GoogleAppsDataAnalysis (1).ipynb

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  {
   "cell_type": "markdown",
   "id": "7517b3f2",
   "metadata": {},
   "source": [
    "# Importing all the necessary Libraries for our Analysis"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "ac02b1dd",
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt \n",
    "import seaborn as sns"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "291e2a52",
   "metadata": {},
   "source": [
    "# Uploading our Data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "fe8e985c",
   "metadata": {},
   "outputs": [],
   "source": [
    "df= pd.read_csv('googleplaystore.csv') "
   ]
  },
  {
   "cell_type": "markdown",
   "id": "bb2f6ec0",
   "metadata": {},
   "source": [
    "# Analyzing our Data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "6d93d930",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "pandas.core.frame.DataFrame"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "type(df)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "7b68b80e",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "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>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",
       "  </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",
       "\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",
       "\n",
       "                      Genres      Last Updated Current Ver   Android Ver  \n",
       "0               Art & Design   January 7, 2018       1.0.0  4.0.3 and up  \n",
       "1  Art & Design;Pretend Play  January 15, 2018       2.0.0  4.0.3 and up  "
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.head(2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "c6a71847",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "  <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>10839</th>\n",
       "      <td>The SCP Foundation DB fr nn5n</td>\n",
       "      <td>BOOKS_AND_REFERENCE</td>\n",
       "      <td>4.5</td>\n",
       "      <td>114</td>\n",
       "      <td>Varies with device</td>\n",
       "      <td>1,000+</td>\n",
       "      <td>Free</td>\n",
       "      <td>0</td>\n",
       "      <td>Mature 17+</td>\n",
       "      <td>Books &amp; Reference</td>\n",
       "      <td>January 19, 2015</td>\n",
       "      <td>Varies with device</td>\n",
       "      <td>Varies with device</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10840</th>\n",
       "      <td>iHoroscope - 2018 Daily Horoscope &amp; Astrology</td>\n",
       "      <td>LIFESTYLE</td>\n",
       "      <td>4.5</td>\n",
       "      <td>398307</td>\n",
       "      <td>19M</td>\n",
       "      <td>10,000,000+</td>\n",
       "      <td>Free</td>\n",
       "      <td>0</td>\n",
       "      <td>Everyone</td>\n",
       "      <td>Lifestyle</td>\n",
       "      <td>July 25, 2018</td>\n",
       "      <td>Varies with device</td>\n",
       "      <td>Varies with device</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                                 App             Category  \\\n",
       "10839                  The SCP Foundation DB fr nn5n  BOOKS_AND_REFERENCE   \n",
       "10840  iHoroscope - 2018 Daily Horoscope & Astrology            LIFESTYLE   \n",
       "\n",
       "       Rating Reviews                Size     Installs  Type Price  \\\n",
       "10839     4.5     114  Varies with device       1,000+  Free     0   \n",
       "10840     4.5  398307                 19M  10,000,000+  Free     0   \n",
       "\n",
       "      Content Rating             Genres      Last Updated         Current Ver  \\\n",
       "10839     Mature 17+  Books & Reference  January 19, 2015  Varies with device   \n",
       "10840       Everyone          Lifestyle     July 25, 2018  Varies with device   \n",
       "\n",
       "              Android Ver  \n",
       "10839  Varies with device  \n",
       "10840  Varies with device  "
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.tail(2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "07a1ea99",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(10841, 13)"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "4bfcdd62",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <th>Rating</th>\n",
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       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>9367.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>4.193338</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>0.537431</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>1.000000</td>\n",
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       "      <th>25%</th>\n",
       "      <td>4.000000</td>\n",
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       "      <th>50%</th>\n",
       "      <td>4.300000</td>\n",
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       "      <th>75%</th>\n",
       "      <td>4.500000</td>\n",
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       "      <th>max</th>\n",
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      "text/plain": [
       "            Rating\n",
       "count  9367.000000\n",
       "mean      4.193338\n",
       "std       0.537431\n",
       "min       1.000000\n",
       "25%       4.000000\n",
       "50%       4.300000\n",
       "75%       4.500000\n",
       "max      19.000000"
      ]
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   "source": [
    "df.describe()"
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  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "cc24a040",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:>"
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     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
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     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "df.boxplot()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "96ac6b4c",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "df.hist();"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f61671f0",
   "metadata": {},
   "source": [
    "# Data Cleaning"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "4ca462c2",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 10841 entries, 0 to 10840\n",
      "Data columns (total 13 columns):\n",
      " #   Column          Non-Null Count  Dtype  \n",
      "---  ------          --------------  -----  \n",
      " 0   App             10841 non-null  object \n",
      " 1   Category        10841 non-null  object \n",
      " 2   Rating          9367 non-null   float64\n",
      " 3   Reviews         10841 non-null  object \n",
      " 4   Size            10841 non-null  object \n",
      " 5   Installs        10841 non-null  object \n",
      " 6   Type            10840 non-null  object \n",
      " 7   Price           10841 non-null  object \n",
      " 8   Content Rating  10840 non-null  object \n",
      " 9   Genres          10841 non-null  object \n",
      " 10  Last Updated    10841 non-null  object \n",
      " 11  Current Ver     10833 non-null  object \n",
      " 12  Android Ver     10838 non-null  object \n",
      "dtypes: float64(1), object(12)\n",
      "memory usage: 1.1+ MB\n"
     ]
    }
   ],
   "source": [
    "df.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "6414d476",
   "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>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>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10836</th>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10837</th>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10838</th>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10839</th>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10840</th>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>10841 rows × 13 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "         App  Category  Rating  Reviews   Size  Installs   Type  Price  \\\n",
       "0      False     False   False    False  False     False  False  False   \n",
       "1      False     False   False    False  False     False  False  False   \n",
       "2      False     False   False    False  False     False  False  False   \n",
       "3      False     False   False    False  False     False  False  False   \n",
       "4      False     False   False    False  False     False  False  False   \n",
       "...      ...       ...     ...      ...    ...       ...    ...    ...   \n",
       "10836  False     False   False    False  False     False  False  False   \n",
       "10837  False     False   False    False  False     False  False  False   \n",
       "10838  False     False    True    False  False     False  False  False   \n",
       "10839  False     False   False    False  False     False  False  False   \n",
       "10840  False     False   False    False  False     False  False  False   \n",
       "\n",
       "       Content Rating  Genres  Last Updated  Current Ver  Android Ver  \n",
       "0               False   False         False        False        False  \n",
       "1               False   False         False        False        False  \n",
       "2               False   False         False        False        False  \n",
       "3               False   False         False        False        False  \n",
       "4               False   False         False        False        False  \n",
       "...               ...     ...           ...          ...          ...  \n",
       "10836           False   False         False        False        False  \n",
       "10837           False   False         False        False        False  \n",
       "10838           False   False         False        False        False  \n",
       "10839           False   False         False        False        False  \n",
       "10840           False   False         False        False        False  \n",
       "\n",
       "[10841 rows x 13 columns]"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.isnull()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "834c0b59",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "App                  0\n",
       "Category             0\n",
       "Rating            1474\n",
       "Reviews              0\n",
       "Size                 0\n",
       "Installs             0\n",
       "Type                 1\n",
       "Price                0\n",
       "Content Rating       1\n",
       "Genres               0\n",
       "Last Updated         0\n",
       "Current Ver          8\n",
       "Android Ver          3\n",
       "dtype: int64"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.isnull().sum()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "7fbd0cd3",
   "metadata": {},
   "source": [
    "# Checking how many outliers we have in our Data "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "a96315f9",
   "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>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>10472</th>\n",
       "      <td>Life Made WI-Fi Touchscreen Photo Frame</td>\n",
       "      <td>1.9</td>\n",
       "      <td>19.0</td>\n",
       "      <td>3.0M</td>\n",
       "      <td>1,000+</td>\n",
       "      <td>Free</td>\n",
       "      <td>0</td>\n",
       "      <td>Everyone</td>\n",
       "      <td>NaN</td>\n",
       "      <td>February 11, 2018</td>\n",
       "      <td>1.0.19</td>\n",
       "      <td>4.0 and up</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                           App Category  Rating Reviews  \\\n",
       "10472  Life Made WI-Fi Touchscreen Photo Frame      1.9    19.0    3.0M   \n",
       "\n",
       "         Size Installs Type     Price Content Rating             Genres  \\\n",
       "10472  1,000+     Free    0  Everyone            NaN  February 11, 2018   \n",
       "\n",
       "      Last Updated Current Ver Android Ver  \n",
       "10472       1.0.19  4.0 and up         NaN  "
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df[df.Rating>5]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "41718442",
   "metadata": {},
   "outputs": [],
   "source": [
    "df.drop([10472],inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "c426f712",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>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>10470</th>\n",
       "      <td>Jazz Wi-Fi</td>\n",
       "      <td>COMMUNICATION</td>\n",
       "      <td>3.4</td>\n",
       "      <td>49</td>\n",
       "      <td>4.0M</td>\n",
       "      <td>10,000+</td>\n",
       "      <td>Free</td>\n",
       "      <td>0</td>\n",
       "      <td>Everyone</td>\n",
       "      <td>Communication</td>\n",
       "      <td>February 10, 2017</td>\n",
       "      <td>0.1</td>\n",
       "      <td>2.3 and up</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10471</th>\n",
       "      <td>Xposed Wi-Fi-Pwd</td>\n",
       "      <td>PERSONALIZATION</td>\n",
       "      <td>3.5</td>\n",
       "      <td>1042</td>\n",
       "      <td>404k</td>\n",
       "      <td>100,000+</td>\n",
       "      <td>Free</td>\n",
       "      <td>0</td>\n",
       "      <td>Everyone</td>\n",
       "      <td>Personalization</td>\n",
       "      <td>August 5, 2014</td>\n",
       "      <td>3.0.0</td>\n",
       "      <td>4.0.3 and up</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10473</th>\n",
       "      <td>osmino Wi-Fi: free WiFi</td>\n",
       "      <td>TOOLS</td>\n",
       "      <td>4.2</td>\n",
       "      <td>134203</td>\n",
       "      <td>4.1M</td>\n",
       "      <td>10,000,000+</td>\n",
       "      <td>Free</td>\n",
       "      <td>0</td>\n",
       "      <td>Everyone</td>\n",
       "      <td>Tools</td>\n",
       "      <td>August 7, 2018</td>\n",
       "      <td>6.06.14</td>\n",
       "      <td>4.4 and up</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10474</th>\n",
       "      <td>Sat-Fi Voice</td>\n",
       "      <td>COMMUNICATION</td>\n",
       "      <td>3.4</td>\n",
       "      <td>37</td>\n",
       "      <td>14M</td>\n",
       "      <td>1,000+</td>\n",
       "      <td>Free</td>\n",
       "      <td>0</td>\n",
       "      <td>Everyone</td>\n",
       "      <td>Communication</td>\n",
       "      <td>November 21, 2014</td>\n",
       "      <td>2.2.1.5</td>\n",
       "      <td>2.2 and up</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10475</th>\n",
       "      <td>Wi-Fi Visualizer</td>\n",
       "      <td>TOOLS</td>\n",
       "      <td>3.9</td>\n",
       "      <td>132</td>\n",
       "      <td>2.6M</td>\n",
       "      <td>50,000+</td>\n",
       "      <td>Free</td>\n",
       "      <td>0</td>\n",
       "      <td>Everyone</td>\n",
       "      <td>Tools</td>\n",
       "      <td>May 17, 2017</td>\n",
       "      <td>0.0.9</td>\n",
       "      <td>2.3 and up</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                           App         Category  Rating Reviews  Size  \\\n",
       "10470               Jazz Wi-Fi    COMMUNICATION     3.4      49  4.0M   \n",
       "10471         Xposed Wi-Fi-Pwd  PERSONALIZATION     3.5    1042  404k   \n",
       "10473  osmino Wi-Fi: free WiFi            TOOLS     4.2  134203  4.1M   \n",
       "10474             Sat-Fi Voice    COMMUNICATION     3.4      37   14M   \n",
       "10475         Wi-Fi Visualizer            TOOLS     3.9     132  2.6M   \n",
       "\n",
       "          Installs  Type Price Content Rating           Genres  \\\n",
       "10470      10,000+  Free     0       Everyone    Communication   \n",
       "10471     100,000+  Free     0       Everyone  Personalization   \n",
       "10473  10,000,000+  Free     0       Everyone            Tools   \n",
       "10474       1,000+  Free     0       Everyone    Communication   \n",
       "10475      50,000+  Free     0       Everyone            Tools   \n",
       "\n",
       "            Last Updated Current Ver   Android Ver  \n",
       "10470  February 10, 2017         0.1    2.3 and up  \n",
       "10471     August 5, 2014       3.0.0  4.0.3 and up  \n",
       "10473     August 7, 2018     6.06.14    4.4 and up  \n",
       "10474  November 21, 2014     2.2.1.5    2.2 and up  \n",
       "10475       May 17, 2017       0.0.9    2.3 and up  "
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df[10470:10475]"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "6e9aed53",
   "metadata": {},
   "source": [
    "We dropped our outlier data Row(10472)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "57f35da1",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "df.boxplot();"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "fe2944fa",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "df.hist();"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "438b08ac",
   "metadata": {},
   "source": [
    "# Removing columns that are 90% empty"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "439a2cd4",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "1084.0"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "threshold = len(df)*0.1\n",
    "threshold"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "5ecb3fd3",
   "metadata": {},
   "outputs": [],
   "source": [
    "df.dropna(thresh = threshold, axis = 1, inplace = True )"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "11c536e5",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "App                  0\n",
      "Category             0\n",
      "Rating            1474\n",
      "Reviews              0\n",
      "Size                 0\n",
      "Installs             0\n",
      "Type                 1\n",
      "Price                0\n",
      "Content Rating       0\n",
      "Genres               0\n",
      "Last Updated         0\n",
      "Current Ver          8\n",
      "Android Ver          2\n",
      "dtype: int64\n"
     ]
    }
   ],
   "source": [
    "print(df.isnull().sum())"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "60aa1960",
   "metadata": {},
   "source": [
    "# Data Manipulation"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "cbe0d251",
   "metadata": {},
   "outputs": [],
   "source": [
    "def impute_median(series):\n",
    "    return series.fillna(series.median)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "3ebad3a4",
   "metadata": {},
   "outputs": [],
   "source": [
    "df.Rating = df['Rating'].transform(impute_median)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "id": "48d51b80",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "App               0\n",
       "Category          0\n",
       "Rating            0\n",
       "Reviews           0\n",
       "Size              0\n",
       "Installs          0\n",
       "Type              1\n",
       "Price             0\n",
       "Content Rating    0\n",
       "Genres            0\n",
       "Last Updated      0\n",
       "Current Ver       8\n",
       "Android Ver       2\n",
       "dtype: int64"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.isnull().sum()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "1f283993",
   "metadata": {},
   "source": [
    "Now we have zero non null values rating"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "id": "f4c18344",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0    Free\n",
      "dtype: object\n",
      "0    Varies with device\n",
      "dtype: object\n",
      "0    4.1 and up\n",
      "dtype: object\n"
     ]
    }
   ],
   "source": [
    "print(df['Type'].mode())\n",
    "print(df['Current Ver'].mode())\n",
    "print(df['Android Ver'].mode())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "id": "a23e51f3",
   "metadata": {},
   "outputs": [],
   "source": [
    "df['Type'].fillna(str(df['Type'].mode().values[0]),inplace=True)\n",
    "df['Current Ver'].fillna(str(df['Current Ver'].mode().values[0]),inplace=True)\n",
    "df['Android Ver'].fillna(str(df['Android Ver'].mode().values[0]),inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "id": "719fa218",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "App               0\n",
       "Category          0\n",
       "Rating            0\n",
       "Reviews           0\n",
       "Size              0\n",
       "Installs          0\n",
       "Type              0\n",
       "Price             0\n",
       "Content Rating    0\n",
       "Genres            0\n",
       "Last Updated      0\n",
       "Current Ver       0\n",
       "Android Ver       0\n",
       "dtype: int64"
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.isnull().sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "id": "c8bd1b78",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
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       "\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>10839</th>\n",
       "      <td>The SCP Foundation DB fr nn5n</td>\n",
       "      <td>BOOKS_AND_REFERENCE</td>\n",
       "      <td>4.5</td>\n",
       "      <td>114</td>\n",
       "      <td>Varies with device</td>\n",
       "      <td>1,000+</td>\n",
       "      <td>Free</td>\n",
       "      <td>0</td>\n",
       "      <td>Mature 17+</td>\n",
       "      <td>Books &amp; Reference</td>\n",
       "      <td>January 19, 2015</td>\n",
       "      <td>Varies with device</td>\n",
       "      <td>Varies with device</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10840</th>\n",
       "      <td>iHoroscope - 2018 Daily Horoscope &amp; Astrology</td>\n",
       "      <td>LIFESTYLE</td>\n",
       "      <td>4.5</td>\n",
       "      <td>398307</td>\n",
       "      <td>19M</td>\n",
       "      <td>10,000,000+</td>\n",
       "      <td>Free</td>\n",
       "      <td>0</td>\n",
       "      <td>Everyone</td>\n",
       "      <td>Lifestyle</td>\n",
       "      <td>July 25, 2018</td>\n",
       "      <td>Varies with device</td>\n",
       "      <td>Varies with device</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                                 App             Category  \\\n",
       "10839                  The SCP Foundation DB fr nn5n  BOOKS_AND_REFERENCE   \n",
       "10840  iHoroscope - 2018 Daily Horoscope & Astrology            LIFESTYLE   \n",
       "\n",
       "      Rating Reviews                Size     Installs  Type Price  \\\n",
       "10839    4.5     114  Varies with device       1,000+  Free     0   \n",
       "10840    4.5  398307                 19M  10,000,000+  Free     0   \n",
       "\n",
       "      Content Rating             Genres      Last Updated         Current Ver  \\\n",
       "10839     Mature 17+  Books & Reference  January 19, 2015  Varies with device   \n",
       "10840       Everyone          Lifestyle     July 25, 2018  Varies with device   \n",
       "\n",
       "              Android Ver  \n",
       "10839  Varies with device  \n",
       "10840  Varies with device  "
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.tail(2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "id": "136f46fe",
   "metadata": {},
   "outputs": [],
   "source": [
    "df['Price'] = df['Price'].apply((lambda x: str(x).replace('$','')if '$' in str(x) else str(x)))\n",
    "df['Price'] = df['Price'].apply((lambda x: float(x)))\n",
    "df['Reviews'] = pd.to_numeric(df['Reviews'],errors = 'coerce')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "id": "fb613833",
   "metadata": {},
   "outputs": [],
   "source": [
    "df['Installs'] = df['Installs'].apply(lambda x: str(x).replace('+','')if '+' in str(x) else str(x))\n",
    "df['Installs'] = df['Installs'].apply(lambda x: str(x).replace(',','')if ',' in str(x) else str(x))\n",
    "df['Installs'] = df['Installs'].apply(lambda x: float(x))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "id": "95106156",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
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       "\n",
       "    .dataframe tbody tr th {\n",
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       "    }\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>10000.0</td>\n",
       "      <td>Free</td>\n",
       "      <td>0.0</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>500000.0</td>\n",
       "      <td>Free</td>\n",
       "      <td>0.0</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>5000000.0</td>\n",
       "      <td>Free</td>\n",
       "      <td>0.0</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>50000000.0</td>\n",
       "      <td>Free</td>\n",
       "      <td>0.0</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>100000.0</td>\n",
       "      <td>Free</td>\n",
       "      <td>0.0</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",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>Paper flowers instructions</td>\n",
       "      <td>ART_AND_DESIGN</td>\n",
       "      <td>4.4</td>\n",
       "      <td>167</td>\n",
       "      <td>5.6M</td>\n",
       "      <td>50000.0</td>\n",
       "      <td>Free</td>\n",
       "      <td>0.0</td>\n",
       "      <td>Everyone</td>\n",
       "      <td>Art &amp; Design</td>\n",
       "      <td>March 26, 2017</td>\n",
       "      <td>1.0</td>\n",
       "      <td>2.3 and up</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>Smoke Effect Photo Maker - Smoke Editor</td>\n",
       "      <td>ART_AND_DESIGN</td>\n",
       "      <td>3.8</td>\n",
       "      <td>178</td>\n",
       "      <td>19M</td>\n",
       "      <td>50000.0</td>\n",
       "      <td>Free</td>\n",
       "      <td>0.0</td>\n",
       "      <td>Everyone</td>\n",
       "      <td>Art &amp; Design</td>\n",
       "      <td>April 26, 2018</td>\n",
       "      <td>1.1</td>\n",
       "      <td>4.0.3 and up</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>Infinite Painter</td>\n",
       "      <td>ART_AND_DESIGN</td>\n",
       "      <td>4.1</td>\n",
       "      <td>36815</td>\n",
       "      <td>29M</td>\n",
       "      <td>1000000.0</td>\n",
       "      <td>Free</td>\n",
       "      <td>0.0</td>\n",
       "      <td>Everyone</td>\n",
       "      <td>Art &amp; Design</td>\n",
       "      <td>June 14, 2018</td>\n",
       "      <td>6.1.61.1</td>\n",
       "      <td>4.2 and up</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>Garden Coloring Book</td>\n",
       "      <td>ART_AND_DESIGN</td>\n",
       "      <td>4.4</td>\n",
       "      <td>13791</td>\n",
       "      <td>33M</td>\n",
       "      <td>1000000.0</td>\n",
       "      <td>Free</td>\n",
       "      <td>0.0</td>\n",
       "      <td>Everyone</td>\n",
       "      <td>Art &amp; Design</td>\n",
       "      <td>September 20, 2017</td>\n",
       "      <td>2.9.2</td>\n",
       "      <td>3.0 and up</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>Kids Paint Free - Drawing Fun</td>\n",
       "      <td>ART_AND_DESIGN</td>\n",
       "      <td>4.7</td>\n",
       "      <td>121</td>\n",
       "      <td>3.1M</td>\n",
       "      <td>10000.0</td>\n",
       "      <td>Free</td>\n",
       "      <td>0.0</td>\n",
       "      <td>Everyone</td>\n",
       "      <td>Art &amp; Design;Creativity</td>\n",
       "      <td>July 3, 2018</td>\n",
       "      <td>2.8</td>\n",
       "      <td>4.0.3 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",
       "5                         Paper flowers instructions  ART_AND_DESIGN    4.4   \n",
       "6            Smoke Effect Photo Maker - Smoke Editor  ART_AND_DESIGN    3.8   \n",
       "7                                   Infinite Painter  ART_AND_DESIGN    4.1   \n",
       "8                               Garden Coloring Book  ART_AND_DESIGN    4.4   \n",
       "9                      Kids Paint Free - Drawing Fun  ART_AND_DESIGN    4.7   \n",
       "\n",
       "   Reviews  Size    Installs  Type  Price Content Rating  \\\n",
       "0      159   19M     10000.0  Free    0.0       Everyone   \n",
       "1      967   14M    500000.0  Free    0.0       Everyone   \n",
       "2    87510  8.7M   5000000.0  Free    0.0       Everyone   \n",
       "3   215644   25M  50000000.0  Free    0.0           Teen   \n",
       "4      967  2.8M    100000.0  Free    0.0       Everyone   \n",
       "5      167  5.6M     50000.0  Free    0.0       Everyone   \n",
       "6      178   19M     50000.0  Free    0.0       Everyone   \n",
       "7    36815   29M   1000000.0  Free    0.0       Everyone   \n",
       "8    13791   33M   1000000.0  Free    0.0       Everyone   \n",
       "9      121  3.1M     10000.0  Free    0.0       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",
       "5               Art & Design      March 26, 2017                 1.0   \n",
       "6               Art & Design      April 26, 2018                 1.1   \n",
       "7               Art & Design       June 14, 2018            6.1.61.1   \n",
       "8               Art & Design  September 20, 2017               2.9.2   \n",
       "9    Art & Design;Creativity        July 3, 2018                 2.8   \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  \n",
       "5    2.3 and up  \n",
       "6  4.0.3 and up  \n",
       "7    4.2 and up  \n",
       "8    3.0 and up  \n",
       "9  4.0.3 and up  "
      ]
     },
     "execution_count": 30,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.head(10)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "id": "9bf4d41e",
   "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>Reviews</th>\n",
       "      <th>Installs</th>\n",
       "      <th>Price</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>1.084000e+04</td>\n",
       "      <td>1.084000e+04</td>\n",
       "      <td>10840.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>4.441529e+05</td>\n",
       "      <td>1.546434e+07</td>\n",
       "      <td>1.027368</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>2.927761e+06</td>\n",
       "      <td>8.502936e+07</td>\n",
       "      <td>15.949703</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>3.800000e+01</td>\n",
       "      <td>1.000000e+03</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>2.094000e+03</td>\n",
       "      <td>1.000000e+05</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>5.477550e+04</td>\n",
       "      <td>5.000000e+06</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>7.815831e+07</td>\n",
       "      <td>1.000000e+09</td>\n",
       "      <td>400.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "            Reviews      Installs         Price\n",
       "count  1.084000e+04  1.084000e+04  10840.000000\n",
       "mean   4.441529e+05  1.546434e+07      1.027368\n",
       "std    2.927761e+06  8.502936e+07     15.949703\n",
       "min    0.000000e+00  0.000000e+00      0.000000\n",
       "25%    3.800000e+01  1.000000e+03      0.000000\n",
       "50%    2.094000e+03  1.000000e+05      0.000000\n",
       "75%    5.477550e+04  5.000000e+06      0.000000\n",
       "max    7.815831e+07  1.000000e+09    400.000000"
      ]
     },
     "execution_count": 31,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.describe()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ddd35473",
   "metadata": {},
   "source": [
    "# Data Visualization and EDA"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "id": "1210dd43",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Category\n",
      "ART_AND_DESIGN         1.912894e+06\n",
      "AUTO_AND_VEHICLES      6.250613e+05\n",
      "BEAUTY                 5.131519e+05\n",
      "BOOKS_AND_REFERENCE    8.318050e+06\n",
      "BUSINESS               2.178076e+06\n",
      "COMICS                 9.347692e+05\n",
      "COMMUNICATION          8.435989e+07\n",
      "DATING                 1.129533e+06\n",
      "EDUCATION              5.586231e+06\n",
      "ENTERTAINMENT          1.925611e+07\n",
      "EVENTS                 2.495806e+05\n",
      "FAMILY                 5.201959e+06\n",
      "FINANCE                2.395215e+06\n",
      "FOOD_AND_DRINK         2.156683e+06\n",
      "GAME                   3.066960e+07\n",
      "HEALTH_AND_FITNESS     4.642441e+06\n",
      "HOUSE_AND_HOME         1.917187e+06\n",
      "LIBRARIES_AND_DEMO     7.411284e+05\n",
      "LIFESTYLE              1.407444e+06\n",
      "MAPS_AND_NAVIGATION    5.286729e+06\n",
      "MEDICAL                1.150269e+05\n",
      "NEWS_AND_MAGAZINES     2.648876e+07\n",
      "PARENTING              5.253518e+05\n",
      "PERSONALIZATION        5.932385e+06\n",
      "PHOTOGRAPHY            3.011417e+07\n",
      "PRODUCTIVITY           3.343418e+07\n",
      "SHOPPING               1.249173e+07\n",
      "SOCIAL                 4.769447e+07\n",
      "SPORTS                 4.560350e+06\n",
      "TOOLS                  1.358573e+07\n",
      "TRAVEL_AND_LOCAL       2.662359e+07\n",
      "VIDEO_PLAYERS          3.555430e+07\n",
      "WEATHER                5.196348e+06\n",
      "Name: Installs, dtype: float64\n",
      "Category\n",
      "ART_AND_DESIGN            5.97\n",
      "AUTO_AND_VEHICLES        13.47\n",
      "BEAUTY                    0.00\n",
      "BOOKS_AND_REFERENCE     119.77\n",
      "BUSINESS                185.27\n",
      "COMICS                    0.00\n",
      "COMMUNICATION            83.14\n",
      "DATING                   31.43\n",
      "EDUCATION                17.96\n",
      "ENTERTAINMENT             7.98\n",
      "EVENTS                  109.99\n",
      "FAMILY                 2434.78\n",
      "FINANCE                2900.83\n",
      "FOOD_AND_DRINK            8.48\n",
      "GAME                    287.30\n",
      "HEALTH_AND_FITNESS       67.34\n",
      "HOUSE_AND_HOME            0.00\n",
      "LIBRARIES_AND_DEMO        0.99\n",
      "LIFESTYLE              2360.87\n",
      "MAPS_AND_NAVIGATION      26.95\n",
      "MEDICAL                1439.96\n",
      "NEWS_AND_MAGAZINES        3.98\n",
      "PARENTING                 9.58\n",
      "PERSONALIZATION         153.96\n",
      "PHOTOGRAPHY             134.21\n",
      "PRODUCTIVITY            250.93\n",
      "SHOPPING                  5.48\n",
      "SOCIAL                   15.97\n",
      "SPORTS                  100.00\n",
      "TOOLS                   267.25\n",
      "TRAVEL_AND_LOCAL         49.95\n",
      "VIDEO_PLAYERS            10.46\n",
      "WEATHER                  32.42\n",
      "Name: Price, dtype: float64\n",
      "Category\n",
      "ART_AND_DESIGN            1714440\n",
      "AUTO_AND_VEHICLES         1163666\n",
      "BEAUTY                     396240\n",
      "BOOKS_AND_REFERENCE      21959069\n",
      "BUSINESS                 13954552\n",
      "COMICS                    3383276\n",
      "COMMUNICATION           815462260\n",
      "DATING                    7291278\n",
      "EDUCATION                39595786\n",
      "ENTERTAINMENT            59178154\n",
      "EVENTS                     161018\n",
      "FAMILY                  410226330\n",
      "FINANCE                  17550728\n",
      "FOOD_AND_DRINK            8883330\n",
      "GAME                   1585422349\n",
      "HEALTH_AND_FITNESS       37893743\n",
      "HOUSE_AND_HOME            3976385\n",
      "LIBRARIES_AND_DEMO        1037118\n",
      "LIFESTYLE                12882784\n",
      "MAPS_AND_NAVIGATION      30659254\n",
      "MEDICAL                   1585975\n",
      "NEWS_AND_MAGAZINES       54400863\n",
      "PARENTING                  958331\n",
      "PERSONALIZATION          89346140\n",
      "PHOTOGRAPHY             213516650\n",
      "PRODUCTIVITY            114116975\n",
      "SHOPPING                115041222\n",
      "SOCIAL                  621241422\n",
      "SPORTS                   70830169\n",
      "TOOLS                   273185044\n",
      "TRAVEL_AND_LOCAL         62617919\n",
      "VIDEO_PLAYERS           110380188\n",
      "WEATHER                  14604735\n",
      "Name: Reviews, dtype: int64\n"
     ]
    }
   ],
   "source": [
    "grp = df.groupby('Category')\n",
    "x = grp['Installs'].agg(np.mean)\n",
    "y = grp['Price'].agg(np.sum)\n",
    "z = grp['Reviews'].agg(np.sum)\n",
    "print(x)\n",
    "print(y)\n",
    "print(z)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "id": "49846679",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\ALBOCH~1\\AppData\\Local\\Temp/ipykernel_10152/3256865734.py:2: UserWarning: color is redundantly defined by the 'color' keyword argument and the fmt string \"ro\" (-> color='r'). The keyword argument will take precedence.\n",
      "  plt.plot(x , 'ro', color='b')\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1152x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(16,5))\n",
    "plt.plot(x , 'ro', color='b')\n",
    "plt.xticks(rotation=90)\n",
    "plt.title('Category vs Installs')\n",
    "plt.xlabel('Categories ------->')\n",
    "plt.ylabel('Installs ------->')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "id": "26125ea8",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<script>\n",
       "code_show_err=false; \n",
       "function code_toggle_err() {\n",
       " if (code_show_err){\n",
       " $('div.output_stderr').hide();\n",
       " } else {\n",
       " $('div.output_stderr').show();\n",
       " }\n",
       " code_show_err = !code_show_err\n",
       "} \n",
       "$( document ).ready(code_toggle_err);\n",
       "</script>\n",
       "To toggle on/off output_stderr, click <a href=\"javascript:code_toggle_err()\">here</a>."
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "execution_count": 34,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from IPython.display import HTML\n",
    "HTML('''<script>\n",
    "code_show_err=false; \n",
    "function code_toggle_err() {\n",
    " if (code_show_err){\n",
    " $('div.output_stderr').hide();\n",
    " } else {\n",
    " $('div.output_stderr').show();\n",
    " }\n",
    " code_show_err = !code_show_err\n",
    "} \n",
    "$( document ).ready(code_toggle_err);\n",
    "</script>\n",
    "To toggle on/off output_stderr, click <a href=\"javascript:code_toggle_err()\">here</a>.''')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "id": "bfeee965",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\ALBOCH~1\\AppData\\Local\\Temp/ipykernel_10152/3751501016.py:2: UserWarning: color is redundantly defined by the 'color' keyword argument and the fmt string \"r--\" (-> color='r'). The keyword argument will take precedence.\n",
      "  plt.plot(y , 'r--', color='r')\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1152x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(16,5))\n",
    "plt.plot(y , 'r--', color='r')\n",
    "plt.xticks(rotation=90)\n",
    "plt.title('Category vs Pricing')\n",
    "plt.xlabel('Categories ------->')\n",
    "plt.ylabel('Prices ------->')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "id": "1690575e",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\ALBOCH~1\\AppData\\Local\\Temp/ipykernel_10152/1818589174.py:2: UserWarning: color is redundantly defined by the 'color' keyword argument and the fmt string \"g^\" (-> color='g'). The keyword argument will take precedence.\n",
      "  plt.plot(z , 'g^', color='g')\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1152x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(16,5))\n",
    "plt.plot(z , 'g^', color='g')\n",
    "plt.xticks(rotation=90)\n",
    "plt.title('Category vs Reviews')\n",
    "plt.xlabel('Categories ------->')\n",
    "plt.ylabel('Reviews ------->')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "id": "dd38c3f1",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Int64Index: 10840 entries, 0 to 10840\n",
      "Data columns (total 13 columns):\n",
      " #   Column          Non-Null Count  Dtype  \n",
      "---  ------          --------------  -----  \n",
      " 0   App             10840 non-null  object \n",
      " 1   Category        10840 non-null  object \n",
      " 2   Rating          10840 non-null  object \n",
      " 3   Reviews         10840 non-null  int64  \n",
      " 4   Size            10840 non-null  object \n",
      " 5   Installs        10840 non-null  float64\n",
      " 6   Type            10840 non-null  object \n",
      " 7   Price           10840 non-null  float64\n",
      " 8   Content Rating  10840 non-null  object \n",
      " 9   Genres          10840 non-null  object \n",
      " 10  Last Updated    10840 non-null  object \n",
      " 11  Current Ver     10840 non-null  object \n",
      " 12  Android Ver     10840 non-null  object \n",
      "dtypes: float64(2), int64(1), object(10)\n",
      "memory usage: 1.2+ MB\n"
     ]
    }
   ],
   "source": [
    "df.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "id": "0c65998c",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Requirement already satisfied: nbconvert in c:\\users\\al bochi\\anaconda3\\lib\\site-packages (6.1.0)\n",
      "Collecting nbconvert\n",
      "  Downloading nbconvert-6.5.0-py3-none-any.whl (561 kB)\n",
      "Requirement already satisfied: mistune<2,>=0.8.1 in c:\\users\\al bochi\\anaconda3\\lib\\site-packages (from nbconvert) (0.8.4)\n",
      "Requirement already satisfied: beautifulsoup4 in c:\\users\\al bochi\\anaconda3\\lib\\site-packages (from nbconvert) (4.10.0)\n",
      "Collecting tinycss2\n",
      "  Downloading tinycss2-1.1.1-py3-none-any.whl (21 kB)\n",
      "Requirement already satisfied: pygments>=2.4.1 in c:\\users\\al bochi\\anaconda3\\lib\\site-packages (from nbconvert) (2.10.0)\n",
      "Requirement already satisfied: traitlets>=5.0 in c:\\users\\al bochi\\anaconda3\\lib\\site-packages (from nbconvert) (5.1.0)\n",
      "Requirement already satisfied: packaging in c:\\users\\al bochi\\anaconda3\\lib\\site-packages (from nbconvert) (21.0)\n",
      "Requirement already satisfied: MarkupSafe>=2.0 in c:\\users\\al bochi\\anaconda3\\lib\\site-packages (from nbconvert) (2.0.1)\n",
      "Requirement already satisfied: bleach in c:\\users\\al bochi\\anaconda3\\lib\\site-packages (from nbconvert) (4.0.0)\n",
      "Requirement already satisfied: jupyter-core>=4.7 in c:\\users\\al bochi\\anaconda3\\lib\\site-packages (from nbconvert) (4.8.1)\n",
      "Requirement already satisfied: nbclient>=0.5.0 in c:\\users\\al bochi\\anaconda3\\lib\\site-packages (from nbconvert) (0.5.3)\n",
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      "Requirement already satisfied: nbformat>=5.1 in c:\\users\\al bochi\\anaconda3\\lib\\site-packages (from nbconvert) (5.1.3)\n",
      "Collecting jinja2>=3.0\n",
      "  Downloading Jinja2-3.1.2-py3-none-any.whl (133 kB)\n",
      "Requirement already satisfied: defusedxml in c:\\users\\al bochi\\anaconda3\\lib\\site-packages (from nbconvert) (0.7.1)\n",
      "Requirement already satisfied: jupyterlab-pygments in c:\\users\\al bochi\\anaconda3\\lib\\site-packages (from nbconvert) (0.1.2)\n",
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      "Requirement already satisfied: nest-asyncio in c:\\users\\al bochi\\anaconda3\\lib\\site-packages (from nbclient>=0.5.0->nbconvert) (1.5.1)\n",
      "Requirement already satisfied: async-generator in c:\\users\\al bochi\\anaconda3\\lib\\site-packages (from nbclient>=0.5.0->nbconvert) (1.10)\n",
      "Requirement already satisfied: tornado>=4.1 in c:\\users\\al bochi\\anaconda3\\lib\\site-packages (from jupyter-client>=6.1.5->nbclient>=0.5.0->nbconvert) (6.1)\n",
      "Requirement already satisfied: python-dateutil>=2.1 in c:\\users\\al bochi\\anaconda3\\lib\\site-packages (from jupyter-client>=6.1.5->nbclient>=0.5.0->nbconvert) (2.8.2)\n",
      "Requirement already satisfied: pyzmq>=13 in c:\\users\\al bochi\\anaconda3\\lib\\site-packages (from jupyter-client>=6.1.5->nbclient>=0.5.0->nbconvert) (22.2.1)\n",
      "Requirement already satisfied: jsonschema!=2.5.0,>=2.4 in c:\\users\\al bochi\\anaconda3\\lib\\site-packages (from nbformat>=5.1->nbconvert) (3.2.0)\n",
      "Requirement already satisfied: ipython-genutils in c:\\users\\al bochi\\anaconda3\\lib\\site-packages (from nbformat>=5.1->nbconvert) (0.2.0)\n",
      "Requirement already satisfied: setuptools in c:\\users\\al bochi\\anaconda3\\lib\\site-packages (from jsonschema!=2.5.0,>=2.4->nbformat>=5.1->nbconvert) (58.0.4)Note: you may need to restart the kernel to use updated packages.\n",
      "\n",
      "Requirement already satisfied: six>=1.11.0 in c:\\users\\al bochi\\anaconda3\\lib\\site-packages (from jsonschema!=2.5.0,>=2.4->nbformat>=5.1->nbconvert) (1.16.0)\n",
      "Requirement already satisfied: pyrsistent>=0.14.0 in c:\\users\\al bochi\\anaconda3\\lib\\site-packages (from jsonschema!=2.5.0,>=2.4->nbformat>=5.1->nbconvert) (0.18.0)\n",
      "Requirement already satisfied: attrs>=17.4.0 in c:\\users\\al bochi\\anaconda3\\lib\\site-packages (from jsonschema!=2.5.0,>=2.4->nbformat>=5.1->nbconvert) (21.2.0)\n",
      "Requirement already satisfied: soupsieve>1.2 in c:\\users\\al bochi\\anaconda3\\lib\\site-packages (from beautifulsoup4->nbconvert) (2.2.1)\n",
      "Requirement already satisfied: webencodings in c:\\users\\al bochi\\anaconda3\\lib\\site-packages (from bleach->nbconvert) (0.5.1)\n",
      "Requirement already satisfied: pyparsing>=2.0.2 in c:\\users\\al bochi\\anaconda3\\lib\\site-packages (from packaging->nbconvert) (3.0.4)\n",
      "Installing collected packages: tinycss2, jinja2, nbconvert\n",
      "Successfully installed jinja2-3.1.2 nbconvert-6.5.0 tinycss2-1.1.1\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "  WARNING: The scripts jupyter-dejavu.exe and jupyter-nbconvert.exe are installed in 'C:\\Users\\Al Bochi\\AppData\\Roaming\\Python\\Python39\\Scripts' which is not on PATH.\n",
      "  Consider adding this directory to PATH or, if you prefer to suppress this warning, use --no-warn-script-location.\n",
      "ERROR: pip's dependency resolver does not currently take into account all the packages that are installed. This behaviour is the source of the following dependency conflicts.\n",
      "spyder 5.1.5 requires pyqt5<5.13, which is not installed.\n",
      "spyder 5.1.5 requires pyqtwebengine<5.13, which is not installed.\n",
      "anaconda-project 0.10.1 requires ruamel-yaml, which is not installed.\n",
      "pandas-profiling 3.1.0 requires joblib~=1.0.1, but you have joblib 1.1.0 which is incompatible.\n",
      "cookiecutter 1.7.2 requires Jinja2<3.0.0, but you have jinja2 3.1.2 which is incompatible.\n",
      "cookiecutter 1.7.2 requires MarkupSafe<2.0.0, but you have markupsafe 2.0.1 which is incompatible.\n"
     ]
    }
   ],
   "source": [
    "pip install --upgrade --user nbconvert"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "797509b7",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.9.7"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}