flask-ui-skeleton.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Capstone Project Flask UI"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Pada capstone ini anda diminta untuk membangun sebuah Flask UI sederhana yang berisi beberapa tampilan plot dari skeleton yang sudah disediakan dan satu plot tambahan berdasarkan analisis anda.\n",
    "\n",
    "File ini dapat dimanfaatkan untuk membantu anda dalam proses wrangling dan visualization. Apabila proses wrangling sudah tepat dan hasil visualisasi sudah sesuai dengan ketentuan, anda dapat memindahkan kembali kode program yang sudah anda lengkapi ke dalam file `app.py`."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Data Preprocessing"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Import library**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-02-02T09:56:05.789070Z",
     "start_time": "2021-02-02T09:56:03.554294Z"
    }
   },
   "outputs": [],
   "source": [
    "from flask import Flask, render_template\n",
    "import pandas as pd\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "from io import BytesIO\n",
    "import base64"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Load data**\n",
    "\n",
    "Bacalah file `googleplaystore.csv` data dan simpan ke objek dataframe dengan nama playstore"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-02-02T09:59:28.086254Z",
     "start_time": "2021-02-02T09:59:28.032673Z"
    }
   },
   "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>App</th>\n",
       "      <th>Category</th>\n",
       "      <th>Rating</th>\n",
       "      <th>Reviews</th>\n",
       "      <th>Size</th>\n",
       "      <th>Installs</th>\n",
       "      <th>Type</th>\n",
       "      <th>Price</th>\n",
       "      <th>Content Rating</th>\n",
       "      <th>Genres</th>\n",
       "      <th>Last Updated</th>\n",
       "      <th>Current Ver</th>\n",
       "      <th>Android Ver</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Photo Editor &amp; Candy Camera &amp; Grid &amp; ScrapBook</td>\n",
       "      <td>ART_AND_DESIGN</td>\n",
       "      <td>4.1</td>\n",
       "      <td>159</td>\n",
       "      <td>19M</td>\n",
       "      <td>10,000+</td>\n",
       "      <td>Free</td>\n",
       "      <td>0</td>\n",
       "      <td>Everyone</td>\n",
       "      <td>Art &amp; Design</td>\n",
       "      <td>January 7, 2018</td>\n",
       "      <td>1.0.0</td>\n",
       "      <td>4.0.3 and up</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Coloring book moana</td>\n",
       "      <td>ART_AND_DESIGN</td>\n",
       "      <td>3.9</td>\n",
       "      <td>967</td>\n",
       "      <td>14M</td>\n",
       "      <td>500,000+</td>\n",
       "      <td>Free</td>\n",
       "      <td>0</td>\n",
       "      <td>Everyone</td>\n",
       "      <td>Art &amp; Design;Pretend Play</td>\n",
       "      <td>January 15, 2018</td>\n",
       "      <td>2.0.0</td>\n",
       "      <td>4.0.3 and up</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>U Launcher Lite – FREE Live Cool Themes, Hide ...</td>\n",
       "      <td>ART_AND_DESIGN</td>\n",
       "      <td>4.7</td>\n",
       "      <td>87510</td>\n",
       "      <td>8.7M</td>\n",
       "      <td>5,000,000+</td>\n",
       "      <td>Free</td>\n",
       "      <td>0</td>\n",
       "      <td>Everyone</td>\n",
       "      <td>Art &amp; Design</td>\n",
       "      <td>August 1, 2018</td>\n",
       "      <td>1.2.4</td>\n",
       "      <td>4.0.3 and up</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Sketch - Draw &amp; Paint</td>\n",
       "      <td>ART_AND_DESIGN</td>\n",
       "      <td>4.5</td>\n",
       "      <td>215644</td>\n",
       "      <td>25M</td>\n",
       "      <td>50,000,000+</td>\n",
       "      <td>Free</td>\n",
       "      <td>0</td>\n",
       "      <td>Teen</td>\n",
       "      <td>Art &amp; Design</td>\n",
       "      <td>June 8, 2018</td>\n",
       "      <td>Varies with device</td>\n",
       "      <td>4.2 and up</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Pixel Draw - Number Art Coloring Book</td>\n",
       "      <td>ART_AND_DESIGN</td>\n",
       "      <td>4.3</td>\n",
       "      <td>967</td>\n",
       "      <td>2.8M</td>\n",
       "      <td>100,000+</td>\n",
       "      <td>Free</td>\n",
       "      <td>0</td>\n",
       "      <td>Everyone</td>\n",
       "      <td>Art &amp; Design;Creativity</td>\n",
       "      <td>June 20, 2018</td>\n",
       "      <td>1.1</td>\n",
       "      <td>4.4 and up</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                                 App        Category  Rating  \\\n",
       "0     Photo Editor & Candy Camera & Grid & ScrapBook  ART_AND_DESIGN     4.1   \n",
       "1                                Coloring book moana  ART_AND_DESIGN     3.9   \n",
       "2  U Launcher Lite – FREE Live Cool Themes, Hide ...  ART_AND_DESIGN     4.7   \n",
       "3                              Sketch - Draw & Paint  ART_AND_DESIGN     4.5   \n",
       "4              Pixel Draw - Number Art Coloring Book  ART_AND_DESIGN     4.3   \n",
       "\n",
       "  Reviews  Size     Installs  Type Price Content Rating  \\\n",
       "0     159   19M      10,000+  Free     0       Everyone   \n",
       "1     967   14M     500,000+  Free     0       Everyone   \n",
       "2   87510  8.7M   5,000,000+  Free     0       Everyone   \n",
       "3  215644   25M  50,000,000+  Free     0           Teen   \n",
       "4     967  2.8M     100,000+  Free     0       Everyone   \n",
       "\n",
       "                      Genres      Last Updated         Current Ver  \\\n",
       "0               Art & Design   January 7, 2018               1.0.0   \n",
       "1  Art & Design;Pretend Play  January 15, 2018               2.0.0   \n",
       "2               Art & Design    August 1, 2018               1.2.4   \n",
       "3               Art & Design      June 8, 2018  Varies with device   \n",
       "4    Art & Design;Creativity     June 20, 2018                 1.1   \n",
       "\n",
       "    Android Ver  \n",
       "0  4.0.3 and up  \n",
       "1  4.0.3 and up  \n",
       "2  4.0.3 and up  \n",
       "3    4.2 and up  \n",
       "4    4.4 and up  "
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "playstore = pd.read_csv('data/googleplaystore.csv')\n",
    "playstore.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Data Cleansing** "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**_Task 1:_** Hapus data yang duplikat berdasarkan kolom App, dengan tetap keep data pertama (hint : gunakan parameter subset)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "playstore.drop_duplicates(subset='App', keep='first', inplace=True)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Bagian ini untuk menghapus row 10472 karena nilai data tersebut tidak tersimpan pada kolom yang benar"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-02-02T10:01:18.760162Z",
     "start_time": "2021-02-02T10:01:18.747974Z"
    }
   },
   "outputs": [],
   "source": [
    "playstore.drop([10472], inplace=True)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**_Task 2:_** Cek tipe data kolom Category. Jika masih tersimpan dengan format tipe data yang salah, ubah ke tipe data yang sesuai\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Int64Index: 9659 entries, 0 to 10840\n",
      "Data columns (total 13 columns):\n",
      " #   Column          Non-Null Count  Dtype  \n",
      "---  ------          --------------  -----  \n",
      " 0   App             9659 non-null   object \n",
      " 1   Category        9659 non-null   object \n",
      " 2   Rating          8196 non-null   float64\n",
      " 3   Reviews         9659 non-null   object \n",
      " 4   Size            9659 non-null   object \n",
      " 5   Installs        9659 non-null   object \n",
      " 6   Type            9658 non-null   object \n",
      " 7   Price           9659 non-null   object \n",
      " 8   Content Rating  9659 non-null   object \n",
      " 9   Genres          9659 non-null   object \n",
      " 10  Last Updated    9659 non-null   object \n",
      " 11  Current Ver     9651 non-null   object \n",
      " 12  Android Ver     9657 non-null   object \n",
      "dtypes: float64(1), object(12)\n",
      "memory usage: 1.0+ MB\n"
     ]
    }
   ],
   "source": [
    "playstore.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-02-02T10:03:32.164554Z",
     "start_time": "2021-02-02T10:03:32.153250Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Int64Index: 9659 entries, 0 to 10840\n",
      "Data columns (total 13 columns):\n",
      " #   Column          Non-Null Count  Dtype   \n",
      "---  ------          --------------  -----   \n",
      " 0   App             9659 non-null   object  \n",
      " 1   Category        9659 non-null   category\n",
      " 2   Rating          8196 non-null   float64 \n",
      " 3   Reviews         9659 non-null   object  \n",
      " 4   Size            9659 non-null   object  \n",
      " 5   Installs        9659 non-null   object  \n",
      " 6   Type            9658 non-null   object  \n",
      " 7   Price           9659 non-null   object  \n",
      " 8   Content Rating  9659 non-null   object  \n",
      " 9   Genres          9659 non-null   object  \n",
      " 10  Last Updated    9659 non-null   object  \n",
      " 11  Current Ver     9651 non-null   object  \n",
      " 12  Android Ver     9657 non-null   object  \n",
      "dtypes: category(1), float64(1), object(11)\n",
      "memory usage: 991.7+ KB\n"
     ]
    }
   ],
   "source": [
    "playstore.Category = playstore.Category.astype('category')\n",
    "playstore.info()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**_Task 3:_** Pada kolom Installs Buang tanda koma(,) dan tanda tambah(+) kemudian ubah tipe data menjadi integer"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-02-02T10:16:20.985521Z",
     "start_time": "2021-02-02T10:16:20.969640Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0           10000\n",
       "1          500000\n",
       "2         5000000\n",
       "3        50000000\n",
       "4          100000\n",
       "           ...   \n",
       "10836        5000\n",
       "10837         100\n",
       "10838        1000\n",
       "10839        1000\n",
       "10840    10000000\n",
       "Name: Installs, Length: 9659, dtype: int64"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "playstore.Installs = playstore.Installs.apply(lambda x: x.replace(',', ''))\n",
    "playstore.Installs = playstore.Installs.apply(lambda x: x.replace('+', ''))\n",
    "playstore.Installs = playstore.Installs.astype('int')\n",
    "playstore.Installs"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Bagian ini untuk merapikan kolom Size, Anda tidak perlu mengubah apapun di bagian ini"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-02-02T10:17:51.003771Z",
     "start_time": "2021-02-02T10:17:50.934201Z"
    }
   },
   "outputs": [],
   "source": [
    "playstore['Size'].replace('Varies with device', np.nan, inplace = True ) \n",
    "playstore.Size = (playstore.Size.replace(r'[kM]+$', '', regex=True).astype(float) * \\\n",
    "             playstore.Size.str.extract(r'[\\d\\.]+([kM]+)', expand=False)\n",
    "            .fillna(1)\n",
    "            .replace(['k','M'], [10**3, 10**6]).astype(int))\n",
    "playstore['Size'].fillna(playstore.groupby('Category')['Size'].transform('mean'),inplace = True)\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**_Task 4:_** Pada kolom Price, buang karakater $ pada nilai Price lalu ubah tipe datanya menjadi float"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-02-02T10:17:51.850791Z",
     "start_time": "2021-02-02T10:17:51.831652Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([  0.  ,   4.99,   3.99,   6.99,   1.49,   2.99,   7.99,   5.99,\n",
       "         3.49,   1.99,   9.99,   7.49,   0.99,   9.  ,   5.49,  10.  ,\n",
       "        24.99,  11.99,  79.99,  16.99,  14.99,   1.  ,  29.99,  12.99,\n",
       "         2.49,  10.99,   1.5 ,  19.99,  15.99,  33.99,  74.99,  39.99,\n",
       "         3.95,   4.49,   1.7 ,   8.99,   2.  ,   3.88,  25.99, 399.99,\n",
       "        17.99, 400.  ,   3.02,   1.76,   4.84,   4.77,   1.61,   2.5 ,\n",
       "         1.59,   6.49,   1.29,   5.  ,  13.99, 299.99, 379.99,  37.99,\n",
       "        18.99, 389.99,  19.9 ,   8.49,   1.75,  14.  ,   4.85,  46.99,\n",
       "       109.99, 154.99,   3.08,   2.59,   4.8 ,   1.96,  19.4 ,   3.9 ,\n",
       "         4.59,  15.46,   3.04,   4.29,   2.6 ,   3.28,   4.6 ,  28.99,\n",
       "         2.95,   2.9 ,   1.97, 200.  ,  89.99,   2.56,  30.99,   3.61,\n",
       "       394.99,   1.26,   1.2 ,   1.04])"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "playstore.Price = playstore.Price.apply(lambda x: x.replace('$', ''))\n",
    "playstore.Price = playstore.Price.astype('float')\n",
    "playstore.Price.unique()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Ubah tipe data Reviews, Size, Installs ke dalam tipe data integer"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-02-02T10:17:53.379441Z",
     "start_time": "2021-02-02T10:17:53.359741Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
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       "\n",
       "    .dataframe tbody tr th {\n",
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       "    .dataframe thead th {\n",
       "        text-align: right;\n",
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Reviews</th>\n",
       "      <th>Size</th>\n",
       "      <th>Installs</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>159</td>\n",
       "      <td>19000000</td>\n",
       "      <td>10000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>967</td>\n",
       "      <td>14000000</td>\n",
       "      <td>500000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>87510</td>\n",
       "      <td>8700000</td>\n",
       "      <td>5000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>215644</td>\n",
       "      <td>25000000</td>\n",
       "      <td>50000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>967</td>\n",
       "      <td>2800000</td>\n",
       "      <td>100000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10836</th>\n",
       "      <td>38</td>\n",
       "      <td>53000000</td>\n",
       "      <td>5000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10837</th>\n",
       "      <td>4</td>\n",
       "      <td>3600000</td>\n",
       "      <td>100</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10838</th>\n",
       "      <td>3</td>\n",
       "      <td>9500000</td>\n",
       "      <td>1000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10839</th>\n",
       "      <td>114</td>\n",
       "      <td>13134701</td>\n",
       "      <td>1000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10840</th>\n",
       "      <td>398307</td>\n",
       "      <td>19000000</td>\n",
       "      <td>10000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>9659 rows × 3 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "       Reviews      Size  Installs\n",
       "0          159  19000000     10000\n",
       "1          967  14000000    500000\n",
       "2        87510   8700000   5000000\n",
       "3       215644  25000000  50000000\n",
       "4          967   2800000    100000\n",
       "...        ...       ...       ...\n",
       "10836       38  53000000      5000\n",
       "10837        4   3600000       100\n",
       "10838        3   9500000      1000\n",
       "10839      114  13134701      1000\n",
       "10840   398307  19000000  10000000\n",
       "\n",
       "[9659 rows x 3 columns]"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "##code here\n",
    "integer_columns = ['Reviews', 'Size', 'Installs']\n",
    "playstore[integer_columns] = playstore[integer_columns].astype('int')\n",
    "playstore[integer_columns]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Data Wrangling"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-02-02T10:18:50.436751Z",
     "start_time": "2021-02-02T10:18:50.425327Z"
    }
   },
   "outputs": [],
   "source": [
    "df2 = playstore.copy()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**_Task 5:_** Dataframe top_category dibuat untuk menyimpan frekuensi aplikasi untuk setiap Category. \n",
    "Gunakan crosstab untuk menghitung frekuensi aplikasi di setiap category kemudian gunakan `Jumlah`\n",
    "sebagai nama kolom dan urutkan nilai frekuensi dari nilai yang paling banyak. Terakhir reset index dari dataframe top_category."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-02-02T10:22:20.387102Z",
     "start_time": "2021-02-02T10:22:20.334148Z"
    }
   },
   "outputs": [],
   "source": [
    "top_category = pd.crosstab(\n",
    "                            index=df2.Category,\n",
    "                            columns='Jumlah'\n",
    ").sort_values(by='Jumlah', ascending=False).reset_index()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-02-02T10:24:18.993255Z",
     "start_time": "2021-02-02T10:24:18.969721Z"
    }
   },
   "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>col_0</th>\n",
       "      <th>Category</th>\n",
       "      <th>Jumlah</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>FAMILY</td>\n",
       "      <td>1832</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>GAME</td>\n",
       "      <td>959</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>TOOLS</td>\n",
       "      <td>827</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>BUSINESS</td>\n",
       "      <td>420</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>MEDICAL</td>\n",
       "      <td>395</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "col_0  Category  Jumlah\n",
       "0        FAMILY    1832\n",
       "1          GAME     959\n",
       "2         TOOLS     827\n",
       "3      BUSINESS     420\n",
       "4       MEDICAL     395"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "top_category.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**_Task 6:_** Ini adalah bagian untuk melengkapi konten value box \n",
    "most category mengambil nama category paling banyak mengacu pada dataframe `top_category`\n",
    "total mengambil frekuensi/jumlah category paling banyak mengacu pada dataframe `top_category`"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "1832"
      ]
     },
     "execution_count": 49,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "top_category.iloc[0, 1]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-02-02T10:25:55.268573Z",
     "start_time": "2021-02-02T10:25:55.257944Z"
    }
   },
   "outputs": [],
   "source": [
    "most_categories = top_category.iloc[0, 0]\n",
    "total = top_category.iloc[0, 1]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "`rev_table` adalah tabel yang berisi 10 aplikasi yang paling banyak direview oleh pengguna.\n",
    "Silahkan melakukan agregasi data yang tepat menggunakan `groupby` untuk menampilkan 10 aplikasi yang diurutkan berdasarkan jumlah Review pengguna. \n",
    "\n",
    "Tabel yang ditampilkan terdiri dari 4 kolom yaitu nama Category, nama App, total Reviews, dan rata-rata Rating.\n",
    "Pindahkan kode wrangling yang disimpan dalam variable `rev_table` pada `blank code` yang telah di chaining dengan kode `.to_html`."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/var/folders/0d/5t1d2r_d5zlgjhh41spwmb740000gn/T/ipykernel_49605/488419021.py:1: FutureWarning: Indexing with multiple keys (implicitly converted to a tuple of keys) will be deprecated, use a list instead.\n",
      "  df2.groupby(['Category', 'App'])['Reviews', 'Rating'].agg('sum')\\\n"
     ]
    },
    {
     "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>Category</th>\n",
       "      <th>App</th>\n",
       "      <th>Reviews</th>\n",
       "      <th>Rating</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>SOCIAL</td>\n",
       "      <td>Facebook</td>\n",
       "      <td>78158306</td>\n",
       "      <td>4.1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>COMMUNICATION</td>\n",
       "      <td>WhatsApp Messenger</td>\n",
       "      <td>69119316</td>\n",
       "      <td>4.4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>SOCIAL</td>\n",
       "      <td>Instagram</td>\n",
       "      <td>66577313</td>\n",
       "      <td>4.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>COMMUNICATION</td>\n",
       "      <td>Messenger – Text and Video Chat for Free</td>\n",
       "      <td>56642847</td>\n",
       "      <td>4.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>GAME</td>\n",
       "      <td>Clash of Clans</td>\n",
       "      <td>44891723</td>\n",
       "      <td>4.6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>TOOLS</td>\n",
       "      <td>Clean Master- Space Cleaner &amp; Antivirus</td>\n",
       "      <td>42916526</td>\n",
       "      <td>4.7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>GAME</td>\n",
       "      <td>Subway Surfers</td>\n",
       "      <td>27722264</td>\n",
       "      <td>4.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>VIDEO_PLAYERS</td>\n",
       "      <td>YouTube</td>\n",
       "      <td>25655305</td>\n",
       "      <td>4.3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>TOOLS</td>\n",
       "      <td>Security Master - Antivirus, VPN, AppLock, Boo...</td>\n",
       "      <td>24900999</td>\n",
       "      <td>4.7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>GAME</td>\n",
       "      <td>Clash Royale</td>\n",
       "      <td>23133508</td>\n",
       "      <td>4.6</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "        Category                                                App   Reviews  \\\n",
       "0         SOCIAL                                           Facebook  78158306   \n",
       "1  COMMUNICATION                                 WhatsApp Messenger  69119316   \n",
       "2         SOCIAL                                          Instagram  66577313   \n",
       "3  COMMUNICATION           Messenger – Text and Video Chat for Free  56642847   \n",
       "4           GAME                                     Clash of Clans  44891723   \n",
       "5          TOOLS            Clean Master- Space Cleaner & Antivirus  42916526   \n",
       "6           GAME                                     Subway Surfers  27722264   \n",
       "7  VIDEO_PLAYERS                                            YouTube  25655305   \n",
       "8          TOOLS  Security Master - Antivirus, VPN, AppLock, Boo...  24900999   \n",
       "9           GAME                                       Clash Royale  23133508   \n",
       "\n",
       "   Rating  \n",
       "0     4.1  \n",
       "1     4.4  \n",
       "2     4.5  \n",
       "3     4.0  \n",
       "4     4.6  \n",
       "5     4.7  \n",
       "6     4.5  \n",
       "7     4.3  \n",
       "8     4.7  \n",
       "9     4.6  "
      ]
     },
     "execution_count": 34,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df2.groupby(['Category', 'App'])['Reviews', 'Rating'].agg('sum')\\\n",
    ".sort_values('Reviews', ascending=False).head(10).reset_index()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-02-02T10:32:27.727779Z",
     "start_time": "2021-02-02T10:32:24.299980Z"
    }
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/var/folders/0d/5t1d2r_d5zlgjhh41spwmb740000gn/T/ipykernel_49605/4284592107.py:1: FutureWarning: Indexing with multiple keys (implicitly converted to a tuple of keys) will be deprecated, use a list instead.\n",
      "  rev_table = df2.groupby(['Category', 'App'])['Reviews', 'Rating'].agg('sum')\\\n"
     ]
    }
   ],
   "source": [
    "rev_table = df2.groupby(['Category', 'App'])['Reviews', 'Rating'].agg('sum')\\\n",
    ".sort_values('Reviews', ascending=False).head(10).reset_index()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Apabila menuliskan kode program yang tepat maka hasil wrangling adalah sebagai berikut :"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-02-02T10:32:37.483995Z",
     "start_time": "2021-02-02T10:32:37.467075Z"
    }
   },
   "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>Category</th>\n",
       "      <th>App</th>\n",
       "      <th>Reviews</th>\n",
       "      <th>Rating</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>SOCIAL</td>\n",
       "      <td>Facebook</td>\n",
       "      <td>78158306</td>\n",
       "      <td>4.1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>COMMUNICATION</td>\n",
       "      <td>WhatsApp Messenger</td>\n",
       "      <td>69119316</td>\n",
       "      <td>4.4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>SOCIAL</td>\n",
       "      <td>Instagram</td>\n",
       "      <td>66577313</td>\n",
       "      <td>4.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>COMMUNICATION</td>\n",
       "      <td>Messenger – Text and Video Chat for Free</td>\n",
       "      <td>56642847</td>\n",
       "      <td>4.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>GAME</td>\n",
       "      <td>Clash of Clans</td>\n",
       "      <td>44891723</td>\n",
       "      <td>4.6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>TOOLS</td>\n",
       "      <td>Clean Master- Space Cleaner &amp; Antivirus</td>\n",
       "      <td>42916526</td>\n",
       "      <td>4.7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>GAME</td>\n",
       "      <td>Subway Surfers</td>\n",
       "      <td>27722264</td>\n",
       "      <td>4.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>VIDEO_PLAYERS</td>\n",
       "      <td>YouTube</td>\n",
       "      <td>25655305</td>\n",
       "      <td>4.3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>TOOLS</td>\n",
       "      <td>Security Master - Antivirus, VPN, AppLock, Boo...</td>\n",
       "      <td>24900999</td>\n",
       "      <td>4.7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>GAME</td>\n",
       "      <td>Clash Royale</td>\n",
       "      <td>23133508</td>\n",
       "      <td>4.6</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "        Category                                                App   Reviews  \\\n",
       "0         SOCIAL                                           Facebook  78158306   \n",
       "1  COMMUNICATION                                 WhatsApp Messenger  69119316   \n",
       "2         SOCIAL                                          Instagram  66577313   \n",
       "3  COMMUNICATION           Messenger – Text and Video Chat for Free  56642847   \n",
       "4           GAME                                     Clash of Clans  44891723   \n",
       "5          TOOLS            Clean Master- Space Cleaner & Antivirus  42916526   \n",
       "6           GAME                                     Subway Surfers  27722264   \n",
       "7  VIDEO_PLAYERS                                            YouTube  25655305   \n",
       "8          TOOLS  Security Master - Antivirus, VPN, AppLock, Boo...  24900999   \n",
       "9           GAME                                       Clash Royale  23133508   \n",
       "\n",
       "   Rating  \n",
       "0     4.1  \n",
       "1     4.4  \n",
       "2     4.5  \n",
       "3     4.0  \n",
       "4     4.6  \n",
       "5     4.7  \n",
       "6     4.5  \n",
       "7     4.3  \n",
       "8     4.7  \n",
       "9     4.6  "
      ]
     },
     "execution_count": 36,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "rev_table"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Data Visualization"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Membuat Bar Plot**"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**_Task 7:_** \n",
    "Lengkapi tahap agregasi untuk membuat dataframe yang mengelompokkan aplikasi berdasarkan Category.\n",
    "Buatlah bar plot dimana axis x adalah nama Category dan axis y adalah jumlah aplikasi pada setiap kategori, kemudian urutkan dari jumlah terbanyak"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 147,
   "metadata": {},
   "outputs": [],
   "source": [
    "x = df2.groupby('Category').agg({\n",
    "'Category' : 'count'\n",
    " }).rename({'Category':'Total'}, axis=1).sort_values('Total', ascending=False).head().reset_index()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 148,
   "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>Category</th>\n",
       "      <th>Total</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>FAMILY</td>\n",
       "      <td>1832</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>GAME</td>\n",
       "      <td>959</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>TOOLS</td>\n",
       "      <td>827</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>BUSINESS</td>\n",
       "      <td>420</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>MEDICAL</td>\n",
       "      <td>395</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   Category  Total\n",
       "0    FAMILY   1832\n",
       "1      GAME    959\n",
       "2     TOOLS    827\n",
       "3  BUSINESS    420\n",
       "4   MEDICAL    395"
      ]
     },
     "execution_count": 148,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "x"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 57,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-02-02T10:37:53.665508Z",
     "start_time": "2021-02-02T10:37:52.980775Z"
    }
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/var/folders/0d/5t1d2r_d5zlgjhh41spwmb740000gn/T/ipykernel_49605/2887132352.py:11: MatplotlibDeprecationWarning: Using a string of single character colors as a color sequence is deprecated since 3.2 and will be removed two minor releases later. Use an explicit list instead.\n",
      "  plt.barh(X,Y, color=my_colors)\n"
     ]
    },
    {
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\n",
      "text/plain": [
       "<Figure size 2400x900 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "cat_order = df2.groupby('Category').agg({\n",
    "'Category' : 'count'\n",
    " }).rename({'Category':'Total'}, axis=1).sort_values('Total', ascending=False).head().reset_index()\n",
    "X = cat_order['Category'].values\n",
    "Y = cat_order['Total'].values\n",
    "my_colors = 'rgbkymc'\n",
    "# bagian ini digunakan untuk membuat kanvas/figure\n",
    "fig = plt.figure(figsize=(8,3),dpi=300)\n",
    "fig.add_subplot()\n",
    "# bagian ini digunakan untuk membuat bar plot\n",
    "plt.barh(X,Y, color=my_colors)\n",
    "# bagian ini digunakan untuk menyimpan plot dalam format image.png\n",
    "plt.savefig('cat_order1.png',bbox_inches=\"tight\") "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Membuat Scatter Plot**"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**_Task 8:_** Buatlah scatter plot untuk menampilkan hubungan dan persebaran apalikasi dilihat dari Review vs Rating.\n",
    "Ukuran scatter menggambarkan berapa banyak pengguna yang telah menginstall aplikasi \n",
    "    "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 62,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-02-02T10:41:20.616033Z",
     "start_time": "2021-02-02T10:41:20.149283Z"
    },
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 360x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "X = df2['Reviews'].values # axis x\n",
    "Y = df2['Rating'].values # axis y\n",
    "area = playstore['Installs'].values/10000000 # ukuran besar/kecilnya lingkaran scatter plot\n",
    "fig = plt.figure(figsize=(5,5))\n",
    "fig.add_subplot()\n",
    "# isi nama method untuk scatter plot, variabel x, dan variabel y\n",
    "plt.scatter(x=X,y=Y, s=area, alpha=0.3)\n",
    "plt.xlabel('Reviews')\n",
    "plt.ylabel('Rating')\n",
    "plt.savefig('rev_rat1.png',bbox_inches=\"tight\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Membuat Histogram Size Distribution**"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**_Task 9:_** Buatlah sebuah histogram yang menggambarkan distribusi Size aplikasi dalam satuan Mb(Megabytes). Histogram yang terbentuk terbagi menjadi 100 bins"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 63,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-02-02T10:44:25.038732Z",
     "start_time": "2021-02-02T10:44:24.670174Z"
    },
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 360x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "X=(df2['Size']/1000000).values\n",
    "fig = plt.figure(figsize=(5,5))\n",
    "fig.add_subplot()\n",
    "plt.hist(X,bins=100, density=True,  alpha=0.75)\n",
    "plt.xlabel('Size')\n",
    "plt.ylabel('Frequency')\n",
    "plt.savefig('hist_size1.png',bbox_inches=\"tight\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**_Task 10:_** Buatlah plot berdasarkan hasil analisis anda. Plot yang dibuat tidak diperbolehkan sama dengan plot yang sudah dicontohkan."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 162,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-02-02T10:47:53.948656Z",
     "start_time": "2021-02-02T10:47:53.936544Z"
    }
   },
   "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>Category</th>\n",
       "      <th>Installs</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>GAME</td>\n",
       "      <td>13.878924</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>COMMUNICATION</td>\n",
       "      <td>11.038276</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>TOOLS</td>\n",
       "      <td>8.001772</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>PRODUCTIVITY</td>\n",
       "      <td>5.793091</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>SOCIAL</td>\n",
       "      <td>5.487868</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "        Category   Installs\n",
       "0           GAME  13.878924\n",
       "1  COMMUNICATION  11.038276\n",
       "2          TOOLS   8.001772\n",
       "3   PRODUCTIVITY   5.793091\n",
       "4         SOCIAL   5.487868"
      ]
     },
     "execution_count": 162,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "## code here\n",
    "top_installs = df2.groupby('Category').agg({'Installs':'sum'}).sort_values('Installs', ascending=False).head(5).reset_index()\n",
    "top_installs['Installs'] = top_installs['Installs']/1000000000\n",
    "top_installs\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 178,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 1800x1800 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "X = top_installs['Category'].values\n",
    "Y = top_installs['Installs'].values\n",
    "\n",
    "# bagian ini digunakan untuk membuat kanvas/figure\n",
    "fig = plt.figure(figsize=(6,6),dpi=300)\n",
    "fig.add_subplot()\n",
    "# bagian ini digunakan untuk membuat bar plot\n",
    "plt.bar(X,Y)\n",
    "plt.xticks(fontsize=8)\n",
    "plt.yticks(fontsize=8)\n",
    "plt.title('Most Installed Category')\n",
    "plt.xlabel('Category', fontsize=8)\n",
    "plt.ylabel('Number of installed (in bilion)', fontsize=8)\n",
    "# bagian ini digunakan untuk menyimpan plot dalam format image.png\n",
    "plt.savefig('self_fig.png',bbox_inches=\"tight\") "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "capstone-flask",
   "language": "python",
   "name": "capstone-flask"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.8.12"
  },
  "toc": {
   "base_numbering": 1,
   "nav_menu": {},
   "number_sections": true,
   "sideBar": true,
   "skip_h1_title": false,
   "title_cell": "Table of Contents",
   "title_sidebar": "Contents",
   "toc_cell": false,
   "toc_position": {},
   "toc_section_display": true,
   "toc_window_display": false
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}