description|   categoryTitle|view_to_like_ratio|like_to_comment_ratio|   engagement_rate|   comments_per_view|average_views_per_day|\n",
      "+----------+------+-----------+----------------------+--------------------+--------------------+--------------------+--------------------+--------------------+----------+------+--------+-------------+--------------------+-----------------+----------------+--------------------+----------------+------------------+---------------------+------------------+--------------------+---------------------+\n",
      "|        10| 60792|--14w5SOEUs|     Migos - Avalanche|2021-06-10T16:00:00Z|UCGIelM2Dj3zza3xy...|           MigosVEVO|2021-06-11T00:00:00Z|Migos|Avalanche|Q...|   1076217|122830|     867|         9539|https://i.ytimg.c...|            false|           false|Music video by Mi...|           Music| 8.761841569649109|   12.876611804172345| 12.29947120329822|0.008863454117524625|            1076217.0|\n",
      "|        10| 60991|--14w5SOEUs|  Migos - Avalanche...|2021-06-10T16:00:00Z|UCGIelM2Dj3zza3xy...|           MigosVEVO|2021-06-11T00:00:00Z|Migos|Avalanche|Q...|   2146104|167034|    1755|        12998|https://i.ytimg.c...|            false|           false|Watch the the off...|           Music|12.848306332842416|   12.850746268656716|  8.38878264986226|0.006056556439016935|            2146104.0|\n",
      "|        10| 61197|--14w5SOEUs|  Migos - Avalanche...|2021-06-10T16:00:00Z|UCGIelM2Dj3zza3xy...|           MigosVEVO|2021-06-12T00:00:00Z|Migos|Avalanche|Q...|   3317372|202153|    2518|        14721|https://i.ytimg.c...|            false|           false|Watch the the off...|           Music|16.410204152300484|   13.732287208749405| 6.537524281268425|0.004437548758475082|            1658686.0|\n",
      "|        10| 61398|--14w5SOEUs|  Migos - Avalanche...|2021-06-10T16:00:00Z|UCGIelM2Dj3zza3xy...|           MigosVEVO|2021-06-12T00:00:00Z|Migos|Avalanche|Q...|   3963014|218568|    2847|        15442|https://i.ytimg.c...|            false|           false|Watch the the off...|           Music| 18.13172102046045|    14.15412511332729|    5.904849188017|0.003896529257782082|            1981507.0|\n",
      "|        10| 61605|--14w5SOEUs|  Migos - Avalanche...|2021-06-10T16:00:00Z|UCGIelM2Dj3zza3xy...|           MigosVEVO|2021-06-13T00:00:00Z|Migos|Avalanche|Q...|   4690242|232455|    3145|        15743|https://i.ytimg.c...|            false|           false|Watch the the off...|           Music|20.176989094663483|   14.765610112430922|5.2917951781592505|0.003356543223142857|            1563414.0|\n",
      "|        10| 61818|--14w5SOEUs|  Migos - Avalanche...|2021-06-10T16:00:00Z|UCGIelM2Dj3zza3xy...|           MigosVEVO|2021-06-13T00:00:00Z|Migos|Avalanche|Q...|   5167987|240113|    3414|        16241|https://i.ytimg.c...|            false|           false|Watch the the off...|           Music| 21.52314535239658|   14.784372883443138| 4.960422694561731|0.003142616264321...|   1722662.3333333333|\n",
      "|        10| 62030|--14w5SOEUs|  Migos - Avalanche...|2021-06-10T16:00:00Z|UCGIelM2Dj3zza3xy...|           MigosVEVO|2021-06-14T00:00:00Z|Migos|Avalanche|Q...|   5726392|247336|    3627|        15890|https://i.ytimg.c...|            false|           false|Watch the the off...|           Music|23.152278681631465|    15.56551290119572| 4.596716396642074|0.002774871157964736|            1431598.0|\n",
      "|        10| 62243|--14w5SOEUs|  Migos - Avalanche...|2021-06-10T16:00:00Z|UCGIelM2Dj3zza3xy...|           MigosVEVO|2021-06-14T00:00:00Z|Migos|Avalanche|Q...|   6078723|252005|    3778|        16228|https://i.ytimg.c...|            false|           false|Watch the the off...|           Music|24.121438066705025|   15.529023909292581| 4.412653776130282|0.002669639659514013|           1519680.75|\n",
      "|        10| 62481|--14w5SOEUs|  Migos - Avalanche...|2021-06-10T16:00:00Z|UCGIelM2Dj3zza3xy...|           MigosVEVO|2021-06-15T00:00:00Z|Migos|Avalanche|Q...|   6553613|258885|    3977|        16296|https://i.ytimg.c...|            false|           false|Watch the the off...|           Music|25.314765243254726|   15.886413843888072| 4.198920503850319|0.002486567333164...|            1310722.6|\n",
      "|        10| 62681|--14w5SOEUs|  Migos - Avalanche...|2021-06-10T16:00:00Z|UCGIelM2Dj3zza3xy...|           MigosVEVO|2021-06-15T00:00:00Z|Migos|Avalanche|Q...|   6823249|262692|    4107|        16445|https://i.ytimg.c...|            false|           false|Watch the the off...|           Music|25.974331155878367|   15.973973852234721| 4.090968979733848|0.002410142147824299|            1364649.8|\n",
      "|        24|116015|--2O86Z0hsM|  MY TESLA PAYS FOR...|2022-03-09T23:19:08Z|UCXJEvxZSozjAAqhb...|             jf.okay|2022-03-11T00:00:00Z|              [None]|    466980| 16481|       0|         1278|https://i.ytimg.c...|            false|           false|                NULL|   Entertainment|28.334445725380743|   12.895931142410015|3.8029465930018413|0.002736733907233...|             233490.0|\n",
      "|        24|116480|--2O86Z0hsM|  MY TESLA PAYS FOR...|2022-03-09T23:19:08Z|UCXJEvxZSozjAAqhb...|             jf.okay|2022-03-13T00:00:00Z|              [None]|    506401| 16829|       0|         1433|https://i.ytimg.c...|            false|           false|                NULL|   Entertainment| 30.09097391407689|   11.743893928820656| 3.606233005069105|0.002829773242943833|            126600.25|\n",
      "|        24|116719|--2O86Z0hsM|  MY TESLA PAYS FOR...|2022-03-09T23:19:08Z|UCXJEvxZSozjAAqhb...|             jf.okay|2022-03-14T00:00:00Z|              [None]|    519009| 16978|       0|         1362|https://i.ytimg.c...|            false|           false|                NULL|   Entertainment|30.569501708092826|   12.465491923641704|3.5336574124918836|0.002624231949734976|             103801.8|\n",
      "|        24|116969|--2O86Z0hsM|  MY TESLA PAYS FOR...|2022-03-09T23:19:08Z|UCXJEvxZSozjAAqhb...|             jf.okay|2022-03-15T00:00:00Z|              [None]|    538485| 17290|       0|         1439|https://i.ytimg.c...|            false|           false|                NULL|   Entertainment|31.144303065355697|   12.015288394718555| 3.478091311735703|0.002672312134971262|              89747.5|\n",
      "|        24| 82203|--40TEbZ9Is|  Supporting Actres...|2021-09-20T01:03:32Z|UClBKH8yZRcM4AsRj...|  Television Academy|2021-09-21T00:00:00Z|              [None]|    527742|  6299|     286|          586|https://i.ytimg.c...|            false|           false|Hannah Waddingham...|   Entertainment| 83.78187013811716|   10.749146757679181|1.3046147549370715|0.001110391062299...|             527742.0|\n",
      "|        24| 82443|--40TEbZ9Is|  Supporting Actres...|2021-09-20T01:03:32Z|UClBKH8yZRcM4AsRj...|  Television Academy|2021-09-22T00:00:00Z|              [None]|    596317|  6998|     351|          675|https://i.ytimg.c...|            false|           false|Hannah Waddingham...|   Entertainment| 85.21248928265219|   10.367407407407407|1.2867317215507859|0.001131948275833...|             298158.5|\n",
      "|        24| 82676|--40TEbZ9Is|  Supporting Actres...|2021-09-20T01:03:32Z|UClBKH8yZRcM4AsRj...|  Television Academy|2021-09-23T00:00:00Z|              [None]|    638046|  7548|     362|          699|https://i.ytimg.c...|            false|           false|Hannah Waddingham...|   Entertainment| 84.53179650238474|   10.798283261802576|1.2925400362983235|0.001095532297044...|             212682.0|\n",
      "|        24| 82907|--40TEbZ9Is|  Supporting Actres...|2021-09-20T01:03:32Z|UClBKH8yZRcM4AsRj...|  Television Academy|2021-09-24T00:00:00Z|              [None]|    663938|  7831|     368|          706|https://i.ytimg.c...|            false|           false|Hannah Waddingham...|   Entertainment| 84.78329715234325|   11.092067988668555| 1.285812831921053|0.001063352300967...|             165984.5|\n",
      "|        24| 83138|--40TEbZ9Is|  Supporting Actres...|2021-09-20T01:03:32Z|UClBKH8yZRcM4AsRj...|  Television Academy|2021-09-25T00:00:00Z|              [None]|    682609|  8029|     369|          723|https://i.ytimg.c...|            false|           false|Hannah Waddingham...|   Entertainment| 85.01793498567692|   11.105117565698478| 1.282139555733956|0.001059171502280222|             136521.8|\n",
      "|        17|245023|--47FjCWgrU|  San Francisco 49e...|2023-12-18T00:21:58Z|UCDVYQ4Zhbm3S2dlz...|                 NFL|2023-12-19T00:00:00Z|              [None]|   1635672| 20234|       0|         1834|https://i.ytimg.c...|            false|           false|Check out our oth...|          Sports|  80.8377977661362|   11.032715376226827| 1.349170249292034|0.001121251693493...|            1635672.0|\n",
      "|        17|245260|--47FjCWgrU|  San Francisco 49e...|2023-12-18T00:21:58Z|UCDVYQ4Zhbm3S2dlz...|                 NFL|2023-12-20T00:00:00Z|              [None]|   1758484| 21315|       0|         1919|https://i.ytimg.c...|            false|           false|Check out our oth...|          Sports| 82.49983579638752|    11.10734757686295|1.3212517145450287|0.001091280898774...|             879242.0|\n",
      "|        17|245497|--47FjCWgrU|  San Francisco 49e...|2023-12-18T00:21:58Z|UCDVYQ4Zhbm3S2dlz...|                 NFL|2023-12-21T00:00:00Z|              [None]|   1829323| 21916|       0|         1961|https://i.ytimg.c...|            false|           false|Check out our oth...|          Sports| 83.46974812922066|    11.17593064762876|1.3052369647131754|0.001071981273946...|    609774.3333333334|\n",
      "|        17|245738|--47FjCWgrU|  San Francisco 49e...|2023-12-18T00:21:58Z|UCDVYQ4Zhbm3S2dlz...|                 NFL|2023-12-22T00:00:00Z|              [None]|   1872689| 22207|       0|         1992|https://i.ytimg.c...|            false|           false|Check out our oth...|          Sports|  84.3287702075922|   11.148092369477911|1.2922060203269203|0.001063711059337669|            468172.25|\n",
      "|        17|245959|--47FjCWgrU|  San Francisco 49e...|2023-12-18T00:21:58Z|UCDVYQ4Zhbm3S2dlz...|                 NFL|2023-12-23T00:00:00Z|              [None]|   1906087| 22403|       0|         2005|https://i.ytimg.c...|            false|           false|Check out our oth...|          Sports| 85.08177476230863|    11.17356608478803|1.2805291678711412|0.001051893224181...|             381217.4|\n",
      "|        17|246175|--47FjCWgrU|  San Francisco 49e...|2023-12-18T00:21:58Z|UCDVYQ4Zhbm3S2dlz...|                 NFL|2023-12-24T00:00:00Z|              [None]|   1927291| 22541|       0|         2006|https://i.ytimg.c...|            false|           false|Check out our oth...|          Sports| 85.50157490794552|    11.23678963110668|1.2736530186671342|0.001040839188269...|    321215.1666666667|\n",
      "|        17|246373|--47FjCWgrU|  San Francisco 49e...|2023-12-18T00:21:58Z|UCDVYQ4Zhbm3S2dlz...|                 NFL|2023-12-25T00:00:00Z|              [None]|   1940781| 22612|       0|         2018|https://i.ytimg.c...|            false|           false|Check out our oth...|          Sports| 85.82969219883248|   11.205153617443013|1.2690767273587285|0.001039787590665...|    277254.4285714286|\n",
      "|        17|174003|--5-brQiQFg|  Washington Comman...|2022-12-25T00:30:17Z|UCDVYQ4Zhbm3S2dlz...|                 NFL|2022-12-26T00:00:00Z|              [None]|   1280997| 14603|       0|         2078|https://i.ytimg.c...|            false|           false|Check out our oth...|          Sports| 87.72149558309937|    7.027430221366699|1.3021888419723076|0.001622173978549...|            1280997.0|\n",
      "|        27| 97415|--DKkzWVh-E|  Why Retaining Wal...|2021-12-07T13:00:00Z|UCMOqf8ab-42UUQId...|Practical Enginee...|2021-12-08T00:00:00Z|retaining wall|Ne...|    320130| 18445|     147|          612|https://i.ytimg.c...|            false|           false|One of the most i...|       Education|17.355923014367036|    30.13888888888889| 5.952894136756943|0.001911723362384...|             320130.0|\n",
      "|        27| 97662|--DKkzWVh-E|  Why Retaining Wal...|2021-12-07T13:00:00Z|UCMOqf8ab-42UUQId...|Practical Enginee...|2021-12-09T00:00:00Z|retaining wall|Ne...|    402839| 22121|     199|          726|https://i.ytimg.c...|            false|           false|One of the most i...|       Education|18.210704760182633|    30.46969696969697| 5.671496553213567|0.001802208822879612|             201419.5|\n",
      "|        27| 97907|--DKkzWVh-E|  Why Retaining Wal...|2021-12-07T13:00:00Z|UCMOqf8ab-42UUQId...|Practical Enginee...|2021-12-10T00:00:00Z|retaining wall|Ne...|    511186| 26314|     257|          909|https://i.ytimg.c...|            false|           false|One of the most i...|       Education|19.426388994451624|   28.948294829482947|5.3254588349446195|0.001778217713317...|   170395.33333333334|\n",
      "|        27| 98144|--DKkzWVh-E|  Why Retaining Wal...|2021-12-07T13:00:00Z|UCMOqf8ab-42UUQId...|Practical Enginee...|2021-12-11T00:00:00Z|retaining wall|Ne...|    623949| 29991|     320|          998|https://i.ytimg.c...|            false|           false|One of the most i...|       Education|20.804541362408724|   30.051102204408817| 4.966591820805867|0.001599489701882686|            155987.25|\n",
      "|        10| 96405|--FmExEAsM8|IVE 아이브 'ELEVEN' MV|2021-12-01T09:00:03Z|UCYDmx2Sfpnaxg488...|          starshipTV|2021-12-02T00:00:00Z|Kpop|girl group|1...|  13023979|560144|    9482|        37136|https://i.ytimg.c...|            false|           false|IVE Twitter: http...|           Music|23.251126496043874|   15.083584661783714| 4.586002480501543|0.002851355948900102|          1.3023979E7|\n",
      "|        10| 96638|--FmExEAsM8|IVE 아이브 'ELEVEN' MV|2021-12-01T09:00:03Z|UCYDmx2Sfpnaxg488...|          starshipTV|2021-12-03T00:00:00Z|Kpop|girl group|1...|  21851660|645891|   11464|        44064|https://i.ytimg.c...|            false|           false|IVE Twitter: http...|           Music| 33.83180753408857|   14.658020152505447|3.1574489077717662|0.002016505839830...|           1.092583E7|\n",
      "|        10| 96934|--FmExEAsM8|IVE 아이브 'ELEVEN' MV|2021-12-01T09:00:03Z|UCYDmx2Sfpnaxg488...|          starshipTV|2021-12-05T00:00:00Z|Kpop|girl group|1...|  30906926|765457|   13597|        49743|https://i.ytimg.c...|            false|           false|IVE Twitter: http...|           Music|40.377089764676526|   15.388235530627425| 2.637596505068152|0.001609445080368...|            7726731.5|\n",
      "|        10| 97160|--FmExEAsM8|IVE 아이브 'ELEVEN' MV|2021-12-01T09:00:03Z|UCYDmx2Sfpnaxg488...|          starshipTV|2021-12-06T00:00:00Z|Kpop|girl group|1...|  31967789|810589|   14252|        52092|https://i.ytimg.c...|            false|           false|IVE Twitter: http...|           Music|39.437728614624675|    15.56071949627582|2.6985945133709435|0.001629515259876...|            6393557.8|\n",
      "|        10|  7125|--SvHNpSvpk|  YoungBoy Never Br...|2020-09-11T15:00:00Z|UClW4jraMKz6Qj69l...|YoungBoy Never Br...|2020-09-16T00:00:00Z|YoungBoy Never Br...|   4286288|164916|    3978|        14475|https://i.ytimg.c...|            false|           false|YoungBoy Never Br...|           Music| 25.99073467704771|   11.393160621761657| 4.185229737245841|0.003377047925850993|             857257.6|\n",
      "|        10|  7356|--SvHNpSvpk|  YoungBoy Never Br...|2020-09-11T15:00:00Z|UClW4jraMKz6Qj69l...|YoungBoy Never Br...|2020-09-17T00:00:00Z|YoungBoy Never Br...|   4791731|169382|    4235|        15007|https://i.ytimg.c...|            false|           false|YoungBoy Never Br...|           Music|28.289493570745417|   11.286866129139735|3.8480665963928273|0.003131853603635...|    798621.8333333334|\n",
      "|        10|  7585|--SvHNpSvpk|  YoungBoy Never Br...|2020-09-11T15:00:00Z|UClW4jraMKz6Qj69l...|YoungBoy Never Br...|2020-09-18T00:00:00Z|YoungBoy Never Br...|   5308719|175482|    4544|        15346|https://i.ytimg.c...|            false|           false|YoungBoy Never Br...|           Music|30.252213902280577|   11.435031930144664|3.5946148213909983|0.002890716197259...|    758388.4285714285|\n",
      "|        10|  6226|--SvHNpSvpk|  YoungBoy Never Br...|2020-09-11T15:00:00Z|UClW4jraMKz6Qj69l...|YoungBoy Never Br...|2020-09-12T00:00:00Z|YoungBoy Never Br...|   1736660|127830|    2242|        11037|https://i.ytimg.c...|            false|           false|YoungBoy Never Br...|           Music|13.585699757490417|   11.581951617287306| 7.996211117892966|0.006355302707495998|            1736660.0|\n",
      "|        10|  6894|--SvHNpSvpk|  YoungBoy Never Br...|2020-09-11T15:00:00Z|UClW4jraMKz6Qj69l...|YoungBoy Never Br...|2020-09-15T00:00:00Z|YoungBoy Never Br...|   3724865|159889|    3665|        13636|https://i.ytimg.c...|            false|           false|YoungBoy Never Br...|           Music|23.296568244219426|   11.725506013493693| 4.658558095394062|0.003660803814366...|            931216.25|\n",
      "|         1|135617|--gJDs10ShA|  what happens if y...|2022-06-16T01:11:59Z|UC_54BddY_xCboN2k...|   Hydraulic Beanbag|2022-06-17T00:00:00Z|Blender|Animation...|   1876340|112561|       0|         2934|https://i.ytimg.c...|            false|           false|today was suppose...|Film & Animation|16.669539183198445|   38.364349011588274| 6.155334321071874|0.001563682488248...|            1876340.0|\n",
      "|         1|135846|--gJDs10ShA|  what happens if y...|2022-06-16T01:11:59Z|UC_54BddY_xCboN2k...|   Hydraulic Beanbag|2022-06-18T00:00:00Z|Blender|Animation...|   2342763|131047|       0|         3401|https://i.ytimg.c...|            false|           false|today was suppose...|Film & Animation|17.877273039443864|    38.53190238165246| 5.738864750723825|0.001451704675206...|            1171381.5|\n",
      "|         1|136107|--gJDs10ShA|  what happens if y...|2022-06-16T01:11:59Z|UC_54BddY_xCboN2k...|   Hydraulic Beanbag|2022-06-19T00:00:00Z|Blender|Animation...|   2656328|144482|       0|         3657|https://i.ytimg.c...|            false|           false|today was suppose...|Film & Animation| 18.38518292936144|   39.508340169537874| 5.576833884972037|0.001376712514418...|    885442.6666666666|\n",
      "|         1|136339|--gJDs10ShA|  what happens if y...|2022-06-16T01:11:59Z|UC_54BddY_xCboN2k...|   Hydraulic Beanbag|2022-06-20T00:00:00Z|Blender|Animation...|   2908403|152265|       0|         3837|https://i.ytimg.c...|            false|           false|today was suppose...|Film & Animation|19.100929300889895|   39.683346364347145| 5.367275442914892|0.001319280718662...|            727100.75|\n",
      "|         1|136576|--gJDs10ShA|  what happens if y...|2022-06-16T01:11:59Z|UC_54BddY_xCboN2k...|   Hydraulic Beanbag|2022-06-21T00:00:00Z|Blender|Animation...|   3089272|157048|       0|         3945|https://i.ytimg.c...|            false|           false|today was suppose...|Film & Animation|19.670877693444044|    39.80937896070976| 5.211357238857569|0.001276999888646...|             617854.4|\n",
      "|        26|121834|--hjHKgm67g|  The Third Attempt...|2022-04-07T19:14:45Z|UC6I0KzAD7uFTL1qz...|    Blacktail Studio|2022-04-09T00:00:00Z|bookmatched guita...|    400200| 17339|       0|         2561|https://i.ytimg.c...|            false|           false|I tried to make t...|   Howto & Style|23.080915854432206|    6.770402186645842| 4.972513743128435|0.006399300349825087|             200100.0|\n",
      "|        26|122060|--hjHKgm67g|  The Third Attempt...|2022-04-07T19:14:45Z|UC6I0KzAD7uFTL1qz...|    Blacktail Studio|2022-04-10T00:00:00Z|bookmatched guita...|    532932| 20978|       0|         2970|https://i.ytimg.c...|            false|           false|I tried to make t...|   Howto & Style|25.404328343979408|    7.063299663299663| 4.493631457671898|0.005572943640089167|             177644.0|\n",
      "|        26|122307|--hjHKgm67g|  The Third Attempt...|2022-04-07T19:14:45Z|UC6I0KzAD7uFTL1qz...|    Blacktail Studio|2022-04-11T00:00:00Z|bookmatched guita...|    711518| 25432|       0|         3466|https://i.ytimg.c...|            false|           false|I tried to make t...|   Howto & Style|27.977272727272727|    7.337564916330064| 4.061457334881197|0.004871275217211652|             177879.5|\n",
      "|        26|122554|--hjHKgm67g|  The Third Attempt...|2022-04-07T19:14:45Z|UC6I0KzAD7uFTL1qz...|    Blacktail Studio|2022-04-12T00:00:00Z|bookmatched guita...|    811063| 27485|       0|         3711|https://i.ytimg.c...|            false|           false|I tried to make t...|   Howto & Style| 29.50929597962525|    7.406359471840474|3.8463103359418445|0.004575476874176235|             162212.6|\n",
      "|        26|122787|--hjHKgm67g|  The Third Attempt...|2022-04-07T19:14:45Z|UC6I0KzAD7uFTL1qz...|    Blacktail Studio|2022-04-13T00:00:00Z|bookmatched guita...|    857931| 28461|       0|         3871|https://i.ytimg.c...|            false|           false|I tried to make t...|   Howto & Style| 30.14409191525245|   7.3523637303022475|3.7686014376447523| 0.00451201786623866|             142988.5|\n",
      "+----------+------+-----------+----------------------+--------------------+--------------------+--------------------+--------------------+--------------------+----------+------+--------+-------------+--------------------+-----------------+----------------+--------------------+----------------+------------------+---------------------+------------------+--------------------+---------------------+\n",
      "only showing top 50 rows\n",
      "\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "                                                                                \r"
     ]
    }
   ],
   "source": [
    "# show 50 rows, asc video_id\n",
    "df.orderBy(\"video_id\").show(50)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Saving Engagement Data\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 247,
   "metadata": {},
   "outputs": [],
   "source": [
    "# subset data\n",
    "df_subset = df.select(\"id\", \"video_id\",\n",
    "                      # engagement variables\n",
    "                      \"likes\", \"dislikes\", \"comment_count\", \"view_count\",\n",
    "                      # engagement metrics\n",
    "                      \"view_to_like_ratio\", \"like_to_comment_ratio\", \"engagement_rate\", \"comments_per_view\", \"average_views_per_day\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 248,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "                                                                                \r"
     ]
    }
   ],
   "source": [
    "# Example: Specifying an absolute path and ensuring the directory exists\n",
    "import os\n",
    "\n",
    "output_path = \"data/processed/engagement.parquet\"\n",
    "os.makedirs(os.path.dirname(output_path), exist_ok=True)\n",
    "df_subset.write.mode('overwrite').parquet(output_path)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 192,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "[Stage 267:>                                                        (0 + 1) / 1]\r"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "+-----------+------+--------+-------------+----------+------------------+---------------------+------------------+--------------------+---------------------+\n",
      "|   video_id| likes|dislikes|comment_count|view_count|view_to_like_ratio|like_to_comment_ratio|   engagement_rate|   comments_per_view|average_views_per_day|\n",
      "+-----------+------+--------+-------------+----------+------------------+---------------------+------------------+--------------------+---------------------+\n",
      "|--14w5SOEUs|122830|     867|         9539|   1076217| 8.761841569649109|   12.876611804172345| 12.29947120329822|0.008863454117524625|            1076217.0|\n",
      "|--14w5SOEUs|167034|    1755|        12998|   2146104|12.848306332842416|   12.850746268656716|  8.38878264986226|0.006056556439016935|            2146104.0|\n",
      "|--14w5SOEUs|202153|    2518|        14721|   3317372|16.410204152300484|   13.732287208749405| 6.537524281268425|0.004437548758475082|            1658686.0|\n",
      "|--14w5SOEUs|218568|    2847|        15442|   3963014| 18.13172102046045|    14.15412511332729|    5.904849188017|0.003896529257782082|            1981507.0|\n",
      "|--14w5SOEUs|232455|    3145|        15743|   4690242|20.176989094663483|   14.765610112430922|5.2917951781592505|0.003356543223142857|            1563414.0|\n",
      "|--14w5SOEUs|240113|    3414|        16241|   5167987| 21.52314535239658|   14.784372883443138| 4.960422694561731|0.003142616264321...|   1722662.3333333333|\n",
      "|--14w5SOEUs|247336|    3627|        15890|   5726392|23.152278681631465|    15.56551290119572| 4.596716396642074|0.002774871157964736|            1431598.0|\n",
      "|--14w5SOEUs|252005|    3778|        16228|   6078723|24.121438066705025|   15.529023909292581| 4.412653776130282|0.002669639659514013|           1519680.75|\n",
      "|--14w5SOEUs|258885|    3977|        16296|   6553613|25.314765243254726|   15.886413843888072| 4.198920503850319|0.002486567333164...|            1310722.6|\n",
      "|--14w5SOEUs|262692|    4107|        16445|   6823249|25.974331155878367|   15.973973852234721| 4.090968979733848|0.002410142147824299|            1364649.8|\n",
      "|--2O86Z0hsM| 16481|       0|         1278|    466980|28.334445725380743|   12.895931142410015|3.8029465930018413|0.002736733907233...|             233490.0|\n",
      "|--2O86Z0hsM| 16829|       0|         1433|    506401| 30.09097391407689|   11.743893928820656| 3.606233005069105|0.002829773242943833|            126600.25|\n",
      "|--2O86Z0hsM| 16978|       0|         1362|    519009|30.569501708092826|   12.465491923641704|3.5336574124918836|0.002624231949734976|             103801.8|\n",
      "|--2O86Z0hsM| 17290|       0|         1439|    538485|31.144303065355697|   12.015288394718555| 3.478091311735703|0.002672312134971262|              89747.5|\n",
      "|--40TEbZ9Is|  6299|     286|          586|    527742| 83.78187013811716|   10.749146757679181|1.3046147549370715|0.001110391062299...|             527742.0|\n",
      "|--40TEbZ9Is|  6998|     351|          675|    596317| 85.21248928265219|   10.367407407407407|1.2867317215507859|0.001131948275833...|             298158.5|\n",
      "|--40TEbZ9Is|  7548|     362|          699|    638046| 84.53179650238474|   10.798283261802576|1.2925400362983235|0.001095532297044...|             212682.0|\n",
      "|--40TEbZ9Is|  7831|     368|          706|    663938| 84.78329715234325|   11.092067988668555| 1.285812831921053|0.001063352300967...|             165984.5|\n",
      "|--40TEbZ9Is|  8029|     369|          723|    682609| 85.01793498567692|   11.105117565698478| 1.282139555733956|0.001059171502280222|             136521.8|\n",
      "|--47FjCWgrU| 20234|       0|         1834|   1635672|  80.8377977661362|   11.032715376226827| 1.349170249292034|0.001121251693493...|            1635672.0|\n",
      "|--47FjCWgrU| 21315|       0|         1919|   1758484| 82.49983579638752|    11.10734757686295|1.3212517145450287|0.001091280898774...|             879242.0|\n",
      "|--47FjCWgrU| 21916|       0|         1961|   1829323| 83.46974812922066|    11.17593064762876|1.3052369647131754|0.001071981273946...|    609774.3333333334|\n",
      "|--47FjCWgrU| 22207|       0|         1992|   1872689|  84.3287702075922|   11.148092369477911|1.2922060203269203|0.001063711059337669|            468172.25|\n",
      "|--47FjCWgrU| 22403|       0|         2005|   1906087| 85.08177476230863|    11.17356608478803|1.2805291678711412|0.001051893224181...|             381217.4|\n",
      "|--47FjCWgrU| 22541|       0|         2006|   1927291| 85.50157490794552|    11.23678963110668|1.2736530186671342|0.001040839188269...|    321215.1666666667|\n",
      "|--47FjCWgrU| 22612|       0|         2018|   1940781| 85.82969219883248|   11.205153617443013|1.2690767273587285|0.001039787590665...|    277254.4285714286|\n",
      "|--5-brQiQFg| 14603|       0|         2078|   1280997| 87.72149558309937|    7.027430221366699|1.3021888419723076|0.001622173978549...|            1280997.0|\n",
      "|--DKkzWVh-E| 18445|     147|          612|    320130|17.355923014367036|    30.13888888888889| 5.952894136756943|0.001911723362384...|             320130.0|\n",
      "|--DKkzWVh-E| 22121|     199|          726|    402839|18.210704760182633|    30.46969696969697| 5.671496553213567|0.001802208822879612|             201419.5|\n",
      "|--DKkzWVh-E| 26314|     257|          909|    511186|19.426388994451624|   28.948294829482947|5.3254588349446195|0.001778217713317...|   170395.33333333334|\n",
      "|--DKkzWVh-E| 29991|     320|          998|    623949|20.804541362408724|   30.051102204408817| 4.966591820805867|0.001599489701882686|            155987.25|\n",
      "|--FmExEAsM8|560144|    9482|        37136|  13023979|23.251126496043874|   15.083584661783714| 4.586002480501543|0.002851355948900102|          1.3023979E7|\n",
      "|--FmExEAsM8|645891|   11464|        44064|  21851660| 33.83180753408857|   14.658020152505447|3.1574489077717662|0.002016505839830...|           1.092583E7|\n",
      "|--FmExEAsM8|765457|   13597|        49743|  30906926|40.377089764676526|   15.388235530627425| 2.637596505068152|0.001609445080368...|            7726731.5|\n",
      "|--FmExEAsM8|810589|   14252|        52092|  31967789|39.437728614624675|    15.56071949627582|2.6985945133709435|0.001629515259876...|            6393557.8|\n",
      "|--SvHNpSvpk|164916|    3978|        14475|   4286288| 25.99073467704771|   11.393160621761657| 4.185229737245841|0.003377047925850993|             857257.6|\n",
      "|--SvHNpSvpk|169382|    4235|        15007|   4791731|28.289493570745417|   11.286866129139735|3.8480665963928273|0.003131853603635...|    798621.8333333334|\n",
      "|--SvHNpSvpk|175482|    4544|        15346|   5308719|30.252213902280577|   11.435031930144664|3.5946148213909983|0.002890716197259...|    758388.4285714285|\n",
      "|--SvHNpSvpk|127830|    2242|        11037|   1736660|13.585699757490417|   11.581951617287306| 7.996211117892966|0.006355302707495998|            1736660.0|\n",
      "|--SvHNpSvpk|159889|    3665|        13636|   3724865|23.296568244219426|   11.725506013493693| 4.658558095394062|0.003660803814366...|            931216.25|\n",
      "|--gJDs10ShA|112561|       0|         2934|   1876340|16.669539183198445|   38.364349011588274| 6.155334321071874|0.001563682488248...|            1876340.0|\n",
      "|--gJDs10ShA|131047|       0|         3401|   2342763|17.877273039443864|    38.53190238165246| 5.738864750723825|0.001451704675206...|            1171381.5|\n",
      "|--gJDs10ShA|144482|       0|         3657|   2656328| 18.38518292936144|   39.508340169537874| 5.576833884972037|0.001376712514418...|    885442.6666666666|\n",
      "|--gJDs10ShA|152265|       0|         3837|   2908403|19.100929300889895|   39.683346364347145| 5.367275442914892|0.001319280718662...|            727100.75|\n",
      "|--gJDs10ShA|157048|       0|         3945|   3089272|19.670877693444044|    39.80937896070976| 5.211357238857569|0.001276999888646...|             617854.4|\n",
      "|--hjHKgm67g| 17339|       0|         2561|    400200|23.080915854432206|    6.770402186645842| 4.972513743128435|0.006399300349825087|             200100.0|\n",
      "|--hjHKgm67g| 20978|       0|         2970|    532932|25.404328343979408|    7.063299663299663| 4.493631457671898|0.005572943640089167|             177644.0|\n",
      "|--hjHKgm67g| 25432|       0|         3466|    711518|27.977272727272727|    7.337564916330064| 4.061457334881197|0.004871275217211652|             177879.5|\n",
      "|--hjHKgm67g| 27485|       0|         3711|    811063| 29.50929597962525|    7.406359471840474|3.8463103359418445|0.004575476874176235|             162212.6|\n",
      "|--hjHKgm67g| 28461|       0|         3871|    857931| 30.14409191525245|   7.3523637303022475|3.7686014376447523| 0.00451201786623866|             142988.5|\n",
      "+-----------+------+--------+-------------+----------+------------------+---------------------+------------------+--------------------+---------------------+\n",
      "only showing top 50 rows\n",
      "\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "                                                                                \r"
     ]
    }
   ],
   "source": [
    "# show top 50 rows asc by video_id\n",
    "df_subset.orderBy(\"video_id\").show(50)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Calculate Engagement Metrics by Category"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 193,
   "metadata": {},
   "outputs": [],
   "source": [
    "# calculate avg, median, min, max, std for each metric for each category\n",
    "\n",
    "eng_metrics_by_category = df.groupBy(\"categoryTitle\").agg(\n",
    "    F.avg(\"view_to_like_ratio\").alias(\"avg_view_to_like_ratio\"),\n",
    "    F.avg(\"like_to_comment_ratio\").alias(\"avg_like_to_comment_ratio\"),\n",
    "    F.avg(\"engagement_rate\").alias(\"avg_engagement_rate\"),\n",
    "    F.avg(\"comments_per_view\").alias(\"avg_comments_per_view\"),\n",
    "    F.avg(\"average_views_per_day\").alias(\"avg_average_views_per_day\"),\n",
    "    F.stddev(\"view_to_like_ratio\").alias(\"stddev_view_to_like_ratio\"),\n",
    "    F.stddev(\"like_to_comment_ratio\").alias(\"stddev_like_to_comment_ratio\"),\n",
    "    F.stddev(\"engagement_rate\").alias(\"stddev_engagement_rate\"),\n",
    "    F.stddev(\"comments_per_view\").alias(\"stddev_comments_per_view\"),\n",
    "    F.stddev(\"average_views_per_day\").alias(\"stddev_average_views_per_day\"),\n",
    "    F.min(\"view_to_like_ratio\").alias(\"min_view_to_like_ratio\"),\n",
    "    F.min(\"like_to_comment_ratio\").alias(\"min_like_to_comment_ratio\"),\n",
    "    F.min(\"engagement_rate\").alias(\"min_engagement_rate\"),\n",
    "    F.min(\"comments_per_view\").alias(\"min_comments_per_view\"),\n",
    "    F.min(\"average_views_per_day\").alias(\"min_average_views_per_day\"),\n",
    "    F.max(\"view_to_like_ratio\").alias(\"max_view_to_like_ratio\"),\n",
    "    F.max(\"like_to_comment_ratio\").alias(\"max_like_to_comment_ratio\"),\n",
    "    F.max(\"engagement_rate\").alias(\"max_engagement_rate\"),\n",
    "    F.max(\"comments_per_view\").alias(\"max_comments_per_view\"),\n",
    "    F.max(\"average_views_per_day\").alias(\"max_average_views_per_day\"),\n",
    "    F.expr(\"percentile_approx(view_to_like_ratio, 0.5)\").alias(\"median_view_to_like_ratio\"),\n",
    "    F.expr(\"percentile_approx(like_to_comment_ratio, 0.5)\").alias(\"median_like_to_comment_ratio\"),\n",
    "    F.expr(\"percentile_approx(engagement_rate, 0.5)\").alias(\"median_engagement_rate\"),\n",
    "    F.expr(\"percentile_approx(comments_per_view, 0.5)\").alias(\"median_comments_per_view\"),\n",
    "    F.expr(\"percentile_approx(average_views_per_day, 0.5)\").alias(\"median_average_views_per_day\")\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 194,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "[Stage 269:>                                                        (0 + 1) / 1]\r"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "+--------------------+----------------------+-------------------------+-------------------+---------------------+-------------------------+-------------------------+----------------------------+----------------------+------------------------+----------------------------+----------------------+-------------------------+--------------------+---------------------+-------------------------+----------------------+-------------------------+-------------------+---------------------+-------------------------+-------------------------+----------------------------+----------------------+------------------------+----------------------------+\n",
      "|       categoryTitle|avg_view_to_like_ratio|avg_like_to_comment_ratio|avg_engagement_rate|avg_comments_per_view|avg_average_views_per_day|stddev_view_to_like_ratio|stddev_like_to_comment_ratio|stddev_engagement_rate|stddev_comments_per_view|stddev_average_views_per_day|min_view_to_like_ratio|min_like_to_comment_ratio| min_engagement_rate|min_comments_per_view|min_average_views_per_day|max_view_to_like_ratio|max_like_to_comment_ratio|max_engagement_rate|max_comments_per_view|max_average_views_per_day|median_view_to_like_ratio|median_like_to_comment_ratio|median_engagement_rate|median_comments_per_view|median_average_views_per_day|\n",
      "+--------------------+----------------------+-------------------------+-------------------+---------------------+-------------------------+-------------------------+----------------------------+----------------------+------------------------+----------------------------+----------------------+-------------------------+--------------------+---------------------+-------------------------+----------------------+-------------------------+-------------------+---------------------+-------------------------+-------------------------+----------------------------+----------------------+------------------------+----------------------------+\n",
      "|           Education|     57.20983060790685|        24.22762550064578| 6.3610540219626435| 0.004566668954540368|        480069.6768414369|        798.0685453354619|           41.00208305695552|    2.8032270737638343|    0.004706931089395399|          1430012.8398309206|                   0.0|                      0.0|                 0.0|                  0.0|                      0.0|    25118.059701492537|                  800.125|  24.65238293073773|  0.08388601135299402|              6.9618683E7|        18.37872557965677|          14.965614530065244|     5.816320927265892|    0.003388803324057...|                   280458.25|\n",
      "|              Gaming|     26.64151393942163|       22.633539541112995|  5.659747606899841|  0.00406420391392757|        489629.1934400449|        38.66248488518345|          120.08489915060535|     3.047257353430549|    0.004315376481810695|           996252.0853717576|     2.694018067784583|                      0.0|                 0.0|                  0.0|                  13904.5|     2092.328607594937|                  18615.0|  44.88054043418377|   0.1273043870926394|               6.109721E7|        20.47191233093099|           15.70304114490161|     5.253330561811674|    0.003066632491917...|                    244497.2|\n",
      "|       Entertainment|     77.57364438265536|       28.975508795531525|  5.444303681288115| 0.003703096306266...|        887969.3080192516|       1212.9054914186822|          193.74052938842306|     3.549102090035497|    0.004141904692384023|          2217588.5220988803|                   0.0|                      0.0|                 0.0|                  0.0|                      0.0|    139748.70212765958|                  38125.0|  41.50995748489595|  0.09602659962251536|              6.4038454E7|        21.96171911032464|          15.589912970535808|    4.8634752483178465|    0.002632606664156...|           309491.6666666667|\n",
      "|     Travel & Events|     32.45266404225631|        18.97849231009528|  5.352126599270304| 0.004039815733846079|       295930.22179493424|        46.78120402351537|           27.70177566613599|     2.628792387142388|    0.003656331329399...|           743200.1423327419|     5.615537856754247|                      0.0|0.005752264626867...|                  0.0|       29705.714285714286|     566.2142130689042|       471.36576889661166| 17.985547574993806|  0.03295641797829422|              2.0580231E7|       20.850317327266197|          14.096518289995593|    5.1371942997708935|    0.002918872513950...|                    170877.5|\n",
      "|Science & Technology|     69.68083972158797|       22.676339826657962|   4.87674148103927| 0.003329458063163...|        778421.4302374717|         617.464321463924|           39.80230073218135|    2.5091514738160723|    0.003042168230531...|          1767745.9204739046|     4.277695877695877|                      0.0|                 0.0|                  0.0|        6101.777777777777|      17051.4175911252|        911.0555555555555|  24.23464503612182|  0.05915407680774997|               7.293155E7|       23.212610169491526|          14.549415774099318|      4.58537897639384|    0.002728157964818553|                    306693.5|\n",
      "|              Sports|     78.09777654704456|       12.134581088808817|  2.334386249016457| 0.002781742409459...|        536418.1365431664|        188.2532263893306|          21.924292694024654|    1.7123886626660072|    0.003003496725583...|           939702.3927226743|     5.693406555829874|                      0.0|                 0.0|                  0.0|                  6093.48|    14604.296998420221|        627.9371980676328|  18.58493906754582|  0.08077842222032035|              3.4983323E7|        67.56148107211936|           7.342896174863388|    1.7319909129229725|    0.002110666467593...|                   259108.25|\n",
      "|       Howto & Style|    32.857396984261506|       21.663083023004166| 6.3129812327268935|  0.00478428810026406|         349567.686438965|        187.2679659359725|           44.68890460614442|    2.8857804094661943|    0.004423344850089997|           602525.0587107091|                   0.0|                      0.0|0.005929433116731...|                  0.0|                      0.0|     5123.588235294118|       1063.0821529745042| 31.900020842351655|  0.06976576403251407|              1.1134498E7|       18.278256666398132|          14.586028065893837|     5.868890304091705|    0.003674611527921...|                    199336.5|\n",
      "|Nonprofits & Acti...|     35.42411759213455|        15.89669387704344|  7.137742967884617| 0.006652434429801499|        579581.0092497508|       31.562982325570417|          16.195473197238716|     6.892440946751949|     0.00993093582337297|           784973.8563053559|     3.941309463387625|        1.816453723901527|                 0.0|                  0.0|       20269.166666666668|     85.42454936143719|        59.44243002544529| 30.049168812924375|  0.04676890657925544|                4362378.0|       22.048669979538147|           8.434326967862134|     5.309700681214861|    0.003269242005301711|          260602.34782608695|\n",
      "|    Film & Animation|      62.3440720551534|       21.471462256055787|  6.201660488804179| 0.004460058493903198|        770290.9982196275|        381.6513730429432|          165.91429202116868|     4.258393492735968|    0.005782148422715552|          1598866.4176543567|     2.676495807926829|                      0.0|                 0.0|                  0.0|                      0.0|    18837.914705882355|       16571.333333333332|  39.44113197472635|  0.11974299676653098|              5.3229598E7|       19.159648048281323|            14.6019341348667|     5.574905005361574|    0.003291005725870524|                    321628.0|\n",
      "|      People & Blogs|    47.876216621229844|        33.89057470499856|  6.654133371849375| 0.004512726510777208|        456798.9230248631|        948.2639548099589|           325.9419561073226|    3.8306470169840794|    0.005159136625572673|           786892.4759591249|    2.8891909240120794|                      0.0|                 0.0|                  0.0|                      0.0|     64995.07142857143|                  37632.0| 37.947410406089475|  0.10138151887121954|              2.2403513E7|        17.48334371854479|          16.462358427714857|     6.072427043724868|    0.003164794220217...|                    226961.5|\n",
      "|     News & Politics|    115.78373811644745|        8.012079221022944| 1.8001111528288616| 0.004597047980258767|       418346.11461412883|       107.17527603392165|           92.31088295821134|    1.3954895002869843|    0.004680743248250192|          1118427.2104752043|     5.338977337551211|                      0.0|                 0.0|                  0.0|                 9952.125|    1925.0683229813665|                   3464.0| 19.364761562483306|   0.0418368326600545|              6.9880692E7|        97.85355163078509|           2.826321883442686|    1.4850212421346256|    0.003265736753646...|           219155.7142857143|\n",
      "|      Pets & Animals|     38.54565741419394|       21.715645598625056|  5.339382159781284| 0.003708131444284146|       351053.49022509746|        52.87643091040175|          24.695820286610143|    3.1184713385277725|    0.004267239888553279|          295695.07976440975|     6.115382472561145|                      0.0| 0.03634476569803495|                  0.0|                   8063.4|    427.97257992895203|       289.95478723404256| 16.477240887439823|  0.04644021751153705|                2676071.0|        20.86275898707278|          17.196136701337295|     5.082982593117828|    0.002850932839462...|                    266268.0|\n",
      "|    Autos & Vehicles|    149.80836107034742|       14.594315984367666|  5.354673485520131| 0.004206645819779544|       301016.26919627836|       3848.2597362500437|           9.632151588758578|     2.531388053436561|    0.003237810938827...|           540084.8004643279|      3.69242445768808|                      0.0|0.001197813059533971|                  0.0|       23101.545454545456|    132594.58823529413|                    347.3| 27.900724788831084|  0.05641694817551533|              2.4615975E7|        21.04472049689441|          13.263399693721286|     5.153047563203509|    0.003524970963995354|          197654.66666666666|\n",
      "|               Music|    21.405362097748274|       32.437601804561915|  7.603008276250007| 0.005232904666079...|        1166978.866177091|       25.028682673274893|           979.8740439516157|     4.927848873723953|    0.007072991757749969|          3018167.8090377576|                   0.0|                      0.0|                 0.0|                  0.0|                      0.0|     2205.920099255583|                 170676.0|  56.94730741123403|  0.43700599982131116|             1.33484128E8|       16.657747549247414|           16.68753585771658|     6.403165534889792|    0.003559286559450...|                    393168.0|\n",
      "|              Comedy|    21.302494608841535|        35.05924941867323|  8.097748584784728| 0.004981746623803...|        421703.1571358864|       144.38817662130847|           78.22810429179482|    3.8820619993870618|    0.004615865149532021|           660555.6437355613|    3.5962499971291626|                      0.0|                 0.0|                  0.0|       16801.333333333332|     6961.815730337079|       1549.3876792352628| 30.260353974410414|  0.06684925778799916|               1.484518E7|       13.879930534581698|          17.347876004592422|     7.659180939844863|    0.003862158868980...|          250137.22222222222|\n",
      "+--------------------+----------------------+-------------------------+-------------------+---------------------+-------------------------+-------------------------+----------------------------+----------------------+------------------------+----------------------------+----------------------+-------------------------+--------------------+---------------------+-------------------------+----------------------+-------------------------+-------------------+---------------------+-------------------------+-------------------------+----------------------------+----------------------+------------------------+----------------------------+\n",
      "\n"
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    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "                                                                                \r"
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   ],
   "source": [
    "# show the dataframe\n",
    "eng_metrics_by_category.show()"
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      "                                                                                \r"
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            "gridcolor": "#506784",
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        },
        "title": {
         "text": "median_average_views_per_day"
        },
        "xaxis": {
         "tickangle": -45,
         "title": {
          "text": "Category Title"
         }
        },
        "yaxis": {
         "title": {
          "text": "median_average_views_per_day"
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   ],
   "source": [
    "# graph one by one of the columns on bar chart\n",
    "\n",
    "# convert the spark dataframe to pandas dataframe\n",
    "eng_metrics_by_category_pd = eng_metrics_by_category.toPandas()\n",
    "\n",
    "import plotly.graph_objects as go\n",
    "import numpy as np\n",
    "\n",
    "\n",
    "# Assuming eng_metrics_by_category_pd is the pandas DataFrame converted from Spark DataFrame\n",
    "\n",
    "def plot_bar_chart(df, column_name):\n",
    "    # Create a bar chart using Plotly, with colors based on the column values\n",
    "    fig = go.Figure(data=[go.Bar(\n",
    "        x=df['categoryTitle'],\n",
    "        y=df[column_name],\n",
    "        marker=dict(color=df[column_name], colorscale='Viridis')  # Apply color based on column value\n",
    "    )])\n",
    "    fig.update_layout(title_text=column_name, xaxis_title='Category Title', yaxis_title=column_name)\n",
    "    # Hide legend (since it's not needed here)\n",
    "    fig.update_layout(showlegend=False)\n",
    "\n",
    "    # vertical text\n",
    "    fig.update_layout(xaxis_tickangle=-45)\n",
    "\n",
    "    # add mean line, full width of paper\n",
    "    fig.add_shape(\n",
    "        type=\"line\",\n",
    "        x0=-0.5,\n",
    "        y0=df[column_name].mean(),\n",
    "        x1=len(df['categoryTitle']) - 0.5,\n",
    "        y1=df[column_name].mean(),\n",
    "        line=dict(\n",
    "            color=\"red\",\n",
    "            width=2\n",
    "        )\n",
    "    )\n",
    "\n",
    "    fig.show()\n",
    "\n",
    "for column in eng_metrics_by_category_pd.columns:\n",
    "    if column != \"categoryTitle\":\n",
    "        plot_bar_chart(eng_metrics_by_category_pd, column)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 196,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "[Stage 277:>                                                        (0 + 1) / 1]\r"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "+-------+-----------------+-----------------+-----------------+------------------+\n",
      "|summary|       view_count|            likes|         dislikes|     comment_count|\n",
      "+-------+-----------------+-----------------+-----------------+------------------+\n",
      "|  count|           260787|           260787|           260787|            260787|\n",
      "|   mean|2692467.785077477|131219.9604351444|1169.073017443354|10208.705188525502|\n",
      "| stddev|8729430.316258594| 452251.692125242|8167.300333295543| 73606.70150388542|\n",
      "|    min|                0|                0|                0|                 0|\n",
      "|    max|        277791741|         16021534|           879354|           6738537|\n",
      "+-------+-----------------+-----------------+-----------------+------------------+\n",
      "\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "                                                                                \r"
     ]
    }
   ],
   "source": [
    "df.describe([\"view_count\", \"likes\", \"dislikes\", \"comment_count\"]).show()\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Category Distribution"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 197,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "[Stage 281:>                                                        (0 + 1) / 1]\r"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "+--------------------+-----+\n",
      "|       categoryTitle|count|\n",
      "+--------------------+-----+\n",
      "|       Entertainment|52387|\n",
      "|              Gaming|51741|\n",
      "|               Music|42139|\n",
      "|              Sports|30298|\n",
      "|      People & Blogs|22036|\n",
      "|              Comedy|12840|\n",
      "|    Film & Animation|10514|\n",
      "|     News & Politics| 9328|\n",
      "|Science & Technology| 7909|\n",
      "|       Howto & Style| 6853|\n",
      "|           Education| 6456|\n",
      "|    Autos & Vehicles| 5303|\n",
      "|     Travel & Events| 1654|\n",
      "|      Pets & Animals| 1209|\n",
      "|Nonprofits & Acti...|  120|\n",
      "+--------------------+-----+\n",
      "\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "                                                                                \r"
     ]
    }
   ],
   "source": [
    "from pyspark.sql.functions import col\n",
    "\n",
    "df.groupBy(\"categoryTitle\").count().orderBy(col(\"count\").desc()).show()\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Correlation Analysis"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 200,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "                                                                                \r"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Correlation between view_count and likes:  0.8775228350162698\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "                                                                                \r"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Correlation between view_count and dislikes:  0.35551205161845817\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "                                                                                \r"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Correlation between view_count and comment_count:  0.5225916085460038\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "                                                                                \r"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Correlation between likes and view_count:  0.8775228350162697\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "                                                                                \r"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Correlation between likes and dislikes:  0.38891483068449223\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "                                                                                \r"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Correlation between likes and comment_count:  0.6891492201977686\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "                                                                                \r"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Correlation between dislikes and view_count:  0.3555120516184583\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "                                                                                \r"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Correlation between dislikes and likes:  0.38891483068449223\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "                                                                                \r"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Correlation between dislikes and comment_count:  0.417436511796521\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "                                                                                \r"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Correlation between comment_count and view_count:  0.5225916085460038\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "                                                                                \r"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Correlation between comment_count and likes:  0.6891492201977686\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "[Stage 333:>                                                        (0 + 1) / 1]\r"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Correlation between comment_count and dislikes:  0.417436511796521\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "                                                                                \r"
     ]
    }
   ],
   "source": [
    "numeric_features = [\"view_count\", \"likes\", \"dislikes\", \"comment_count\"]\n",
    "for i in numeric_features:\n",
    "    for j in numeric_features:\n",
    "        if i != j:  # Avoid comparing a variable with itself\n",
    "            print(f\"Correlation between {i} and {j}: \", df.stat.corr(i, j))\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 201,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "[Stage 340:>                                                        (0 + 1) / 1]\r"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Pearson correlation matrix:\n",
      "DenseMatrix([[1.        , 0.87752284, 0.35551205, 0.52259161],\n",
      "             [0.87752284, 1.        , 0.38891483, 0.68914922],\n",
      "             [0.35551205, 0.38891483, 1.        , 0.41743651],\n",
      "             [0.52259161, 0.68914922, 0.41743651, 1.        ]])\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "                                                                                \r"
     ]
    }
   ],
   "source": [
    "# build a correlation matrix\n",
    "from pyspark.ml.feature import VectorAssembler\n",
    "\n",
    "assembler = VectorAssembler(inputCols=numeric_features, outputCol=\"features\")\n",
    "df_vector = assembler.transform(df)\n",
    "\n",
    "from pyspark.ml.stat import Correlation\n",
    "\n",
    "pearson_corr = Correlation.corr(df_vector, \"features\").head()\n",
    "\n",
    "print(\"Pearson correlation matrix:\\n\" + str(pearson_corr[0]))\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 202,
   "metadata": {},
   "outputs": [
    {
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         "type": "heatmap",
         "x": [
          "view_count",
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          "comment_count"
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         "y": [
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   "source": [
    "# use plotly go.Figure to visualize the correlation matrix\n",
    "import plotly.graph_objects as go\n",
    "\n",
    "fig = go.Figure(data=go.Heatmap(\n",
    "    z=pearson_corr[0].toArray(),\n",
    "    x=numeric_features,\n",
    "    y=numeric_features,\n",
    "    colorscale='Viridis'))\n",
    "\n",
    "# add labels with values\n",
    "for i in range(len(numeric_features)):\n",
    "    for j in range(len(numeric_features)):\n",
    "        fig.add_annotation(\n",
    "            x=i, y=j,\n",
    "            text=str(round(pearson_corr[0].toArray()[i][j], 2)),\n",
    "            showarrow=False,\n",
    "            # add outline to text\n",
    "            font=dict(color=\"white\", size=18),\n",
    "            bgcolor=\"black\",\n",
    "        )\n",
    "\n",
    "\n",
    "# change style of labels to Monospace white font with black outline\n",
    "fig.update_yaxes(tickfont=dict(color='white', family='Courier New, monospace', size=18))\n",
    "fig.update_xaxes(tickfont=dict(color='white', family='Courier New, monospace', size=18))\n",
    "\n",
    "fig.update_layout(\n",
    "    title=\"Correlation matrix of numerical features\",\n",
    "    title_x=0.5,\n",
    "    width=800,\n",
    "    height=800,\n",
    "    # change label font\n",
    "    font=dict(\n",
    "        family=\"Courier New, monospace\",\n",
    "        size=18,\n",
    "        color=\"white\"\n",
    "    )\n",
    ")\n",
    "\n",
    "\n",
    "\n",
    "\n",
    "fig.show()\n",
    "\n",
    "# save the correlation matrix as an image\n",
    "fig.write_image(\"charts/eng_metrics/correlation_matrix.png\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Time Series Analysis\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 203,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "[Stage 342:>                                                        (0 + 1) / 1]\r"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "+----------------+---------------+\n",
      "|publishedAt_date|sum(view_count)|\n",
      "+----------------+---------------+\n",
      "|      2020-08-03|        8257287|\n",
      "|      2020-08-05|       15711937|\n",
      "|      2020-08-06|       92448003|\n",
      "|      2020-08-07|      637964497|\n",
      "|      2020-08-08|      305669994|\n",
      "|      2020-08-09|      255042172|\n",
      "|      2020-08-10|      178660898|\n",
      "|      2020-08-11|      525409368|\n",
      "|      2020-08-12|      120581624|\n",
      "|      2020-08-13|      574566491|\n",
      "|      2020-08-14|      907164535|\n",
      "|      2020-08-15|      407042731|\n",
      "|      2020-08-16|      305527729|\n",
      "|      2020-08-17|      772416732|\n",
      "|      2020-08-18|      695655425|\n",
      "|      2020-08-19|      366439033|\n",
      "|      2020-08-20|      355228147|\n",
      "|      2020-08-21|     1954903659|\n",
      "|      2020-08-22|      315550934|\n",
      "|      2020-08-23|      521486151|\n",
      "+----------------+---------------+\n",
      "only showing top 20 rows\n",
      "\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "                                                                                \r"
     ]
    }
   ],
   "source": [
    "from pyspark.sql.functions import to_date\n",
    "\n",
    "df.withColumn(\"publishedAt_date\", to_date(\"publishedAt\")).groupBy(\"publishedAt_date\").sum(\"view_count\").orderBy(\"publishedAt_date\").show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Distribution"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 204,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "[Stage 346:>                                                        (0 + 1) / 1]\r"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "+-------+-----------------+-----------------+-----------------+------------------+\n",
      "|summary|       view_count|            likes|         dislikes|     comment_count|\n",
      "+-------+-----------------+-----------------+-----------------+------------------+\n",
      "|  count|           260787|           260787|           260787|            260787|\n",
      "|   mean|2692467.785077477|131219.9604351444|1169.073017443354|10208.705188525502|\n",
      "| stddev|8729430.316258594| 452251.692125242|8167.300333295543| 73606.70150388542|\n",
      "|    min|                0|                0|                0|                 0|\n",
      "|    max|        277791741|         16021534|           879354|           6738537|\n",
      "+-------+-----------------+-----------------+-----------------+------------------+\n",
      "\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "                                                                                \r"
     ]
    }
   ],
   "source": [
    "# For numerical columns\n",
    "numerical_cols = ['view_count', 'likes', 'dislikes', 'comment_count']\n",
    "df.select(numerical_cols).describe().show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 205,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "                                                                                \r"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1000x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "                                                                                \r"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1000x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "                                                                                \r"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1000x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "                                                                                \r"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1000x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "\n",
    "def plot_histograms(df, columns, bins=50):\n",
    "    \"\"\"\n",
    "    Plots histograms for the specified continuous variables in a Spark DataFrame.\n",
    "    \n",
    "    Parameters:\n",
    "    - df: Spark DataFrame containing the data.\n",
    "    - columns: List of column names (strings) for which to plot histograms.\n",
    "    - bins: Number of bins to use in the histograms (default is 50).\n",
    "    \"\"\"\n",
    "    for column in columns:\n",
    "        # Aggregate data in Spark\n",
    "        data = df.select(column).rdd.flatMap(lambda x: x).collect()\n",
    "        \n",
    "        # Plot using Matplotlib in Python\n",
    "        plt.figure(figsize=(10, 6))\n",
    "        plt.hist(data, bins=bins, color='skyblue', edgecolor='black')\n",
    "        plt.title(f'{column.capitalize()} Distribution')\n",
    "        plt.xlabel(column.capitalize())\n",
    "        plt.ylabel('Frequency')\n",
    "        plt.show()\n",
    "\n",
    "# Example usage with your DataFrame and continuous variables\n",
    "continuous_vars = ['view_count', 'likes', 'dislikes', 'comment_count']\n",
    "plot_histograms(df, continuous_vars)\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "above plots show that all continuous variables are heaviliy right-tail skewed, therefore log transformation might be beneficial"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Transformations"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 206,
   "metadata": {},
   "outputs": [],
   "source": [
    "from pyspark.sql.functions import log1p\n",
    "\n",
    "# Apply log transformation to each specified column\n",
    "for column in continuous_vars:\n",
    "    # Add a new column with the log transformation applied\n",
    "    df = df.withColumn(column + '_log', log1p(col(column)))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 207,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "                                                                                \r"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1000x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "                                                                                \r"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1000x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "                                                                                \r"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1000x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "                                                                                \r"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1000x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Replot histograms for the log-transformed variables\n",
    "plot_histograms(df, continuous_vars)\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## save transformed data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 210,
   "metadata": {},
   "outputs": [],
   "source": [
    "# subset columns\n",
    "# 'video_id', 'title', 'categoryTitle', 'tags', 'view_count', 'likes', 'dislikes', 'comment_count' + logged versions\n",
    "\n",
    "df = df.select('video_id', 'title', 'categoryTitle', 'tags', 'view_count', 'likes', 'dislikes', 'comment_count', 'view_count_log', 'likes_log', 'dislikes_log', 'comment_count_log')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 211,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "                                                                                \r"
     ]
    }
   ],
   "source": [
    "# save parquet file\n",
    "df.write.parquet(\"data/processed/tranformed_US_youtube_trending_data.parquet\", mode=\"overwrite\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 212,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "root\n",
      " |-- video_id: string (nullable = true)\n",
      " |-- title: string (nullable = true)\n",
      " |-- categoryTitle: string (nullable = true)\n",
      " |-- tags: string (nullable = true)\n",
      " |-- view_count: integer (nullable = true)\n",
      " |-- likes: integer (nullable = true)\n",
      " |-- dislikes: integer (nullable = true)\n",
      " |-- comment_count: integer (nullable = true)\n",
      " |-- view_count_log: double (nullable = true)\n",
      " |-- likes_log: double (nullable = true)\n",
      " |-- dislikes_log: double (nullable = true)\n",
      " |-- comment_count_log: double (nullable = true)\n",
      "\n"
     ]
    }
   ],
   "source": [
    "# df_with_categories to pandas\n",
    "# df_with_categories = df_with_categories.toPandas()\n",
    "df.head(5)\n",
    "\n",
    "df.printSchema()"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "base",
   "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": "3.11.5"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}