{ "cells": [ { "cell_type": "markdown", "metadata": {}, "source": [ "# Let's Clean Some Data\n", "\n", "Fivethirtyeight has some great data sets and this is one of them. Some light cleaning should make it more useable!" ] }, { "cell_type": "code", "execution_count": 1, "metadata": { "scrolled": false }, "outputs": [], "source": [ "# import libraries\n", "import pandas as pd\n", "import numpy as np\n", "star_wars = pd.read_csv(\"star_wars.csv\", encoding=\"ISO-8859-1\")" ] }, { "cell_type": "code", "execution_count": 2, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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RespondentIDHave you seen any of the 6 films in the Star Wars franchise?Do you consider yourself to be a fan of the Star Wars film franchise?Which of the following Star Wars films have you seen? Please select all that apply.Unnamed: 4Unnamed: 5Unnamed: 6Unnamed: 7Unnamed: 8Please rank the Star Wars films in order of preference with 1 being your favorite film in the franchise and 6 being your least favorite film....Unnamed: 28Which character shot first?Are you familiar with the Expanded Universe?Do you consider yourself to be a fan of the Expanded Universe?Do you consider yourself to be a fan of the Star Trek franchise?GenderAgeHousehold IncomeEducationLocation (Census Region)
03292879998YesYesStar Wars: Episode I The Phantom MenaceStar Wars: Episode II Attack of the ClonesStar Wars: Episode III Revenge of the SithStar Wars: Episode IV A New HopeStar Wars: Episode V The Empire Strikes BackStar Wars: Episode VI Return of the Jedi3.0...Very favorablyI don't understand this questionYesNoNoMale18-29NaNHigh school degreeSouth Atlantic
13292879538NoNaNNaNNaNNaNNaNNaNNaNNaN...NaNNaNNaNNaNYesMale18-29$0 - $24,999Bachelor degreeWest South Central
23292765271YesNoStar Wars: Episode I The Phantom MenaceStar Wars: Episode II Attack of the ClonesStar Wars: Episode III Revenge of the SithNaNNaNNaN1.0...Unfamiliar (N/A)I don't understand this questionNoNaNNoMale18-29$0 - $24,999High school degreeWest North Central
33292763116YesYesStar Wars: Episode I The Phantom MenaceStar Wars: Episode II Attack of the ClonesStar Wars: Episode III Revenge of the SithStar Wars: Episode IV A New HopeStar Wars: Episode V The Empire Strikes BackStar Wars: Episode VI Return of the Jedi5.0...Very favorablyI don't understand this questionNoNaNYesMale18-29$100,000 - $149,999Some college or Associate degreeWest North Central
43292731220YesYesStar Wars: Episode I The Phantom MenaceStar Wars: Episode II Attack of the ClonesStar Wars: Episode III Revenge of the SithStar Wars: Episode IV A New HopeStar Wars: Episode V The Empire Strikes BackStar Wars: Episode VI Return of the Jedi5.0...Somewhat favorablyGreedoYesNoNoMale18-29$100,000 - $149,999Some college or Associate degreeWest North Central
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5 rows × 38 columns

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" ], "text/plain": [ " RespondentID Have you seen any of the 6 films in the Star Wars franchise? \\\n", "0 3292879998 Yes \n", "1 3292879538 No \n", "2 3292765271 Yes \n", "3 3292763116 Yes \n", "4 3292731220 Yes \n", "\n", " Do you consider yourself to be a fan of the Star Wars film franchise? \\\n", "0 Yes \n", "1 NaN \n", "2 No \n", "3 Yes \n", "4 Yes \n", "\n", " Which of the following Star Wars films have you seen? Please select all that apply. \\\n", "0 Star Wars: Episode I The Phantom Menace \n", "1 NaN \n", "2 Star Wars: Episode I The Phantom Menace \n", "3 Star Wars: Episode I The Phantom Menace \n", "4 Star Wars: Episode I The Phantom Menace \n", "\n", " Unnamed: 4 \\\n", "0 Star Wars: Episode II Attack of the Clones \n", "1 NaN \n", "2 Star Wars: Episode II Attack of the Clones \n", "3 Star Wars: Episode II Attack of the Clones \n", "4 Star Wars: Episode II Attack of the Clones \n", "\n", " Unnamed: 5 \\\n", "0 Star Wars: Episode III Revenge of the Sith \n", "1 NaN \n", "2 Star Wars: Episode III Revenge of the Sith \n", "3 Star Wars: Episode III Revenge of the Sith \n", "4 Star Wars: Episode III Revenge of the Sith \n", "\n", " Unnamed: 6 \\\n", "0 Star Wars: Episode IV A New Hope \n", "1 NaN \n", "2 NaN \n", "3 Star Wars: Episode IV A New Hope \n", "4 Star Wars: Episode IV A New Hope \n", "\n", " Unnamed: 7 \\\n", "0 Star Wars: Episode V The Empire Strikes Back \n", "1 NaN \n", "2 NaN \n", "3 Star Wars: Episode V The Empire Strikes Back \n", "4 Star Wars: Episode V The Empire Strikes Back \n", "\n", " Unnamed: 8 \\\n", "0 Star Wars: Episode VI Return of the Jedi \n", "1 NaN \n", "2 NaN \n", "3 Star Wars: Episode VI Return of the Jedi \n", "4 Star Wars: Episode VI Return of the Jedi \n", "\n", " Please rank the Star Wars films in order of preference with 1 being your favorite film in the franchise and 6 being your least favorite film. \\\n", "0 3.0 \n", "1 NaN \n", "2 1.0 \n", "3 5.0 \n", "4 5.0 \n", "\n", " ... Unnamed: 28 Which character shot first? \\\n", "0 ... Very favorably I don't understand this question \n", "1 ... NaN NaN \n", "2 ... Unfamiliar (N/A) I don't understand this question \n", "3 ... Very favorably I don't understand this question \n", "4 ... Somewhat favorably Greedo \n", "\n", " Are you familiar with the Expanded Universe? \\\n", "0 Yes \n", "1 NaN \n", "2 No \n", "3 No \n", "4 Yes \n", "\n", " Do you consider yourself to be a fan of the Expanded Universe? \\\n", "0 No \n", "1 NaN \n", "2 NaN \n", "3 NaN \n", "4 No \n", "\n", " Do you consider yourself to be a fan of the Star Trek franchise? Gender \\\n", "0 No Male \n", "1 Yes Male \n", "2 No Male \n", "3 Yes Male \n", "4 No Male \n", "\n", " Age Household Income Education \\\n", "0 18-29 NaN High school degree \n", "1 18-29 $0 - $24,999 Bachelor degree \n", "2 18-29 $0 - $24,999 High school degree \n", "3 18-29 $100,000 - $149,999 Some college or Associate degree \n", "4 18-29 $100,000 - $149,999 Some college or Associate degree \n", "\n", " Location (Census Region) \n", "0 South Atlantic \n", "1 West South Central \n", "2 West North Central \n", "3 West North Central \n", "4 West North Central \n", "\n", "[5 rows x 38 columns]" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "# print the head\n", "display(star_wars.head())" ] }, { "cell_type": "code", "execution_count": 3, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "Index(['RespondentID',\n", " 'Have you seen any of the 6 films in the Star Wars franchise?',\n", " 'Do you consider yourself to be a fan of the Star Wars film franchise?',\n", " 'Which of the following Star Wars films have you seen? Please select all that apply.',\n", " 'Unnamed: 4', 'Unnamed: 5', 'Unnamed: 6', 'Unnamed: 7', 'Unnamed: 8',\n", " 'Please rank the Star Wars films in order of preference with 1 being your favorite film in the franchise and 6 being your least favorite film.',\n", " 'Unnamed: 10', 'Unnamed: 11', 'Unnamed: 12', 'Unnamed: 13',\n", " 'Unnamed: 14',\n", " 'Please state whether you view the following characters favorably, unfavorably, or are unfamiliar with him/her.',\n", " 'Unnamed: 16', 'Unnamed: 17', 'Unnamed: 18', 'Unnamed: 19',\n", " 'Unnamed: 20', 'Unnamed: 21', 'Unnamed: 22', 'Unnamed: 23',\n", " 'Unnamed: 24', 'Unnamed: 25', 'Unnamed: 26', 'Unnamed: 27',\n", " 'Unnamed: 28', 'Which character shot first?',\n", " 'Are you familiar with the Expanded Universe?',\n", " 'Do you consider yourself to be a fan of the Expanded Universe?',\n", " 'Do you consider yourself to be a fan of the Star Trek franchise?',\n", " 'Gender', 'Age', 'Household Income', 'Education',\n", " 'Location (Census Region)'],\n", " dtype='object')" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "# print the columns\n", "display(star_wars.columns)" ] }, { "cell_type": "code", "execution_count": 4, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Yes 936\n", "No 250\n", "Name: Have you seen any of the 6 films in the Star Wars franchise?, dtype: int64\n", "Yes 552\n", "NaN 350\n", "No 284\n", "Name: Do you consider yourself to be a fan of the Star Wars film franchise?, dtype: int64\n" ] } ], "source": [ "# value counts for columns 1:2\n", "print(star_wars[\"Have you seen any of the 6 films in the Star Wars franchise?\"].value_counts(dropna=False))\n", "print(star_wars[\"Do you consider yourself to be a fan of the Star Wars film franchise?\"].value_counts(dropna=False))" ] }, { "cell_type": "code", "execution_count": 5, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "True 936\n", "False 250\n", "Name: Have you seen any of the 6 films in the Star Wars franchise?, dtype: int64\n", "True 552\n", "NaN 350\n", "False 284\n", "Name: Do you consider yourself to be a fan of the Star Wars film franchise?, dtype: int64\n" ] } ], "source": [ "# switch values to boolean for columns 1:2\n", "yes_no_bool = {\"Yes\":True, \"No\":False}\n", "star_wars[\"Have you seen any of the 6 films in the Star Wars franchise?\"] = star_wars[\"Have you seen any of the 6 films in the Star Wars franchise?\"].map(yes_no_bool)\n", "star_wars[\"Do you consider yourself to be a fan of the Star Wars film franchise?\"] = star_wars[\"Do you consider yourself to be a fan of the Star Wars film franchise?\"].map(yes_no_bool)\n", "print(star_wars[\"Have you seen any of the 6 films in the Star Wars franchise?\"].value_counts(dropna=False))\n", "print(star_wars[\"Do you consider yourself to be a fan of the Star Wars film franchise?\"].value_counts(dropna=False))" ] }, { "cell_type": "code", "execution_count": 6, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Star Wars: Episode I The Phantom Menace 673\n", "NaN 513\n", "Name: Which of the following Star Wars films have you seen? Please select all that apply., dtype: int64\n" ] } ], "source": [ "# value counts for columns 3\n", "print(star_wars[\"Which of the following Star Wars films have you seen? Please select all that apply.\"].value_counts(dropna=False))" ] }, { "cell_type": "code", "execution_count": 7, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "True 673\n", "False 513\n", "Name: Which of the following Star Wars films have you seen? Please select all that apply., dtype: int64" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "# switch values to boolean for columns 3:9\n", "watch_bool = {\"Star Wars: Episode I The Phantom Menace\" : True,\n", " \"Star Wars: Episode II Attack of the Clones\" : True,\n", " \"Star Wars: Episode III Revenge of the Sith\" : True,\n", " \"Star Wars: Episode IV A New Hope\" : True,\n", " \"Star Wars: Episode V The Empire Strikes Back\" : True,\n", " \"Star Wars: Episode VI Return of the Jedi\" : True,\n", " np.NaN : False}\n", "\n", "for col in star_wars.columns[3:9]:\n", " star_wars[col] = star_wars[col].map(watch_bool)\n", "\n", "# value counts for columns 3\n", "display(star_wars.iloc[:,3].value_counts(dropna=False))" ] }, { "cell_type": "code", "execution_count": 8, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "Index(['seen_ep_1', 'seen_ep_2', 'seen_ep_3', 'seen_ep_4', 'seen_ep_5',\n", " 'seen_ep_6'],\n", " dtype='object')" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "# rename columns\n", "star_wars = star_wars.rename(columns={\"Which of the following Star Wars films have you seen? Please select all that apply.\" : \"seen_ep_1\",\n", " \"Unnamed: 4\" : \"seen_ep_2\",\n", " \"Unnamed: 5\" : \"seen_ep_3\",\n", " \"Unnamed: 6\" : \"seen_ep_4\",\n", " \"Unnamed: 7\" : \"seen_ep_5\",\n", " \"Unnamed: 8\" : \"seen_ep_6\"})\n", "\n", "display(star_wars.columns[3:9])" ] }, { "cell_type": "code", "execution_count": 9, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "dtype('float64')" ] }, "execution_count": 9, "metadata": {}, "output_type": "execute_result" } ], "source": [ "# convert rankings to float\n", "star_wars[star_wars.columns[9:15]] = star_wars[star_wars.columns[9:15]].astype(float)\n", "\n", "# star_wars.columns[9].dtype # why does this work sometimes?\n", "star_wars.iloc[:,9].dtype" ] }, { "cell_type": "code", "execution_count": 10, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "Index(['rank_ep_1', 'rank_ep_2', 'rank_ep_3', 'rank_ep_4', 'rank_ep_5',\n", " 'rank_ep_6'],\n", " dtype='object')" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "# rename more columns\n", "new_columns = {\"Please rank the Star Wars films in order of preference with 1 being your favorite film in the franchise and 6 being your least favorite film.\":\"rank_ep_1\",\n", " \"Unnamed: 10\":\"rank_ep_2\",\n", " \"Unnamed: 11\":\"rank_ep_3\",\n", " \"Unnamed: 12\":\"rank_ep_4\",\n", " \"Unnamed: 13\":\"rank_ep_5\",\n", " \"Unnamed: 14\":\"rank_ep_6\",}\n", "star_wars = star_wars.rename(columns = new_columns)\n", "\n", "display(star_wars.columns[9:15])" ] }, { "cell_type": "code", "execution_count": 11, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "Are you a fan of the Star Wars films? 0.660287\n", "seen_ep_1 0.567454\n", "seen_ep_2 0.481450\n", "seen_ep_3 0.463744\n", "seen_ep_4 0.511804\n", "seen_ep_5 0.639123\n", "seen_ep_6 0.622260\n", "rank_ep_1 3.732934\n", "rank_ep_2 4.087321\n", "rank_ep_3 4.341317\n", "rank_ep_4 3.272727\n", "rank_ep_5 2.513158\n", "rank_ep_6 3.047847\n", "dtype: float64" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "# get average value for seen any, which episode, rankings by episode\n", "means = star_wars.iloc[:,2:15].mean()\n", "means = means.rename({\"Do you consider yourself to be a fan of the Star Wars film franchise?\":\"Are you a fan of the Star Wars films?\"})\n", "display(means)" ] }, { "cell_type": "code", "execution_count": 12, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "0.6602870813397129" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "# math check :)\n", "star_wars[\"Do you consider yourself to be a fan of the Star Wars film franchise?\"].value_counts()\n", "display(552/(552+284))" ] }, { "cell_type": "code", "execution_count": 13, "metadata": {}, "outputs": [ { "data": { "image/png": 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bt65F7Z85c8bWtpubm3r06KEPP/xQAwcObJX6AQDA1ePpMcB1zmw2KzU1VZWVlXar4dyd7zw9BgBgdNfr02N4TjsAAABgcIR2wI7y8vLk4eHR7Ks1REZGNtt+U0+9AQAAxsPyGMCOTp06pfLy8maPd+vW7ar7OHLkiGpqapo81rlz5wueMX8lWB4DALheXK/LY7gRFbAjV1fXVgnmF/Pzv/IKAACuP4R2AK3m3+kJ1+R59QAAtHWsaQcAAAAMjtAOAAAAGByhHQAAADA4QjsAAABgcIR2AAAAwOAI7QAAAIDBEdoBAAAAgyO0AwAAAAZHaAcAAAAMjtAOAAAAGByhHQAAADA4QjsAAABgcIR2AAAAwOAI7QAAAIDBEdoBAAAAgyO0AwAAAAZHaAcAAAAMjtAOAAAAGByhHQAAADA4QjsAAABgcE72LgDAr8et89+Xg7ObvcsAgF+NkqVD7V0CDIKZdgAAAMDgCO0AAACAwRHaAQAAAIMjtAMAAAAGR2gHAAAADI7QDgAAABgcoR2ATX5+vpycnNSrVy97lwIAAM5DaAcgSaqsrNS4ceM0aNAge5cCAAB+htAOSNq8ebOioqLk6uoqX19fDR48WCdOnJAkrV27VhEREXJxcVF4eLhWr17d6NqysjKNGjVKPj4+6tixo4YNG6aSkhLb8QkTJmj48OFavny5AgIC5OvrqylTpqimpqZFtVVXV2vmzJkKCgqSu7u7YmJiZLFYbMfNZrN8fHz05ptvqnv37nJxcVFCQoLKysouawwefvhhjR07VrfffvtlXQcAAK49QjvavIqKCo0ZM0YTJ05UUVGRLBaLkpKS1NDQoA0bNmjevHlavHixioqKlJGRoblz5yo7O1uSVFNTo4SEBHl6eiovL0/5+fny8PBQYmKizpw5Y+sjJydHxcXFysnJUXZ2tsxms8xmc4vqS0lJ0c6dO7Vx40bt379fI0eOVGJiog4ePGg75+TJk1q8eLHWr1+v/Px8VVZWavTo0S0eg6ysLB0+fFjz589v0fnV1dWyWq2NXgAA4NpxsncBgL1VVFSotrZWSUlJCg0NlSRFRUVJkubPn6/MzEwlJSVJkrp27aovvvhCL7zwgsaPH69Nmzapvr5ea9eulclkknQ2APv4+MhisSg+Pl6S1KFDBz333HNydHRUeHi4hg4dqu3bt2vy5MkXra20tFRZWVkqLS1VYGCgJGnmzJl67733lJWVpYyMDElnf3h47rnnFBMTI0nKzs5WRESEdu3apX79+l20j4MHD+qxxx5TXl6enJxa9iVhyZIlSk9Pb9G5AADg6hHa0eb17NlTgwYNUlRUlBISEhQfH68RI0aoffv2Ki4u1qRJkxqF69raWnl7e0uS9u3bp0OHDsnT07NRm6dPn1ZxcbFtOzIyUo6OjrbtgIAAFRYWXrK2wsJC1dXVKSwsrNH+6upq+fr62radnJzUt29f23Z4eLh8fHxUVFR00dBeV1ensWPHKj09/YI+LmbOnDmaPn26bdtqtSokJKTF1wMAgMtDaEeb5+joqA8++EA7duzQtm3btGrVKj3++OPaunWrJGnNmjW2Gezzr5GkqqoqRUdHa8OGDRe06+fnZ/u4Xbt2jY6ZTCbV19dfsraqqio5Ojpqz549jUK/JHl4eLTsDV7E8ePHtXv3bn322WdKSUmRJNXX16uhoUFOTk7atm2bfve7311wnbOzs5ydna+6fwAA0DKEdkBnQ3RcXJzi4uI0b948hYaGKj8/X4GBgTp8+LCSk5ObvK5Pnz7atGmT/P395eXl1ep19e7dW3V1dfr+++/Vv3//Zs+rra3V7t27bbPqBw4cUGVlpSIiIi7avpeX1wUz/qtXr9Y///lPbd68WV27dr36NwEAAK4aoR1tXkFBgbZv3674+Hj5+/uroKBAR48eVUREhNLT0zVt2jR5e3srMTFR1dXV2r17t3788UdNnz5dycnJWrZsmYYNG6aFCxcqODhYR44c0ZYtWzR79mwFBwdfVW1hYWFKTk7WuHHjlJmZqd69e+vo0aPavn27evTooaFDh0o6O5M/depUrVy5Uk5OTkpJSVFsbOwl17M7ODjo1ltvbbTP399fLi4uF+wHAAD2Q2hHm+fl5aXc3FytWLFCVqtVoaGhyszM1JAhQyRJbm5uWrZsmWbNmiV3d3dFRUUpNTXVdiw3N1dpaWlKSkrS8ePHFRQUpEGDBrXazHtWVpYWLVqkGTNmqLy8XJ06dVJsbKzuvvtu2zlubm5KS0vT2LFjVV5erv79+2vdunWt0j8AALA/U0NDQ4O9iwBw5cxms1JTU1VZWWm3GqxWq7y9vRWS+pocnN3sVgcA/NqULB1q7xJwjZ37Hnrs2LGLTvjxnHYAAADA4AjtgB3l5eXJw8Oj2VdriIyMbLb9pp56AwAAjIflMYAdnTp1SuXl5c0e79at21X3ceTIEdXU1DR5rHPnzhc8Y/5KsDwGAK4Nlsf8+rV0eQw3ogJ25Orq2irB/GLO/ZVXAABw/SK0A2g1/05PuCbPqwcAoK1jTTsAAABgcIR2AAAAwOAI7QAAAIDBEdoBAAAAgyO0AwAAAAZHaAcAAAAMjtAOAAAAGByhHQAAADA4QjsAAABgcIR2AAAAwOAI7QAAAIDBEdoBAAAAgyO0AwAAAAZHaAcAAAAMjtAOAAAAGByhHQAAADA4QjsAAABgcIR2AAAAwOAI7QAAAIDBEdoBAAAAg3OydwEAfj1unf++HJzd7F0GALSakqVD7V0CIImZdgAAAMDwCO0AAACAwRHaAQAAAIMjtAMAAAAGR2gHAAAADI7QDgAAABgcoR0AAAAwOEI70MZ9/PHHiouLk6+vr1xdXRUeHq5nnnnG3mUBAIDz8MeVgDbO3d1dKSkp6tGjh9zd3fXxxx/rj3/8o9zd3fXQQw/ZuzwAACBm2gFJ0ubNmxUVFSVXV1f5+vpq8ODBOnHihCRp7dq1ioiIkIuLi8LDw7V69epG15aVlWnUqFHy8fFRx44dNWzYMJWUlNiOT5gwQcOHD9fy5csVEBAgX19fTZkyRTU1NS2qrbq6WjNnzlRQUJDc3d0VExMji8ViO242m+Xj46M333xT3bt3l4uLixISElRWVtai9nv37q0xY8YoMjJSXbp00f3336+EhATl5eVdtCar1droBQAArh1CO9q8iooKjRkzRhMnTlRRUZEsFouSkpLU0NCgDRs2aN68eVq8eLGKioqUkZGhuXPnKjs7W5JUU1OjhIQEeXp6Ki8vT/n5+fLw8FBiYqLOnDlj6yMnJ0fFxcXKyclRdna2zGazzGZzi+pLSUnRzp07tXHjRu3fv18jR45UYmKiDh48aDvn5MmTWrx4sdavX6/8/HxVVlZq9OjRVzQen332mXbs2KEBAwY0e86SJUvk7e1te4WEhFxRXwAAoGVMDQ0NDfYuArCnTz/9VNHR0SopKVFoaGijY926ddOTTz6pMWPG2PYtWrRI77zzjnbs2KGXX35ZixYtUlFRkUwmkyTpzJkztpnv+Ph4TZgwQRaLRcXFxXJ0dJQkjRo1Sg4ODtq4ceNFaystLdVNN92k0tJSBQYG2vYPHjxY/fr1U0ZGhsxmsx588EF98skniomJkSR9+eWXioiIUEFBgfr169eicQgODtbRo0dVW1urBQsWaO7cuc2eW11drerqatu21WpVSEiIQlJfk4OzW4v6A4DrQcnSofYuAb9yVqtV3t7eOnbsmLy8vJo9jzXtaPN69uypQYMGKSoqSgkJCYqPj9eIESPUvn17FRcXa9KkSZo8ebLt/NraWnl7e0uS9u3bp0OHDsnT07NRm6dPn1ZxcbFtOzIy0hbYJSkgIECFhYWXrK2wsFB1dXUKCwtrtL+6ulq+vr62bScnJ/Xt29e2HR4eLh8fHxUVFbU4tOfl5amqqkqffPKJHnvsMXXr1q3RDyvnc3Z2lrOzc4vaBQAAV4/QjjbP0dFRH3zwgXbs2KFt27Zp1apVevzxx7V161ZJ0po1a2wz2OdfI0lVVVWKjo7Whg0bLmjXz8/P9nG7du0aHTOZTKqvr79kbVVVVXJ0dNSePXsahX5J8vDwaNkbbKGuXbtKkqKiovSf//xHCxYsaDa0AwCAXxahHdDZEB0XF6e4uDjNmzdPoaGhys/PV2BgoA4fPqzk5OQmr+vTp482bdokf3//i/5K60r17t1bdXV1+v7779W/f/9mz6utrdXu3btts+oHDhxQZWWlIiIirqjf+vr6RstfAACAfRHa0eYVFBRo+/btio+Pl7+/vwoKCnT06FFFREQoPT1d06ZNk7e3txITE1VdXa3du3frxx9/1PTp05WcnKxly5Zp2LBhWrhwoYKDg3XkyBFt2bJFs2fPVnBw8FXVFhYWpuTkZI0bN06ZmZnq3bu3jh49qu3bt6tHjx4aOvTsWst27dpp6tSpWrlypZycnJSSkqLY2NgWLY35y1/+ohtvvFHh4eGSpNzcXC1fvlzTpk27qtoBAEDrIbSjzfPy8lJubq5WrFghq9Wq0NBQZWZmasiQIZIkNzc3LVu2TLNmzZK7u7uioqKUmppqO5abm6u0tDQlJSXp+PHjCgoK0qBBg1pt5j0rK0uLFi3SjBkzVF5erk6dOik2NlZ333237Rw3NzelpaVp7NixKi8vV//+/bVu3boWtV9fX685c+bo66+/lpOTk26++WY99dRT+uMf/9gq9QMAgKvH02OA65zZbFZqaqoqKyvtVsO5O995egyAXxueHoNrraVPj+E57QAAAIDBEdoBO8rLy5OHh0ezr9YQGRnZbPtNPfUGAAAYD8tjADs6deqUysvLmz3erVu3q+7jyJEjqqmpafJY586dL3jG/JVgeQyAXyuWx+Baa+nyGEI7gKvW0i84AACgMda0AwAAAL8ShHYAAADA4AjtAAAAgMER2gEAAACDI7QDAAAABkdoBwAAAAyO0A4AAAAYHKEdAAAAMDhCOwAAAGBwhHYAAADA4AjtAAAAgMER2gEAAACDI7QDAAAABkdoBwAAAAyO0A4AAAAYHKEdAAAAMDhCOwAAAGBwhHYAAADA4AjtAAAAgMER2gEAAACDI7QDAAAABudk7wIA/HrcOv99OTi72bsMALCbkqVD7V0CfqWYaQcAAAAMjtAOAAAAGByhHQAAADA4QjsAAABgcIR2AAAAwOAI7QAAAIDBEdqBNm7Lli2666675OfnJy8vL91+++16//337V0WAAA4D6EdaONyc3N111136Z133tGePXs0cOBA3XPPPfrss8/sXRoAAPg/hHZA0ubNmxUVFSVXV1f5+vpq8ODBOnHihCRp7dq1ioiIkIuLi8LDw7V69epG15aVlWnUqFHy8fFRx44dNWzYMJWUlNiOT5gwQcOHD9fy5csVEBAgX19fTZkyRTU1NS2qrbq6WjNnzlRQUJDc3d0VExMji8ViO242m+Xj46M333xT3bt3l4uLixISElRWVtai9lesWKHZs2erb9++6t69uzIyMtS9e3dt3br1ojVZrdZGLwAAcO0Q2tHmVVRUaMyYMZo4caKKiopksViUlJSkhoYGbdiwQfPmzdPixYtVVFSkjIwMzZ07V9nZ2ZKkmpoaJSQkyNPTU3l5ecrPz5eHh4cSExN15swZWx85OTkqLi5WTk6OsrOzZTabZTabW1RfSkqKdu7cqY0bN2r//v0aOXKkEhMTdfDgQds5J0+e1OLFi7V+/Xrl5+ersrJSo0ePvqLxqK+v1/Hjx9WxY8dmz1myZIm8vb1tr5CQkCvqCwAAtIypoaGhwd5FAPb06aefKjo6WiUlJQoNDW10rFu3bnryySc1ZswY275FixbpnXfe0Y4dO/Tyyy9r0aJFKioqkslkkiSdOXPGNvMdHx+vCRMmyGKxqLi4WI6OjpKkUaNGycHBQRs3brxobaWlpbrppptUWlqqwMBA2/7BgwerX79+ysjIkNls1oMPPqhPPvlEMTExkqQvv/xSERERKigoUL9+/S5rPP785z9r6dKl+vLLL+Xv79/kOdXV1aqurrZtW61WhYSEKCT1NTk4u11WfwDwa1KydKi9S8B1xmq1ytvbW8eOHZOXl1ez5zn9gjUBhtSzZ08NGjRIUVFRSkhIUHx8vHdKz/UAACAASURBVEaMGKH27duruLhYkyZN0uTJk23n19bWytvbW5K0b98+HTp0SJ6eno3aPH36tIqLi23bkZGRtsAuSQEBASosLLxkbYWFhaqrq1NYWFij/dXV1fL19bVtOzk5qW/fvrbt8PBw+fj4qKio6LJC+yuvvKL09HT9z//8T7OBXZKcnZ3l7Ozc4nYBAMDVIbSjzXN0dNQHH3ygHTt2aNu2bVq1apUef/xx25ruNWvW2Gawz79GkqqqqhQdHa0NGzZc0K6fn5/t43bt2jU6ZjKZVF9ff8naqqqq5OjoqD179jQK/ZLk4eHRsjfYQhs3btQf/vAH/f3vf9fgwYNbtW0AAHB1CO2AzobouLg4xcXFad68eQoNDVV+fr4CAwN1+PBhJScnN3ldnz59tGnTJvn7+1/0V1pXqnfv3qqrq9P333+v/v37N3tebW2tdu/ebZtVP3DggCorKxUREdGifl599VVNnDhRGzdu1NCh/GoXAACj4UZUtHkFBQXKyMjQ7t27VVpaqi1btujo0aOKiIhQenq6lixZopUrV+qrr75SYWGhsrKy9PTTT0uSkpOT1alTJw0bNkx5eXn6+uuvZbFYNG3aNH3zzTdXXVtYWJiSk5M1btw4bdmyRV9//bV27dqlJUuW6O2337ad165dO02dOlUFBQXas2ePJkyYoNjY2BYtjXnllVc0btw4ZWZmKiYmRt99952+++47HTt27KrrBwAArYOZdrR5Xl5eys3N1YoVK2S1WhUaGqrMzEwNGTJEkuTm5qZly5Zp1qxZcnd3V1RUlFJTU23HcnNzlZaWpqSkJB0/flxBQUEaNGhQq828Z2VladGiRZoxY4bKy8vVqVMnxcbG6u6777ad4+bmprS0NI0dO1bl5eXq37+/1q1b16L2X3zxRdXW1mrKlCmaMmWKbf/48eNb/IQbAABwbfH0GOA6ZzablZqaqsrKSrvVcO7Od54eA6Ct4+kxuFwtfXoMy2MAAAAAgyO0A3aUl5cnDw+PZl+tITIystn2m3rqDQAAMB6WxwB2dOrUKZWXlzd7vFu3blfdx5EjR1RTU9Pksc6dO1/wjPkrwfIYADiL5TG4XC1dHkNoB3DVWvoFBwAANMaadgAAAOBXgtAOAAAAGByhHQAAADA4QjsAAABgcIR2AAAAwOAI7QAAAIDBEdoBAAAAgyO0AwAAAAZHaAcAAAAMjtAOAAAAGByhHQAAADA4QjsAAABgcIR2AAAAwOAI7QAAAIDBEdoBAAAAgyO0AwAAAAZHaAcAAAAMjtAOAAAAGByhHQAAADA4QjsAAABgcIR2AAAAwOCc7F0AgF+PW+e/LwdnN3uXAQC4hkqWDrV3CW0SM+0AAACAwRHaAQAAAIMjtAMAAAAGR2gHAAAADI7QDgAAABgcoR0AAAAwOEI70IZVVFRo7NixCgsLk4ODg1JTU+1dEgAAaAKhHWjDqqur5efnpyeeeEI9e/a0dzkAAKAZhHa0eZs3b1ZUVJRcXV3l6+urwYMH68SJE5KktWvXKiIiQi4uLgoPD9fq1asbXVtWVqZRo0bJx8dHHTt21LBhw1RSUmI7PmHCBA0fPlzLly9XQECAfH19NWXKFNXU1LSoturqas2cOVNBQUFyd3dXTEyMLBaL7bjZbJaPj4/efPNNde/eXS4uLkpISFBZWVmL2u/SpYueffZZjRs3Tt7e3i26BgAA/PII7WjTKioqNGbMGE2cOFFFRUWyWCxKSkpSQ0ODNmzYoHnz5mnx4sUqKipSRkaG5s6dq+zsbElSTU2NEhIS5Onpqby8POXn58vDw0OJiYk6c+aMrY+cnBwVFxcrJydH2dnZMpvNMpvNLaovJSVFO3fu1MaNG7V//36NHDlSiYmJOnjwoO2ckydPavHixVq/fr3y8/NVWVmp0aNHt+o4/Vx1dbWsVmujFwAAuHac7F0AYE8VFRWqra1VUlKSQkNDJUlRUVGSpPnz5yszM1NJSUmSpK5du+qLL77QCy+8oPHjx2vTpk2qr6/X2rVrZTKZJElZWVny8fGRxWJRfHy8JKlDhw567rnn5OjoqPDwcA0dOlTbt2/X5MmTL1pbaWmpsrKyVFpaqsDAQEnSzJkz9d577ykrK0sZGRmSzv7w8NxzzykmJkaSlJ2drYiICO3atUv9+vVr5RE7a8mSJUpPT78mbQMAgAsR2tGm9ezZU4MGDVJUVJQSEhIUHx+vESNGqH379iouLtakSZMaheva2lrbMpJ9+/bp0KFD8vT0bNTm6dOnVVxcbNuOjIyUo6OjbTsgIECFhYWXrK2wsFB1dXUKCwtrtL+6ulq+vr62bScnJ/Xt29e2HR4eLh8fHxUVFV2z0D5nzhxNnz7dtm21WhUSEnJN+gIAAIR2tHGOjo764IMPtGPHDm3btk2rVq3S448/rq1bt0qS1qxZY5vBPv8aSaqqqlJ0dLQ2bNhwQbt+fn62j9u1a9fomMlkUn19/SVrq6qqkqOjo/bs2dMo9EuSh4dHy97gNeLs7CxnZ2e71gAAQFtCaEebZzKZFBcXp7i4OM2bN0+hoaHKz89XYGCgDh8+rOTk5Cav69OnjzZt2iR/f395eXm1el29e/dWXV2dvv/+e/Xv37/Z82pra7V7927brPqBAwdUWVmpiIiIVq8JAADYB6EdbVpBQYG2b9+u+Ph4+fv7q6CgQEePHlVERITS09M1bdo0eXt7KzExUdXV1dq9e7d+/PFHTZ8+XcnJyVq2bJmGDRumhQsXKjg4WEeOHNGWLVs0e/ZsBQcHX1VtYWFhSk5O1rhx45SZmanevXvr6NGj2r59u3r06KGhQ4dKOjuTP3XqVK1cuVJOTk5KSUlRbGxsi5fG7N27V9LZmf2jR49q7969at++vX7zm99cVf0AAKD1ENrRpnl5eSk3N1crVqyQ1WpVaGioMjMzNWTIEEmSm5ubli1bplmzZsnd3V1RUVG2P0Dk5uam3NxcpaWlKSkpScePH1dQUJAGDRrUajPvWVlZWrRokWbMmKHy8nJ16tRJsbGxuvvuu23nuLm5KS0tTWPHjlV5ebn69++vdevWtbiP3r172z7es2ePXnnlFYWGhjZ6dCUAALAvU0NDQ4O9iwBwZcxms1JTU1VZWWnXOqxWq7y9vRWS+pocnN3sWgsA4NoqWTrU3iX8qpz7Hnrs2LGLTvrxnHYAAADA4AjtgJ3k5eXJw8Oj2VdriIyMbLb9pp56AwAAjInlMYCdnDp1SuXl5c0e79at21X3ceTIEdXU1DR5rHPnzhc8Y/5KsTwGANoOlse0rpYujyG0A7hqLf2CAwAAGmNNOwAAAPArQWgHAAAADI7QDgAAABgcoR0AAAAwOEI7AAAAYHCEdgAAAMDgCO0AAACAwRHaAQAAAIMjtAMAAAAGR2gHAAAADI7QDgAAABgcoR0AAAAwOEI7AAAAYHCEdgAAAMDgCO0AAACAwRHaAQAAAIMjtAMAAAAGR2gHAAAADI7QDgAAABgcoR0AAAAwOEI7AAAAYHBO9i4AwK/HrfPfl4Ozm73LAACg1ZUsHWrX/plpBwAAAAyO0A4AAAAYHKEdAAAAMDhCOwAAAGBwhHYAAADA4AjtreS7777TXXfdJXd3d/n4+Ni1loaGBj300EPq2LGjTCaT9u7d2+Jru3TpohUrVlzD6tCUF198USEhIXJwcNCKFSu0YMEC9erVy3Z8woQJGj58uB0rBAAA9nRFoX3nzp1ydHTU0KH2ffSNkTzzzDOqqKjQ3r179dVXX9m1lvfee09ms1lvvfWWKioqdOutt15wjtls/kV/uHjjjTcUGxsrb29veXp6KjIyUqmpqbbjPw+prS0gIEBLly5ttO+xxx6TyWSSxWJptP/OO+/UAw88cM1q+Tmr1aqUlBSlpaWpvLxcDz30kGbOnKnt27f/YjUcOXJE48aNU1BQkDw9PRUfH6/Dhw//Yv0DAICLu6LQvm7dOk2dOlW5ubn69ttvL3puQ0ODamtrr6i460lxcbGio6PVvXt3+fv7272WgIAA3XHHHbrhhhvk5GTfx/Fv375d9913n+69917t2rVLe/bs0eLFi1VTU9PqfdXV1am+vv6C/XfeeecF4TwnJ0chISGN9p8+fVqffPKJfve7311R/2fOnLnsa0pLS1VTU6OhQ4cqICBAbm5u8vDwkK+v7xXVcCV2796t0NBQvfXWW8rPz9eJEyc0adKkX6x/AABwcZcd2quqqrRp0yY98sgjGjp0qMxmc6PjFotFJpNJ7777rqKjo+Xs7KyPP/5Y9fX1WrJkibp27SpXV1f17NlTmzdvbrafhQsXNjlD3KtXL82dO1eSVF9fr4ULFyo4OFjOzs7q1auX3nvvvQtqqaystO3bu3evTCaTSkpKmu376aefVlRUlNzd3RUSEqJHH31UVVVVzZ7fpUsXvf7661q/fr1MJpMmTJjQonbOzXa///77ioiIkIeHhxITE1VRUdFsX5L00UcfqV+/fnJ2dlZAQIAee+wx2w9GEyZM0NSpU1VaWiqTyaQuXbpccL3FYtGDDz6oY8eOyWQyyWQyacGCBbbjJ0+e1MSJE+Xp6akbb7xRL774YqPry8rKNGrUKPn4+Khjx44aNmzYRcdz69atiouL06xZs3TLLbcoLCxMw4cP11/+8hfbOKSnp2vfvn22es79u2rpGP7jH//Qb37zGzk7O6u0tPSCGgYOHKj8/HzbOB0/flyfffaZ0tLSGoX2nTt3qrq6WgMHDtQPP/ygMWPGKCgoSG5uboqKitKrr77aqN0777xTKSkpSk1NVadOnZSQkKCGhgYtWLBAN954o5ydnRUYGKhp06Y1OTZms1lRUVGSpJtuusn2b/NSv3m48847NXXqVKWmpqpDhw7q3Lmz1qxZoxMnTujBBx+Up6enunXrpnfffdd2zY8//qjk5GT5+fnJ1dVV3bt3V1ZWliTp3nvv1ZNPPqnevXurR48euvfee1VWVtZs/wAA4Jd12aH9tddeU3h4uG655Rbdf//9+tvf/qaGhoYLznvssce0dOlSFRUVqUePHlqyZInWr1+vv/71r/r888/1pz/9Sffff78++uijJvuZOHGiioqK9K9//cu277PPPtP+/fv14IMPSpKeffZZZWZmavny5dq/f78SEhL03//93zp48ODlvq1GHBwctHLlSn3++efKzs7WP//5T82ePbvZ8//1r38pMTFRo0aNUkVFhZ599tkWt3Py5EktX75cL730knJzc1VaWqqZM2c221d5ebl+//vfq2/fvtq3b5+ef/55rVu3TosWLbKNybkfZCoqKhqN3zl33HGHVqxYIS8vL1VUVKiioqJRn5mZmbrtttv02Wef6dFHH9UjjzyiAwcOSJJqamqUkJAgT09P5eXlKT8/3/bDRnOzzDfccIM+//xz/fvf/27y+H333acZM2YoMjLSVs999913WWP41FNPae3atfr888+b/E3HwIEDVVVVZRuPvLw8hYWF6d5771VBQYFOnz4t6ezse5cuXdSlSxedPn1a0dHRevvtt/Xvf/9bDz30kB544AHt2rWrUdvZ2dlq37698vPz9de//lWvv/66nnnmGb3wwgs6ePCg3nzzTVswb+q9f/jhh5KkXbt2qaKiQiEhIU2e+3PZ2dnq1KmTdu3apalTp+qRRx7RyJEjdccdd+jTTz9VfHy8HnjgAZ08eVKSNHfuXH3xxRd69913VVRUpOeff16dOnW6oN2ysjI988wzmjhxYrN9V1dXy2q1NnoBAIBr57LXTaxbt07333+/JCkxMVHHjh3TRx99pDvvvLPReQsXLtRdd90l6ew3+IyMDH344Ye6/fbbJZ2dVfz444/1wgsvaMCAARf0ExwcrISEBGVlZalv376SpKysLA0YMEA33XSTJGn58uVKS0vT6NGjJUlPPfWUcnJytGLFCtss7pU4f611ly5dtGjRIj388MNavXp1k+f7+fnJ2dlZrq6uuuGGGy6rnZqaGv31r3/VzTffLElKSUnRwoULm61t9erVCgkJ0XPPPSeTyaTw8HB9++23SktL07x582xrxh0dHRvVcr727dvL29tbJpOpyXN+//vf69FHH5UkpaWl6ZlnnlFOTo5uueUWbdq0SfX19Vq7dq1MJpOks58XHx8fWSwWxcfHX9De1KlTlZeXp6ioKIWGhio2Nlbx8fFKTk62jZuHh4ecnJwuqKelY7h69Wr17Nmz2XHr3r27goKCZLFYdPvtt8tisWjAgAG64YYbdOONN2rnzp0aOHCgLBaLBg4cKEkKCgpq9MPM1KlT9f777+u1115Tv379GrX95z//2bb99ttv64YbbtDgwYPVrl073XjjjY3OP5+rq6ttGYyfn1+zn7Om9OzZU0888YQkac6cOVq6dKk6deqkyZMnS5LmzZun559/Xvv371dsbKxKS0vVu3dv3Xbbbbbx/LlvvvlG//Vf/6Xhw4fr//2//9ds30uWLFF6enqLawUAAFfnsmbaDxw4oF27dmnMmDGSJCcnJ913331at27dBeeeCwaSdOjQIZ08eVJ33XWXPDw8bK/169eruLi42f4mT56sV199VadPn9aZM2f0yiuv2Gb/rFarvv32W8XFxTW6Ji4uTkVFRZfzti7w4YcfatCgQbab8h544AH98MMPthnL1mzHzc3NFtilszdMfv/99822WVRUpNtvv90WmKWz77mqqkrffPPNZdXXnB49etg+Phfsz9W0b98+HTp0SJ6enrbPY8eOHXX69OlmP5fu7u56++23dejQIT3xxBPy8PDQjBkz1K9fv0uOaUvGsH379o1qbs7569otFovtB80BAwbIYrHo1KlTKigosIX2uro6Pfnkk4qKilLHjh3l4eGh999//4LlN9HR0Y22R44cqVOnTummm27S5MmT9cYbb1yT+zrOf8+Ojo7y9fVtNKPfuXNnSbJ97h555BFt3LhRvXr10uzZs7Vjx44L2lyyZImCgoK0cuXKi/Y9Z84cHTt2zPZiKQ0AANfWZYX2devWqba2VoGBgXJycpKTk5Oef/55vf766zp27Fijc93d3W0fn1uD/Pbbb2vv3r221xdffHHRde333HOPnJ2d9cYbb2jr1q2qqanRiBEjWv7mHM6+vfOX71zq5seSkhLdfffd6tGjh15//XXt2bPHNmt/OTcZtrSddu3aNbrOZDI1udzol9RUTedu7qyqqlJ0dHSjz+O5J+aMHTv2ou3efPPN+sMf/qC1a9fq008/1RdffKFNmzY1e35Lx9DV1bXRDzHNObeu/YcfftBnn31m+w3PgAEDlJOTox07dujMmTO2m1CXLVumZ599VmlpacrJydHevXuVkJBwwb+D8/+tS1JISIgOHDig1atXy9XVVY8++qh++9vftvqNt019ns7fd25Mzn3uhgwZoiNHjuhPf/qTvv32Ww0aNOiCpVjffvutwsLCLjmezs7O8vLyavQCAADXTouXx9TW1mr9+vXKzMy8YAnE8OHD9eqrr+rhhx9u8trzbxBsailMs8U5OWn8+PHKyspS+/btNXr0aLm6ukqSvLy8FBgYqPz8/EZt5ufn25Yi+Pn5SZIqKirUoUMHSbrkM8v37Nmj+vp6ZWZm2kL/a6+91uKaW7udn4uIiNDrr7+uhoYGW7DKz8+Xp6engoODW9xO+/btVVdXd9n99+nTR5s2bZK/v/9VBbUuXbrIzc1NJ06caLae1h7DgQMH6sSJE3r66acbPeXnt7/9rSZNmqR3333XtoxGOjuuw4YNsy0Hq6+v11dffaXf/OY3l+zL1dVV99xzj+655x5NmTJF4eHhKiwsVJ8+fa64/tbg5+en8ePHa/z48erfv79mzZql5cuX244vX75cjo6OdqwQAAA0pcWh/a233tKPP/6oSZMmydvbu9Gxe++9V+vWrWs2tHt6emrmzJn605/+pPr6ev3Xf/2Xjh07pvz8fHl5eWn8+PHN9vuHP/xBERERks6GqPPNmjVL8+fP180336xevXopKytLe/fu1YYNGyRJ3bp1U0hIiBYsWKDFixfrq6++UmZm5kXfZ7du3VRTU6NVq1bpnnvusd1ceLlaq52fe/TRR7VixQpNnTpVKSkpOnDggObPn6/p06fbgm1LdOnSRVVVVdq+fbt69uwpNzc3ubm5XfK65ORkLVu2TMOGDbPd8HrkyBFt2bJFs2fPbvIHhwULFujkyZP6/e9/r9DQUFVWVmrlypWqqamx3ffQpUsXff3119q7d6+Cg4NtTz9pzTG86aabdOONN2rVqlVKTk627Q8JCVFgYKBefPFF29Iv6exa9c2bN2vHjh3q0KGDnn76af3nP/+5ZGg3m82qq6tTTEyM3Nzc9PLLL8vV1VWhoaFXXHtrmDdvnqKjoxUZGanq6mq99dZbtv9b56SnpysoKEhLliyxU5UAAKApLU5569at0+DBgy8I7NLZ0L57927t37+/2euffPJJzZ07V0uWLFFERIQSExP19ttvq2vXrhftt3v37rrjjjsUHh6umJiYRsemTZum6dOna8aMGYqKitJ7772nf/zjH+revbuks8sHXn31VX355Zfq0aOHnnrqKdtTVprTs2dPPf3003rqqad06623asOGDVcUYFqrnZ8LCgrSO++8o127dqlnz556+OGHNWnSJNsNiS11xx136OGHH9Z9990nPz+/RjdSXoybm5tyc3N14403KikpSREREZo0aZJOnz7d7Mz7gAEDdPjwYY0bN07h4eEaMmSIvvvuO23btk233HKLpLP/hhITEzVw4ED5+fnp1VdfvSZjOHDgQB0/fvyCG6cHDBig48eP29azS9ITTzyhPn36KCEhQXfeeaduuOGGFv1VUh8fH61Zs0ZxcXHq0aOHPvzwQ23duvUXfe56U9q3b685c+aoR48e+u1vfytHR0dt3Lix0TmlpaWXfOQoAAD45Zka7L2A+hIaGhrUvXt3Pfroo5o+fbq9ywHQBKvVKm9vb4WkviYH50v/xgYAgOtNydKh16Tdc99Djx07dtGlx/b9U5mXcPToUW3cuFHfffed7dnsAAAAQFtj6NDu7++vTp066cUXX7TdSAoAAAC0NYYO7QZfuQMAAAD8Igwd2gFcX/6dnsAz2wEAuAYu648rAQAAAPjlEdoBAAAAgyO0AwAAAAZHaAcAAAAMjtAOAAAAGByhHQAAADA4QjsAAABgcIR2AAAAwOAI7QAAAIDB8RdRAVy1hoYGSZLVarVzJQAAXF/Ofe889720OYR2AFfthx9+kCSFhITYuRIAAK5Px48fl7e3d7PHCe0ArlrHjh0lSaWlpRf9gtMWWK1WhYSEqKysTF5eXvYux64Yi58wFj9hLH7CWPykLY9FQ0ODjh8/rsDAwIueR2gHcNUcHM7eHuPt7d3mvtg2x8vLi7H4P4zFTxiLnzAWP2EsftJWx6IlE17ciAoAAAAYHKEdAAAAMDjHBQsWLLB3EQCuf46Ojrrzzjvl5MSqO8biJ4zFTxiLnzAWP2EsfsJYXJyp4VLPlwEAAABgVyyPAQAAAAyO0A4AAAAYHKEdAAAAMDhCOwAAAGBwhHYAAADA4AjtAFrkL3/5i7p06SIXFxfFxMRo165dFz3/73//u8LDw+Xi4qKoqCi98847v1Cl197ljMXnn3+ue++9V126dJHJZNKKFSt+wUqvvcsZizVr1qh///7q0KGDOnTooMGDB1/y39H15HLGYsuWLbrtttvk4+Mjd3d39erVSy+99NIvWO21dblfL87ZuHGjTCaThg8ffo0r/OVczliYzWaZTKZGLxcXl1+w2mvrcv9dVFZW/v927i80qT6MA/jzTj3uItuK4Z/FEmysRhGNjQ2NWsEi2KjdRQRjQVQXdhExKGghtbXJMgpGRFlbQZDECIqK9UfaxdYiWAqiYmlGLFLoJjYCTX3eq1fa26r3mOfofL8fOBf+9jvwPV/EPYoeslqtZDAYSK1WU11dXUn9LxGNAQB+w+VysSAIPDIywn6/nw8ePMiVlZUcj8cX3T81NcUKhYKHhoY4EAhwb28vq1Qq9vl8MifPP7FdvHr1int6evj27dus1+v5woULMieWjtgu9u3bx5cuXWKPx8PBYJD379/PFRUVPDs7K3Py/BPbxfPnz/nu3bscCAQ4HA7zxYsXWaFQ8Pj4uMzJ809sF/+IRqO8atUq3rJlC3d2dsqUVlpiuxgdHeXly5fzp0+fskcsFpM5tTTEdpFIJLipqYnb29t5cnKSo9EoT0xMsNfrlTl58cDQDgC/1dzczFarNfs4nU5zdXU1Dw4OLrp/z5493NHRsWCtpaWFDx8+LGlOOYjt4ntGo7GkhvY/6YKZOZVKsUaj4Zs3b0oVUTZ/2gUzc0NDA/f29koRT1a5dJFKpdhisfC1a9e4u7u7ZIZ2sV2Mjo5yRUWFXPFkJbaLy5cvs8lk4mQyKVfEooevxwDALyWTSZqZmaG2trbsWllZGbW1tdH09PSi50xPTy/YT0S0c+fOn+5fKnLpolTlo4uvX7/St2/faOXKlVLFlMWfdsHM5Ha7KRQK0datW6WMKrlcuzhz5gxptVo6cOCAHDFlkWsX8/PzZDQaqaamhjo7O8nv98sRV1K5dHH//n0ym81ktVpJp9PRhg0baGBggNLptFyxiw6GdgD4pc+fP1M6nSadTrdgXafTUSwWW/ScWCwmav9SkUsXpSofXRw/fpyqq6t/eIO31OTaxZcvX2jZsmUkCAJ1dHTQ8PAw7dixQ+q4ksqli8nJSbp+/To5nU45Isomly7Wrl1LIyMjdO/ePbp16xZlMhmyWCw0OzsrR2TJ5NLFu3fvaGxsjNLpND169IhOnTpF58+fp/7+fjkiFyVloQMAAMD/j91uJ5fLRRMTEyX1QzsxNBoNeb1emp+fJ7fbTceOHSOTyUTbtm0rdDTZzM3NUVdXFzmdTqqqqip0nIIzm81kNpuzjy0WpJ/hegAAA1FJREFUC9XX19OVK1eor6+vgMnkl8lkSKvV0tWrV0mhUFBjYyN9/PiRzp07RzabrdDxCgJDOwD8UlVVFSkUCorH4wvW4/E46fX6Rc/R6/Wi9i8VuXRRqv6kC4fDQXa7nZ49e0YbN26UMqYscu2irKyMamtriYho06ZNFAwGaXBwcEkP7WK7iEQi9P79e9q1a1d2LZPJEBGRUqmkUChEa9askTa0RPLxeqFSqaihoYHC4bAUEWWTSxcGg4FUKhUpFIrsWn19PcViMUomkyQIgqSZixG+HgMAvyQIAjU2NpLb7c6uZTIZcrvdCz4R+p7ZbF6wn4jo6dOnP92/VOTSRanKtYuhoSHq6+uj8fFxampqkiOq5PL1vMhkMpRIJKSIKBuxXaxbt458Ph95vd7ssXv3btq+fTt5vV6qqamRM35e5eN5kU6nyefzkcFgkCqmLHLpYvPmzRQOh7Nv4oiI3rx5QwaD4X85sBMRbvkIAL/ncrlYrVbzjRs3OBAI8KFDh7iysjJ7K7Kuri4+ceJEdv/U1BQrlUp2OBwcDAbZZrOV1C0fxXSRSCTY4/Gwx+Nhg8HAPT097PF4+O3bt4W6hLwR24XdbmdBEHhsbGzBLe3m5uYKdQl5I7aLgYEBfvLkCUciEQ4EAuxwOFipVLLT6SzUJeSN2C7+rZTuHiO2i9OnT/Pjx485EonwzMwM7927l8vLy9nv9xfqEvJGbBcfPnxgjUbDR44c4VAoxA8ePGCtVsv9/f2FuoSCw9AOAP/J8PAwr169mgVB4ObmZn758mX2b62trdzd3b1g/507d7iuro4FQeD169fzw4cPZU4sHTFdRKNRJqIfjtbWVvmDS0BMF0ajcdEubDab/MElIKaLkydPcm1tLZeXl/OKFSvYbDazy+UqQGppiH29+F4pDe3M4ro4evRodq9Op+P29nZ+/fp1AVJLQ+zz4sWLF9zS0sJqtZpNJhOfPXuWU6mUzKmLx1/MzIX6lB8AAAAAAH4P32kHAAAAAChyGNoBAAAAAIochnYAAAAAgCKHoR0AAAAAoMhhaAcAAAAAKHIY2gEAAAAAihyGdgAAAACAIoehHQAAAACgyGFoBwAAAAAochjaAQAAAACKHIZ2AAAAAIAi9zfQKu8wWOvSIAAAAABJRU5ErkJggg==\n", 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" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "# bar chart for fan & episodes seen in % of total respondents\n", "import matplotlib.pyplot as plt\n", "%matplotlib inline\n", "means[0:7].plot.barh()\n", "plt.show()" ] }, { "cell_type": "code", "execution_count": 14, "metadata": {}, "outputs": [ { "data": { "image/png": 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\n", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "# bar chart for rankings\n", "means[7:14].plot.barh()\n", "plt.show()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "# Impressions\n", "* It seems unusual that more of the respondents haven't seen some of these movies, especially Episode I and Episodes IV-VI. I would think that if 66% had seen at least one movie that there would be at least one higher...\n", "\n", "* Episode V is the favorite, but not by much. It's interesting that the first three even pulled as much as they did." ] }, { "cell_type": "code", "execution_count": 15, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "Have you seen any of the 6 films in the Star Wars franchise? 936.0\n", "Are you a fan of the Star Wars films? 552.0\n", "seen_ep_1 673.0\n", "seen_ep_2 571.0\n", "seen_ep_3 550.0\n", "seen_ep_4 607.0\n", "dtype: float64" ] }, "metadata": {}, "output_type": "display_data" }, { "data": { "text/plain": [ "(1186, 38)" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "sums = star_wars.iloc[:,1:7].sum()\n", "sums = sums.rename({\"Do you consider yourself to be a fan of the Star Wars film franchise?\":\"Are you a fan of the Star Wars films?\"})\n", "display(sums)\n", "display(star_wars.shape)" ] } ], "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": "3.8.2" } }, "nbformat": 4, "nbformat_minor": 1 }