classification.ipynb

{
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   "id": "initial_id",
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    "ExecuteTime": {
     "end_time": "2024-01-02T08:00:46.414805400Z",
     "start_time": "2024-01-02T08:00:42.928752700Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": "                                        major   grade  \\\nsample0                               English   third   \nsample1                     Political Science   first   \nsample2                     Political Science  second   \nsample3                               English   third   \nsample4                             Sociology   first   \n...                                       ...     ...   \nsample995                           Economics   third   \nsample996                          Psychology  second   \nsample997                             Biology  fourth   \nsample998  Pre-Medical or Pre-Health Sciences   first   \nsample999                             History  fourth   \n\n                                                     answer1  \\\nsample0    \"Liberal arts is an education in the fundament...   \nsample1    \"(Eric thinks for a moment) To me, liberal art...   \nsample2    \"Liberal arts is the education system that foc...   \nsample3    \"Liberal arts is a field of study that involve...   \nsample4    \"Well, I guess liberal arts is more like a lea...   \n...                                                      ...   \nsample995  \"I think liberal arts is a very broad educatio...   \nsample996  \"To be honest, I was also confused about the d...   \nsample997  \"I think liberal arts is a way of learning tha...   \nsample998  \"Liberal arts is the idea of learning the art ...   \nsample999  \"Well, in my opinion, liberal arts is a kind o...   \n\n                                                     answer2  \nsample0    \"\\\"I've found that studying liberal arts has g...  \nsample1    \"\\\"(Eric smiles) I've found that the liberal a...  \nsample2    \"I have always enjoyed reading and analyzing d...  \nsample3    \"\\\"I have found liberal arts education to be e...  \nsample4    \"\\\"Hmm, I'd say my experience of liberal arts ...  \n...                                                      ...  \nsample995  \"\\\"I've found that the liberal arts education ...  \nsample996  \"\\\"I've been able to take classes in a wide ra...  \nsample997  \"\\\"My experience of liberal arts education has...  \nsample998  \"\\\"I've found that liberal arts education enco...  \nsample999  \"\\\"Well, for me, liberal arts education is not...  \n\n[1000 rows x 4 columns]",
      "text/html": "<div>\n<style scoped>\n    .dataframe tbody tr th:only-of-type {\n        vertical-align: middle;\n    }\n\n    .dataframe tbody tr th {\n        vertical-align: top;\n    }\n\n    .dataframe thead th {\n        text-align: right;\n    }\n</style>\n<table border=\"1\" class=\"dataframe\">\n  <thead>\n    <tr style=\"text-align: right;\">\n      <th></th>\n      <th>major</th>\n      <th>grade</th>\n      <th>answer1</th>\n      <th>answer2</th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th>sample0</th>\n      <td>English</td>\n      <td>third</td>\n      <td>\"Liberal arts is an education in the fundament...</td>\n      <td>\"\\\"I've found that studying liberal arts has g...</td>\n    </tr>\n    <tr>\n      <th>sample1</th>\n      <td>Political Science</td>\n      <td>first</td>\n      <td>\"(Eric thinks for a moment) To me, liberal art...</td>\n      <td>\"\\\"(Eric smiles) I've found that the liberal a...</td>\n    </tr>\n    <tr>\n      <th>sample2</th>\n      <td>Political Science</td>\n      <td>second</td>\n      <td>\"Liberal arts is the education system that foc...</td>\n      <td>\"I have always enjoyed reading and analyzing d...</td>\n    </tr>\n    <tr>\n      <th>sample3</th>\n      <td>English</td>\n      <td>third</td>\n      <td>\"Liberal arts is a field of study that involve...</td>\n      <td>\"\\\"I have found liberal arts education to be e...</td>\n    </tr>\n    <tr>\n      <th>sample4</th>\n      <td>Sociology</td>\n      <td>first</td>\n      <td>\"Well, I guess liberal arts is more like a lea...</td>\n      <td>\"\\\"Hmm, I'd say my experience of liberal arts ...</td>\n    </tr>\n    <tr>\n      <th>...</th>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n    </tr>\n    <tr>\n      <th>sample995</th>\n      <td>Economics</td>\n      <td>third</td>\n      <td>\"I think liberal arts is a very broad educatio...</td>\n      <td>\"\\\"I've found that the liberal arts education ...</td>\n    </tr>\n    <tr>\n      <th>sample996</th>\n      <td>Psychology</td>\n      <td>second</td>\n      <td>\"To be honest, I was also confused about the d...</td>\n      <td>\"\\\"I've been able to take classes in a wide ra...</td>\n    </tr>\n    <tr>\n      <th>sample997</th>\n      <td>Biology</td>\n      <td>fourth</td>\n      <td>\"I think liberal arts is a way of learning tha...</td>\n      <td>\"\\\"My experience of liberal arts education has...</td>\n    </tr>\n    <tr>\n      <th>sample998</th>\n      <td>Pre-Medical or Pre-Health Sciences</td>\n      <td>first</td>\n      <td>\"Liberal arts is the idea of learning the art ...</td>\n      <td>\"\\\"I've found that liberal arts education enco...</td>\n    </tr>\n    <tr>\n      <th>sample999</th>\n      <td>History</td>\n      <td>fourth</td>\n      <td>\"Well, in my opinion, liberal arts is a kind o...</td>\n      <td>\"\\\"Well, for me, liberal arts education is not...</td>\n    </tr>\n  </tbody>\n</table>\n<p>1000 rows × 4 columns</p>\n</div>"
     },
     "execution_count": 1,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import json\n",
    "with open('samples.json', 'r') as json_file:\n",
    "    data = json.load(json_file)\n",
    "\n",
    "import pandas as pd\n",
    "from harvesttext import HarvestText\n",
    "\n",
    "ht = HarvestText()\n",
    "df = pd.DataFrame(data).T\n",
    "df"
   ]
  },
  {
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   "id": "7fffce36b680c6e1",
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     "end_time": "2024-01-02T08:00:46.443240700Z",
     "start_time": "2024-01-02T08:00:46.420838300Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": "                                        major   grade  \\\nsample0                               English   third   \nsample1                     Political Science   first   \nsample2                     Political Science  second   \nsample3                               English   third   \nsample4                             Sociology   first   \n...                                       ...     ...   \nsample995                           Economics   third   \nsample996                          Psychology  second   \nsample997                             Biology  fourth   \nsample998  Pre-Medical or Pre-Health Sciences   first   \nsample999                             History  fourth   \n\n                                                     answer1  \\\nsample0    \"Liberal arts is an education in the fundament...   \nsample1    \"(Eric thinks for a moment) To me, liberal art...   \nsample2    \"Liberal arts is the education system that foc...   \nsample3    \"Liberal arts is a field of study that involve...   \nsample4    \"Well, I guess liberal arts is more like a lea...   \n...                                                      ...   \nsample995  \"I think liberal arts is a very broad educatio...   \nsample996  \"To be honest, I was also confused about the d...   \nsample997  \"I think liberal arts is a way of learning tha...   \nsample998  \"Liberal arts is the idea of learning the art ...   \nsample999  \"Well, in my opinion, liberal arts is a kind o...   \n\n                                                     answer2  \\\nsample0    \"\\\"I've found that studying liberal arts has g...   \nsample1    \"\\\"(Eric smiles) I've found that the liberal a...   \nsample2    \"I have always enjoyed reading and analyzing d...   \nsample3    \"\\\"I have found liberal arts education to be e...   \nsample4    \"\\\"Hmm, I'd say my experience of liberal arts ...   \n...                                                      ...   \nsample995  \"\\\"I've found that the liberal arts education ...   \nsample996  \"\\\"I've been able to take classes in a wide ra...   \nsample997  \"\\\"My experience of liberal arts education has...   \nsample998  \"\\\"I've found that liberal arts education enco...   \nsample999  \"\\\"Well, for me, liberal arts education is not...   \n\n           critical_thinking  creativity  all-rounded  \\\nsample0                 True       False        False   \nsample1                False       False        False   \nsample2                 True        True        False   \nsample3                 True       False         True   \nsample4                False       False        False   \n...                      ...         ...          ...   \nsample995               True        True         True   \nsample996              False       False        False   \nsample997               True        True        False   \nsample998              False       False         True   \nsample999              False       False        False   \n\n           wide_range_of_knowledge  communication  \nsample0                      False           True  \nsample1                      False          False  \nsample2                      False           True  \nsample3                      False           True  \nsample4                      False          False  \n...                            ...            ...  \nsample995                    False          False  \nsample996                    False          False  \nsample997                    False           True  \nsample998                    False          False  \nsample999                    False          False  \n\n[1000 rows x 9 columns]",
      "text/html": "<div>\n<style scoped>\n    .dataframe tbody tr th:only-of-type {\n        vertical-align: middle;\n    }\n\n    .dataframe tbody tr th {\n        vertical-align: top;\n    }\n\n    .dataframe thead th {\n        text-align: right;\n    }\n</style>\n<table border=\"1\" class=\"dataframe\">\n  <thead>\n    <tr style=\"text-align: right;\">\n      <th></th>\n      <th>major</th>\n      <th>grade</th>\n      <th>answer1</th>\n      <th>answer2</th>\n      <th>critical_thinking</th>\n      <th>creativity</th>\n      <th>all-rounded</th>\n      <th>wide_range_of_knowledge</th>\n      <th>communication</th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th>sample0</th>\n      <td>English</td>\n      <td>third</td>\n      <td>\"Liberal arts is an education in the fundament...</td>\n      <td>\"\\\"I've found that studying liberal arts has g...</td>\n      <td>True</td>\n      <td>False</td>\n      <td>False</td>\n      <td>False</td>\n      <td>True</td>\n    </tr>\n    <tr>\n      <th>sample1</th>\n      <td>Political Science</td>\n      <td>first</td>\n      <td>\"(Eric thinks for a moment) To me, liberal art...</td>\n      <td>\"\\\"(Eric smiles) I've found that the liberal a...</td>\n      <td>False</td>\n      <td>False</td>\n      <td>False</td>\n      <td>False</td>\n      <td>False</td>\n    </tr>\n    <tr>\n      <th>sample2</th>\n      <td>Political Science</td>\n      <td>second</td>\n      <td>\"Liberal arts is the education system that foc...</td>\n      <td>\"I have always enjoyed reading and analyzing d...</td>\n      <td>True</td>\n      <td>True</td>\n      <td>False</td>\n      <td>False</td>\n      <td>True</td>\n    </tr>\n    <tr>\n      <th>sample3</th>\n      <td>English</td>\n      <td>third</td>\n      <td>\"Liberal arts is a field of study that involve...</td>\n      <td>\"\\\"I have found liberal arts education to be e...</td>\n      <td>True</td>\n      <td>False</td>\n      <td>True</td>\n      <td>False</td>\n      <td>True</td>\n    </tr>\n    <tr>\n      <th>sample4</th>\n      <td>Sociology</td>\n      <td>first</td>\n      <td>\"Well, I guess liberal arts is more like a lea...</td>\n      <td>\"\\\"Hmm, I'd say my experience of liberal arts ...</td>\n      <td>False</td>\n      <td>False</td>\n      <td>False</td>\n      <td>False</td>\n      <td>False</td>\n    </tr>\n    <tr>\n      <th>...</th>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n    </tr>\n    <tr>\n      <th>sample995</th>\n      <td>Economics</td>\n      <td>third</td>\n      <td>\"I think liberal arts is a very broad educatio...</td>\n      <td>\"\\\"I've found that the liberal arts education ...</td>\n      <td>True</td>\n      <td>True</td>\n      <td>True</td>\n      <td>False</td>\n      <td>False</td>\n    </tr>\n    <tr>\n      <th>sample996</th>\n      <td>Psychology</td>\n      <td>second</td>\n      <td>\"To be honest, I was also confused about the d...</td>\n      <td>\"\\\"I've been able to take classes in a wide ra...</td>\n      <td>False</td>\n      <td>False</td>\n      <td>False</td>\n      <td>False</td>\n      <td>False</td>\n    </tr>\n    <tr>\n      <th>sample997</th>\n      <td>Biology</td>\n      <td>fourth</td>\n      <td>\"I think liberal arts is a way of learning tha...</td>\n      <td>\"\\\"My experience of liberal arts education has...</td>\n      <td>True</td>\n      <td>True</td>\n      <td>False</td>\n      <td>False</td>\n      <td>True</td>\n    </tr>\n    <tr>\n      <th>sample998</th>\n      <td>Pre-Medical or Pre-Health Sciences</td>\n      <td>first</td>\n      <td>\"Liberal arts is the idea of learning the art ...</td>\n      <td>\"\\\"I've found that liberal arts education enco...</td>\n      <td>False</td>\n      <td>False</td>\n      <td>True</td>\n      <td>False</td>\n      <td>False</td>\n    </tr>\n    <tr>\n      <th>sample999</th>\n      <td>History</td>\n      <td>fourth</td>\n      <td>\"Well, in my opinion, liberal arts is a kind o...</td>\n      <td>\"\\\"Well, for me, liberal arts education is not...</td>\n      <td>False</td>\n      <td>False</td>\n      <td>False</td>\n      <td>False</td>\n      <td>False</td>\n    </tr>\n  </tbody>\n</table>\n<p>1000 rows × 9 columns</p>\n</div>"
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df['critical_thinking'] = [True if 'criti' in i else False for i in df['answer1']]\n",
    "df['creativity'] = [True if 'crea' in i or 'inno' in i else False for i in df['answer1']]\n",
    "df['all-rounded'] = [True if 'round' in i or 'overall' in i  else False for i in df['answer1']]\n",
    "df['wide_range_of_knowledge'] = [True if ('wide' in i or 'variety' in i) and 'subject' in i else False for i in df['answer1']]\n",
    "df['communication'] = [True if 'commun' in i else False for i in df['answer1']]\n",
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "5866e28695cdd21d",
   "metadata": {
    "collapsed": false,
    "ExecuteTime": {
     "end_time": "2024-01-02T08:00:47.055369900Z",
     "start_time": "2024-01-02T08:00:46.439250500Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": "([0, 1, 2, 3, 4],\n [Text(0, 0, 'critical_thinking'),\n  Text(1, 0, 'creativity'),\n  Text(2, 0, 'all-rounded'),\n  Text(3, 0, 'wide_range_of_knowledge'),\n  Text(4, 0, 'communication')])"
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "text/plain": "<Figure size 640x480 with 1 Axes>",
      "image/png": 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"
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "from matplotlib import pyplot as plt\n",
    "\n",
    "\n",
    "plt.bar(df.columns[4:], [len(df[df[i]]) for i in df.columns[4:]])\n",
    "plt.xticks(rotation=15)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "6e759471ddb9dd1a",
   "metadata": {
    "collapsed": false,
    "ExecuteTime": {
     "end_time": "2024-01-02T08:00:47.236087100Z",
     "start_time": "2024-01-02T08:00:47.056377600Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": "<Figure size 640x480 with 1 Axes>",
      "image/png": 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"
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "for j in df.columns[4:]:\n",
    "    plt.plot([1, 2, 3, 4], [len(df[(df[j]) & (df['grade'] == 'first')]) for i in ['first', 'second', 'third', 'fourth']])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "178466ab207bae69",
   "metadata": {
    "collapsed": false,
    "ExecuteTime": {
     "end_time": "2024-01-02T08:00:47.249140100Z",
     "start_time": "2024-01-02T08:00:47.233492600Z"
    }
   },
   "outputs": [],
   "source": [
    "science_majors = [\n",
    "    \"Nursing\",\n",
    "    \"Biology\",\n",
    "    \"Computer Science\",\n",
    "    \"Environmental Science/Studies\",\n",
    "    \"Engineering\",\n",
    "    \"Pre-Medical or Pre-Health Sciences\",\n",
    "    \"Mathematics\",\n",
    "    \"Chemistry\"\n",
    "]\n",
    "\n",
    "non_science_majors = [\n",
    "    \"Business Administration\",\n",
    "    \"Psychology\",\n",
    "    \"Political Science\",\n",
    "    \"English\",\n",
    "    \"Economics\",\n",
    "    \"Communications\",\n",
    "    \"Education\",\n",
    "    \"Sociology\",\n",
    "    \"History\",\n",
    "    \"Art and Design\",\n",
    "    \"Social Work\",\n",
    "    \"Anthropology\"\n",
    "]\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "outputs": [
    {
     "data": {
      "text/plain": "([<matplotlib.patches.Wedge at 0x29e580483d0>,\n  <matplotlib.patches.Wedge at 0x29e580499d0>],\n [Text(0.2769047043327299, 1.0645768101543465, 'science major'),\n  Text(-0.27690480400560347, -1.0645767842286524, 'non-science major')])"
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "text/plain": "<Figure size 640x480 with 1 Axes>",
      "image/png": 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"
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.pie([len(df[df['major'].isin(science_majors)])/1000,\n",
    "         len(df[df['major'].isin(non_science_majors)])/1000,\n",
    "        ], labels=['science major', 'non-science major'])"
   ],
   "metadata": {
    "collapsed": false,
    "ExecuteTime": {
     "end_time": "2024-01-02T08:00:47.312063400Z",
     "start_time": "2024-01-02T08:00:47.245619100Z"
    }
   },
   "id": "5df8578a6212318e"
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "d2f020d6fd6ecf63",
   "metadata": {
    "collapsed": false,
    "ExecuteTime": {
     "end_time": "2024-01-02T08:00:47.393913400Z",
     "start_time": "2024-01-02T08:00:47.315572900Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": "([<matplotlib.patches.Wedge at 0x29e58000e90>,\n  <matplotlib.patches.Wedge at 0x29e58002490>],\n [Text(-0.04588166056977235, 1.0990427076430471, 'science major'),\n  Text(0.04588186636938024, -1.0990426990515256, 'non-science major')])"
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "text/plain": "<Figure size 640x480 with 1 Axes>",
      "image/png": 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"
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.pie([len(df[(df['critical_thinking']) & (df['major'].isin(science_majors))])/len(df[df['major'].isin(science_majors)]),\n",
    "        len(df[(df['critical_thinking']) & (df['major'].isin(non_science_majors))])/len(df[df['major'].isin(non_science_majors)]),\n",
    "        ], labels=['science major', 'non-science major'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "8421464c62d8ba58",
   "metadata": {
    "collapsed": false,
    "ExecuteTime": {
     "end_time": "2024-01-02T08:00:47.528527600Z",
     "start_time": "2024-01-02T08:00:47.389916600Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": "([<matplotlib.patches.Wedge at 0x29e580ab850>,\n  <matplotlib.patches.Wedge at 0x29e580b8610>],\n [Text(0.10693173772648551, 1.094790209796742, 'science major'),\n  Text(-0.10693184022814188, -1.0947901997850653, 'non-science major')])"
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "text/plain": "<Figure size 640x480 with 1 Axes>",
      "image/png": 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8V8fx+SEWAlFbuDra4aMZN2FYLz/ZUTSPx311gje3pLMQiNqhqt6ERz9LxI+ni2VH0TyWQgf7eO9pvL87W3YMItWrbTDj0ZVJOM6LTHUolkIHWpuUh9c2pcmOQaQZlXWNeGj5IWQV8Oz/jsJS6CBbUy/i+a+Oy45BpDklVfV48N+HkFdSLTuKJrEUOsCB7CI8+fkRnodA1EEultdixicHUVBRKzuK5rAUrOxYfhke++ww6ht5pjJRR8otrsbDyxNRVccLUVkTS8GKsgsrMWt5Iir5n5SoU6SeL8ec1cloNPFDmLWwFKzkfFkNZvz7IEqq6mVHIdKVPRmFePHrE7JjaAZLwQpKquox45ODOP8T5zeJZPgiKQ9Ld2TKjqEJLIV2MpsFnvw8GdmFVbKjEOna29szsO5wvuwYqsdSaKe3t2cgIYtnWRLZgue/OoaUvDLZMVSNpdAOu9IL8N7uLNkxiOhnDSaBuf9Nxk81vHBVW7EU2ii/tBp/XpsCLidIZFvyS2vw7JdHZcdQLZZCG9Q3mjFndTIvo0lko7advIRP9ufIjqFKLIU2eHVjKo5xUS4im/bG5jTuX2gDlsIN+ubIOfznRy6DTWTrlP0LHNHfEJbCDci8VIEXvuYid0RqkV9ag7+s4/6FG8FSaKWqukb88T+HUV1vkh2FiG7A9pOX8O99p2XHUA2WQis9t/4YT1AjUqnFW9Jx5Gyp7BiqwFJohVU/5GLjsQuyYxBRG1n2Lxzh/oVWYClcx7myGry+OV12DCJqp3NlNXiG5y9cF0vhOhZ8c4L7EYg04vu0S1wf6TpYCtew8dh57EgvkB2DiKzo9U1pKKvmEvctYSm04KeaBrzy3UnZMYjIyoqr6rF4C6eEW8JSaMEbm9NRWFEnOwYRdYA1iXk4fIZHIzWHpdCMxNwSrEnkWctEWiUE8OLXx3kZz2awFK5Q32jGC18d5+qnRBqXfrECyxNyZcewOSyFK3y4JxuZBZWyYxBRJ/jH9xm48FON7Bg2haXwK6cLK/HuLl40h0gvqupNWPhtquwYNoWl8CsvfH0c9Y2cYyTSk62pl7Aj7ZLsGDaDpfCztYl5+PF0iewYRCTBy9+mooYnqQJgKQAAqusbedwykY7ll9Zg6c5M2TFsAksBwIoDuSiu4hmORHr2732nkV3Ig0x0XwoVtQ34116utU6kdw0mgWU7OFrQfSl8uj8XZVxOl4gAfHfsAk7rfLSg61L4qaYBn+znKIGILExmgXd36vuwdF2Xwr/3nUZ5baPsGERkQzYcPY/cIv1eZVG3pVBaVc9T3InoKiaz0PVJrLothY/2nkZlHUcJRHS1b46cw9niatkxpNBlKRRV1uGzH3JlxyAiG9VoFnh3lz6PRNJlKXy4O5uX2CSia/oq+RzySvQ3WtBdKRSU1+I/B8/IjkFENq7RLPCeDvct6K4U3tuVhdoGLnpHRNe3Pjkf+aX6Gi3oqhTKquuxJjFPdgwiUokGk8D7u7Nlx+hUuiqFdYfzUcelsYnoBqxLytfVhXh0VQqfH+J1l4noxtSbzPhCRzMMuimFg6eLkV2o37MUiajtvkzKh9msjwu366YUOEogorY6V1aDhOwi2TE6hS5Koay6HptPXJQdg4hUTC9TSLoohfXJ57iDmYjaZdvJSyir1v7FuHRRCpw6IqL2qm8045sj52TH6HCaL4VDOSXIKtD3RTOIyDq+SMqXHaHDab4UOEogImtJu1CO4/k/yY7RoTRdCj9VN2DT8QuyYxCRhnyRpO0PmpouhfXJPIOZiKzr25TzqG3Q7irLmi6FNYnabnQi6nzltY3YouFD3DVbClkFlci4xB3MRGR9Wj5nQbOlsDP9kuwIRKRRP+YUa3aRPA2XQoHsCESkUUIAu08Vyo7RITRZCuW1DUjKLZUdg4g0bPcpbX7w1GQp7DlViEadrGhIRHIcyCpGg0l7RzdqshR2ceqIiDpYRV0jDp/R3oyE5krBbBbYnaHNuT4isi1a3K+guVI4kleKkirtr2RIRPLt0eAHUM2VAo86IqLOknahHJfKa2XHsCrNlcKONJYCEXWePRqbQtJUKZwvq0H6xQrZMYhIR3ZnaOuDqKZKYQenjoiok+3PLIJJQ4fAa6oUeCgqEXW28tpGJJ/VzqGpmikFIQQSc0pkxyAiHdLS2c2aKYXswkpU1DXKjkFEOpSQVSw7gtVophSOnC2THYGIdCr9Yrlm9itophSO5pfJjkBEOlXbYMbpQm1cv0UzpZCSVyY7AhHp2MkL5bIjWIUmSqG2wYRTPD+BiCQ6eZ6lYDPKLuZiVtAZdO1SJzsKEemUVkYK9rIDWEPQhZ14sfiveBFAY0A4Ct1jkGHsgR9rw7C5KAi5NV1kRyQijUtjKdiQi8eUv9qXn0Vw+VkEAxgB4DkAjf6hKHaPQaZdTxyqC8OW4mBkVDnLSktEGlRUWY+C8loEeKj7Q6hGSuH4Ne+2rziHwIpzCMT3GAbgaQAm3yCUeMYiy64nkurDsbUkECcq3DolLhFpU+qFctWXgkEIoe6Da81m4O/BQGP7l681u/ij1DMW2faRSKoPx/dlwUj+iUVBRK3zbHwUnrgrUnaMdlH/SKE83yqFAADG6kL4Vu+BL/bgZgBzAJi9fVHmGYMch0gkN3TD9rIgHCrztMrzEZG2aGFns/pLoeR0h27eWFMMn5r98MF+DAbwBwBmLy+Ue8Ug16EXjjR0w47yECSUekAIQ4dmISLblqaBw1LVXwrF2Z3+lMbaMnhd/AED8AMGAHgYgPBwR4VXLM44RiKlMQI7fwrG3lIvmIQmjvololbILa5CdX0jXBzV+9aq3uSXdfBIobUMdRXwuHQQcTiIOAAzAAh3V1R6xSDPqRdSTBHYXR6KXSXeaDBzREGkRWYBpF+swKBwb9lR2oyl0IEM9VVwL0hCLJIQC+B+AMLFGdXeUcjvEoVjpm7YU9EVO0q8UWOykx2XiKzgfFkNS0EqCdNH7WForIFrYQqikIIoAPcCEF2cUOMdhXPOvXHc3B37KkOxrdgXVY0sCiK1KaxQ98oK6i4FsxkozZWdot0Mpjq4FB1DLxxDLwBTAAhHB9QG9sYFlyicEBHYV9kVW4r8UNGo7n8yIq1jKchUVQCY1P0P0BKDuQHOxanoUZyKHgDuAfCmoz3qAiJx0SUKJ9ED+6tCsbXYH8X1DrLjEtHPiirV/Z6k7lKo1M4l8FrDYG5El5J0RJSkIwLAeACv2RlRH9wTl1yjkYbuOFAdhs3FASioY1EQycCRgkxV+iqF5hiEGU6lmQgvzUQ4gHgACw0GNAR1R4FrNE4Ze+KH6q7YXByAc7VOsuMSaV4hRwoS6Wyk0FoGCDiWnUbXstPoCmAUgJcANAR0U1aQPVgbhs1FgVxBlsjKOFKQiaVwQxzKzyCk/AxCANyJX1aQLXKPRZZdDxysC8eW4iBkcgVZojYrrqyHEAIGgzrPR1J3KVQVyk6gevYV5xBUcQ5BAIYBeAaAyS8YJR4xyLKLRGJdGLaWBiG1wlVyUiJ1aDQLlFY3wMfVUXaUNlF3KXCk0CHsKi/Av/IC/LETtwGYB8DkG4AyjxhlBdntpUE4Uu4uOyqRTSqsqGMpSMGRQqexqyqAb1XBFSvI+qHMMxo5Dr1wuMGy1PihMg/ZUYmkK6yoQ1SQOj80qbsU6ipkJ9A1Y01RkxVkH8PlFWRjkesQieTGbthRFowDZZ5cQZZ0pbDSOsv5y6DuUmiokZ2ArmBZQfYABuAABgB4BIDw8EC5VwzOOlmWGt/5Uwj2lXpyBVnSLDUfgaTyUqiWnYBawVBXDs9frSA7E7+sIHvWqReOmiKwuzwEu0p8uIIsaUJpdYPsCG2m8lLgSEGtLq8g2wdJ6IOfV5B1dUGVVxTyu/TGMVME9lSEYidXkCUVajSZZUdoM5YC2QxDQzXcCo8gGkcQDWAafr2CbBSOmyOwtzIU24v8UGXi1BPZrkazkB2hzVReCpw+0rpmV5B1ckCtdxTOO/dGKixLjXMFWbIlJpaCBKZGwKzeeTtqO8sKsifQEyfQE01XkL3gEo00RGB/VRg2F/mjtEG9/8VJvThSkMFULzsB2ZDLK8h2L0lHd/y8gqy9EfV+kbjkGoU09MCBnxcG5Aqy1NG4T0EGA+eU6dosK8hmILw04+oVZN1ikI7u+KEmDJuKA3GhVp1nn5JtUvNIwSCEUGd6UwOwyE92CtIAAQMaPcLR6KDOM1DJ9tT3HAPP8Qtlx2gT9Y4UjOqNTrbFAAGH8jPgpBJZi3PXfrIjtJl652AMBk4hEZFtUvF7k3qTA4CBJzURkQ1S6bUUALWXAqeQiMgW2av3ioYsBSIia3Nyk52gzdRdCg7qbWMi0jBHloIcXbxkJyAiupqTei82pfJS8JSdgIjoapw+ksTZS3YCIqKrcfpIEk4fEZEtclLv2fHqLgWOFIjIFrEUJOFIgYhskau/7ARtpu5S4EiBiGyOAXAPlh2izdRdCir+xRORRrn4AvbqXYpd3aXg2VV2AiKipjzU/WFV5aUQJjsBEVFTKp/BUHcpuAdz/SMisi0sBYmMRsA9RHYKIqJfeKj7PUndpQAAXpxCIiIb4hEqO0G7qL8UuLOZiGyJXy/ZCdpF/aXg1U12AiKiX/j1lp2gXdRfCv5RshMQEVm4+AEuPrJTtIv6SyEgVnYCIiILDXxIVX8p+PUCjA6yUxARqX5/AqCFUrBzAHwjZacgIgL8OFKwDQExshMQEal+JzOgmVLgfgUisgFBfWUnaDeNlAJHCkQkmUco4B4kO0W7aaMUgvvLTkBEehc6SHYCq9BGKXiFAW7qb2giUrHQwbITWIU2SgEAut4kOwER6RlLwcawFIhIFoMRCBkoO4VVaKcUwm6RnYCI9MqvN+DkLjuFVWinFEIHA3ZOslMQkR5paKZCO6Vg76SZ4RsRqUz3EbITWI12SgEAut0uOwER6VGPO2UnsBptlULPu2QnICK9CYgF3AJkp7AabZVC+G2Ao5vsFESkJz209WFUW6Vg5wB0v0N2CiLSEw1NHQFaKwUAiBwlOwER6YXRAYgYKjuFVWmwFEbLTkBEehF2M+DoKjuFVWmvFLwjeNEdIuocvcbKTmB12isFAIgcIzsBEelB7D2yE1idNksherzsBESkdYFxgE8P2SmsTpul0G0Y4BYoOwURaVnMRNkJOoQ2S8FoBGInyU5BRFqmwakjQKulAAB9pshOQERa5dtLs5cB1m4phN8KuIfITkFEWqTRqSNAy6VgMAB9JstOQURa1Oe3shN0GO2WAsApJCKyvqA4ILif7BQdRtulEDYE8O4uOwURacnAGbITdChtlwIADJopOwERaYWdExB3r+wUHUr7pTDwQcuiVURE7RU9HnDxkZ2iQ2m/FNwCgKhxslMQkRYMfFB2gg6n/VIAgMGzZCcgIrXzCAV6jJSdosPpoxR6jgS8wmWnICI1G/CAZbUEjdP+KwQs5yxwhzMRtZXRAbjpEdkpOoU+SgEABs4E7BxlpyAiNYqdBHgEy07RKfRTCu6BQNw02SmISI1u+aPsBJ1GP6UAAEPnATDITkFEatJ1iOVEWJ3QVyn4RwG942WnICI1uf1J2Qk6lb5KAQCG/o/sBESkFt7dgWjtrojaHP2VQrfbLcNBIqLruX2uLg5D/TV9vdrLbp8nOwER2TqPrppf/K45+iyF6AmAX2/ZKYjIlg1/GrB3kp2i0+mzFIxG4K4XZKcgIlvlGa7LUQKg11IAgNjJQHB/2SmIyBbd8Qxgr8+TXfVbCgYDMHKB7BREZGu8I4AB2l8NtSX6LQUA6DUa6DZUdgoisiV3PAvY2ctOIY2+SwEARv5NdgIishW+kUC/38tOIRVLodttQK+xslMQkS0Y+5quRwkAS8Fi9ELAYCc7BRHJ1HMkEHW37BTSsRQAILAPMGS27BREJIvRHoh/XXYKm8BSuOyuFwEXP9kpiEiGmx4BAqJlp7AJLIXLnL2AUTxElUh3nL2BO5+XncJmsBR+bdBMIGSQ7BRE1JnufB5w8ZGdwmawFH7NYADGvwVeiIdIJ4LigJu4P/HXWApX6joYGKjfsxmJdMNgB9zzru4PQb0SS6E5Y14F3AJlpyCijnT7XCBkgOwUNoel0BwXH2DCP2SnIKKO4tOTO5dbwFJoSfR4IG6a7BREZHUG4J6lgIOz7CA2iaVwLeMWcxqJSGsGPwREDJOdwmaxFK7FxQeY8I7sFERkLR6hwJhFslPYNJbC9UT/Boi7V3YKImovgxH47UdAFw/ZSWwaS6E1xr1p+YRBROo17Gmg+3DZKWweS6E1XHyAKf+yfNIgIvXpOoRHG7US3+VaK2IYMPwvslMQ0Y1y8gB+92+epNZKLIUbcedfgfDbZacgohsx4R3LdZepVVgKN8JoB0z9lEtsE6lF//uBuKmyU6gKS+FGeQQDv/uY+xeIbF1QHPCbJbJTqA7f2dqi50hgxF9lpyCilrj4Ar//L+DoIjuJ6rAU2mrEfCB2kuwURHQloz0wdTngFS47iSqxFNrKYAAmfwgE9ZOdhIh+bcwioMcI2SlUi6XQHo4uwPTPuT4Ska3oPx24bY7sFKrGUmgvz67AfasBOyfZSYj0LWQgl7y3ApaCNYQNsSzFS0RyeHUDpn8BOHSRnUT1WArW0v/3wPBnZKcg0h9nH+DBrwB3TuNaA0vBmkYtAAbNlJ2CSD8cXID71wJ+kbKTaAZLwdom/AOIuUd2CiLtM/y8wkDYENlJNIWlYG1GO8viW93vkJ2ESNsmvANEjZOdQnNYCh3B3slyNmXIQNlJiLTprhctl9Ukq2MpdBQnd+CB9YBvL9lJiLTljmctKwpQh2ApdCRXX2DmBsCnp+wkRNow/Blg5EuyU2gaS6GjeYYCs/6PIwai9hr2tOUIP+pQLIXO4BEMPLwJ8I+RnYRInYY+BYx+WXYKXWApdBa3AGDWRiCwr+wkROpy+zxgzCuyU+iGQQghZIfQleoS4LNJwMVjspMQ2b475gMjX5SdQldYCjLUlAKr7wXyE2UnIbJRBuDuN4Bb/yg7iO6wFGRpqAHWPQKc2iQ7CZFtMdoDk96zrCdGnY6lIJPZBGyeDyT+W3YSItvg6AZMWwlEjpadRLdYCrZg39vAjlcB8J+CdMw1AHhgLVcCkIylYCuOfQlsmAOY6mUnIep8AbGWqxh6R8hOonssBVuSsxdYO9OyI5pIL6InAL/9CHByk52EwFKwPaW5wJoHgUvHZSch6mAGyzpGd70AGAyyw9DPWAq2qL4a+G4ecPxL2UmIOoaDKzD5faDPZNlJ6AosBVv2w/vA9r8B5kbZSYisxyvcsrR8UJzsJNQMloKty9kHfDkLqC6SnYSo/XrFA5M/sKwgTDaJpaAGP+UD6x8Fzv4gOwlR29g5AqMXArfO4f4DG8dSUAuzCdi3BNizmNNJpC4+PSzXUub5B6rAUlCb/CTLqKE0R3YSouuLmwZMeNtyJUJSBZaCGtVVWpbHSFktOwlR8xzdgXGLgYEPyE5CN4iloGapXwMb/8yT3ci2RI4GJvwD8AqTnYTagKWgdpUFwObngNSvZCchveviBcT/naMDlWMpaEXGVmDj00B5vuwkpEfRE4DfLAHcg2QnoXZiKWhJXSWwcxFw6F+AMMtOQ3rg4geMfxPo+zvZSchKWApalJ8EfDsPKEiVnYS0ymgP3DQbuOt5wNlbdhqyIpaCVpkaLRfv2f06UFsmOw1pSfcRliOLAmJkJ6EOwFLQuuoSYNdrQNJyQJhkpyE18woHxr4GxN4jOwl1IJaCXhSkA9sXAJlbZSchtXFwBYY9Bdw+D3DoIjsNdTCWgt6c3mNZefXCUdlJyNbZd7HsNxj2Z8DNX3Ya6iQsBb1K3wTseYPlQFczOgCDZlougOMRLDsNdTKWgt6d2gzsfgO4kCI7CclmsAP6TwdGzAe8u8lOQ5KwFMji1BbLyOH8EdlJqLPZOQH9pgFDnwL8ImWnIclYCtRU1veWK75l7wTA/xqa5uwDDJkN3PwY4BYgOw3ZCJYCNa8wAzj4IXB0DdBQJTsNWZN3d+C2J4ABDwCOLrLTkI1hKdC11ZQCyZ8Bhz4GfsqTnYbazAB0vwMY8qhlnSKjUXYgslEsBWodswk4tQk48h/LFBOv/qYO7iHAgPuBQTMA7wjZaUgFWAp04yoLgGNrgZT/cn0lW2S0B3rfbTmsNHI0YLSTnYhUhKVA7XPhqKUcjn8JVBfLTqNvoYMtq5XG3csdx9RmLAWyDlMjcGY/kLYRSP8/oOK87ET6EDIQiJ0E9Pktp4fIKlgKZH1CAOeSgfTvLCVRnCk7kXYYHYCwW4Do3wAxE3nJS7I6lgJ1vMIMIGu7Zd2lMweA+grZidTFNxLoOdLyFTEccHKTnYg0jKVAncvUCJxPBnL2WEoi7xBgqpOdyra4BgDht/5SBFxygjoRS4HkaqgF8hOBc4ctS2ycPwKUnZGdqvPYOQJBcUDXIT9/3cR9AyQVS4FsT3WJZTRx/ghw7ghQcBIoO6v+iwQ5ewP+0YB/FOAfA4QOAoL7A/ZOspMRKVgKpA6N9UBpDlCUCRRnWXZeF2db/l5VKDvdLxzdAY8QwDPUspyEUgLRgHug7HRE18VSIPVrrAMqLgDl5y1fVYWWr8oCy6ijvhKorwIaqn/5e3010FjT/PYMRgAGy0lfjq6AkwfQxdPy5eQBdLn8vZelADxCLSXgEWK5nUjFWAqkX2azZbkOg8FSBAaj5e9EOsZSICIiBZdKJCIiBUuBiIgULAUiIlKwFIiISMFSICIiBUuBiIgULAUbkJubC4PBgJSUFNlRpNi9ezcMBgPKyspkRyHSPZ6nYANMJhMKCwvh5+cHe3t72XE6XX19PUpKShAYGAgDTx4jkoqlQJpQX18PR0dH2TGIVE9z00d33nkn5s2bh/nz58PHxwdBQUFYuHBhk585e/YsJk2aBDc3N3h4eGDatGm4dOmScv/ChQsxYMAArFq1ChEREfD09MTvf/97VFRc++Iw77//Pnr16oUuXbogMDAQU6dOVe4zm8148803ERkZCScnJ4SHh+O1114D0Pz00YkTJzBu3Di4ubkhMDAQM2bMQFFR0Q29zrKyMjz++OMIDAxEly5d0LdvX2zcuFG5f//+/Rg+fDicnZ0RFhaGefPmoaqqqsXXd/n38umnnyI8PBxubm6YM2cOTCYT3nzzTQQFBSEgIEB5XZe9/fbbiIuLg6urK8LCwjBnzhxUVlYq9zc3fbR+/Xr06dMHTk5OiIiIwJIlS5psMyIiAosWLcLMmTPh4eGBxx57rOV/GCJqPaExI0aMEB4eHmLhwoUiIyNDrFy5UhgMBrFt2zYhhBAmk0kMGDBADBs2TCQlJYkff/xRDB48WIwYMULZxssvvyzc3NzElClTxPHjx8XevXtFUFCQeOGFF1p83sTERGFnZyf++9//itzcXJGcnCz++c9/KvfPnz9feHt7ixUrVoisrCyxb98+8fHHHwshhMjJyREAxJEjR4QQQpSWlgp/f3/x/PPPi7S0NJGcnCzGjBkj7rrrrht6nbfeeqvo06eP2LZtm8jOzhbfffed2LRpkxBCiKysLOHq6ireeecdkZGRIRISEsTAgQPFrFmzWnyNl38vU6dOFampqeLbb78Vjo6OIj4+Xjz55JMiPT1dfPrppwKA+PHHH5XHvfPOO2Lnzp0iJydH7NixQ0RFRYk//elPyv27du0SAERpaakQQoikpCRhNBrFq6++Kk6dOiWWL18unJ2dxfLly5XHdOvWTXh4eIi33npLZGVliaysrBZzE1HrabIUhg0b1uS2IUOGiOeee04IIcS2bduEnZ2dOHv2rHJ/amqqACAOHTokhLC8+bm4uIjy8nLlZ5599llxyy23tPi869evFx4eHk0ec1l5eblwcnJSSuBKV5bCokWLxNixY5v8TF5engAgTp061arXuXXrVmE0GpWfv9Ls2bPFY4891uS2ffv2CaPRKGpqapp9THO/l/j4eBERESFMJpNyW1RUlHj99deb3YYQQnz55ZfC19dX+f7KUrj//vvFmDFjmjzm2WefFbGxscr33bp1E5MnT27xOYiobTQ3fQQA/fr1a/J9cHAwCgoKAABpaWkICwtDWNgvFzyPjY2Fl5cX0tLSlNsiIiLg7u7e7DZWr14NNzc35Wvfvn0YM2YMunXrhh49emDGjBlYvXo1qqurleesq6vDqFGjWpX/6NGj2LVrV5PniI6OBgBkZ2e36nWmpKSga9eu6N27d4vPsWLFiibPER8fD7PZjJycnBazXfl7CQwMRGxsLIxGY5PbLucAgO+//x6jRo1CaGgo3N3dMWPGDBQXFyu/nyulpaVh6NChTW4bOnQoMjMzYTL9cqGdm266qcWcRNQ2mjzUxcHBocn3BoMBZrPZatu45557cMsttyj3hYaGwtnZGcnJydi9eze2bduGBQsWYOHChUhMTISzs/MNPXdlZSUmTpyIxYsXX3VfcHBwqzJe7zkrKyvx+OOPY968eVfdFx4e3uLjmnvOa+XIzc3FhAkT8Kc//QmvvfYafHx8sH//fsyePRv19fVwcXG5Zs5rcXV1bfNjiah5miyFa4mJiUFeXh7y8vKU0cLJkydRVlaG2NjYVm3D3d29yafly+zt7TF69GiMHj0aL7/8Mry8vLBz506MHz8ezs7O2LFjBx599NHrbn/QoEFYv349IiIi2nyIar9+/ZCfn4+MjIxmRwuDBg3CyZMnERkZ2abtt9bhw4dhNpuxZMkSZTSxdu3aaz4mJiYGCQkJTW5LSEhA7969YWdn12FZiUiDRx9dz+jRoxEXF4cHHngAycnJOHToEGbOnIkRI0a0azpi48aNWLp0KVJSUnDmzBl89tlnMJvNiIqKQpcuXfDcc89h/vz5+Oyzz5CdnY0ff/wRn3zySbPbeuKJJ1BSUoLp06cjMTER2dnZ2Lp1Kx5++OEm0yfXMmLECNxxxx343e9+h+3btyMnJwebN2/Gli1bAADPPfccDhw4gLlz5yIlJQWZmZnYsGED5s6d2+bfQXMiIyPR0NCAZcuW4fTp01i1ahU+/PDDaz7mmWeewY4dO7Bo0SJkZGRg5cqVePfdd/GXv/zFqtmI6Gq6KwWDwYANGzbA29sbd9xxB0aPHo0ePXrgiy++aNd2vby88NVXX2HkyJGIiYnBhx9+iM8//xx9+vQBAPztb3/DM888gwULFiAmJgb33Xdfk3n3XwsJCUFCQgJMJhPGjh2LuLg4PPXUU/Dy8moyd38969evx5AhQzB9+nTExsZi/vz5Sqn069cPe/bsQUZGBoYPH46BAwdiwYIFCAkJadfv4Ur9+/fH22+/jcWLF6Nv375YvXo1Xn/99Ws+ZtCgQVi7di3WrFmDvn37YsGCBXj11Vcxa9Ysq2Yjoqvx5DWSbuvWrRg3bhxqa2t5AhqRZLobKZBtuXTpEjZs2IBevXqxEIhsgO52NJNtGT9+PCoqKvD+++/LjkJE4PQRERH9CqePiIhIwVIgIiIFS4GIiBQsBSIiUrAUiIhIwVIgIiIFS4GIiBQsBSIiUrAUiIhIwVIgIiIFS4GIiBQsBSIiUrAUiIhIwVIgIiIFS4GIiBQsBSIiUrAUiIhIwVIgIiIFS4GIiBQsBSIiUrAUiIhIwVIgIiIFS4GIiBQsBSIiUvx/sFBwQ4NGpP8AAAAASUVORK5CYII="
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.pie([len(df[(df['creativity']) & (df['major'].isin(science_majors))])/len(df[df['major'].isin(science_majors)]),\n",
    "        len(df[(df['creativity']) & (df['major'].isin(non_science_majors))])/len(df[df['major'].isin(non_science_majors)]),\n",
    "        ], labels=['science major', 'non-science major'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "9f48e416afc554bb",
   "metadata": {
    "collapsed": false,
    "ExecuteTime": {
     "end_time": "2024-01-02T08:00:47.541443900Z",
     "start_time": "2024-01-02T08:00:47.465456900Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": "([<matplotlib.patches.Wedge at 0x29e58102110>,\n  <matplotlib.patches.Wedge at 0x29e58102b90>],\n [Text(-0.05022674936264798, 1.098852707895131, 'science major'),\n  Text(0.05022685224466335, -1.0988527031925586, 'non-science major')])"
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "text/plain": "<Figure size 640x480 with 1 Axes>",
      "image/png": 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"
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.pie([len(df[(df['all-rounded']) & (df['major'].isin(science_majors))])/len(df[df['major'].isin(science_majors)]),\n",
    "        len(df[(df['all-rounded']) & (df['major'].isin(non_science_majors))])/len(df[df['major'].isin(non_science_majors)]),\n",
    "        ], labels=['science major', 'non-science major'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "1a2597b37a2f663d",
   "metadata": {
    "collapsed": false,
    "ExecuteTime": {
     "end_time": "2024-01-02T08:00:47.680909300Z",
     "start_time": "2024-01-02T08:00:47.539445800Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": "([<matplotlib.patches.Wedge at 0x29e5813f9d0>,\n  <matplotlib.patches.Wedge at 0x29e5812bc10>],\n [Text(0.13827584099089185, 1.0912743888675578, 'science major'),\n  Text(-0.13827573881840885, -1.0912744018138716, 'non-science major')])"
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "text/plain": "<Figure size 640x480 with 1 Axes>",
      "image/png": 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"
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.pie([len(df[(df['wide_range_of_knowledge']) & (df['major'].isin(science_majors))])/len(df[df['major'].isin(science_majors)]),\n",
    "        len(df[(df['wide_range_of_knowledge']) & (df['major'].isin(non_science_majors))])/len(df[df['major'].isin(non_science_majors)]),\n",
    "        ], labels=['science major', 'non-science major'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "561af243e8088f2d",
   "metadata": {
    "collapsed": false,
    "ExecuteTime": {
     "end_time": "2024-01-02T08:00:47.775397600Z",
     "start_time": "2024-01-02T08:00:47.613242700Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": "([<matplotlib.patches.Wedge at 0x29e5818dfd0>,\n  <matplotlib.patches.Wedge at 0x29e5818ec90>],\n [Text(-0.06316984222595153, 1.0981846707330913, 'science major'),\n  Text(0.0631697394064818, -1.098184676647474, 'non-science major')])"
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "text/plain": "<Figure size 640x480 with 1 Axes>",
      "image/png": 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"
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.pie([len(df[(df['communication']) & (df['major'].isin(science_majors))])/len(df[df['major'].isin(science_majors)]),\n",
    "        len(df[(df['communication']) & (df['major'].isin(non_science_majors))])/len(df[df['major'].isin(non_science_majors)]),\n",
    "        ], labels=['science major', 'non-science major'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "35ec888a44dd154f",
   "metadata": {
    "collapsed": false,
    "ExecuteTime": {
     "end_time": "2024-01-02T08:00:47.924576200Z",
     "start_time": "2024-01-02T08:00:47.678917Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": "<Figure size 640x480 with 1 Axes>",
      "image/png": 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"
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "\n",
    "# Data\n",
    "categories = df.columns[4:]\n",
    "segment1 = [(len(df[(df[i]) & (df['major'].isin(science_majors))])/1000) for i in categories]\n",
    "segment2 = [(len(df[(df[i]) & (df['major'].isin(science_majors))])/1000) + (len(df[(df[i]) & (df['major'].isin(non_science_majors))])/1000) for i in categories]\n",
    "\n",
    "x = range(len(categories))\n",
    "\n",
    "plt.bar(x, segment2, width=0.2, label='non-science major')\n",
    "plt.bar(x, segment1, width=0.2, label='science major')\n",
    "\n",
    "\n",
    "plt.xlabel('Categories')\n",
    "plt.ylabel('Values')\n",
    "plt.title('')\n",
    "plt.xticks(x, categories)\n",
    "plt.xticks(rotation=15)\n",
    "\n",
    "plt.legend()\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "outputs": [
    {
     "data": {
      "text/plain": "<Figure size 640x480 with 1 Axes>",
      "image/png": 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"
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Data\n",
    "categories = df.columns[4:]\n",
    "segment1 = [(len(df[(df[i]) & (df['major'].isin(science_majors))])/len(df[df['major'].isin(science_majors)])) for i in df.columns[4:]]\n",
    "segment2 = [(len(df[(df[i]) & (df['major'].isin(science_majors))])/len(df[df['major'].isin(science_majors)])) + (len(df[(df[i]) & (df['major'].isin(non_science_majors))])/len(df[df['major'].isin(non_science_majors)])) for i in df.columns[4:]]\n",
    "\n",
    "x = range(len(categories))\n",
    "\n",
    "plt.bar(x, segment2, width=0.2, label='non-science major')\n",
    "plt.bar(x, segment1, width=0.2, label='science major')\n",
    "\n",
    "\n",
    "plt.xlabel('Categories')\n",
    "plt.ylabel('Values')\n",
    "plt.title('')\n",
    "plt.xticks(x, categories)\n",
    "plt.xticks(rotation=15)\n",
    "\n",
    "plt.legend()\n",
    "\n",
    "plt.show()"
   ],
   "metadata": {
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     "end_time": "2024-01-02T08:00:48.119788800Z",
     "start_time": "2024-01-02T08:00:47.934619200Z"
    }
   },
   "id": "a6f94d2eaa7abfe3"
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  {
   "cell_type": "code",
   "execution_count": 14,
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "there's no significant difference in considering critical_thinking as part of liberal arts education between science students and non-science students\n",
      "there's no significant difference in considering creativity as part of liberal arts education between science students and non-science students\n",
      "there's no significant difference in considering all-rounded as part of liberal arts education between science students and non-science students\n",
      "there's no significant difference in considering wide_range_of_knowledge as part of liberal arts education between science students and non-science students\n",
      "there's no significant difference in considering communication as part of liberal arts education between science students and non-science students\n"
     ]
    }
   ],
   "source": [
    "import statsmodels.api as sm\n",
    "\n",
    "for i in df.columns[4:]:\n",
    "    z_stat, p_value = sm.stats.proportions_ztest(\n",
    "        [len(df[(df[i]) & (df['major'].isin(science_majors))]), \n",
    "         len(df[(df[i]) & (df['major'].isin(non_science_majors))])], \n",
    "         [len(df[df['major'].isin(science_majors)]), \n",
    "          len(df[df['major'].isin(non_science_majors)])])\n",
    "    \n",
    "    alpha = 0.05\n",
    "    if p_value < alpha:\n",
    "        print(f\"there's a significant difference in considering {i} as part of liberal arts education between science students and non-science students\")\n",
    "    else:\n",
    "        print(f\"there's no significant difference in considering {i} as part of liberal arts education between science students and non-science students\")"
   ],
   "metadata": {
    "collapsed": false,
    "ExecuteTime": {
     "end_time": "2024-01-02T08:00:49.003342500Z",
     "start_time": "2024-01-02T08:00:48.115255400Z"
    }
   },
   "id": "1aece9a57bb16b82"
  }
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