PROJ_08_GOOGLE PLAY STORE APPS AND REVIEWS.ipynb

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    }
   },
   "cell_type": "markdown",
   "id": "d147c861",
   "metadata": {},
   "source": [
    "![get-it-on-google-play-vector.png](attachment:get-it-on-google-play-vector.png)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "5b3140d6",
   "metadata": {},
   "source": [
    "# Mobile apps are everywhere. They are easy to create and can be lucrative. Because of these two factors, more and more apps are being developed. In this notebook, we will do a comprehensive analysis of the Android app market by comparing over ten thousand apps in Google Play across different categories. We'll look for insights in the data to devise strategies to drive growth and retention.\n",
    "\n",
    "#  Two files:\n",
    "\n",
    "# apps.csv: contains all the details of the applications on Google Play. There are 13 features that describe a given app.\n",
    "\n",
    "# user_reviews.csv: contains 100 reviews for each app, most helpful first. The text in each review has been pre-processed and attributed with three new features: Sentiment (Positive, Negative or Neutral), Sentiment Polarity and Sentiment Subjectivity."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "bc2442c5",
   "metadata": {},
   "source": [
    "## IMPORT THE DATA, DROP DUPLICATE ROWS, AND INSPECT THE DATA"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "03772f25",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Total number of apps in the dataset = \n",
      " App               10358\n",
      "Category          10358\n",
      "Rating             8893\n",
      "Reviews           10358\n",
      "Size              10358\n",
      "Installs          10358\n",
      "Type              10357\n",
      "Price             10358\n",
      "Content Rating    10357\n",
      "Genres            10358\n",
      "Last Updated      10358\n",
      "Current Ver       10350\n",
      "Android Ver       10355\n",
      "dtype: int64\n",
      "                                                 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  19.0      10,000+  Free     0       Everyone   \n",
      "1     967  14.0     500,000+  Free     0       Everyone   \n",
      "2   87510   8.7   5,000,000+  Free     0       Everyone   \n",
      "3  215644  25.0  50,000,000+  Free     0           Teen   \n",
      "4     967   2.8     100,000+  Free     0       Everyone   \n",
      "\n",
      "                      Genres Last Updated         Current Ver   Android Ver  \n",
      "0               Art & Design     7-Jan-18               1.0.0  4.0.3 and up  \n",
      "1  Art & Design;Pretend Play    15-Jan-18               2.0.0  4.0.3 and up  \n",
      "2               Art & Design     1-Aug-18               1.2.4  4.0.3 and up  \n",
      "3               Art & Design     8-Jun-18  Varies with device    4.2 and up  \n",
      "4    Art & Design;Creativity    20-Jun-18                 1.1    4.4 and up  \n"
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   ],
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    "# Reading in dataset\n",
    "import pandas as pd\n",
    "import numpy as np\n",
    "apps_with_duplicates = pd.read_csv(r\"E:\\Desktop\\DataCamp\\PROJ_08_GOOGLE PLAY STORE APPS AND REVIEWS\\archive\\google_apps.csv\")\n",
    "\n",
    "# Dropping duplicates from apps_with_duplicates\n",
    "apps = apps_with_duplicates.drop_duplicates()\n",
    "\n",
    "# Printing the total number of apps\n",
    "print('Total number of apps in the dataset = \\n', apps.count())\n",
    "\n",
    "# Having a look at a random sample of 5 rows\n",
    "print(apps.head(5))"
   ]
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   "source": [
    "## DATA CLEANING"
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   "id": "ed0ec971",
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      "<class 'pandas.core.frame.DataFrame'>\n",
      "Int64Index: 10358 entries, 0 to 10840\n",
      "Data columns (total 13 columns):\n",
      " #   Column          Non-Null Count  Dtype  \n",
      "---  ------          --------------  -----  \n",
      " 0   App             10358 non-null  object \n",
      " 1   Category        10358 non-null  object \n",
      " 2   Rating          8893 non-null   float64\n",
      " 3   Reviews         10358 non-null  object \n",
      " 4   Size            10358 non-null  float64\n",
      " 5   Installs        10358 non-null  object \n",
      " 6   Type            10357 non-null  object \n",
      " 7   Price           10358 non-null  object \n",
      " 8   Content Rating  10357 non-null  object \n",
      " 9   Genres          10358 non-null  object \n",
      " 10  Last Updated    10358 non-null  object \n",
      " 11  Current Ver     10350 non-null  object \n",
      " 12  Android Ver     10355 non-null  object \n",
      "dtypes: float64(2), object(11)\n",
      "memory usage: 1.1+ MB\n",
      "None\n"
     ]
    },
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     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\Sadat\\anaconda3\\lib\\site-packages\\pandas\\core\\indexing.py:1676: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame.\n",
      "Try using .loc[row_indexer,col_indexer] = value instead\n",
      "\n",
      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  self._setitem_single_column(ilocs[0], value, pi)\n"
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    "# Listing of the characters to remove\n",
    "chars_to_remove = [\"+\", \",\", \"$\"]\n",
    "# Listing of the column names to clean\n",
    "cols_to_clean = [\"Installs\", \"Price\"]\n",
    "\n",
    "# Looping for each column in cols_to_clean\n",
    "for col in cols_to_clean:\n",
    "    # Looping for each char in chars_to_remove\n",
    "    for char in chars_to_remove:\n",
    "        # Replacing the character with an empty string\n",
    "        apps.loc[:, col] = apps.loc[:, col].apply(lambda x: x.replace(char, ''))\n",
    "        apps.loc[:, col] = apps.loc[:, col].apply(lambda x: x.replace(char, ''))\n",
    "# Printing a summary of the apps dataframe\n",
    "print(apps.info())"
   ]
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   "cell_type": "markdown",
   "id": "602c8a2a",
   "metadata": {},
   "source": [
    "## CORRECTING DATA TYPES"
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  },
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   "cell_type": "code",
   "execution_count": 3,
   "id": "ce482725",
   "metadata": {
    "scrolled": true
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     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Int64Index: 10358 entries, 0 to 10840\n",
      "Data columns (total 13 columns):\n",
      " #   Column          Non-Null Count  Dtype  \n",
      "---  ------          --------------  -----  \n",
      " 0   App             10358 non-null  object \n",
      " 1   Category        10358 non-null  object \n",
      " 2   Rating          8893 non-null   float64\n",
      " 3   Reviews         10358 non-null  object \n",
      " 4   Size            10358 non-null  float64\n",
      " 5   Installs        10358 non-null  float64\n",
      " 6   Type            10357 non-null  object \n",
      " 7   Price           10358 non-null  float64\n",
      " 8   Content Rating  10357 non-null  object \n",
      " 9   Genres          10358 non-null  object \n",
      " 10  Last Updated    10358 non-null  object \n",
      " 11  Current Ver     10350 non-null  object \n",
      " 12  Android Ver     10355 non-null  object \n",
      "dtypes: float64(4), object(9)\n",
      "memory usage: 1.1+ MB\n",
      "None\n"
     ]
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    "# Converting Installs to float data type\n",
    "apps.loc[:, \"Installs\"] = apps.loc[:, \"Installs\"].astype(float)\n",
    "\n",
    "# Converting Price to float data type\n",
    "apps.loc[:, \"Price\"] = apps.loc[:, \"Price\"].astype(float)\n",
    "\n",
    "# Converting Size to float data type\n",
    "apps.loc[:, \"Size\"] = apps.loc[:, \"Size\"].astype(float)\n",
    "\n",
    "# Checking dtypes of the apps dataframe\n",
    "print(apps.info())"
   ]
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   "cell_type": "markdown",
   "id": "d9d7f2ee",
   "metadata": {},
   "source": [
    "## EXPLORING APP CATEGORIES"
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   "cell_type": "code",
   "execution_count": 4,
   "id": "407a5a28",
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   ],
   "source": [
    "import plotly\n",
    "plotly.offline.init_notebook_mode(connected=True)\n",
    "import plotly.graph_objs as go\n",
    "\n",
    "# Printing the total number of unique categories\n",
    "num_categories = len(apps[\"Category\"].unique())\n",
    "print('Number of categories = ', num_categories)\n",
    "\n",
    "# Counting the number of apps in each 'Category'. \n",
    "num_apps_in_category = apps['Category'].value_counts()\n",
    "\n",
    "# Sorting num_apps_in_category in descending order based on the count of apps in each category\n",
    "sorted_num_apps_in_category = num_apps_in_category.sort_values(ascending = False)\n",
    "\n",
    "data = [go.Bar(\n",
    "        x = num_apps_in_category.index, # index = category name\n",
    "        y = num_apps_in_category.values, # value = count\n",
    ")]\n",
    "\n",
    "plotly.offline.iplot(data)"
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   "cell_type": "markdown",
   "id": "8a5b994a",
   "metadata": {},
   "source": [
    "## DISTRIBUTION OF APP RATINGS"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "e3304914",
   "metadata": {
    "scrolled": true
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     "output_type": "stream",
     "text": [
      "Average app rating =  4.189542336669298\n"
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          4,
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          4,
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          4,
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          4,
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          4,
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          4,
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          4,
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          4,
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          4,
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          3,
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          4,
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          4,
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          4,
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          4,
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          4,
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          4,
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          4,
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          4,
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          4,
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          4,
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          4,
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     "metadata": {},
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   ],
   "source": [
    "# Measuring Average rating of apps\n",
    "avg_app_rating = apps[\"Rating\"].mean()\n",
    "print('Average app rating = ', avg_app_rating)\n",
    "\n",
    "# Making the Distribution of apps according to their ratings\n",
    "data = [go.Histogram(\n",
    "        x = apps['Rating']\n",
    ")]\n",
    "\n",
    "# Adding Vertical dashed line to indicate the average app rating\n",
    "layout = {'shapes': [{\n",
    "              'type' :'line',\n",
    "              'x0': avg_app_rating,\n",
    "              'y0': 0,\n",
    "              'x1': avg_app_rating,\n",
    "              'y1': 1000,\n",
    "              'line': { 'dash': 'dash'}\n",
    "          }]\n",
    "          }\n",
    "\n",
    "plotly.offline.iplot({'data': data, 'layout': layout})"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "3f869716",
   "metadata": {},
   "source": [
    "## SIZE AND PRICE OF AN APP"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "054616f2",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x432 with 3 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x432 with 3 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "%matplotlib inline\n",
    "import seaborn as sns\n",
    "sns.set_style(\"darkgrid\")\n",
    "import warnings\n",
    "warnings.filterwarnings(\"ignore\")\n",
    "\n",
    "# Selecting rows where both 'Rating' and 'Size' values are present (ie. the two values are not null)\n",
    "apps_with_size_and_rating_present = apps[(~apps['Rating'].isnull()) & (~apps['Size'].isnull())]\n",
    "\n",
    "# Subsetting for categories with at least 250 apps\n",
    "large_categories = apps_with_size_and_rating_present.groupby(['Category']).filter(lambda x: len(x) >= 250)\n",
    "\n",
    "# Plotting size vs. rating\n",
    "plt1 = sns.jointplot(x = large_categories['Size'], y = large_categories['Rating'])\n",
    "\n",
    "# Selecting apps whose 'Type' is 'Paid'\n",
    "paid_apps = apps_with_size_and_rating_present[apps_with_size_and_rating_present['Type'] == 'Paid']\n",
    "\n",
    "# Plotting price vs. rating\n",
    "plt2 = sns.jointplot(x = paid_apps['Price'], y = paid_apps['Rating'])"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "d5637d29",
   "metadata": {},
   "source": [
    "## RELATION BETWEEN APP CATEGORY AND APP PRICE"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "e83a87af",
   "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>Category</th>\n",
       "      <th>App</th>\n",
       "      <th>Price</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>4197</th>\n",
       "      <td>FAMILY</td>\n",
       "      <td>most expensive app (H)</td>\n",
       "      <td>399.99</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4362</th>\n",
       "      <td>LIFESTYLE</td>\n",
       "      <td>💎 I'm rich</td>\n",
       "      <td>399.99</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4367</th>\n",
       "      <td>LIFESTYLE</td>\n",
       "      <td>I'm Rich - Trump Edition</td>\n",
       "      <td>400.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5351</th>\n",
       "      <td>LIFESTYLE</td>\n",
       "      <td>I am rich</td>\n",
       "      <td>399.99</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5354</th>\n",
       "      <td>FAMILY</td>\n",
       "      <td>I am Rich Plus</td>\n",
       "      <td>399.99</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5355</th>\n",
       "      <td>LIFESTYLE</td>\n",
       "      <td>I am rich VIP</td>\n",
       "      <td>299.99</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5356</th>\n",
       "      <td>FINANCE</td>\n",
       "      <td>I Am Rich Premium</td>\n",
       "      <td>399.99</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5357</th>\n",
       "      <td>LIFESTYLE</td>\n",
       "      <td>I am extremely Rich</td>\n",
       "      <td>379.99</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5358</th>\n",
       "      <td>FINANCE</td>\n",
       "      <td>I am Rich!</td>\n",
       "      <td>399.99</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5359</th>\n",
       "      <td>FINANCE</td>\n",
       "      <td>I am rich(premium)</td>\n",
       "      <td>399.99</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5362</th>\n",
       "      <td>FAMILY</td>\n",
       "      <td>I Am Rich Pro</td>\n",
       "      <td>399.99</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5364</th>\n",
       "      <td>FINANCE</td>\n",
       "      <td>I am rich (Most expensive app)</td>\n",
       "      <td>399.99</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5366</th>\n",
       "      <td>FAMILY</td>\n",
       "      <td>I Am Rich</td>\n",
       "      <td>389.99</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5369</th>\n",
       "      <td>FINANCE</td>\n",
       "      <td>I am Rich</td>\n",
       "      <td>399.99</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5373</th>\n",
       "      <td>FINANCE</td>\n",
       "      <td>I AM RICH PRO PLUS</td>\n",
       "      <td>399.99</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9917</th>\n",
       "      <td>FINANCE</td>\n",
       "      <td>Eu Sou Rico</td>\n",
       "      <td>394.99</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9934</th>\n",
       "      <td>LIFESTYLE</td>\n",
       "      <td>I'm Rich/Eu sou Rico/أنا غني/我很有錢</td>\n",
       "      <td>399.99</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       Category                                App   Price\n",
       "4197     FAMILY             most expensive app (H)  399.99\n",
       "4362  LIFESTYLE                         💎 I'm rich  399.99\n",
       "4367  LIFESTYLE           I'm Rich - Trump Edition  400.00\n",
       "5351  LIFESTYLE                          I am rich  399.99\n",
       "5354     FAMILY                     I am Rich Plus  399.99\n",
       "5355  LIFESTYLE                      I am rich VIP  299.99\n",
       "5356    FINANCE                  I Am Rich Premium  399.99\n",
       "5357  LIFESTYLE                I am extremely Rich  379.99\n",
       "5358    FINANCE                         I am Rich!  399.99\n",
       "5359    FINANCE                 I am rich(premium)  399.99\n",
       "5362     FAMILY                      I Am Rich Pro  399.99\n",
       "5364    FINANCE     I am rich (Most expensive app)  399.99\n",
       "5366     FAMILY                          I Am Rich  389.99\n",
       "5369    FINANCE                          I am Rich  399.99\n",
       "5373    FINANCE                 I AM RICH PRO PLUS  399.99\n",
       "9917    FINANCE                        Eu Sou Rico  394.99\n",
       "9934  LIFESTYLE  I'm Rich/Eu sou Rico/أنا غني/我很有錢  399.99"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1080x576 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "fig, ax = plt.subplots()\n",
    "fig.set_size_inches(15, 8)\n",
    "\n",
    "# Selecting a few popular app categories\n",
    "popular_app_cats = apps[apps.Category.isin(['GAME', 'FAMILY', 'PHOTOGRAPHY',\n",
    "                                            'MEDICAL', 'TOOLS', 'FINANCE',\n",
    "                                            'LIFESTYLE','BUSINESS'])]\n",
    "\n",
    "# Examining the price trend by plotting Price vs Category\n",
    "ax = sns.stripplot(x = popular_app_cats[\"Price\"], y = popular_app_cats[\"Category\"], jitter=True, linewidth=1)\n",
    "ax.set_title('App pricing trend across categories')\n",
    "\n",
    "# Determining the Apps whose Price is greater than 200\n",
    "apps_above_200 = popular_app_cats[popular_app_cats['Price'] > 200]\n",
    "apps_above_200[['Category', 'App', 'Price']]"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "aa1ece6a",
   "metadata": {},
   "source": [
    "## FILTER OUT 'JUNK' APPS"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "0ee15d15",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0.5, 1.0, 'App pricing trend across categories after filtering for junk apps')"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1080x576 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Selecting apps priced below $100\n",
    "apps_under_100 = popular_app_cats[popular_app_cats[\"Price\"] < 100]\n",
    "\n",
    "fig, ax = plt.subplots()\n",
    "fig.set_size_inches(15, 8)\n",
    "\n",
    "# Examining price vs category with the authentic apps (apps_under_100)\n",
    "ax = sns.stripplot(x = apps_under_100[\"Price\"], y = apps_under_100[\"Category\"], data = apps_under_100, jitter = True, linewidth = 1)\n",
    "ax.set_title('App pricing trend across categories after filtering for junk apps')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "e6e8e140",
   "metadata": {},
   "source": [
    "## POPULARITY OF PAID APPS VS FREE APPS"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "262d9e69",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/vnd.plotly.v1+json": {
       "config": {
        "linkText": "Export to plot.ly",
        "plotlyServerURL": "https://plot.ly",
        "showLink": false
       },
       "data": [
        {
         "name": "Paid",
         "type": "box",
         "y": [
          100000,
          100000,
          100000,
          10000,
          1000,
          50,
          100,
          100,
          100,
          10000,
          1000,
          1000,
          500000,
          100000,
          100000,
          100000,
          10000,
          50000,
          100000,
          10000,
          100000,
          100000,
          100000,
          100000,
          100000,
          100000,
          100000,
          100000,
          100000,
          100000,
          5000,
          5000,
          1000,
          500,
          100000,
          500000,
          10000,
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          1000,
          1000,
          1000,
          100,
          100,
          1000,
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          5000,
          1000,
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          1000,
          10000,
          10000,
          50000,
          10000000,
          1000000,
          100000,
          10000,
          10000,
          10000,
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     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "trace0 = go.Box(\n",
    "    # Subsetting Data for paid apps\n",
    "    y = apps[apps['Type'] == 'Paid']['Installs'],\n",
    "    name = 'Paid'\n",
    ")\n",
    "\n",
    "trace1 = go.Box(\n",
    "    # Subsetting Data for free apps\n",
    "    y = apps[apps['Type'] == 'Free']['Installs'],\n",
    "    name = 'Free'\n",
    ")\n",
    "\n",
    "layout = go.Layout(\n",
    "    title = \"Number of downloads of paid apps vs. free apps\",\n",
    "    yaxis = dict(title = \"Log number of downloads\",\n",
    "                type = 'log',\n",
    "                autorange = True)\n",
    ")\n",
    "\n",
    "# Adding trace0 and trace1 to a list for plotting\n",
    "data = [trace0, trace1]\n",
    "plotly.offline.iplot({'data': data, 'layout': layout})"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "948cf08a",
   "metadata": {},
   "source": [
    "## SENTIMENT ANALYSIS OF USER REVIEWS"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "eda9a95c",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0.5, 1.0, 'Sentiment Polarity Distribution')"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 792x576 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Loading user_reviews.csv\n",
    "reviews_df = pd.read_csv(r\"E:\\Desktop\\DataCamp\\PROJ_08_GOOGLE PLAY STORE APPS AND REVIEWS\\archive\\google_store_user_reviews.csv\")\n",
    "\n",
    "# Joining the two dataframes\n",
    "merged_df = apps.merge(reviews_df)\n",
    "\n",
    "# Dropping NA values from Sentiment and Review columns\n",
    "merged_df = merged_df.dropna(subset = ['Sentiment', 'Translated_Review'])\n",
    "\n",
    "sns.set_style('ticks')\n",
    "fig, ax = plt.subplots()\n",
    "fig.set_size_inches(11, 8)\n",
    "\n",
    "# Measuring User review sentiment polarity for paid vs. free apps\n",
    "ax = sns.boxplot(x = 'Type', y = 'Sentiment_Polarity', data = merged_df)\n",
    "ax.set_title('Sentiment Polarity Distribution')"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "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": "3.8.8"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}