{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "![](images/python_with_Birds.gif)\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "tags": []
   },
   "source": [
    "# การวิเคราะห์ข้อมูลเบื้องต้น (Introduction to Data Analysis)\n",
    "**30** minutes\n",
    "\n",
    "<font size=\"4\"> **วัตถุประสงค์**\n",
    "</font>\n",
    "\n",
    "<B> หลังจากทำทำแล็บ นศ.จะสามารถ </B>\n",
    "\n",
    "\n",
    "* วิเคราะห์ข้อมูลและแสดงผลโดยใช้ Pandas เบื้องต้นได้\n",
    "\n",
    "Ref: \n",
    "* http://pandas.pydata.org/pandas-docs/stable/getting_started/index.html\n",
    "* https://www.kaggle.com/leonardodata/analysis-from-2010-2019-spotify"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "tags": []
   },
   "source": [
    "## Dataset"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "tags": []
   },
   "source": [
    "ตอนนี้ในมือของคุณมีชุดข้อมูล (Dataset) เพลง เป็นข้อมูลเพลงฮิตในแต่ละปีตั้งแต่ปี 2010 ถึงปี 2019 โดยข้อมูลอยู่ในรูปแบบของตาราง แต่ละแถว (row) ในตารางเป็นข้อมูลของเพลงแต่ละเพลง และแต่ละคอลัมน์ (column) มีข้อมูลดังต่อไปนี้\n",
    "\n",
    "* **artist** - ชื่อศิลปิน (นักร้อง วงดนตรี)\n",
    "* Top genre คือแนวเพลงหรือประเภทของแนวดนตรี\n",
    "* Year คือปีของเพลงที่อยู่ในบิลบอร์ด (Billboard)\n",
    "* Bpm (Tempo) คือจังหวะเร็วช้าขนาดไหน หน่วยเป็น bpm (Beats.Per.Minute)\n",
    "* Nrgy (Energy) คือพลังหรือความพุ่งของเพลง\n",
    "* Dnce (Danceability) คือความดิ้น หรือความน่าเต้นของเพลง\n",
    "* dB (Loudness) คือระดับความดังในหน่วย decibel \n",
    "* Live (Liveness) คือระดับของการแสดงสด (Live) ของเพลง \n",
    "* Val (Valence) คือระดับความ positive ในเพลง (ค่าต่ำ: เศร้า-หดหู่-โกรธ,คาสูง: มีความสุข-ให้กำลังใจ)\n",
    "* Dur (Length) - คือความยาว (ระยะเวลา) ของเพลง/ดนตรี\n",
    "* Acous (Acousticness) คือความ “acoustic” ของเพลง\n",
    "* Spch (Speechiness) คือปริมาณของคำพูดหรือเนื้อร้อง\n",
    "* Popularity คือระดับความนิยม ยิ่งค่าสูงเท่าไหร่ ยิ่งเป็นที่นิยม\n",
    "\n",
    "<br>\n",
    "\n",
    "ชุดข้อมูลที่ได้รับอยู่ในรูปตาราง (Format CSV)\n",
    "\n",
    "(Source: spotifycharts.com, kaggle.com)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "|#|title                                                                                               |artist                  |top genre                |year|bpm|nrgy|dnce|dB |live|val|dur|acous|spch|pop|\n",
    "|------|----------------------------------------------------------------------------------------------------|------------------------|-------------------------|----|---|----|----|---|----|---|---|-----|----|---|\n",
    "|1     |Memories                                                                                            |Maroon 5                |pop                      |2019|91 |32  |76  |-7 |8   |57 |189|84   |5   |99 |\n",
    "|2     |Lose You To Love Me                                                                                 |Selena Gomez            |dance pop                |2019|102|34  |51  |-9 |21  |9  |206|58   |4   |97 |\n",
    "|3     |Someone You Loved                                                                                   |Lewis Capaldi           |pop                      |2019|110|41  |50  |-6 |11  |45 |182|75   |3   |96 |\n",
    "|4     |Senorita                                                                                            |Shawn Mendes            |canadian pop             |2019|117|54  |76  |-6 |9   |75 |191|4    |3   |95 |\n",
    "|5     |How Do You Sleep?                                                                                   |Sam Smith               |pop                      |2019|111|68  |48  |-5 |8   |35 |202|15   |9   |93 |\n",
    "|6     |South of the Border (feat. Camila Cabello & Cardi B)                                                |Ed Sheeran              |pop                      |2019|98 |62  |86  |-6 |9   |67 |204|15   |8   |92 |\n",
    "|7     |Trampoline (with ZAYN)                                                                              |SHAED                   |electropop               |2019|127|46  |62  |-6 |14  |50 |184|56   |3   |92 |\n",
    "|8     |Happier                                                                                             |Marshmello              |brostep                  |2019|100|79  |69  |-3 |17  |67 |214|19   |5   |90 |\n",
    "|9     |Truth Hurts                                                                                         |Lizzo                   |escape room              |2019|158|62  |72  |-3 |12  |41 |173|11   |11  |90 |\n",
    "|10    |Good as Hell (feat. Ariana Grande) - Remix                                                          |Lizzo                   |escape room              |2019|96 |89  |67  |-3 |74  |48 |159|30   |6   |90 |\n",
    "|11    |Underneath the Tree                                                                                 |Kelly Clarkson          |dance pop                |2013|160|81  |51  |-5 |21  |69 |230|0    |5   |88 |\n",
    "|12    |Higher Love                                                                                         |Kygo                    |edm                      |2019|104|68  |69  |-7 |10  |40 |228|2    |3   |88 |\n",
    "|13    |Shape of You                                                                                        |Ed Sheeran              |pop                      |2017|96 |65  |83  |-3 |9   |93 |234|58   |8   |87 |\n",
    "|14    |Only Human                                                                                          |Jonas Brothers          |boy band                 |2019|94 |50  |80  |-6 |6   |87 |183|11   |7   |87 |\n",
    "|15    |All of Me                                                                                           |John Legend             |neo mellow               |2014|120|26  |42  |-7 |13  |33 |270|92   |3   |86 |\n",
    "|16    |Closer                                                                                              |The Chainsmokers        |electropop               |2017|95 |52  |75  |-6 |11  |66 |245|41   |3   |86 |\n",
    "|17    |One Kiss (with Dua Lipa)                                                                            |Calvin Harris           |dance pop                |2018|124|86  |79  |-3 |8   |59 |215|4    |11  |86 |\n",
    "|18    |Beautiful People (feat. Khalid)                                                                     |Ed Sheeran              |pop                      |2019|93 |65  |64  |-8 |8   |55 |198|12   |19  |86 |\n",
    "|19    |Sucker                                                                                              |Jonas Brothers          |boy band                 |2019|138|73  |84  |-5 |11  |95 |181|4    |6   |86 |\n",
    "|20    |Don't Call Me Up                                                                                    |Mabel                   |dance pop                |2019|99 |88  |67  |-3 |8   |23 |178|30   |15  |86 |\n",
    "\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "tags": []
   },
   "source": [
    "## Pandas คือ ?\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "[Pandas](https://pypi.org/project/pandas/)<sup>*</sup> เป็นไลบรารี่ที่ได้รับความนิยมอย่างมากอันหนึ่งของภาษาไพทอน ใช้ในการจัดการข้อมูล (Data wrangling/ Data cleaning) และการวิเคราะห์ข้อมูล (Data analysis) สามารถจัดการกับข้อมูลที่มีขนาดใหญ่ๆ ได้โดยที่ไม่มีปัญหา (ในขณะที่โปรแกรม Spreadsheets อย่าง Excel มีปัญหาเรื่องการประมวลผลช้าและไม่เสถียร)\n",
    "\n",
    "เนื่องจาก Pandas ไม่ใช่โมดูลมาตรฐานของไพทอน ดังนั้น ก่อนจะใช้งานจำเป็นต้องติดตั้งลงเครื่องก่อน (pip install หรือ conda install)\n",
    "\n",
    "เราจะเริ่มต้นเขียนโปรแกรมโดยการ import เข้ามา ณ ที่นี้จะตั้งชื่อว่า pd เพื่อให้เวลาเรียกใช้งานฟังก์ชันจะได้เขียนง่ายๆ เช่น <code>pd.read_csv()</code> \n",
    "\n",
    "(<sup>*</sup>Pandas มาจาก Panel data ซึ่งหมายถึงข้อมูลที่มีหลายมิติ)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Import ไลบรารี่ที่จะใช้งาน"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "#import matplotlib as mpl\n",
    "%matplotlib inline"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**โหลดชุดข้อมูลไฟล์ CSV เข้าสู่โปรแกรมในรูปแบบ DataFrame**\n",
    "\n",
    "_The top songs BY YEAR in the world by spotify. This dataset has several variables about the songs and is based on Billboard._\n",
    "\n",
    "(ชุดข้อมูลข้างต้นสามารถดาวโหลดได้จาก spotifycharts.com หรือ [kaggle.com](https://www.kaggle.com/leonardopena/top-spotify-songs-from-20102019-by-year) โดยข้อมูลดิบจะเรียงตามปี (Year) ในรูปของไฟล์ CSV (Comma-Separated Values) )\n",
    "\n",
    "\n",
    "ก่อนอื่น เราจะโหลดไฟล์ข้อมูล csv ที่อยู่ในเครื่องของเราเข้าสู่ไพทอนในรูปแบบ DataFrame (DataFrame คือ ตารางข้อมูลที่ถูกแบ่งเป็นแถวและคอลัมน์เหมือน Excel) โดยใช้ฟังก์ชัน <code>read_csv()</code>\n",
    "\n",
    "ตัวแปร <code>csv_path</code> เก็บที่อยู่ของไฟล์ (path) <b>.csv</b> ส่งเป็นอาร์กิวเมนต์ให้กับฟังก์ชั่น <code>read_csv</code>  ผลลัพธ์จะถูกเก็บในออบเจ็กต์ชื่อ  <code>df</code> ซึ่งเป็นชื่อย่อของตัวแปรที่นิยมใช้เก็บ DataFrame"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "# Read data from CSV file\n",
    "csv_path = 'docs/Top_Spotify_songs_from_2010_2019.csv'\n",
    "df = pd.read_csv(csv_path, encoding='ISO-8859-1')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "tags": []
   },
   "source": [
    "แสดงตัวอย่างข้อมูล (Preview) ของ Dataframe ได้โดยใช้ฟังก์ชัน ใช้เมธอด <code>head()</code>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Unnamed: 0</th>\n",
       "      <th>title</th>\n",
       "      <th>artist</th>\n",
       "      <th>top genre</th>\n",
       "      <th>year</th>\n",
       "      <th>bpm</th>\n",
       "      <th>nrgy</th>\n",
       "      <th>dnce</th>\n",
       "      <th>dB</th>\n",
       "      <th>live</th>\n",
       "      <th>val</th>\n",
       "      <th>dur</th>\n",
       "      <th>acous</th>\n",
       "      <th>spch</th>\n",
       "      <th>pop</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>Hey, Soul Sister</td>\n",
       "      <td>Train</td>\n",
       "      <td>neo mellow</td>\n",
       "      <td>2010</td>\n",
       "      <td>97</td>\n",
       "      <td>89</td>\n",
       "      <td>67</td>\n",
       "      <td>-4</td>\n",
       "      <td>8</td>\n",
       "      <td>80</td>\n",
       "      <td>217</td>\n",
       "      <td>19</td>\n",
       "      <td>4</td>\n",
       "      <td>83</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2</td>\n",
       "      <td>Love The Way You Lie</td>\n",
       "      <td>Eminem</td>\n",
       "      <td>detroit hip hop</td>\n",
       "      <td>2010</td>\n",
       "      <td>87</td>\n",
       "      <td>93</td>\n",
       "      <td>75</td>\n",
       "      <td>-5</td>\n",
       "      <td>52</td>\n",
       "      <td>64</td>\n",
       "      <td>263</td>\n",
       "      <td>24</td>\n",
       "      <td>23</td>\n",
       "      <td>82</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3</td>\n",
       "      <td>TiK ToK</td>\n",
       "      <td>Kesha</td>\n",
       "      <td>dance pop</td>\n",
       "      <td>2010</td>\n",
       "      <td>120</td>\n",
       "      <td>84</td>\n",
       "      <td>76</td>\n",
       "      <td>-3</td>\n",
       "      <td>29</td>\n",
       "      <td>71</td>\n",
       "      <td>200</td>\n",
       "      <td>10</td>\n",
       "      <td>14</td>\n",
       "      <td>80</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>4</td>\n",
       "      <td>Bad Romance</td>\n",
       "      <td>Lady Gaga</td>\n",
       "      <td>dance pop</td>\n",
       "      <td>2010</td>\n",
       "      <td>119</td>\n",
       "      <td>92</td>\n",
       "      <td>70</td>\n",
       "      <td>-4</td>\n",
       "      <td>8</td>\n",
       "      <td>71</td>\n",
       "      <td>295</td>\n",
       "      <td>0</td>\n",
       "      <td>4</td>\n",
       "      <td>79</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>5</td>\n",
       "      <td>Just the Way You Are</td>\n",
       "      <td>Bruno Mars</td>\n",
       "      <td>pop</td>\n",
       "      <td>2010</td>\n",
       "      <td>109</td>\n",
       "      <td>84</td>\n",
       "      <td>64</td>\n",
       "      <td>-5</td>\n",
       "      <td>9</td>\n",
       "      <td>43</td>\n",
       "      <td>221</td>\n",
       "      <td>2</td>\n",
       "      <td>4</td>\n",
       "      <td>78</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   Unnamed: 0                 title      artist        top genre  year  bpm  \\\n",
       "0           1      Hey, Soul Sister       Train       neo mellow  2010   97   \n",
       "1           2  Love The Way You Lie      Eminem  detroit hip hop  2010   87   \n",
       "2           3               TiK ToK       Kesha        dance pop  2010  120   \n",
       "3           4           Bad Romance   Lady Gaga        dance pop  2010  119   \n",
       "4           5  Just the Way You Are  Bruno Mars              pop  2010  109   \n",
       "\n",
       "   nrgy  dnce  dB  live  val  dur  acous  spch  pop  \n",
       "0    89    67  -4     8   80  217     19     4   83  \n",
       "1    93    75  -5    52   64  263     24    23   82  \n",
       "2    84    76  -3    29   71  200     10    14   80  \n",
       "3    92    70  -4     8   71  295      0     4   79  \n",
       "4    84    64  -5     9   43  221      2     4   78  "
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Print first five rows of the dataframe\n",
    "\n",
    "df.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "tags": []
   },
   "source": [
    "ในกรณีที่ข้อมูลเป็นไฟล์ excel (.xlsx, .xls) Pandas จะใช้ไลบรารี [xlrd](https://pypi.org/project/xlrd/) โดยเรียกใช้ใช้ฟังก์ชั่น <code>read_excel()</code> ซึ่งผลลัพท์ที่ได้จะเป็น Dataframe เช่นเดียวกัน"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# ตัวอย่างการวิเคราะห์ข้อมูลเพลงฮิตสปอติฟายในช่วง 2010~2019\n",
    "\n",
    "Ref: https://www.kaggle.com/scratchpad/notebook42c2f8a089\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## จัดเตรียมชุดข้อมูล (Data preparation)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "จากข้อมูลที่ได้มา เราจะเปลี่ยนชื่อของคอลัมน์จาก top genres เป็น top_genres และลบคอลัมน์ไม่มีชื่อ (Unnamed: 0) ทิ้ง เพื่อหลีกเลี่ยงปัญหาที่อาจเกิดขึ้นได้ในภายหลัง\n",
    "\n",
    "เนื่องจากชุดข้อมูลนี้ไม่มีช่องใดที่มีค่า NaN จึงพร้อมสำหรับการวิเคราะห์"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Index(['title', 'artist', 'top_genre', 'year', 'bpm', 'nrgy', 'dnce', 'dB',\n",
      "       'live', 'val', 'dur', 'acous', 'spch', 'pop'],\n",
      "      dtype='object')\n"
     ]
    }
   ],
   "source": [
    "df = df.rename(columns={'top genre': 'top_genre'})\n",
    "df = df.drop('Unnamed: 0', axis=1)\n",
    "print(df.columns)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>title</th>\n",
       "      <th>artist</th>\n",
       "      <th>top_genre</th>\n",
       "      <th>year</th>\n",
       "      <th>bpm</th>\n",
       "      <th>nrgy</th>\n",
       "      <th>dnce</th>\n",
       "      <th>dB</th>\n",
       "      <th>live</th>\n",
       "      <th>val</th>\n",
       "      <th>dur</th>\n",
       "      <th>acous</th>\n",
       "      <th>spch</th>\n",
       "      <th>pop</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Hey, Soul Sister</td>\n",
       "      <td>Train</td>\n",
       "      <td>neo mellow</td>\n",
       "      <td>2010</td>\n",
       "      <td>97</td>\n",
       "      <td>89</td>\n",
       "      <td>67</td>\n",
       "      <td>-4</td>\n",
       "      <td>8</td>\n",
       "      <td>80</td>\n",
       "      <td>217</td>\n",
       "      <td>19</td>\n",
       "      <td>4</td>\n",
       "      <td>83</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Love The Way You Lie</td>\n",
       "      <td>Eminem</td>\n",
       "      <td>detroit hip hop</td>\n",
       "      <td>2010</td>\n",
       "      <td>87</td>\n",
       "      <td>93</td>\n",
       "      <td>75</td>\n",
       "      <td>-5</td>\n",
       "      <td>52</td>\n",
       "      <td>64</td>\n",
       "      <td>263</td>\n",
       "      <td>24</td>\n",
       "      <td>23</td>\n",
       "      <td>82</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>TiK ToK</td>\n",
       "      <td>Kesha</td>\n",
       "      <td>dance pop</td>\n",
       "      <td>2010</td>\n",
       "      <td>120</td>\n",
       "      <td>84</td>\n",
       "      <td>76</td>\n",
       "      <td>-3</td>\n",
       "      <td>29</td>\n",
       "      <td>71</td>\n",
       "      <td>200</td>\n",
       "      <td>10</td>\n",
       "      <td>14</td>\n",
       "      <td>80</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Bad Romance</td>\n",
       "      <td>Lady Gaga</td>\n",
       "      <td>dance pop</td>\n",
       "      <td>2010</td>\n",
       "      <td>119</td>\n",
       "      <td>92</td>\n",
       "      <td>70</td>\n",
       "      <td>-4</td>\n",
       "      <td>8</td>\n",
       "      <td>71</td>\n",
       "      <td>295</td>\n",
       "      <td>0</td>\n",
       "      <td>4</td>\n",
       "      <td>79</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Just the Way You Are</td>\n",
       "      <td>Bruno Mars</td>\n",
       "      <td>pop</td>\n",
       "      <td>2010</td>\n",
       "      <td>109</td>\n",
       "      <td>84</td>\n",
       "      <td>64</td>\n",
       "      <td>-5</td>\n",
       "      <td>9</td>\n",
       "      <td>43</td>\n",
       "      <td>221</td>\n",
       "      <td>2</td>\n",
       "      <td>4</td>\n",
       "      <td>78</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                  title      artist        top_genre  year  bpm  nrgy  dnce  \\\n",
       "0      Hey, Soul Sister       Train       neo mellow  2010   97    89    67   \n",
       "1  Love The Way You Lie      Eminem  detroit hip hop  2010   87    93    75   \n",
       "2               TiK ToK       Kesha        dance pop  2010  120    84    76   \n",
       "3           Bad Romance   Lady Gaga        dance pop  2010  119    92    70   \n",
       "4  Just the Way You Are  Bruno Mars              pop  2010  109    84    64   \n",
       "\n",
       "   dB  live  val  dur  acous  spch  pop  \n",
       "0  -4     8   80  217     19     4   83  \n",
       "1  -5    52   64  263     24    23   82  \n",
       "2  -3    29   71  200     10    14   80  \n",
       "3  -4     8   71  295      0     4   79  \n",
       "4  -5     9   43  221      2     4   78  "
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### ตรวจสอบความสัมพันธ์ของแต่ละฟีเจอร์ (Features) ในชุดข้อมูล"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/var/folders/nb/qx4_7k_n2mx3zzwh39qtrg_c0000gn/T/ipykernel_60190/2964105268.py:1: FutureWarning: The default value of numeric_only in DataFrame.corr is deprecated. In a future version, it will default to False. Select only valid columns or specify the value of numeric_only to silence this warning.\n",
      "  df.corr() # corr() is used to find the pairwise correlation of all columns in the dataframe.\n"
     ]
    },
    {
     "data": {
      "text/html": [
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>year</th>\n",
       "      <th>bpm</th>\n",
       "      <th>nrgy</th>\n",
       "      <th>dnce</th>\n",
       "      <th>dB</th>\n",
       "      <th>live</th>\n",
       "      <th>val</th>\n",
       "      <th>dur</th>\n",
       "      <th>acous</th>\n",
       "      <th>spch</th>\n",
       "      <th>pop</th>\n",
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       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>year</th>\n",
       "      <td>1.000000</td>\n",
       "      <td>-0.104247</td>\n",
       "      <td>-0.225596</td>\n",
       "      <td>0.079269</td>\n",
       "      <td>-0.126471</td>\n",
       "      <td>-0.136331</td>\n",
       "      <td>-0.122025</td>\n",
       "      <td>-0.215344</td>\n",
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       "      <td>0.004778</td>\n",
       "      <td>0.241261</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>bpm</th>\n",
       "      <td>-0.104247</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.126170</td>\n",
       "      <td>-0.131301</td>\n",
       "      <td>0.183870</td>\n",
       "      <td>0.081579</td>\n",
       "      <td>0.016021</td>\n",
       "      <td>-0.029359</td>\n",
       "      <td>-0.113257</td>\n",
       "      <td>0.058999</td>\n",
       "      <td>0.018983</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>nrgy</th>\n",
       "      <td>-0.225596</td>\n",
       "      <td>0.126170</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.167209</td>\n",
       "      <td>0.537528</td>\n",
       "      <td>0.186738</td>\n",
       "      <td>0.409577</td>\n",
       "      <td>-0.143610</td>\n",
       "      <td>-0.562287</td>\n",
       "      <td>0.107313</td>\n",
       "      <td>-0.057645</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>dnce</th>\n",
       "      <td>0.079269</td>\n",
       "      <td>-0.131301</td>\n",
       "      <td>0.167209</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.233170</td>\n",
       "      <td>-0.028801</td>\n",
       "      <td>0.501696</td>\n",
       "      <td>-0.176841</td>\n",
       "      <td>-0.240064</td>\n",
       "      <td>-0.028041</td>\n",
       "      <td>0.116054</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>dB</th>\n",
       "      <td>-0.126471</td>\n",
       "      <td>0.183870</td>\n",
       "      <td>0.537528</td>\n",
       "      <td>0.233170</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.081934</td>\n",
       "      <td>0.282922</td>\n",
       "      <td>-0.104723</td>\n",
       "      <td>-0.190401</td>\n",
       "      <td>-0.001110</td>\n",
       "      <td>0.156897</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>live</th>\n",
       "      <td>-0.136331</td>\n",
       "      <td>0.081579</td>\n",
       "      <td>0.186738</td>\n",
       "      <td>-0.028801</td>\n",
       "      <td>0.081934</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.020226</td>\n",
       "      <td>0.098339</td>\n",
       "      <td>-0.098167</td>\n",
       "      <td>0.144103</td>\n",
       "      <td>-0.075749</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>val</th>\n",
       "      <td>-0.122025</td>\n",
       "      <td>0.016021</td>\n",
       "      <td>0.409577</td>\n",
       "      <td>0.501696</td>\n",
       "      <td>0.282922</td>\n",
       "      <td>0.020226</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>-0.262256</td>\n",
       "      <td>-0.249038</td>\n",
       "      <td>0.122013</td>\n",
       "      <td>0.038953</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>dur</th>\n",
       "      <td>-0.215344</td>\n",
       "      <td>-0.029359</td>\n",
       "      <td>-0.143610</td>\n",
       "      <td>-0.176841</td>\n",
       "      <td>-0.104723</td>\n",
       "      <td>0.098339</td>\n",
       "      <td>-0.262256</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.091802</td>\n",
       "      <td>0.054564</td>\n",
       "      <td>-0.104363</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>acous</th>\n",
       "      <td>0.101725</td>\n",
       "      <td>-0.113257</td>\n",
       "      <td>-0.562287</td>\n",
       "      <td>-0.240064</td>\n",
       "      <td>-0.190401</td>\n",
       "      <td>-0.098167</td>\n",
       "      <td>-0.249038</td>\n",
       "      <td>0.091802</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.002763</td>\n",
       "      <td>0.026704</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>spch</th>\n",
       "      <td>0.004778</td>\n",
       "      <td>0.058999</td>\n",
       "      <td>0.107313</td>\n",
       "      <td>-0.028041</td>\n",
       "      <td>-0.001110</td>\n",
       "      <td>0.144103</td>\n",
       "      <td>0.122013</td>\n",
       "      <td>0.054564</td>\n",
       "      <td>0.002763</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>-0.041490</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>pop</th>\n",
       "      <td>0.241261</td>\n",
       "      <td>0.018983</td>\n",
       "      <td>-0.057645</td>\n",
       "      <td>0.116054</td>\n",
       "      <td>0.156897</td>\n",
       "      <td>-0.075749</td>\n",
       "      <td>0.038953</td>\n",
       "      <td>-0.104363</td>\n",
       "      <td>0.026704</td>\n",
       "      <td>-0.041490</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "           year       bpm      nrgy      dnce        dB      live       val  \\\n",
       "year   1.000000 -0.104247 -0.225596  0.079269 -0.126471 -0.136331 -0.122025   \n",
       "bpm   -0.104247  1.000000  0.126170 -0.131301  0.183870  0.081579  0.016021   \n",
       "nrgy  -0.225596  0.126170  1.000000  0.167209  0.537528  0.186738  0.409577   \n",
       "dnce   0.079269 -0.131301  0.167209  1.000000  0.233170 -0.028801  0.501696   \n",
       "dB    -0.126471  0.183870  0.537528  0.233170  1.000000  0.081934  0.282922   \n",
       "live  -0.136331  0.081579  0.186738 -0.028801  0.081934  1.000000  0.020226   \n",
       "val   -0.122025  0.016021  0.409577  0.501696  0.282922  0.020226  1.000000   \n",
       "dur   -0.215344 -0.029359 -0.143610 -0.176841 -0.104723  0.098339 -0.262256   \n",
       "acous  0.101725 -0.113257 -0.562287 -0.240064 -0.190401 -0.098167 -0.249038   \n",
       "spch   0.004778  0.058999  0.107313 -0.028041 -0.001110  0.144103  0.122013   \n",
       "pop    0.241261  0.018983 -0.057645  0.116054  0.156897 -0.075749  0.038953   \n",
       "\n",
       "            dur     acous      spch       pop  \n",
       "year  -0.215344  0.101725  0.004778  0.241261  \n",
       "bpm   -0.029359 -0.113257  0.058999  0.018983  \n",
       "nrgy  -0.143610 -0.562287  0.107313 -0.057645  \n",
       "dnce  -0.176841 -0.240064 -0.028041  0.116054  \n",
       "dB    -0.104723 -0.190401 -0.001110  0.156897  \n",
       "live   0.098339 -0.098167  0.144103 -0.075749  \n",
       "val   -0.262256 -0.249038  0.122013  0.038953  \n",
       "dur    1.000000  0.091802  0.054564 -0.104363  \n",
       "acous  0.091802  1.000000  0.002763  0.026704  \n",
       "spch   0.054564  0.002763  1.000000 -0.041490  \n",
       "pop   -0.104363  0.026704 -0.041490  1.000000  "
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.corr() # corr() is used to find the pairwise correlation of all columns in the dataframe. "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### พล็อตข้อมูลตรวจสอบความสัมพันธ์กันระหว่างข้อมูล\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**พล็อต Heatmap ด้วย Seaborn**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [],
   "source": [
    "import seaborn as sn\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/var/folders/nb/qx4_7k_n2mx3zzwh39qtrg_c0000gn/T/ipykernel_60190/4252206390.py:2: FutureWarning: The default value of numeric_only in DataFrame.corr is deprecated. In a future version, it will default to False. Select only valid columns or specify the value of numeric_only to silence this warning.\n",
      "  sn.heatmap(df.corr(),\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 800x700 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(8, 7))\n",
    "sn.heatmap(df.corr(),\n",
    "            annot = True,\n",
    "            fmt = '.2f',\n",
    "            cmap='Blues')\n",
    "plt.title('Correlation between variables in the Spotify data set')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "จากแผนภูมิข้างต้น เราพบฟีเจอร์ (Features) ที่มีความสัมพันธ์กัน\n",
    "\n",
    "    -> Acous กับ NRGY  -0.56\n",
    "    -> Val   กับ DNCE   0.50\n",
    "    -> dB    กับ NRGY   0.54\n",
    "    \n",
    "**พล็อตข้อมูลที่มีความสัมพันธ์กัน**\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "* Top genre คือแนวเพลงหรือประเภทของแนวดนตรี\n",
    "* Year คือปีของเพลงที่อยู่ในบิลบอร์ด (Billboard)\n",
    "* Bpm (Tempo) คือจังหวะเร็วช้าขนาดไหน หน่วยเป็น bpm (Beats.Per.Minute)\n",
    "* Nrgy (Energy) คือพลังหรือความพุ่งของเพลง\n",
    "* Dnce (Danceability) คือความดิ้น หรือความน่าเต้นของเพลง\n",
    "* dB (Loudness) คือระดับความดังในหน่วย decibel \n",
    "* Live (Liveness) คือระดับของการแสดงสด (Live) ของเพลง \n",
    "* Val (Valence) คือระดับความ positive ในเพลง (ค่าต่ำ: เศร้า-หดหู่-โกรธ,ค่าสูง: มีความสุข-ให้กำลังใจ)\n",
    "* Dur (Length) - คือความยาว (ระยะเวลา) ของเพลง/ดนตรี\n",
    "* Acous (Acousticness) คือความ “acoustic” ของเพลง\n",
    "* Spch (Speechiness) คือปริมาณของคำพูดหรือเนื้อร้อง\n",
    "* Popularity คือระดับความนิยม ยิ่งค่าสูงเท่าไหร่ ยิ่งเป็นที่นิยม\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0, 0.5, 'Loudness (dB)')"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "df.plot(x='acous',y='nrgy',kind='scatter', title='Relationship between Energy and Acousticness  ',color='r')\n",
    "plt.xlabel('Acousticness')\n",
    "plt.ylabel('Energy')\n",
    "\n",
    "df.plot(x='nrgy',y='dB',kind='scatter', title='Relationship between Loudness (dB) and Energy',color='b')\n",
    "plt.xlabel('Energy')\n",
    "plt.ylabel('Loudness (dB)')\n",
    "\n",
    "df.plot(x='val',y='dnce',kind='scatter', title='Relationship between Loudness (dB) and Valence',color='g')\n",
    "plt.xlabel('Valence')\n",
    "plt.ylabel('Loudness (dB)')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## วิเคราะห์ชุดข้อมูล\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "\n",
    " ### ศิลปินที่มีจำนวนเพลงมาก 10 อันดับแรก?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "The dfset has 184 artists\n",
      "<class 'numpy.ndarray'>\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "array(['Train', 'Eminem', 'Kesha', 'Lady Gaga', 'Bruno Mars',\n",
       "       'Justin Bieber', 'Taio Cruz', 'OneRepublic', 'Alicia Keys',\n",
       "       'Rihanna'], dtype=object)"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "artists = df['artist'].unique() # Return unique values of Series object. Uniques are returned in order of appearance\n",
    "print(\"The dfset has {} artists\".format (len(artists)))\n",
    "print(type(artists))\n",
    "artists[0:10] "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Katy Perry             17\n",
       "Justin Bieber          16\n",
       "Rihanna                15\n",
       "Maroon 5               15\n",
       "Lady Gaga              14\n",
       "                       ..\n",
       "Iggy Azalea             1\n",
       "5 Seconds of Summer     1\n",
       "Michael Jackson         1\n",
       "Disclosure              1\n",
       "Daddy Yankee            1\n",
       "Name: artist, Length: 184, dtype: int64"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# ดูความถี่ของค่าในคอลัมน์ต่างๆ กรณี 'artist'\n",
    "df['artist'].value_counts() # Type: pandas.core.series.Series"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "              index  artist\n",
      "0        Katy Perry      17\n",
      "1     Justin Bieber      16\n",
      "2           Rihanna      15\n",
      "3          Maroon 5      15\n",
      "4         Lady Gaga      14\n",
      "5        Bruno Mars      13\n",
      "6      Shawn Mendes      11\n",
      "7           Pitbull      11\n",
      "8        Ed Sheeran      11\n",
      "9  The Chainsmokers      11\n"
     ]
    }
   ],
   "source": [
    "# value_counts() function return a Series containing counts of unique values.\n",
    "# reset_index() resets the index of the DataFrame, and use the default one instead.\n",
    "artists = df['artist'].value_counts().reset_index().head(10)\n",
    "\n",
    "print(type(artists))\n",
    "print(artists)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0.5, 1.0, 'Number of Musics on top score by the 10 Top Artists')"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1500x800 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(15,8))\n",
    "sn.barplot(x='index',y='artist', data=artists)\n",
    "plt.title(\"Number of Musics on top score by the 10 Top Artists\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### เพลงที่มีชื่อในชุดข้อมูลมากกว่าหนึ่งครั้ง"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "A Little Party Never Killed Nobody (All We Got)     True\n",
       "All I Ask                                           True\n",
       "Kissing Strangers                                   True\n",
       "Written in the Stars (feat. Eric Turner)            True\n",
       "The Hills                                           True\n",
       "Love Yourself                                       True\n",
       "We Are Never Ever Getting Back Together             True\n",
       "Sugar                                               True\n",
       "Say Something                                       True\n",
       "First Time                                          True\n",
       "Stitches                                            True\n",
       "I Like It                                           True\n",
       "Hello                                               True\n",
       "Castle Walls (feat. Christina Aguilera)             True\n",
       "Company                                             True\n",
       "Runnin' (Lose It All)                               True\n",
       "Marry You                                           True\n",
       "Just the Way You Are                                True\n",
       "Here                                                True\n",
       "Ain't Your Mama                                    False\n",
       "Name: title, dtype: bool"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df['title'].value_counts().head(20)>1"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "ดูข้อมูลของเพลงทุกเพลงที่ซ้ำ"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "A Little Party Never Killed Nobody (All We Got)    2\n",
       "All I Ask                                          2\n",
       "Kissing Strangers                                  2\n",
       "Written in the Stars (feat. Eric Turner)           2\n",
       "The Hills                                          2\n",
       "Love Yourself                                      2\n",
       "We Are Never Ever Getting Back Together            2\n",
       "Sugar                                              2\n",
       "Say Something                                      2\n",
       "First Time                                         2\n",
       "Stitches                                           2\n",
       "I Like It                                          2\n",
       "Hello                                              2\n",
       "Castle Walls (feat. Christina Aguilera)            2\n",
       "Company                                            2\n",
       "Runnin' (Lose It All)                              2\n",
       "Marry You                                          2\n",
       "Just the Way You Are                               2\n",
       "Here                                               2\n",
       "Name: title, dtype: int64"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "more_than_one = df['title'].value_counts().head(19)\n",
    "more_than_one"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### การวิเคราะห์โดยการเรียงลำดับข้อมูล\n",
    "\n",
    "#### เพลงที่มีระดับความนิยม (Popularity) มากสุด Top 15 \n",
    "\n",
    "จากข้อมูลสรุปได้ว่า เพลงฮิตมากที่สุดแทบทุกเพลงเป็นเพลงในปี 2019"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "df.sort_values(by=['pop'], ascending=False).head(15)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### เพลงที่มีความยาว (ระยะเวลา) มากสุด Top 15"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "scrolled": true
   },
   "outputs": [],
   "source": [
    "df.sort_values(by=['dur'], ascending=False).head(-5)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### เพลงที่มีความ “Acoustic” มากสุด Top 15"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "df.sort_values(by=['acous'], ascending=False).head(5)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### แนวเพลงประเภทไหนที่อยู่ในชุดข้อมูล 10 อันดับแรก?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "genres = df['top_genre'].value_counts().reset_index().head(10)\n",
    "genres.head(10)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "plt.figure(figsize=(23,10))\n",
    "sn.barplot(x='index',y='top_genre', data=genres)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "plt.figure(figsize=(20,10))\n",
    "for i in genres['index']:\n",
    "  tmp = []\n",
    "  for y in range(2010,2020):\n",
    "    songs = df[df['year'] == y][df['top_genre'] == i]\n",
    "    tmp.append(songs.shape[0])\n",
    "  sn.lineplot(x=list(range(2010,2020)),y=tmp)\n",
    "plt.legend(list(genres['index']))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "tags": []
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   "source": [
    "---"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Author\n",
    "\n",
    "S.C.\n",
    "\n",
    "### Change Log\n",
    "\n",
    "    \n",
    "|  Date  |  Version | Change Description |\n",
    "|---|---|---|\n",
    "| 08-08-2021 | 0.1  | First edition |\n",
    "|   |   |   |\n",
    "|   |   |   |\n"
   ]
  }
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