movies_eda.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "First day on letterboxd:\n",
      "2017-07-29\n",
      "\n",
      "Total Hours Watched:\n",
      "3363\n",
      "\n",
      "Average Star Rating:\n",
      "2.69\n",
      "\n",
      "Total Watched By Genre:\n",
      "Action         364\n",
      "Crime          242\n",
      "War             33\n",
      "Drama          840\n",
      "Thriller       340\n",
      "Mystery        136\n",
      "Comedy         513\n",
      "Romance        162\n",
      "Sci_Fi         201\n",
      "Animation      175\n",
      "Documentary    116\n",
      "Adventure      368\n",
      "Music           97\n",
      "Horror         120\n",
      "Fantasy        227\n",
      "History         67\n",
      "Western         13\n",
      "Rom_Com        183\n",
      "dtype: int64\n",
      "\n",
      "Average movies per week:\n",
      "Name    4.3\n",
      "dtype: float64\n",
      "\n",
      "Average movies per month:\n",
      "Name    17.65\n",
      "dtype: float64\n",
      "\n",
      "Average ratings per decade:\n",
      "      Rating\n",
      "Year        \n",
      "1920    4.00\n",
      "1930    3.50\n",
      "1940    3.46\n",
      "1950    3.04\n",
      "1960    2.86\n",
      "1970    2.92\n",
      "1980    2.99\n",
      "1990    2.71\n",
      "2000    2.58\n",
      "2010    2.61\n",
      "2020    2.56\n"
     ]
    }
   ],
   "source": [
    "#Load Requisite Libraries\n",
    "import pandas as pd\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns\n",
    "\n",
    "#Read in files\n",
    "df = pd.read_csv(r'\\movie_data_final.csv')\n",
    "overview_fd = pd.read_csv(r'\\movie_overview_fd.csv')\n",
    "titles_fd = pd.read_csv(r'\\movie_title_fd.csv')\n",
    "\n",
    "genres=['Action', 'Crime', 'War', 'Drama', 'Thriller', 'Mystery', 'Comedy', 'Romance', 'Sci_Fi', 'Animation', 'Documentary', 'Adventure', 'Music', 'Horror', 'Fantasy', 'History', 'Western', 'Rom_Com']\n",
    "\n",
    "#1. First day on letterboxd\n",
    "print(\"\\nFirst day on letterboxd:\")\n",
    "print(df.Logged_Date.min())\n",
    "\n",
    "#2. Total Hours Watched\n",
    "print(\"\\nTotal Hours Watched:\")\n",
    "print(round(sum(df.runtime)/60))\n",
    "\n",
    "#3. Average Star Rating\n",
    "print(\"\\nAverage Star Rating:\")\n",
    "print(round(df.Rating.mean(),2))\n",
    "\n",
    "#4. Aggregate and sum across the genres to see how many of each I'm watching\n",
    "print(\"\\nTotal Watched By Genre:\")\n",
    "print(df[genres].aggregate(\"sum\"))\n",
    "\n",
    "#5. Average movies per week\n",
    "#Filter out all the dates in July and August 2017 where I was backfilling movies\n",
    "normal = df[df['Logged_Date']>'2017-08-31']\n",
    "print(\"\\nAverage movies per week:\")\n",
    "print(round(normal.groupby(['Logged_Year','Logged_Week']).agg({'Name':'size'}).mean(),2))\n",
    "\n",
    "#6. Average movies per month\n",
    "print(\"\\nAverage movies per month:\")\n",
    "print(round(normal.groupby(['Logged_Year','Logged_Month']).agg({'Name':'size'}).mean(),2))\n",
    "\n",
    "#7. Average star ratings per decade\n",
    "print(\"\\nAverage ratings per decade:\")\n",
    "print(round(df.groupby((df.Year//10)*10).agg({'Rating':'mean'}),2))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<BarContainer object of 87 artists>"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "#8 Trended bar graph of release year versus count of films seen  \n",
    "fig_data = df.groupby(['Year']).agg({'Name':'size'})\n",
    "x_axis = list(fig_data.index)\n",
    "y_axis = list(fig_data['Name'])\n",
    "\n",
    "fig = plt.figure(figsize = (10, 5))\n",
    "\n",
    "plt.bar(x_axis,y_axis, color ='yellow',\n",
    "        width = 0.4)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "#9 Line graph of new movies logged each year excluding backfilling\n",
    "\n",
    "fig_data = normal.groupby(['Logged_Year']).agg({'Name':'size'})\n",
    "x_axis = list(fig_data.index)\n",
    "y_axis = list(fig_data['Name'])\n",
    "\n",
    "plt.plot(x_axis,y_axis,color='yellow')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<BarContainer object of 12 artists>"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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n4UzkAABDVqAAAIYEFADAkIACABgSUAAAQwIKAGBIQAEADAkoAIAhAQUAMPQ/AsuZU0YGWDkAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 720x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "#10 Bar graph showing number of new movies watched by month \n",
    "fig_data = normal.groupby(['Logged_Month']).agg({'Name':'size'})\n",
    "x_axis = list(fig_data.index)\n",
    "y_axis = list(fig_data['Name'])\n",
    "\n",
    "fig = plt.figure(figsize = (10, 5))\n",
    "\n",
    "plt.bar(x_axis,y_axis, color ='yellow',\n",
    "        width = 0.4)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<BarContainer object of 7 artists>"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "#11 Bar graph showing number of new movies watched by day of the week  \n",
    "fig_data = normal.groupby(['Logged_DOW']).agg({'Name':'size'})\n",
    "x_axis = list(fig_data.index)\n",
    "y_axis = list(fig_data['Name'])\n",
    "\n",
    "fig = plt.figure(figsize = (10, 5))\n",
    "\n",
    "plt.bar(x_axis,y_axis, color ='yellow',\n",
    "        width = 0.4)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.patches.Circle at 0x19252950460>"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x360 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#12 Donut chart for english language\n",
    "fig, (ax1) = plt.subplots(ncols=1, figsize=(10, 5))\n",
    "df.groupby('english_language').size().plot(kind='pie', colors=['darkgoldenrod','yellow'], ax=ax1)\n",
    "ax1.set_xlabel('English Language?', size=22)\n",
    "\n",
    "#Add in white circle to make it a donut\n",
    "circ=plt.Circle( (0,0), 0.7, color='white')\n",
    "p=plt.gcf()\n",
    "p.gca().add_artist(circ)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.patches.Circle at 0x19252a2c2b0>"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x360 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#13 Donut chart for whether rating was 4 stars or more\n",
    "df['enjoyed'] = np.where(df['Rating']>=4,1,0)\n",
    "fig, (ax1) = plt.subplots(ncols=1, figsize=(10, 5))\n",
    "df.groupby('enjoyed').size().plot(kind='pie', colors=['darkgoldenrod','yellow'], ax=ax1)\n",
    "ax1.set_xlabel('Enjoyed The Movie? (Rating of at least 4 Stars)', size=15)\n",
    "\n",
    "#Add in white circle to make it a donut\n",
    "circ=plt.Circle( (0,0), 0.7, color='white')\n",
    "p=plt.gcf()\n",
    "p.gca().add_artist(circ)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.patches.Circle at 0x19252a659d0>"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x360 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#14 Donut chart for whether a review was written or not\n",
    "fig, (ax1) = plt.subplots(ncols=1, figsize=(10, 5))\n",
    "df.groupby('Review').size().plot(kind='pie', colors=['darkgoldenrod','yellow'], ax=ax1)\n",
    "ax1.set_xlabel('Reviewed?', size=18)\n",
    "\n",
    "#Add in white circle to make it a donut\n",
    "circ=plt.Circle( (0,0), 0.7, color='white')\n",
    "p=plt.gcf()\n",
    "p.gca().add_artist(circ)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "#15 Line graph of average sentiment score of movies by Release year\n",
    "fig_data = normal.groupby(['Year']).agg({'movie_sentiment':'mean'})\n",
    "x_axis = list(fig_data.index)\n",
    "y_axis = list(fig_data['movie_sentiment'])\n",
    "\n",
    "fig = plt.figure(figsize = (10, 5))\n",
    "\n",
    "plt.plot(x_axis,y_axis,color='yellow')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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ejB2IAF5EsQq/SJsH+wGH4UnhkcixNJ5UkoKZHWBmS8xsqZmdUeJ+M7PZyf0PmdnY5Patzew3ZrbYzBaZ2clpxFN7bwKT8LVpr8Ubukl61CSvcbyMf7L+FLBd5FjS9H1gQ3wYSSXQxapOCmbWD59LPh4vYJ5oZmO6bDYeGJ18TQEuTm5fBUwLIbwTGAccX+KxDehcvGzyAuAdkWPJo83wN6Gr8MQr8VyBX/TP0mS1cgzF/45/h/8bpSCNM4XdgaUhhGUhhJX4zK2u/R0mAHODuwcYbGbDQggrQgj3A4QQXsKv2DZ4s6B78eX+PotPVpPaaMXfjNQkL5438U/U7wP2jBxLLUwG9sLLyZ+JHEvjSCMpbAUsL/q9nbXf2HvdxsxGArsCfy61EzObYmZtZtbW0dFRZch99RLe/XQ4fkqt8tPa2QfvwKkhpHh+DjxO4ze+6ysDLgFeIT/XS6qXRlIo9c7YtcFIj9uY2Ub42nmnhBD+U2onIYRLQwgtIYSWIUNilX4ej8+4vRrYNFIMzWId/EzsDtQkL4aAD69sR74bO+6IL8RzDd7MUtJICu143+OCEcBT5W5jZuviCeHqEMKNKcRTI1cDP8GHjj4QOZZmURie+3HMIJrUH/Gh0tPw2cB5Nh3YAe9s/GrkWOJLIyncB4w2s1FmNgCf3ju/yzbzgUlJFdI44MUQwgozM7ynweIQwqwUYqmRZfgL5n3A/0aOpZlsg5rkxTITv+B/VOQ46mE9fBjpcbzFdnOrOimEEFYBJ+DnXouBeSGERWY21cwK0x9vxd9Zl+IrdByX3P5+4AhgbzN7MPn6WLUxpesNvERyHfxsoX/ccJpOKz58dFfsQJrI34Gb8T/TgZFjqZcP4ReeZ+C9zJqXhZC9/uItLS2hra2tTnv7KvBNfD7CoXXap7zlv/iF/f3x/wOpvWPxC/z/xBvgNYvn8GsM2+HDZ/kbNjOzhSGElp620YzmHt2Nz1Y+CiWEWNbHz9R+jq/jLLXVgV/DOYLmSgjgLTy+jxdAzokcSzxKCt36N/B5YHt8kprEoyZ59XMxfnZ2WuxAIjkc72M2HV9hrvkoKZQUgC8C/8LfiDaKG07T2zX50pyF2noNuBBfFyQDjQVqwvDE+AaQka47KVNSKOkyvKf/t4Aeh9+kbiYDDyRfUhtX4cNHeZ2sVq7t8BbbNwC3RI6l/pQU1vII/glhH/LX7yXLDsNLB3W2UBur8TLUscCH44bSEE4HdsInrL4cOZb6UlJYw+t4G4uB+KI5OjyNo9Ak72rUJK8WfomvMXA6at8CsC6+fGc7XoHYPPSut4bpeA//K/AySGkshSZ5P48dSA7NxJsOfDp2IA1kT3yludnAwsix1I+SQqfb8HK044EDI8cipe2Nz3LWEFK67sPLr0/BPyHLW76Dl+Z+Ee/0n39KCgA8DRyJjyGeGzkW6V5xk7wn4oaSKzOBjYEvxA6kAW2Cnyk8kHzPPyUFVuOT017EZ8xuEDUa6c1R+Jj3j+OGkRtPANfja19tHDeUhnUI8An82kL+O/YqKXABPnQ0Ez9TkMa2DfBR/LrPm5FjyYPz8SR7UuxAGpjhi0saPrycvdZAlWjypPAg8GX8GsJxvWwrjaMV78ujJnnVeQGfk3Moa3a2l7W9HfgGXqV1feRYaquJk8KrePnp5viFS5XhZccEfJGjy2MHknGX4jX4zT5ZrVwn4vM4TsITaj41cVI4DZ+oNhfYInIsUpn18b5UapLXdyvxoaN9gPdEjiUr+uOJ9Bm8fD2fmjQp3IgvqvElfHxasmcy/sZ2dexAMuo6fPFDzdqvzG74mcIc4E+RY6mNJlxPoR3YGdgW/08dkFpcUm+74dVj6odUmYCfHbwJ/BUNnVbqZbxh4MbA/WTpPUTrKazlTXzYYSVefpqd/0wpZTJeLHB/7EAy5g58dbFpKCH0xUZ4NdIifKW2fGmypPBdfObmhcDoyLFI9QpN8nTBuTIzgLfhx0/65kB8/sLZ+CrD+dFkSWE0PknnyNiBSCo2BQ7G17x4LXIsWfEQ8Gu8kma9yLFk3Wz8GE4lT3MXmiwpfAa/wKxT5vxoxcsD1SSvPLPwLsBTYweSA8Px3kh3kqeChyZLCpI/HwFGoiZ55XgKP6tqxVuRS/WmAuOAU4HnIseSDiUFybhCk7w7gccjx9LoLsCLLU6JHUiOrIPPXXgBL3HPPiUFyYGjUJO83ryE19YfjJdjS3rejc/3uAL4bdxQUqCkIDnwdmBf1CSvJz/CP81qslptnIUn22PI+sqASgqSE63AcnwYSda0CjgPeD+wR+RY8moD/Ezs7/jF5+xKJSmY2QFmtsTMlprZGSXuNzObndz/kJmNLfexIuWZgF881ZyFtd2Ir5ugs4Ta2hc4HE8KiyPH0ndVJwUz64dP7xuPz/2eaGZjumw2Hp8kUJgocHEFjxUpw3r4bPWbyEsVSDoCPllte7TMbD3MAgbhw0irI8fSN2mcKewOLA0hLAshrMQ7bU3oss0EYG5w9wCDzWxYmY8VKZOa5K3tD/gazKcB/SLH0gyG4kv6/p6slkmnkRS2wgdzC9qT28rZppzHAmBmU8yszczaOjo6qg5a8mgXvEne5eRphml1ZuBrhmgWf/0cDeyFl6g+HTmWyqWRFEpND+76F9ndNuU81m8M4dIQQksIoWXIkCEVhijNYzLeykFN8mAJcAu+quDAyLE0E8M7J7yKT2rLljSSQjtrruU3Ap86Wc425TxWpAKH4Yvw6IIzfB/vBHx87ECa0I74QjzX4mvAZ0caSeE+YLSZjTKzAfiCr/O7bDMfmJRUIY0DXgwhrCjzsSIVGIya5AF0AFcCk4AtI8fSrKYDO+Bnaq9GjqV8VSeFEMIq4ATgdrwOa14IYZGZTTWzQtetW4FleI/ZH+JHqdvHVhuTNLtW4EW8FLNZ/QCfRHVa7ECa2Hr4MNLjwNcjx1K+Jlx5TfJvNV6COYrmnMz2Gj7Lexx+TUHiasXP2hbixRDxaOU1aVKFJnl34SeozWYu8CyarNYozsUnVk4hC21YlBQkp46iOZvkrcYnUO2Gl0VKfJvhF/3vJZm329CUFCSntgb2o/ma5P0C779zOlpMqpEchr8e/wd4MnIsPVNSkBxrxaue74gdSB3NwK8nfDp2ILIGwy/+vwGcFDmWnikpSI4dhM/mbZY5C/fi7RVOAfpHjkXWth3w//CquMatvFdSkBwrbpL3bORY6mEmsAnwhdiBSLem4YvyHI8vfNR4lBQk5ybjp+x5b5L3OHA93p1zUORYpHvr4st3Pgl8NXIspSkpSM7tDLSQ/yZ55+N/zifGDkR6NQ44Fl8zu/HmWykpSBOYDPwVnzyUR88DlwET8fZh0vi+jbcf+SK+Ml7jUFKQJjCRfDfJuwR4BR+vlmzYBJgNPIif5TUOJQVpAoOBQ/AmedlpTFaelfiby0eJ3UJBKnUI8AngLHy51MagpCBNohX4D/lrknctsAK1tMgiw1cjNrwaqTGueSkpSJP4ELAtWV0isbSAl6HuhM+Wlex5O/ANvJH0zyLH4pQUpEkUmuT9BngscixpWYBfQJ+GWlpk2YnAWOBk4IXIsSgpSFM5inw1yZsBDMMvpEt29ceXmXkGOCNyLEoK0lRGAPvjSSHrTfL+gp8pnITP3JZsK5wpXAL8MWokSgrSZApN8hbEDqRKs4AN8RnMkg9n49cYpuBVZXEoKUiTOZDsN8lrx8trW4FNI8ci6dkIr0b6G74wTxxKCtJk1gOOAG4mu03yLsAX0zkldiCSuk/gbc+/ATwaJQIlBWlChSZ5V8UOpA9ewsedD8HXoJb8OR//8HIsMeYuKClIE3o38F6y2STvcuBF1NIiz4YD5wB3EuODi5KCNKnJwMM0YpfK7q0CzgM+COwRORaprWOAPYHTqPcwp5KCNKksNsm7AfgHOktoBuvg6y68AHyp7nsWaUKb4Bf0riUbTfICXpEyGq+gkvzbCU8IP8Zn4teHkoI0sUKTvBtiB1KG3+HrQUxDf7bN5Kt4z65jgP/WZY9VvbrMbDMzW2BmjybfSxZNm9kBZrbEzJaa2RlFt59rZo+Y2UNm9nMzG1xNPCKV+RC+mHoWmuTNBLYAJsUOROpqA2AOXp767brssdqPHGcAd4YQRuOXytdq3GFm/fAZGeOBMcBEMxuT3L0A2CmEsDPwd2B6lfGIVMDwJnm/pbGb5D0C3IK3V94gcixSf/sCh+MVSX+r+d6qTQoTgCuTn68EPllim92BpSGEZSGElcB1yeMIIfw6hFBYi+4etJag1N2R+J/BFbED6cEs/KL4cbEDkWhmAYPwYaTVNd1TtUlhyxDCCoDk+9AS22wFLC/6vT25ravJwK+625GZTTGzNjNr6+joqCJkkWKN3iTvGWAuPmxU6s9LmsNQvNDgD9R63YX+vW1gZncAbytx15ll7qNUo/c1ZgyZ2Zl4EfbV3T1JCOFSvEaLlpaWrM04kobWilci/Rof5WwkFwGv4/Xq0tyOxocPD6npXnpNCiGEj3Z3n5k9bWbDQggrzGwY/rGmq3Zg66LfRwBPFT3HkXjDj31CCHqzlwgOxC/iXk5jJYVX8aRwELBD5FgkPqMea2dUO3w0Hx+UJfl+c4lt7gNGm9koMxsAHJo8DjM7APgKcFAIIQvF4pJLA/AmefOBRhqanAs8hyarST1VmxTOAfY1s0fxS+TnAJjZcDO7FSC5kHwCcDuwGJgXQliUPP5C/OrJAjN70MzmVBmPSB81WpO8N/GLi+/F21qI1IdlccSmpaUltLVlqWeNZMMewCv4usex1zy+CfgU8FPgs5Fjkbwws4UhhJaettHUSJFOk4FF+IhnbDOBbYCDYwciTUZJQaTToXh1R+wmeffgpYenUkYtiEiqlBREOjVKk7yZwGD8zEWkvpQURNbQiq9udn2k/S8DbsRnrg6KFIM0MyUFkTXsBWxPvCZ55wH9gBMj7V+anZKCyBoKTfLuBpbWed//xq9nHEbpTjAitaekILKWWE3yLsGvZailhcSjpCCylq2AA/Ameat63jQ1rwOzgf2Aneu0T5G1KSmIlNSKt+j6dZ32dw3wL+D0Ou1PpDQlBZGSPgEMoT5zFgJehroz0G3/SZG6UFIQKam4SV6p5r9puh2fST2N+O01pNkpKYh0azJ+TaHWTfJmAMPxGdUicSkpiHTrXXiTvMvpsi5Uih7Elzc/CT87EYlLSUGkR5PxxdLvrdHzzwQ2wmcwi8SnpCDSo1o2yWsHrsMrnQbX4PlFKqekINKjjYHP4G/er6T83LOB1cApKT+vSN8pKYj0qhZN8v6Dz2D+DDAyxecVqY6SgkivPkj6TfIuxxOD1l+WxqKkINIrwy84/w54NIXnewPvhroXvgazSONQUhApS5pN8q4H/olaWkgjUlIQKctwYDzVN8kL+GS1HYCPVx+WSMqUFETK1gqswNtS9NXdwP14e2z9+Unj0atSpGwfp/omeTOS5zgilYhE0qakIFK2AcAk4Bbg6T48fjHwS+B4fEKcSONRUhCpSDVN8mYB6wPHpRqRSJqqSgpmtpmZLTCzR5Pvm3az3QFmtsTMlprZGSXuP93MgpltUU08IrU3BhhH5U3yngbmAkfhw0cijanaM4UzgDtDCKPxVo+l3vD7ARfhpRtjgIlmNqbo/q2BffEaPZEMmIwPBf25gsdchM9POLUmEYmkpdqkMAG4Mvn5SuCTJbbZHVgaQlgWQliJN5GZUHT/94EvU7vexCIp+xwwkPIvOL+KJ4WDgHfUKiiRVFSbFLYMIawASL4PLbHNVsDyot/bk9sws4OAJ0MIf+ltR2Y2xczazKyto6OjyrBFqlFpk7wfA/9Gk9UkC3pNCmZ2h5k9XOJrQm+PLTxFiduCmQ0EzgTOKudJQgiXhhBaQggtQ4ZoTFZiawVeBn7Wy3Zv4ifDuwPvr3VQIlXr39sGIYRuVxI3s6fNbFgIYYWZDaP0YrbtwNZFv48AngK2A0YBfzGzwu33m9nuIYR/VfBvEIngA8BovEneUT1sNx9YCsxD6y9LFlQ7fDQfbwpD8v3mEtvcB4w2s1FmNgBftWR+COGvIYShIYSRIYSRePIYq4Qg2VBokvd74O89bDcD/+zzqXoEJVK1ajjT6xoAAAZVSURBVJPCOcC+ZvYoXkF0DoCZDTezWwFCCKuAE/DeAIuBeSGERVXuV6QBHAn0o/smef8H/AlfRKfXk3KRhmAhZK/op6WlJbS1tcUOQwQ4EFiIV1R3feP/NF6pvRxfh1kkLjNbGEJo6WkbzWgWqUqhSd5tXW5/DLgROBYlBMkSJQWRqnwcr8TuOmfhPPzM4YS6RyRSDSUFkaqsizfJ+wVvNcl7Dq9KOhxfh0EkO5QURKpWaJL3k+T3OfgsZq2/LNmjpCBStXcCe+JDSP8FLgD2B3aKGZRInygpiKRiMvAIcCI+jKSWFpJNSgoiqSg0ybsM2AXYJ244In2kpCCSikHAZ5Ofp6GWFpJVmmYpkpozgS3wswaRbFJSEEnN9sC5sYMQqYqGj0REpJOSgoiIdFJSEBGRTkoKIiLSSUlBREQ6KSmIiEgnJQUREemkpCAiIp0yuRynmXUA/+jjw7cAnk0xnLQorsoorsoorso0alxQXWzbhBCG9LRBJpNCNcysrbc1SmNQXJVRXJVRXJVp1Lig9rFp+EhERDopKYiISKdmTAqXxg6gG4qrMoqrMoqrMo0aF9Q4tqa7piAiIt1rxjMFERHphpKCiIi8JYSQmS9ga+A3wGJgEXBycvtmwALg0eT7psntmyfbvwxcWPQ8g4AHi76eBc7rZp/TgaXAEmD/RogLGAm8VrTdnFrGldw3Efgr8BBwG7BF7ONVblzlHq8axPa5JK5FwPd62Ge9j1mvcdXwNbYvsDD5P1sI7F30XLslty8FZpMMb9fpeFUVV6Tj9S1gOfByL++bvR6vNbbvbYNG+gKGAWOTnwcBfwfGAN8DzkhuPwP4bvLzhsAHgKld/zC6PO9CYK8St48B/gKsB4wCHgP6NUBcI4GH63W88BX6niF5w00e/7XYx6uCuMo6XinHtjnwT2BI8vuVwD4NcMzKjatWr7FdgeHJzzsBTxY9173AnvgC178CxtfxeFUbV4zjNS55vm6TQrnHa43HlPOH0qhfwM14Jl0CDCs66Eu6bHcU3bz5AqPxbFsq+08Hphf9fjuwZwPEVdYLMK24gHWBDmCb5A9jDjAl9vGqIK4+Ha8qY3svcEfR70cAP2iAY1ZuXDV9jSW3G/Ac/oY1DHik6L6JwCX1Pl5VxFXX49Xl9p6SQsXHK7PXFMxsJJ5F/wxsGUJYAZB8H1rBU00EfhqSI9bFVvgbc0F7clvsuABGmdkDZna3mX2wtyerJq4QwhvAsfgp7FP4p4/LS2xa1+NVQVxQ4fGqNjb8dH1HMxtpZv2BT+JDB13V+zVWblxQ+9fYIcADIYTX8X9ze9F93R2HehyvvsQF9T1e5ar4eGUyKZjZRsANwCkhhP9U+XSHAtd2t6sSt3X3Jl3PuFYAbw8h7AqcBlxjZhvXKi4zWxd/890VGI6PR08vtWmJ22p2vCqIq6LjlUZsIYTnk9h+CvweeAJYVWpXpR7eAHHV9DVmZu8CvgscU7ipVLilHlrmdvWOq97Hq1wVHS/IYFJI3ghuAK4OIdyY3Py0mQ1L7h+GjzOX81y7AP1DCAu72aSdNT9FjcA/kUaNK4TwegjhueTnhfg44TtqGNd7kn09lpy5zAPeV2K7eh+vsuKq5HilGBshhFtCCHuEEPbEhwceLbFZ3V9j5cRVy9eYmY0Afg5MCiE8ltzcnvzbC7o7DjU7XtXEFeF4lavs41WQqaRgZoYPDywOIcwqums+cGTy85H4OF05JtL9p/HC8x5qZuuZ2Sh8nP/e2HGZ2RAz65f8vG0S17IaxvUkMMbMCt0V98WrJ7qq9/EqK65yj1fKsWFmQ5PvmwLHAZeV2Kzur7Fy4qrVa8zMBgO/xMe5/1jYOBkyecnMxiXPOambf0tNjle1cdX7eFWgrOO1hkouisT+wqspAj5MUCj9+hheUXEn/onnTmCzosc8AfwbL81rB8YU3bcM2LHLPg4Czi76/Uw86y+hRNVBjLjwscVFeFXB/cCBtY4Lr2JZnDzXLcDmjXC8yomr3ONVg9iuBf6WfB3aKK+xcuIq95hVGhfwv8ArrFl6PTS5rwV4ODkWF/JWx4WaH69q44p0vL6X/L+uTr5/ra/Hq/hLbS5ERKRTpoaPRESktpQURESkk5KCiIh0UlIQEZFOSgoiItJJSUFERDopKYiISKf/D0BfUFQqrRlSAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "#16 Line graph of average sentiment score of movies by Logged year\n",
    "fig_data = normal.groupby(['Logged_Year']).agg({'movie_sentiment':'mean'})\n",
    "x_axis = list(fig_data.index)\n",
    "y_axis = list(fig_data['movie_sentiment'])\n",
    "\n",
    "plt.plot(x_axis,y_axis,color='yellow')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x19252aba820>"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "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": [
    "#17 Heatmap of words in titles reimagined as a barplot\n",
    "titles_fd = titles_fd[titles_fd['Frequency']>=10].sort_values(by=['Frequency'],ascending=False)\n",
    "\n",
    "sns.barplot(x='Frequency',y='Word',data=titles_fd,palette='afmhot')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "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": "3.8.3"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}