Exploratory Data Analysis TikTok project lab Mohammed Braimah.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "DtNBZFHO3M7n"
   },
   "source": [
    "# **TikTok Project**\n",
    "**Course 3 - Go Beyond the Numbers: Translate Data into Insights**"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "ASDNhWAxE-r3"
   },
   "source": [
    "Your TikTok data team is still in the early stages of their latest project. So far, you’ve completed a project proposal and used Python to inspect and organize the TikTok dataset.\n",
    "\n",
    "Orion Rainier, a Data Scientist at TikTok, is pleased with the work you have already completed and is requesting your assistance with some Exploratory Data Analysis (EDA) and data visualization. The management team asked to see a Python notebook showing data structuring and cleaning, as well as any matplotlib/seaborn visualizations plotted to help us understand the data. At the very least, include a graph comparing claim counts to opinion counts, as well as boxplots of the most important variables (like “video duration,” “video like count,” “video comment count,” and “video view count”) to check for outliers. Also, include a breakdown of “author ban status” counts.\n",
    "\n",
    "Additionally, the management team has recently asked all EDA to include Tableau visualizations. Tableau visualizations are particularly helpful in status reports to the client and board members. For this data, create a Tableau dashboard showing a simple claims versus opinions count, as well as stacked bar charts of claims versus opinions for variables like video view counts, video like counts, video share counts, and video download counts. Make sure it is easy to understand to someone who isn’t data savvy, and remember that the assistant director is a person with visual impairments.\n",
    "\n",
    "You also notice a follow-up email from the Data Science Lead, Willow Jaffey. Willow suggests including an executive summary of your analysis to share with teammates.\n",
    "\n",
    "A notebook was structured and prepared to help you in this project. Please complete the following questions."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "rgSbVJvomcVa"
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   "source": [
    "# **Course 3 End-of-course project: Exploratory data analysis**\n",
    "\n",
    "In this activity, you will examine data provided and prepare it for analysis. You will also design a professional data visualization that tells a story, and will help data-driven decisions for business needs.\n",
    "\n",
    "Please note that the Tableau visualization activity is optional, and will not affect your completion of the course. Completing the Tableau activity will help you practice planning out and plotting a data visualization based on a specific business need. The structure of this activity is designed to emulate the proposals you will likely be assigned in your career as a data professional. Completing this activity will help prepare you for those career moments.\n",
    "<br/>\n",
    "\n",
    "**The purpose** of this project is to conduct exploratory data analysis on a provided data set. Your mission is to continue the investigation you began in C2 and perform further EDA on this data with the aim of learning more about the variables. Of particular interest is information related to what distinguishes claim videos from opinion videos.\n",
    "\n",
    "**The goal** is to explore the dataset and create visualizations.\n",
    "<br/>\n",
    "*This activity has 4 parts:*\n",
    "\n",
    "**Part 1:** Imports, links, and loading\n",
    "\n",
    "**Part 2:** Data Exploration\n",
    "*   Data cleaning\n",
    "\n",
    "\n",
    "**Part 3:** Build visualizations\n",
    "\n",
    "**Part 4:** Evaluate and share results"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "pI2gfRn9Fs8-"
   },
   "source": [
    "Follow the instructions and answer the question below to complete the activity. Then, you will complete an executive summary using the questions listed on the PACE Strategy Document.\n",
    "\n",
    "Be sure to complete this activity before moving on. The next course item will provide you with a completed exemplar to compare to your own work."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "jPs4VVaxFpd-"
   },
   "source": [
    "# **Visualize a story in Tableau and Python**"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "rdR5eWbYx8GE"
   },
   "source": [
    "<img src=\"images/Pace.png\" width=\"100\" height=\"100\" align=left>\n",
    "\n",
    "# **PACE stages**"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "viBVsQThegig"
   },
   "source": [
    "Throughout these project notebooks, you'll see references to the problem-solving framework PACE. The following notebook components are labeled with the respective PACE stage: Plan, Analyze, Construct, and Execute."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "xKLZJUqMx8GE"
   },
   "source": [
    "<img src=\"images/Plan.png\" width=\"100\" height=\"100\" align=left>\n",
    "\n",
    "\n",
    "## **PACE: Plan**\n",
    "\n",
    "Consider the questions in your PACE Strategy Document and those below where applicable to craft your response:\n",
    "1. Identify any outliers:\n",
    "\n",
    "\n",
    "*   What methods are best for identifying outliers?\n",
    "*   How do you make the decision to keep or exclude outliers from any future models?\n",
    "\n"
   ]
  },
  {
   "cell_type": "markdown",
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   "source": [
    "You can use the mean and the median to make box plots. \n",
    "\n",
    "You can choose to leave them if you think they will not affect your model\n",
    "You can delete them if you think they will impact your analysis \n",
    "you can reassign the outliers to a new variable if you think that can be helpful in building a model"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "SKur6gTPRcvy"
   },
   "source": [
    "### **Task 1. Imports, links, and loading**\n",
    "Go to Tableau Public\n",
    "The following link will help you complete this activity. Keep Tableau Public open as you proceed to the next steps.\n",
    "\n",
    "Link to supporting materials:\n",
    "Public Tableau: https://public.tableau.com/s/\n",
    "\n",
    "For EDA of the data, import the packages that would be most helpful, such as `pandas`, `numpy`, `matplotlib.pyplot`, and `seaborn`.\n"
   ]
  },
  {
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   "execution_count": 3,
   "metadata": {
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   "source": [
    "\"\"\"We are importing packages\"\"\"\n",
    "import pandas as pd\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns \n",
    "\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "JRf06KQ-uK7i"
   },
   "source": [
    "Then, load the dataset into a dataframe. Read in the data and store it as a dataframe object.\n",
    "\n",
    "**Note:** As shown in this cell, the dataset has been automatically loaded in for you. You do not need to download the .csv file, or provide more code, in order to access the dataset and proceed with this lab. Please continue with this activity by completing the following instructions.\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "id": "w7XSDxoqyF9D"
   },
   "outputs": [],
   "source": [
    "# Load dataset into dataframe\n",
    "data = pd.read_csv(\"tiktok_dataset.csv\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "3mipEiyZx8GI"
   },
   "source": [
    "<img src=\"images/Analyze.png\" width=\"100\" height=\"100\" align=left>\n",
    "\n",
    "## **PACE: Analyze**\n",
    "\n",
    "Consider the questions in your PACE Strategy Document and those below where applicable to complete your code."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "n09krlKWRw_2"
   },
   "source": [
    "### **Task 2a: Data exploration and cleaning**\n",
    "\n",
    "The first step is to assess your data. Check the Data Source page on Tableau Public to get a sense of the size, shape and makeup of the data set.\n",
    "\n",
    "Consider functions that help you understand and structure the data.\n",
    "\n",
    "*    `.head()`\n",
    "*    `.info()`\n",
    "*    `.describe()`\n",
    "*    `.groupby()`\n",
    "*    `.sort_values()`\n",
    "\n",
    "Consider the following questions as you work:\n",
    "\n",
    "What do you do about missing data (if any)?\n",
    "\n",
    "Are there data outliers?"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "uk6zuv_mUU2k"
   },
   "source": [
    "Start by discovering, using `.head()`, `.size`, and `.shape`."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "id": "cBOUo5p-tbib"
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   "outputs": [
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       "      <th>#</th>\n",
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      "text/plain": [
       "    # claim_status    video_id  video_duration_sec  \\\n",
       "0   1        claim  7017666017                  59   \n",
       "1   2        claim  4014381136                  32   \n",
       "2   3        claim  9859838091                  31   \n",
       "3   4        claim  1866847991                  25   \n",
       "4   5        claim  7105231098                  19   \n",
       "5   6        claim  8972200955                  35   \n",
       "6   7        claim  4958886992                  16   \n",
       "7   8        claim  2270982263                  41   \n",
       "8   9        claim  5235769692                  50   \n",
       "9  10        claim  4660861094                  45   \n",
       "\n",
       "                            video_transcription_text verified_status  \\\n",
       "0  someone shared with me that drone deliveries a...    not verified   \n",
       "1  someone shared with me that there are more mic...    not verified   \n",
       "2  someone shared with me that american industria...    not verified   \n",
       "3  someone shared with me that the metro of st. p...    not verified   \n",
       "4  someone shared with me that the number of busi...    not verified   \n",
       "5  someone shared with me that gross domestic pro...    not verified   \n",
       "6  someone shared with me that elvis presley has ...    not verified   \n",
       "7  someone shared with me that the best selling s...    not verified   \n",
       "8  someone shared with me that about half of the ...    not verified   \n",
       "9  someone shared with me that it would take a 50...        verified   \n",
       "\n",
       "  author_ban_status  video_view_count  video_like_count  video_share_count  \\\n",
       "0      under review          343296.0           19425.0              241.0   \n",
       "1            active          140877.0           77355.0            19034.0   \n",
       "2            active          902185.0           97690.0             2858.0   \n",
       "3            active          437506.0          239954.0            34812.0   \n",
       "4            active           56167.0           34987.0             4110.0   \n",
       "5      under review          336647.0          175546.0            62303.0   \n",
       "6            active          750345.0          486192.0           193911.0   \n",
       "7            active          547532.0            1072.0               50.0   \n",
       "8            active           24819.0           10160.0             1050.0   \n",
       "9            active          931587.0          171051.0            67739.0   \n",
       "\n",
       "   video_download_count  video_comment_count  \n",
       "0                   1.0                  0.0  \n",
       "1                1161.0                684.0  \n",
       "2                 833.0                329.0  \n",
       "3                1234.0                584.0  \n",
       "4                 547.0                152.0  \n",
       "5                4293.0               1857.0  \n",
       "6                8616.0               5446.0  \n",
       "7                  22.0                 11.0  \n",
       "8                  53.0                 27.0  \n",
       "9                4104.0               2540.0  "
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Display and examine the first few rows of the dataframe\n",
    "data.head(10)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "id": "GvT82D1qyF9F"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "232584"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
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   ],
   "source": [
    "# Get the size of the data\n",
    "data.size\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "id": "ZMVCmsoMvCEm"
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   "outputs": [
    {
     "data": {
      "text/plain": [
       "(19382, 12)"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Get the shape of the data\n",
    "data.shape\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "psmn0VD0UWBk"
   },
   "source": [
    "Get basic information about the data, using `.info()`."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "id": "Thlb8oiyUPwe"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 19382 entries, 0 to 19381\n",
      "Data columns (total 12 columns):\n",
      " #   Column                    Non-Null Count  Dtype  \n",
      "---  ------                    --------------  -----  \n",
      " 0   #                         19382 non-null  int64  \n",
      " 1   claim_status              19084 non-null  object \n",
      " 2   video_id                  19382 non-null  int64  \n",
      " 3   video_duration_sec        19382 non-null  int64  \n",
      " 4   video_transcription_text  19084 non-null  object \n",
      " 5   verified_status           19382 non-null  object \n",
      " 6   author_ban_status         19382 non-null  object \n",
      " 7   video_view_count          19084 non-null  float64\n",
      " 8   video_like_count          19084 non-null  float64\n",
      " 9   video_share_count         19084 non-null  float64\n",
      " 10  video_download_count      19084 non-null  float64\n",
      " 11  video_comment_count       19084 non-null  float64\n",
      "dtypes: float64(5), int64(3), object(4)\n",
      "memory usage: 1.8+ MB\n"
     ]
    }
   ],
   "source": [
    "# Get basic information about the data\n",
    "data.info()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "WulP4lZ9UVgy"
   },
   "source": [
    "Generate a table of descriptive statistics, using `.describe()`."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "id": "xMpkdNQ0UPmW"
   },
   "outputs": [
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>#</th>\n",
       "      <th>claim_status</th>\n",
       "      <th>video_id</th>\n",
       "      <th>video_duration_sec</th>\n",
       "      <th>video_transcription_text</th>\n",
       "      <th>verified_status</th>\n",
       "      <th>author_ban_status</th>\n",
       "      <th>video_view_count</th>\n",
       "      <th>video_like_count</th>\n",
       "      <th>video_share_count</th>\n",
       "      <th>video_download_count</th>\n",
       "      <th>video_comment_count</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>19382.000000</td>\n",
       "      <td>19084</td>\n",
       "      <td>1.938200e+04</td>\n",
       "      <td>19382.000000</td>\n",
       "      <td>19084</td>\n",
       "      <td>19382</td>\n",
       "      <td>19382</td>\n",
       "      <td>19084.000000</td>\n",
       "      <td>19084.000000</td>\n",
       "      <td>19084.000000</td>\n",
       "      <td>19084.000000</td>\n",
       "      <td>19084.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>unique</th>\n",
       "      <td>NaN</td>\n",
       "      <td>2</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>19012</td>\n",
       "      <td>2</td>\n",
       "      <td>3</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>top</th>\n",
       "      <td>NaN</td>\n",
       "      <td>claim</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>a friend read  in the media a claim that badmi...</td>\n",
       "      <td>not verified</td>\n",
       "      <td>active</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>freq</th>\n",
       "      <td>NaN</td>\n",
       "      <td>9608</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2</td>\n",
       "      <td>18142</td>\n",
       "      <td>15663</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>9691.500000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>5.627454e+09</td>\n",
       "      <td>32.421732</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>254708.558688</td>\n",
       "      <td>84304.636030</td>\n",
       "      <td>16735.248323</td>\n",
       "      <td>1049.429627</td>\n",
       "      <td>349.312146</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>5595.245794</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.536440e+09</td>\n",
       "      <td>16.229967</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>322893.280814</td>\n",
       "      <td>133420.546814</td>\n",
       "      <td>32036.174350</td>\n",
       "      <td>2004.299894</td>\n",
       "      <td>799.638865</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>1.000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.234959e+09</td>\n",
       "      <td>5.000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>20.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>4846.250000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.430417e+09</td>\n",
       "      <td>18.000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>4942.500000</td>\n",
       "      <td>810.750000</td>\n",
       "      <td>115.000000</td>\n",
       "      <td>7.000000</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>9691.500000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>5.618664e+09</td>\n",
       "      <td>32.000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>9954.500000</td>\n",
       "      <td>3403.500000</td>\n",
       "      <td>717.000000</td>\n",
       "      <td>46.000000</td>\n",
       "      <td>9.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>14536.750000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>7.843960e+09</td>\n",
       "      <td>47.000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>504327.000000</td>\n",
       "      <td>125020.000000</td>\n",
       "      <td>18222.000000</td>\n",
       "      <td>1156.250000</td>\n",
       "      <td>292.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>19382.000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>9.999873e+09</td>\n",
       "      <td>60.000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>999817.000000</td>\n",
       "      <td>657830.000000</td>\n",
       "      <td>256130.000000</td>\n",
       "      <td>14994.000000</td>\n",
       "      <td>9599.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                   # claim_status      video_id  video_duration_sec  \\\n",
       "count   19382.000000        19084  1.938200e+04        19382.000000   \n",
       "unique           NaN            2           NaN                 NaN   \n",
       "top              NaN        claim           NaN                 NaN   \n",
       "freq             NaN         9608           NaN                 NaN   \n",
       "mean     9691.500000          NaN  5.627454e+09           32.421732   \n",
       "std      5595.245794          NaN  2.536440e+09           16.229967   \n",
       "min         1.000000          NaN  1.234959e+09            5.000000   \n",
       "25%      4846.250000          NaN  3.430417e+09           18.000000   \n",
       "50%      9691.500000          NaN  5.618664e+09           32.000000   \n",
       "75%     14536.750000          NaN  7.843960e+09           47.000000   \n",
       "max     19382.000000          NaN  9.999873e+09           60.000000   \n",
       "\n",
       "                                 video_transcription_text verified_status  \\\n",
       "count                                               19084           19382   \n",
       "unique                                              19012               2   \n",
       "top     a friend read  in the media a claim that badmi...    not verified   \n",
       "freq                                                    2           18142   \n",
       "mean                                                  NaN             NaN   \n",
       "std                                                   NaN             NaN   \n",
       "min                                                   NaN             NaN   \n",
       "25%                                                   NaN             NaN   \n",
       "50%                                                   NaN             NaN   \n",
       "75%                                                   NaN             NaN   \n",
       "max                                                   NaN             NaN   \n",
       "\n",
       "       author_ban_status  video_view_count  video_like_count  \\\n",
       "count              19382      19084.000000      19084.000000   \n",
       "unique                 3               NaN               NaN   \n",
       "top               active               NaN               NaN   \n",
       "freq               15663               NaN               NaN   \n",
       "mean                 NaN     254708.558688      84304.636030   \n",
       "std                  NaN     322893.280814     133420.546814   \n",
       "min                  NaN         20.000000          0.000000   \n",
       "25%                  NaN       4942.500000        810.750000   \n",
       "50%                  NaN       9954.500000       3403.500000   \n",
       "75%                  NaN     504327.000000     125020.000000   \n",
       "max                  NaN     999817.000000     657830.000000   \n",
       "\n",
       "        video_share_count  video_download_count  video_comment_count  \n",
       "count        19084.000000          19084.000000         19084.000000  \n",
       "unique                NaN                   NaN                  NaN  \n",
       "top                   NaN                   NaN                  NaN  \n",
       "freq                  NaN                   NaN                  NaN  \n",
       "mean         16735.248323           1049.429627           349.312146  \n",
       "std          32036.174350           2004.299894           799.638865  \n",
       "min              0.000000              0.000000             0.000000  \n",
       "25%            115.000000              7.000000             1.000000  \n",
       "50%            717.000000             46.000000             9.000000  \n",
       "75%          18222.000000           1156.250000           292.000000  \n",
       "max         256130.000000          14994.000000          9599.000000  "
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Generate a table of descriptive statistics\n",
    "data.describe (include = \"all\")\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "vCGi3U9nw4Er"
   },
   "source": [
    "### **Task 2b. Assess data types**"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "aNBRa33TR_Is"
   },
   "source": [
    "In Tableau, staying on the data source page, double check the data types of the columns in the dataset. Refer to the dimensions and measures in Tableau.\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "WtpiC1JvHRtS"
   },
   "source": [
    "Review the instructions linked in the previous Activity document to create the required Tableau visualization."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "sPlm615Ywifi"
   },
   "source": [
    "### **Task 2c. Select visualization type(s)**"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "2YdC51QBSG2v"
   },
   "source": [
    "Select data visualization types that will help you understand and explain the data.\n",
    "\n",
    "Now that you know which data columns you’ll use, it is time to decide which data visualization makes the most sense for EDA of the TikTok dataset. What type of data visualization(s) would be most helpful? Consider the distribution of the data.\n",
    "\n",
    "* Line graph\n",
    "* Bar chart\n",
    "* Box plot\n",
    "* Histogram\n",
    "* Heat map\n",
    "* Scatter plot\n",
    "* A geographic map\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "7X7AvXvzLs5m"
   },
   "source": [
    "==> ENTER YOUR RESPONSE HERE"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "f0sHpfkhx8GM"
   },
   "source": [
    "<img src=\"images/Construct.png\" width=\"100\" height=\"100\" align=left>\n",
    "\n",
    "## **PACE: Construct**\n",
    "\n",
    "Consider the questions in your PACE Strategy Document to reflect on the Construct stage."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "BYWkZ4i3wgv4"
   },
   "source": [
    "### **Task 3. Build visualizations**\n",
    "\n",
    "Now that you have assessed your data, it’s time to plot your visualization(s)."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "zxNu3SYf60OA"
   },
   "source": [
    "#### **video_duration_sec**\n",
    "\n",
    "Create a box plot to examine the spread of values in the `video_duration_sec` column."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "id": "Ts_lcV6qUQHq"
   },
   "outputs": [
    {
     "data": {
      "image/png": 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PkZ48emU+1e2NQcC1eRsfB74f6S+EFwGbA/PzHxouytNfSTp1ni/pCeDzvVyf9SE/zcDMiuUjKDMrljvJBzhJt/Gn/UjnRcRdzcjTG5J+RHrMb9X0iLi6GXms8XyKZ2bF8imemRXLBcrMiuUCZWbFcoEys2K5QJlZsf4P0NUVPaHlF2MAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 360x72 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Create a boxplot to visualize distribution of `video_duration_sec`\n",
    "### YOUR CODE HERE #### Create a boxplot to visualize distribution of `video_duration_sec`\n",
    "plt.figure(figsize=(5,1))\n",
    "plt.title('video_duration_sec')\n",
    "sns.boxplot(x=data['video_duration_sec']);\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "Kjwc7aGi7C63"
   },
   "source": [
    "Create a histogram of the values in the `video_duration_sec` column to further explore the distribution of this variable."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {
    "id": "0zaJF_yU7UCp"
   },
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 360x216 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Create a histogram\n",
    "plt.figure(figsize=(5,3))\n",
    "sns.histplot(data['video_duration_sec'], bins=range(0,61,5))\n",
    "plt.title('Video duration histogram');\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "1GgGx8g87cqN"
   },
   "source": [
    "**Question:** What do you notice about the duration and distribution of the videos?"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "QWM6LLlE7iMY"
   },
   "source": [
    "#### **video_view_count**\n",
    "\n",
    "Create a box plot to examine the spread of values in the `video_view_count` column."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {
    "id": "qlUccI91a4NH"
   },
   "outputs": [
    {
     "data": {
      "image/png": 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9IOkcitfoHElLgKV8cNfQuyku8ZcB91NcYvd8u6J237LBj17f4uJx4P603Em63QXFoPhMiku7G4GHgfFp33EU41WlS7+T0/ZJFAnjceA6YIc6dV8JvA0MK9v2DOl2IBQ9u8WpjoXA4Wn7GIoe0di0/nPgijp1HUaRXJekn8MpekbXp3gXAcemsgJuSifDLRTJdGLa93bZMacA16floyjuY74IGNPu19WP6g/fzcDMsuVLPDPLlgcMbTOS/oPijo/lLoqIuwdCfda/+BLPzLLlSzwzy5YTlJllywnKzLLlBGVm2XKCMrNs/R9YYL+QPFpM9QAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<Figure size 360x72 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "\n",
    "\n",
    "\n",
    "# Create a boxplot to visualize distribution of `video_view_count`\n",
    "plt.figure(figsize=(5, 1))\n",
    "plt.title('video_view_count')\n",
    "sns.boxplot(x=data['video_view_count']);\n",
    "\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "yiMaq0Mr7jg1"
   },
   "source": [
    "Create a histogram of the values in the `video_view_count` column to further explore the distribution of this variable."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {
    "id": "qpm2TdwB7j61"
   },
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 360x216 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(5,3))\n",
    "sns.histplot(data['video_view_count'], bins=range(0,(10**6+1),10**5))\n",
    "plt.title('Video view count histogram');\n",
    "\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "vhoFNjHp7zg3"
   },
   "source": [
    "**Question:** What do you notice about the distribution of this variable?"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "NIh6KV2X77BA"
   },
   "source": [
    "#### **video_like_count**\n",
    "\n",
    "Create a box plot to examine the spread of values in the `video_like_count` column."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {
    "id": "N0UVdeRUzEEF"
   },
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 720x72 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Create a boxplot to visualize distribution of `video_like_count`\n",
    "\n",
    "plt.figure(figsize=(10,1))\n",
    "plt.title('video_like_count')\n",
    "sns.boxplot(x=data['video_like_count']);\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "-jV2GDg_78ae"
   },
   "source": [
    "Create a histogram of the values in the `video_like_count` column to further explore the distribution of this variable."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {
    "id": "udOrLA5b79MV"
   },
   "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": [
    "# Create a histogram\n",
    "ax = sns.histplot(data['video_like_count'], bins=range(0,(7*10**5+1),10**5))\n",
    "labels = [0] + [str(i) + 'k' for i in range(100, 701, 100)]\n",
    "ax.set_xticks(range(0,7*10**5+1,10**5))\n",
    "plt.title('Video like count histogram');\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "8dwSFmpZ8ENG"
   },
   "source": [
    "**Question:** What do you notice about the distribution of this variable?"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "rJ23hEvE8HK5"
   },
   "source": [
    "#### **video_comment_count**\n",
    "\n",
    "Create a box plot to examine the spread of values in the `video_comment_count` column."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {
    "id": "-gE1fkGo0eG9"
   },
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 360x72 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Create a boxplot to visualize distribution of `video_comment_count`\n",
    "plt.figure(figsize=(5,1))\n",
    "plt.title('video_comment_count')\n",
    "sns.boxplot(x=data['video_comment_count']);\n",
    "\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "ztXyeXEA8H0d"
   },
   "source": [
    "Create a histogram of the values in the `video_comment_count` column to further explore the distribution of this variable."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {
    "id": "pQsVds2G8IYx"
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 360x72 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Create a histogram\n",
    "plt.figure(figsize=(5,1))\n",
    "plt.title('video_share_count')\n",
    "sns.boxplot(x=data['video_share_count']);\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "TXLQaXcV8It4"
   },
   "source": [
    "**Question:** What do you notice about the distribution of this variable?"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "QnWnT6ZK83wv"
   },
   "source": [
    "#### **video_share_count**\n",
    "\n",
    "Create a box plot to examine the spread of values in the `video_share_count` column."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {
    "id": "VGdU83TL88gZ"
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 360x216 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(5,3))\n",
    "sns.histplot(data['video_share_count'], bins=range(0,(270001),10000))\n",
    "plt.title('Video share count histogram');"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "8-T74RQ8888t"
   },
   "source": [
    "*Create* a histogram of the values in the `video_share_count` column to further explore the distribution of this variable."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "id": "_jusEWSJ89co"
   },
   "outputs": [],
   "source": [
    "# Create a histogram\n",
    "### YOUR CODE HERE ###\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "JWKhsOtG9Urp"
   },
   "source": [
    "**Question:** What do you notice about the distribution of this variable?"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "ZDh2nxtC9ems"
   },
   "source": [
    "#### **video_download_count**\n",
    "\n",
    "Create a box plot to examine the spread of values in the `video_download_count` column."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "id": "CVILyJYB9fUe"
   },
   "outputs": [],
   "source": [
    "# Create a boxplot to visualize distribution of `video_download_count`\n",
    "### YOUR CODE HERE ###\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "oVAlHAVY9fvC"
   },
   "source": [
    "Create a histogram of the values in the `video_download_count` column to further explore the distribution of this variable."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "id": "R9QBYK3g9gVu"
   },
   "outputs": [],
   "source": [
    "# Create a histogram\n",
    "### YOUR CODE HERE ###\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "MZZ_BH3Y9sZ-"
   },
   "source": [
    "**Question:** What do you notice about the distribution of this variable?"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "rJc1VcpN-ZRr"
   },
   "source": [
    "#### **Claim status by verification status**\n",
    "\n",
    "Now, create a histogram with four bars: one for each combination of claim status and verification status."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {
    "id": "eTsTPNMK-chP"
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 504x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Create a histogram\n",
    "plt.figure(figsize=(7,4))\n",
    "sns.histplot(data=data,\n",
    "             x='claim_status',\n",
    "             hue='verified_status',\n",
    "             multiple='dodge',\n",
    "             shrink=0.9)\n",
    "plt.title('Claims by verification status histogram');\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "-xJqYoLE-c72"
   },
   "source": [
    "**Question:** What do you notice about the number of verified users compared to unverified? And how does that affect their likelihood to post opinions?"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "iEiA_ARk_Nxd"
   },
   "source": [
    "#### **Claim status by author ban status**\n",
    "\n",
    "The previous course used a `groupby()` statement to examine the count of each claim status for each author ban status. Now, use a histogram to communicate the same information."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {
    "id": "IZHdWGPx_Olx"
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 504x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Create a histogram\n",
    "fig = plt.figure(figsize=(7,4))\n",
    "sns.histplot(data, x='claim_status', hue='author_ban_status',\n",
    "             multiple='dodge',\n",
    "             hue_order=['active', 'under review', 'banned'],\n",
    "             shrink=0.9,\n",
    "             palette={'active':'green', 'under review':'orange', 'banned':'red'},\n",
    "             alpha=0.5)\n",
    "plt.title('Claim status by author ban status - counts');\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "TfjwFMlR_RBT"
   },
   "source": [
    "**Question:** What do you notice about the number of active authors compared to banned authors for both claims and opinions?"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "_uAmAERs_Z9j"
   },
   "source": [
    "#### **Median view counts by ban status**\n",
    "\n",
    "Create a bar plot with three bars: one for each author ban status. The height of each bar should correspond with the median number of views for all videos with that author ban status."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {
    "id": "c7xVuf5O_asQ"
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 360x216 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Create a bar plot\n",
    "ban_status_counts = data.groupby(['author_ban_status']).median(\n",
    "    numeric_only=True).reset_index()\n",
    "\n",
    "fig = plt.figure(figsize=(5,3))\n",
    "sns.barplot(data=ban_status_counts,\n",
    "            x='author_ban_status',\n",
    "            y='video_view_count',\n",
    "            order=['active', 'under review', 'banned'],\n",
    "            palette={'active':'green', 'under review':'orange', 'banned':'red'},\n",
    "            alpha=0.5)\n",
    "plt.title('Median view count by ban status');"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "obw-wzm-_jca"
   },
   "source": [
    "**Question:** What do you notice about the median view counts for non-active authors compared to that of active authors? Based on that insight, what variable might be a good indicator of claim status?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {
    "id": "eFNVhyYQhSL0"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "claim_status\n",
       "claim      501555.0\n",
       "opinion      4953.0\n",
       "Name: video_view_count, dtype: float64"
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Calculate the median view count for claim status.\n",
    "data.groupby('claim_status')['video_view_count'].median()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "id": "h6XBJb0d_kdS"
   },
   "outputs": [],
   "source": [
    "### YOUR CODE HERE ###"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "2FjUxqMd_71P"
   },
   "source": [
    "#### **Total views by claim status**\n",
    "\n",
    "Create a pie graph that depicts the proportions of total views for claim videos and total views for opinion videos."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {
    "id": "aR0WS23aAD6J"
   },
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 216x216 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Create a pie graph\n",
    "fig = plt.figure(figsize=(3,3))\n",
    "plt.pie(data.groupby('claim_status')['video_view_count'].sum(), labels=['claim', 'opinion'])\n",
    "plt.title('Total views by video claim status');\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "_NYxRNBjAMHv"
   },
   "source": [
    "**Question:** What do you notice about the overall view count for claim status?"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "H-rVzm6MAcuc"
   },
   "source": [
    "### **Task 4. Determine outliers**\n",
    "\n",
    "When building predictive models, the presence of outliers can be problematic. For example, if you were trying to predict the view count of a particular video, videos with extremely high view counts might introduce bias to a model. Also, some outliers might indicate problems with how data was captured or recorded.\n",
    "\n",
    "The ultimate objective of the TikTok project is to build a model that predicts whether a video is a claim or opinion. The analysis you've performed indicates that a video's engagement level is strongly correlated with its claim status. There's no reason to believe that any of the values in the TikTok data are erroneously captured, and they align with expectation of how social media works: a very small proportion of videos get super high engagement levels. That's the nature of viral content.\n",
    "\n",
    "Nonetheless, it's good practice to get a sense of just how many of your data points could be considered outliers. The definition of an outlier can change based on the details of your project, and it helps to have domain expertise to decide a threshold. You've learned that a common way to determine outliers in a normal distribution is to calculate the interquartile range (IQR) and set a threshold that is 1.5 * IQR above the 3rd quartile.\n",
    "\n",
    "In this TikTok dataset, the values for the count variables are not normally distributed. They are heavily skewed to the right. One way of modifying the outlier threshold is by calculating the **median** value for each variable and then adding 1.5 * IQR. This results in a threshold that is, in this case, much lower than it would be if you used the 3rd quartile.\n",
    "\n",
    "Write a for loop that iterates over the column names of each count variable. For each iteration:\n",
    "1. Calculate the IQR of the column\n",
    "2. Calculate the median of the column\n",
    "3. Calculate the outlier threshold (median + 1.5 * IQR)\n",
    "4. Calculate the numer of videos with a count in that column that exceeds the outlier threshold\n",
    "5. Print \"Number of outliers, {column name}: {outlier count}\"\n",
    "\n",
    "```\n",
    "Example:\n",
    "Number of outliers, video_view_count: ___\n",
    "Number of outliers, video_like_count: ___\n",
    "Number of outliers, video_share_count: ___\n",
    "Number of outliers, video_download_count: ___\n",
    "Number of outliers, video_comment_count: ___\n",
    "```"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {
    "id": "lBDtA-fjA-2B"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Number of outliers, video_view_count: 2343\n",
      "Number of outliers, video_like_count: 3468\n",
      "Number of outliers, video_share_count: 3732\n",
      "Number of outliers, video_download_count: 3733\n",
      "Number of outliers, video_comment_count: 3882\n"
     ]
    }
   ],
   "source": [
    "### YOUR CODE HERE ###\n",
    "count_cols = ['video_view_count',\n",
    "              'video_like_count',\n",
    "              'video_share_count',\n",
    "              'video_download_count',\n",
    "              'video_comment_count',\n",
    "              ]\n",
    "\n",
    "for column in count_cols:\n",
    "    q1 = data[column].quantile(0.25)\n",
    "    q3 = data[column].quantile(0.75)\n",
    "    iqr = q3 - q1\n",
    "    median = data[column].median()\n",
    "    outlier_threshold = median + 1.5*iqr\n",
    "\n",
    "    # Count the number of values that exceed the outlier threshold\n",
    "    outlier_count = (data[column] > outlier_threshold).sum()\n",
    "    print(f'Number of outliers, {column}:', outlier_count)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "E_jdFb9pBIRT"
   },
   "source": [
    "#### **Scatterplot**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {
    "id": "m70a9DMUBJUA"
   },
   "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": [
    "# Create a scatterplot of `video_like_count` versus `video_comment_count` according to 'claim_status'\n",
    "sns.scatterplot(x=data[\"video_view_count\"], y=data[\"video_like_count\"],\n",
    "                hue=data[\"claim_status\"], s=10, alpha=.3)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {
    "id": "NxyaaJojBRhu"
   },
   "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": [
    "# Create a scatterplot of `video_like_count` versus `video_comment_count` for opinions only\n",
    "opinion = data[data['claim_status']=='opinion']\n",
    "sns.scatterplot(x=opinion[\"video_view_count\"], y=opinion[\"video_like_count\"],\n",
    "                 s=10, alpha=.3)\n",
    "plt.show()\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "z8n8HqJmBe3L"
   },
   "source": [
    "You can do a scatterplot in Tableau Public as well, which can be easier to manipulate and present. If you'd like step by step instructions, you can review the instructions linked in the previous Activity page."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "NsvBtco1x8GN"
   },
   "source": [
    "<img src=\"images/Execute.png\" width=\"100\" height=\"100\" align=left>\n",
    "\n",
    "## **PACE: Execute**\n",
    "\n",
    "Consider the questions in your PACE Strategy Document to reflect on the Execute stage."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "csHAfM-RSO7l"
   },
   "source": [
    "### **Task 5a. Results and evaluation**\n",
    "\n",
    "Having built visualizations in Tableau and in Python, what have you learned about the dataset? What other questions have your visualizations uncovered that you should pursue?\n",
    "\n",
    "***Pro tip:*** Put yourself in your client's perspective, what would they want to know?\n",
    "\n",
    "Use the following code cells to pursue any additional EDA. Also use the space to make sure your visualizations are clean, easily understandable, and accessible.\n",
    "\n",
    "***Ask yourself:*** Did you consider color, contrast, emphasis, and labeling?\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "s_o_6J-QMMnn"
   },
   "source": [
    "==> ENTER YOUR RESPONSE HERE\n",
    "\n",
    "I have learned ....\n",
    "\n",
    "My other questions are ....\n",
    "\n",
    "My client would likely want to know ...\n",
    "\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "U4HeITeOwXfo"
   },
   "source": [
    "### **Task 5b. Conclusion**\n",
    "*Make it professional and presentable*\n",
    "\n",
    "You have visualized the data you need to share with the director now. Remember, the goal of a data visualization is for an audience member to glean the information on the chart in mere seconds.\n",
    "\n",
    "*Questions to ask yourself for reflection:*\n",
    "Why is it important to conduct Exploratory Data Analysis? What other visuals could you create?\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "lJf9_Hv9INR0"
   },
   "source": [
    "EDA is important because ...\n",
    "\n",
    "==> ENTER YOUR RESPONSES HERE\n",
    "\n",
    "Visualizations helped me understand ..\n",
    "\n",
    "==> ENTER YOUR RESPONSES HERE\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "8JabFSqwwLrM"
   },
   "source": [
    "You’ve now completed a professional data visualization according to a business need. Well done! Be sure to save your work as a reference for later work in Tableau."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Congratulations!** You've completed this lab. However, you may not notice a green check mark next to this item on Coursera's platform. Please continue your progress regardless of the check mark. Just click on the \"save\" icon at the top of this notebook to ensure your work has been logged."
   ]
  }
 ],
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  "colab": {
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   "toc_visible": true
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  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
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  "language_info": {
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   "file_extension": ".py",
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