investigating-netflix-movies.ipynb

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     "output_type": "stream",
     "text": [
      "/kaggle/input/netflix-datacamp-analysis/netflix_data.csv\n"
     ]
    }
   ],
   "source": [
    "# This Python 3 environment comes with many helpful analytics libraries installed\n",
    "# It is defined by the kaggle/python Docker image: https://github.com/kaggle/docker-python\n",
    "# For example, here's several helpful packages to load\n",
    "\n",
    "import numpy as np # linear algebra\n",
    "import pandas as pd # data processing, CSV file I/O (e.g. pd.read_csv)\n",
    "\n",
    "# Input data files are available in the read-only \"../input/\" directory\n",
    "# For example, running this (by clicking run or pressing Shift+Enter) will list all files under the input directory\n",
    "\n",
    "import os\n",
    "for dirname, _, filenames in os.walk('/kaggle/input'):\n",
    "    for filename in filenames:\n",
    "        print(os.path.join(dirname, filename))\n",
    "\n",
    "# You can write up to 20GB to the current directory (/kaggle/working/) that gets preserved as output when you create a version using \"Save & Run All\" \n",
    "# You can also write temporary files to /kaggle/temp/, but they won't be saved outside of the current session"
   ]
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  {
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   "id": "b24ee864",
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   "source": [
    "# **DATACAMP : Project: Investigating Netflix Movies and Guest Stars in The Office**\n",
    "\n",
    "\n",
    "Author: Shamso Osman"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "d63d4647",
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   "source": [
    "## 1. Loading your friend's data into a dictionary\n",
    "<p><img src=\"https://assets.datacamp.com/production/project_1237/img/netflix.jpg\" alt=\"Someone's feet on table facing a television\"></p>\n",
    "<p>Netflix! What started in 1997 as a DVD rental service has since exploded into the largest entertainment/media company by <a href=\"https://www.marketwatch.com/story/netflix-shares-close-up-8-for-yet-another-record-high-2020-07-10\">market capitalization</a>, boasting over 200 million subscribers as of <a href=\"https://www.cbsnews.com/news/netflix-tops-200-million-subscribers-but-faces-growing-challenge-from-disney-plus/\">January 2021</a>.</p>\n",
    "<p>Given the large number of movies and series available on the platform, it is a perfect opportunity to flex our data manipulation skills and dive into the entertainment industry. Our friend has also been brushing up on their Python skills and has taken a first crack at a CSV file containing Netflix data. For their first order of business, they have been performing some analyses, and they believe that the average duration of movies has been declining. </p>\n",
    "<p>As evidence of this, they have provided us with the following information. For the years from 2011 to 2020, the average movie durations are 103, 101, 99, 100, 100, 95, 95, 96, 93, and 90, respectively.</p>\n",
    "<p>If we're going to be working with this data, we know a good place to start would be to probably start working with <code>pandas</code>. But first we'll need to create a DataFrame from scratch. Let's start by creating a Python object covered in <a href=\"https://learn.datacamp.com/courses/intermediate-python\">Intermediate Python</a>: a dictionary!</p>\n",
    "\n",
    "As evidence of this, they have provided us with the following information. For the years from 2011 to 2020, the average movie durations are 103, 101, 99, 100, 100, 95, 95, 96, 93, and 90, respectively.\n",
    "\n",
    "If we're going to be working with this data, we know a good place to start would be to probably start working with pandas. But first we'll need to create a DataFrame from scratch. Let's start by creating a Python object covered in Intermediate Python: a dictionary!"
   ]
  },
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    {
     "data": {
      "text/plain": [
       "{'years': [2011, 2012, 2013, 2014, 2015, 2016, 2017, 2018, 2019, 2020],\n",
       " 'durations': [103, 101, 99, 100, 100, 95, 95, 96, 93, 90]}"
      ]
     },
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   ],
   "source": [
    "# Create the years and durations lists\n",
    "years = [2011, 2012, 2013, 2014, 2015, 2016, 2017, 2018, 2019, 2020]\n",
    "durations = [103, 101, 99, 100, 100, 95, 95, 96, 93, 90]\n",
    "\n",
    "# Create a dictionary with the two lists\n",
    "movie_dict = {'years': years, 'durations': durations}\n",
    "\n",
    "# Print the dictionary\n",
    "movie_dict"
   ]
  },
  {
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   "source": [
    "## 2. Creating a DataFrame from a dictionary\n",
    "<p>To convert our dictionary <code>movie_dict</code> to a <code>pandas</code> DataFrame, we will first need to import the library under its usual alias. We'll also want to inspect our DataFrame to ensure it was created correctly. Let's perform these steps now.</p>"
   ]
  },
  {
   "cell_type": "code",
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    {
     "name": "stdout",
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     "text": [
      "   years  durations\n",
      "0   2011        103\n",
      "1   2012        101\n",
      "2   2013         99\n",
      "3   2014        100\n",
      "4   2015        100\n",
      "5   2016         95\n",
      "6   2017         95\n",
      "7   2018         96\n",
      "8   2019         93\n",
      "9   2020         90\n"
     ]
    }
   ],
   "source": [
    "# Import pandas under its usual alias\n",
    "import pandas as pd\n",
    "\n",
    "# Create a DataFrame from the dictionary\n",
    "durations_df = pd.DataFrame(movie_dict)\n",
    "\n",
    "# Print the DataFrame\n",
    "print(durations_df)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "4fa42921",
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   "source": [
    "## 3. A visual inspection of our data\n",
    "<p>Alright, we now have a <code>pandas</code> DataFrame, the most common way to work with tabular data in Python. Now back to the task at hand. We want to follow up on our friend's assertion that movie lengths have been decreasing over time. A great place to start will be a visualization of the data.</p>\n",
    "<p>Given that the data is continuous, a line plot would be a good choice, with the dates represented along the x-axis and the average length in minutes along the y-axis. This will allow us to easily spot any trends in movie durations. There are many ways to visualize data in Python, but <code>matploblib.pyplot</code> is one of the most common packages to do so.</p>\n",
    "<p><em>Note: In order for us to correctly test your plot, you will need to initalize a <code>matplotlib.pyplot</code> Figure object, which we have already provided in the cell below. You can continue to create your plot as you have learned in Intermediate Python.</em></p>"
   ]
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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Import matplotlib.pyplot under its usual alias and create a figure\n",
    "import matplotlib.pyplot as plt\n",
    "fig = plt.figure()\n",
    "\n",
    "# Draw a line plot of release_years and durations\n",
    "plt.plot(durations_df['years'], durations_df['durations'])\n",
    "\n",
    "# Create a title\n",
    "plt.title(\"Netflix Movie Durations 2011-2020\")\n",
    "\n",
    "# Show the plot\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c5ac835c",
   "metadata": {
    "papermill": {
     "duration": 0.027171,
     "end_time": "2022-03-24T17:40:20.475904",
     "exception": false,
     "start_time": "2022-03-24T17:40:20.448733",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "## 4. Loading the rest of the data from a CSV\n",
    "<p>Well, it looks like there is something to the idea that movie lengths have decreased over the past ten years! But equipped only with our friend's aggregations, we're limited in the further explorations we can perform. There are a few questions about this trend that we are currently unable to answer, including:</p>\n",
    "<ol>\n",
    "<li>What does this trend look like over a longer period of time?</li>\n",
    "<li>Is this explainable by something like the genre of entertainment?</li>\n",
    "</ol>\n",
    "<p>Upon asking our friend for the original CSV they used to perform their analyses, they gladly oblige and send it. We now have access to the CSV file, available at the path <code>\"datasets/netflix_data.csv\"</code>. Let's create another DataFrame, this time with all of the data. Given the length of our friend's data, printing the whole DataFrame is probably not a good idea, so we will inspect it by printing only the first five rows.</p>"
   ]
  },
  {
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    {
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       "  <thead>\n",
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       "      <th></th>\n",
       "      <th>show_id</th>\n",
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       "      <td>NaN</td>\n",
       "      <td>João Miguel, Bianca Comparato, Michel Gomes, R...</td>\n",
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       "      <td>Mexico</td>\n",
       "      <td>December 23, 2016</td>\n",
       "      <td>2016</td>\n",
       "      <td>93</td>\n",
       "      <td>After a devastating earthquake hits Mexico Cit...</td>\n",
       "      <td>Dramas</td>\n",
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       "      <td>December 20, 2018</td>\n",
       "      <td>2011</td>\n",
       "      <td>78</td>\n",
       "      <td>When an army recruit is found dead, his fellow...</td>\n",
       "      <td>Horror Movies</td>\n",
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       "      <td>Elijah Wood, John C. Reilly, Jennifer Connelly...</td>\n",
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       "      <td>November 16, 2017</td>\n",
       "      <td>2009</td>\n",
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       "      <td>January 1, 2020</td>\n",
       "      <td>2008</td>\n",
       "      <td>123</td>\n",
       "      <td>A brilliant group of students become card-coun...</td>\n",
       "      <td>Dramas</td>\n",
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       "  show_id     type  title           director  \\\n",
       "0      s1  TV Show     3%                NaN   \n",
       "1      s2    Movie   7:19  Jorge Michel Grau   \n",
       "2      s3    Movie  23:59       Gilbert Chan   \n",
       "3      s4    Movie      9        Shane Acker   \n",
       "4      s5    Movie     21     Robert Luketic   \n",
       "\n",
       "                                                cast        country  \\\n",
       "0  João Miguel, Bianca Comparato, Michel Gomes, R...         Brazil   \n",
       "1  Demián Bichir, Héctor Bonilla, Oscar Serrano, ...         Mexico   \n",
       "2  Tedd Chan, Stella Chung, Henley Hii, Lawrence ...      Singapore   \n",
       "3  Elijah Wood, John C. Reilly, Jennifer Connelly...  United States   \n",
       "4  Jim Sturgess, Kevin Spacey, Kate Bosworth, Aar...  United States   \n",
       "\n",
       "          date_added  release_year  duration  \\\n",
       "0    August 14, 2020          2020         4   \n",
       "1  December 23, 2016          2016        93   \n",
       "2  December 20, 2018          2011        78   \n",
       "3  November 16, 2017          2009        80   \n",
       "4    January 1, 2020          2008       123   \n",
       "\n",
       "                                         description             genre  \n",
       "0  In a future where the elite inhabit an island ...  International TV  \n",
       "1  After a devastating earthquake hits Mexico Cit...            Dramas  \n",
       "2  When an army recruit is found dead, his fellow...     Horror Movies  \n",
       "3  In a postapocalyptic world, rag-doll robots hi...            Action  \n",
       "4  A brilliant group of students become card-coun...            Dramas  "
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   "source": [
    "# Read in the CSV as a DataFrame\n",
    "netflix_df = pd.read_csv(\"../input/netflix-datacamp-analysis/netflix_data.csv\")\n",
    "\n",
    "# Print the first five rows of the DataFrame\n",
    "netflix_df.head(5)"
   ]
  },
  {
   "cell_type": "markdown",
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    "## 5. Filtering for movies!\n",
    "<p>Okay, we have our data! Now we can dive in and start looking at movie lengths. </p>\n",
    "<p>Or can we? Looking at the first five rows of our new DataFrame, we notice a column <code>type</code>. Scanning the column, it's clear there are also TV shows in the dataset! Moreover, the <code>duration</code> column we planned to use seems to represent different values depending on whether the row is a movie or a show (perhaps the number of minutes versus the number of seasons)?</p>\n",
    "<p>Fortunately, a DataFrame allows us to filter data quickly, and we can select rows where <code>type</code> is <code>Movie</code>. While we're at it, we don't need information from all of the columns, so let's create a new DataFrame <code>netflix_movies</code> containing only <code>title</code>, <code>country</code>, <code>genre</code>, <code>release_year</code>, and <code>duration</code>.</p>\n",
    "<p>Let's put our data subsetting skills to work!</p>"
   ]
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      "text/plain": [
       "   title        country          genre  release_year  duration\n",
       "1   7:19         Mexico         Dramas          2016        93\n",
       "2  23:59      Singapore  Horror Movies          2011        78\n",
       "3      9  United States         Action          2009        80\n",
       "4     21  United States         Dramas          2008       123\n",
       "6    122          Egypt  Horror Movies          2019        95"
      ]
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   ],
   "source": [
    "# Subset the DataFrame for type \"Movie\"\n",
    "netflix_df_movies_only = netflix_df[netflix_df['type']=='Movie']\n",
    "\n",
    "\n",
    "# Select only the columns of interest\n",
    "netflix_movies_col_subset = netflix_df_movies_only[['title', 'country', 'genre', 'release_year', 'duration']]\n",
    "\n",
    "# Print the first five rows of the new DataFrame\n",
    "netflix_movies_col_subset[0:5]"
   ]
  },
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    "## 6. Creating a scatter plot\n",
    "<p>Okay, now we're getting somewhere. We've read in the raw data, selected rows of movies, and have limited our DataFrame to our columns of interest. Let's try visualizing the data again to inspect the data over a longer range of time.</p>\n",
    "<p>This time, we are no longer working with aggregates but instead with individual movies. A line plot is no longer a good choice for our data, so let's try a scatter plot instead. We will again plot the year of release on the x-axis and the movie duration on the y-axis.</p>\n",
    "<p><em>Note: Although not taught in Intermediate Python, we have provided you the code <code>fig = plt.figure(figsize=(12,8))</code> to increase the size of the plot (to help you see the results), as well as to assist with testing. For more information on how to create or work with a <code>matplotlib</code> <code>figure</code>, refer to the <a href=\"https://matplotlib.org/stable/api/_as_gen/matplotlib.pyplot.figure.html\">documentation</a>.</em></p>"
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\n",
      "text/plain": [
       "<Figure size 864x576 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Create a figure and increase the figure size\n",
    "fig = plt.figure(figsize=(12,8))\n",
    "\n",
    "# Create a scatter plot of duration versus year\n",
    "plt.scatter(netflix_movies_col_subset['release_year'], netflix_movies_col_subset['duration'])\n",
    "\n",
    "# Create a title\n",
    "plt.title(\"Movie Duration by Year of Release\")\n",
    "\n",
    "# Show the plot\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "19e91057",
   "metadata": {
    "papermill": {
     "duration": 0.019907,
     "end_time": "2022-03-24T17:40:21.204528",
     "exception": false,
     "start_time": "2022-03-24T17:40:21.184621",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "## 7. Digging deeper\n",
    "<p>This is already much more informative than the simple plot we created when our friend first gave us some data. We can also see that, while newer movies are overrepresented on the platform, many short movies have been released in the past two decades.</p>\n",
    "<p>Upon further inspection, something else is going on. Some of these films are under an hour long! Let's filter our DataFrame for movies with a <code>duration</code> under 60 minutes and look at the genres. This might give us some insight into what is dragging down the average.</p>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "fc345179",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-03-24T17:40:21.248538Z",
     "iopub.status.busy": "2022-03-24T17:40:21.247901Z",
     "iopub.status.idle": "2022-03-24T17:40:21.258790Z",
     "shell.execute_reply": "2022-03-24T17:40:21.258242Z",
     "shell.execute_reply.started": "2022-03-24T17:28:19.040055Z"
    },
    "papermill": {
     "duration": 0.033934,
     "end_time": "2022-03-24T17:40:21.258924",
     "exception": false,
     "start_time": "2022-03-24T17:40:21.224990",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "                                                 title         country  \\\n",
      "35                                           #Rucker50   United States   \n",
      "55                 100 Things to do Before High School   United States   \n",
      "67   13TH: A Conversation with Oprah Winfrey & Ava ...             NaN   \n",
      "101                                  3 Seconds Divorce          Canada   \n",
      "146                                     A 3 Minute Hug          Mexico   \n",
      "162  A Christmas Special: Miraculous: Tales of Lady...          France   \n",
      "171                         A Family Reunion Christmas   United States   \n",
      "177                    A Go! Go! Cory Carson Christmas   United States   \n",
      "178                    A Go! Go! Cory Carson Halloween             NaN   \n",
      "179                  A Go! Go! Cory Carson Summer Camp             NaN   \n",
      "181             A Grand Night In: The Story of Aardman  United Kingdom   \n",
      "200                            A Love Song for Latasha   United States   \n",
      "220                         A Russell Peters Christmas          Canada   \n",
      "233                              A StoryBots Christmas   United States   \n",
      "237                             A Tale of Two Kitchens   United States   \n",
      "242                            A Trash Truck Christmas             NaN   \n",
      "247                            A Very Murray Christmas   United States   \n",
      "285                               Abominable Christmas   United States   \n",
      "295                                 Across Grace Alley   United States   \n",
      "305                Adam Devine: Best Time of Our Lives   United States   \n",
      "\n",
      "             genre  release_year  duration  \n",
      "35   Documentaries          2016        56  \n",
      "55   Uncategorized          2014        44  \n",
      "67   Uncategorized          2017        37  \n",
      "101  Documentaries          2018        53  \n",
      "146  Documentaries          2019        28  \n",
      "162  Uncategorized          2016        22  \n",
      "171  Uncategorized          2019        29  \n",
      "177       Children          2020        22  \n",
      "178       Children          2020        22  \n",
      "179       Children          2020        21  \n",
      "181  Documentaries          2015        59  \n",
      "200  Documentaries          2020        20  \n",
      "220       Stand-Up          2011        44  \n",
      "233       Children          2017        26  \n",
      "237  Documentaries          2019        30  \n",
      "242       Children          2020        28  \n",
      "247       Comedies          2015        57  \n",
      "285       Children          2012        44  \n",
      "295         Dramas          2013        24  \n",
      "305       Stand-Up          2019        59  \n"
     ]
    }
   ],
   "source": [
    "# Filter for durations shorter than 60 minutes\n",
    "short_movies = netflix_movies_col_subset[netflix_movies_col_subset['duration'] < 60]\n",
    "\n",
    "# Print the first 20 rows of short_movies\n",
    "print(short_movies[0:20])"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "70b68481",
   "metadata": {
    "papermill": {
     "duration": 0.020463,
     "end_time": "2022-03-24T17:40:21.300010",
     "exception": false,
     "start_time": "2022-03-24T17:40:21.279547",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "## 8. Marking non-feature films\n",
    "<p>Interesting! It looks as though many of the films that are under 60 minutes fall into genres such as \"Children\", \"Stand-Up\", and \"Documentaries\". This is a logical result, as these types of films are probably often shorter than 90 minute Hollywood blockbuster. </p>\n",
    "<p>We could eliminate these rows from our DataFrame and plot the values again. But another interesting way to explore the effect of these genres on our data would be to plot them, but mark them with a different color.</p>\n",
    "<p>In Python, there are many ways to do this, but one fun way might be to use a loop to generate a list of colors based on the contents of the <code>genre</code> column. Much as we did in Intermediate Python, we can then pass this list to our plotting function in a later step to color all non-typical genres in a different color!</p>\n",
    "<p><em>Note: Although we are using the basic colors of red, blue, green, and black, <code>matplotlib</code> has many named colors you can use when creating plots. For more information, you can refer to the documentation <a href=\"https://matplotlib.org/stable/gallery/color/named_colors.html\">here</a>!</em></p>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "0f4f4874",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-03-24T17:40:21.346403Z",
     "iopub.status.busy": "2022-03-24T17:40:21.345799Z",
     "iopub.status.idle": "2022-03-24T17:40:21.627588Z",
     "shell.execute_reply": "2022-03-24T17:40:21.626957Z",
     "shell.execute_reply.started": "2022-03-24T17:29:03.211199Z"
    },
    "papermill": {
     "duration": 0.306268,
     "end_time": "2022-03-24T17:40:21.627729",
     "exception": false,
     "start_time": "2022-03-24T17:40:21.321461",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['black',\n",
       " 'black',\n",
       " 'black',\n",
       " 'black',\n",
       " 'black',\n",
       " 'black',\n",
       " 'black',\n",
       " 'black',\n",
       " 'black',\n",
       " 'blue']"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Define an empty list\n",
    "colors = []\n",
    "\n",
    "# Iterate over rows of netflix_movies_col_subset\n",
    "for lab, row in netflix_movies_col_subset.iterrows() :\n",
    "    if row['genre'] == \"Children\":\n",
    "        colors.append('red')\n",
    "    elif row['genre'] == \"Documentaries\":\n",
    "        colors.append('blue')\n",
    "    elif row['genre'] == \"Stand-up\":\n",
    "        colors.append('green')\n",
    "    else:\n",
    "        colors.append('black')\n",
    "        \n",
    "# Inspect the first 10 values in your list        \n",
    "colors[0:10]"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "1b80ad5e",
   "metadata": {
    "papermill": {
     "duration": 0.031122,
     "end_time": "2022-03-24T17:40:21.692746",
     "exception": false,
     "start_time": "2022-03-24T17:40:21.661624",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "## 9. Plotting with color!\n",
    "<p>Lovely looping! We now have a <code>colors</code> list that we can pass to our scatter plot, which should allow us to visually inspect whether these genres might be responsible for the decline in the average duration of movies.</p>\n",
    "<p>This time, we'll also spruce up our plot with some additional axis labels and a new theme with <code>plt.style.use()</code>. The latter isn't taught in Intermediate Python, but can be a fun way to add some visual flair to a basic <code>matplotlib</code> plot. You can find more information on customizing the style of your plot <a href=\"https://matplotlib.org/stable/tutorials/introductory/customizing.html\">here</a>!</p>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "8bf869c5",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-03-24T17:40:21.758652Z",
     "iopub.status.busy": "2022-03-24T17:40:21.757911Z",
     "iopub.status.idle": "2022-03-24T17:40:22.103029Z",
     "shell.execute_reply": "2022-03-24T17:40:22.103655Z",
     "shell.execute_reply.started": "2022-03-24T17:29:53.119178Z"
    },
    "papermill": {
     "duration": 0.379806,
     "end_time": "2022-03-24T17:40:22.103850",
     "exception": false,
     "start_time": "2022-03-24T17:40:21.724044",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
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\n",
      "text/plain": [
       "<Figure size 864x576 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Set the figure style and initalize a new figure\n",
    "plt.style.use('fivethirtyeight')\n",
    "fig = plt.figure(figsize=(12,8))\n",
    "\n",
    "# Create a scatter plot of duration versus release_year\n",
    "plt.scatter(netflix_movies_col_subset['release_year'], netflix_movies_col_subset['duration'], color=colors)\n",
    "\n",
    "# Create a title and axis labels\n",
    "plt.title('Movie duration by year of release')\n",
    "plt.xlabel('Release year')\n",
    "plt.ylabel('Duration (min)')\n",
    "\n",
    "# Show the plot\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "92b1d5cc",
   "metadata": {
    "papermill": {
     "duration": 0.040716,
     "end_time": "2022-03-24T17:40:22.179900",
     "exception": false,
     "start_time": "2022-03-24T17:40:22.139184",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "## 10. What next?\n",
    "<p>Well, as we suspected, non-typical genres such as children's movies and documentaries are all clustered around the bottom half of the plot. But we can't know for certain until we perform additional analyses. </p>\n",
    "<p>Congratulations, you've performed an exploratory analysis of some entertainment data, and there are lots of fun ways to develop your skills as a Pythonic data scientist. These include learning how to analyze data further with statistics, creating more advanced visualizations, and perhaps most importantly, learning more advanced ways of working with data in <code>pandas</code>. This latter skill is covered in our fantastic course <a href=\"www.datacamp.com/courses/data-manipulation-with-pandas\">Data Manipulation with pandas</a>.</p>\n",
    "<p>We hope you enjoyed this application of the skills learned in Intermediate Python, and wish you all the best on the rest of your journey!</p>"
   ]
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    "# Are we certain that movies are getting shorter?\n",
    "are_movies_getting_shorter = \"maybe\""
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