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Created December 18, 2014 11:32
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I gave myself an hour to look at the REF data. There were a few interruptions, but I still didn't get as far as I thought I would...
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ref2104.ipynb
{
"metadata": {
"name": "",
"signature": "sha256:e587bd2147ac056a83cf27ac8f92f75d67cdd0d1b7813b29ff7f10f410755b39"
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"worksheets": [
{
"cells": [
{
"cell_type": "heading",
"level": 1,
"metadata": {},
"source": [
"Quick Look at REF Data"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"The UK Higher Education [Research Excellence Framework, 2014](http://www.ref.ac.uk/) results are out, so I gave myself an hour to explore the data, see what's there, and get an idea for some of the more obvious stories we might try to pull out.\n",
"\n",
"The data is published as an Excel spreadsheet, so let's grab a copy."
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"#Grab the data file from a copied URL\n",
"#!curl http://results.ref.ac.uk/\\(S\\(jjedtxoydmmvwidxuktryu15\\)\\)/DownloadFile/AllResults/xlsx > ref2014.xlsx"
],
"language": "python",
"metadata": {},
"outputs": [
{
"output_type": "stream",
"stream": "stdout",
"text": [
" % Total % Received % Xferd Average Speed Time Time Time Current\r\n",
" Dload Upload Total Spent Left Speed\r\n",
"\r",
" 0 0 0 0 0 0 0 0 --:--:-- --:--:-- --:--:-- 0"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
"\r",
" 0 0 0 0 0 0 0 0 --:--:-- 0:00:01 --:--:-- 0"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
"\r",
" 0 0 0 0 0 0 0 0 --:--:-- 0:00:02 --:--:-- 0"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
"\r",
" 0 0 0 0 0 0 0 0 --:--:-- 0:00:03 --:--:-- 0"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
"\r",
" 0 0 0 0 0 0 0 0 --:--:-- 0:00:04 --:--:-- 0"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
"\r",
" 0 0 0 0 0 0 0 0 --:--:-- 0:00:05 --:--:-- 0"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
"\r"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
" 70 636k 70 448k 0 0 78559 0 0:00:08 0:00:05 0:00:03 103k"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
"\r",
"100 636k 100 636k 0 0 107k 0 0:00:05 0:00:05 --:--:-- 187k\r\n"
]
}
],
"prompt_number": 5
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"import pandas as pd\n",
"xls=pd.ExcelFile('ref2014.xlsx')\n",
"\n",
"#How many sheets are there?\n",
"xls.sheet_names"
],
"language": "python",
"metadata": {},
"outputs": [
{
"metadata": {},
"output_type": "pyout",
"prompt_number": 37,
"text": [
"['REF2014 Profiles']"
]
}
],
"prompt_number": 37
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"So there's just a single sheet. Let's have a look at it."
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"#Quick preview of the data\n",
"df=pd.read_excel('ref2014.xlsx')\n",
"df[:10]"
],
"language": "python",
"metadata": {},
"outputs": [
{
"html": [
"<div style=\"max-height:1000px;max-width:1500px;overflow:auto;\">\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>2014 Research Excellence Framework Results</th>\n",
" <th>Unnamed: 1</th>\n",
" <th>Unnamed: 2</th>\n",
" <th>Unnamed: 3</th>\n",
" <th>Unnamed: 4</th>\n",
" <th>Unnamed: 5</th>\n",
" <th>Unnamed: 6</th>\n",
" <th>Unnamed: 7</th>\n",
" <th>Unnamed: 8</th>\n",
" <th>Unnamed: 9</th>\n",
" <th>Unnamed: 10</th>\n",
" <th>Unnamed: 11</th>\n",
" <th>Unnamed: 12</th>\n",
" <th>Unnamed: 13</th>\n",
" <th>Unnamed: 14</th>\n",
" <th>Unnamed: 15</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>0</th>\n",
" <td> NaN</td>\n",
" <td> NaN</td>\n",
" <td> NaN</td>\n",
" <td> NaN</td>\n",
" <td> NaN</td>\n",
" <td> NaN</td>\n",
" <td> NaN</td>\n",
" <td> NaN</td>\n",
" <td> NaN</td>\n",
" <td> NaN</td>\n",
" <td> NaN</td>\n",
" <td> NaN</td>\n",
" <td> NaN</td>\n",
" <td> NaN</td>\n",
" <td> NaN</td>\n",
" <td> NaN</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1</th>\n",
" <td> Quality profiles for all submissions</td>\n",
" <td> NaN</td>\n",
" <td> NaN</td>\n",
" <td> NaN</td>\n",
" <td> NaN</td>\n",
" <td> NaN</td>\n",
" <td> NaN</td>\n",
" <td> NaN</td>\n",
" <td> NaN</td>\n",
" <td> NaN</td>\n",
" <td> NaN</td>\n",
" <td> NaN</td>\n",
" <td> NaN</td>\n",
" <td> NaN</td>\n",
" <td> NaN</td>\n",
" <td> NaN</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2</th>\n",
" <td> Note: In this table, joint submissions are sho...</td>\n",
" <td> NaN</td>\n",
" <td> NaN</td>\n",
" <td> NaN</td>\n",
" <td> NaN</td>\n",
" <td> NaN</td>\n",
" <td> NaN</td>\n",
" <td> NaN</td>\n",
" <td> NaN</td>\n",
" <td> NaN</td>\n",
" <td> NaN</td>\n",
" <td> NaN</td>\n",
" <td> NaN</td>\n",
" <td> NaN</td>\n",
" <td> NaN</td>\n",
" <td> NaN</td>\n",
" </tr>\n",
" <tr>\n",
" <th>3</th>\n",
" <td> UKPRN</td>\n",
" <td> Institution</td>\n",
" <td> SortOrder</td>\n",
" <td> MainPanel</td>\n",
" <td> UOA</td>\n",
" <td> UnitOfAssessment</td>\n",
" <td> msubId</td>\n",
" <td> MultipleSubmission</td>\n",
" <td> JointSubmission</td>\n",
" <td> Profile</td>\n",
" <td> StaffFte</td>\n",
" <td> FourStar</td>\n",
" <td> ThreeStar</td>\n",
" <td> TwoStar</td>\n",
" <td> OneStar</td>\n",
" <td> Unclassified</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4</th>\n",
" <td> NaN</td>\n",
" <td> NaN</td>\n",
" <td> NaN</td>\n",
" <td> NaN</td>\n",
" <td> NaN</td>\n",
" <td> NaN</td>\n",
" <td> NaN</td>\n",
" <td> NaN</td>\n",
" <td> NaN</td>\n",
" <td> NaN</td>\n",
" <td> NaN</td>\n",
" <td> Percentage of the submission meeting the stand...</td>\n",
" <td> NaN</td>\n",
" <td> NaN</td>\n",
" <td> NaN</td>\n",
" <td> NaN</td>\n",
" </tr>\n",
" <tr>\n",
" <th>5</th>\n",
" <td> NaN</td>\n",
" <td> NaN</td>\n",
" <td> NaN</td>\n",
" <td> NaN</td>\n",
" <td> NaN</td>\n",
" <td> NaN</td>\n",
" <td> NaN</td>\n",
" <td> NaN</td>\n",
" <td> NaN</td>\n",
" <td> NaN</td>\n",
" <td> NaN</td>\n",
" <td> NaN</td>\n",
" <td> NaN</td>\n",
" <td> NaN</td>\n",
" <td> NaN</td>\n",
" <td> NaN</td>\n",
" </tr>\n",
" <tr>\n",
" <th>6</th>\n",
" <td> Institution code (UKPRN)</td>\n",
" <td> Institution name</td>\n",
" <td> Institution sort order</td>\n",
" <td> Main panel</td>\n",
" <td> Unit of assessment number</td>\n",
" <td> Unit of assessment name</td>\n",
" <td> Multiple submission letter</td>\n",
" <td> Multiple submission name</td>\n",
" <td> Joint submission</td>\n",
" <td> Profile</td>\n",
" <td> FTE Category A staff submitted</td>\n",
" <td> 4*</td>\n",
" <td> 3*</td>\n",
" <td> 2*</td>\n",
" <td> 1*</td>\n",
" <td> unclassified</td>\n",
" </tr>\n",
" <tr>\n",
" <th>7</th>\n",
" <td> 10000291</td>\n",
" <td> Anglia Ruskin University</td>\n",
" <td> 10</td>\n",
" <td> A</td>\n",
" <td> 3</td>\n",
" <td> Allied Health Professions, Dentistry, Nursing ...</td>\n",
" <td> </td>\n",
" <td> NaN</td>\n",
" <td> NaN</td>\n",
" <td> Outputs</td>\n",
" <td> 11.3</td>\n",
" <td> 6.4</td>\n",
" <td> 68.1</td>\n",
" <td> 25.5</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>8</th>\n",
" <td> 10000291</td>\n",
" <td> Anglia Ruskin University</td>\n",
" <td> 10</td>\n",
" <td> A</td>\n",
" <td> 3</td>\n",
" <td> Allied Health Professions, Dentistry, Nursing ...</td>\n",
" <td> </td>\n",
" <td> NaN</td>\n",
" <td> NaN</td>\n",
" <td> Impact</td>\n",
" <td> 11.3</td>\n",
" <td> 20</td>\n",
" <td> 80</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>9</th>\n",
" <td> 10000291</td>\n",
" <td> Anglia Ruskin University</td>\n",
" <td> 10</td>\n",
" <td> A</td>\n",
" <td> 3</td>\n",
" <td> Allied Health Professions, Dentistry, Nursing ...</td>\n",
" <td> </td>\n",
" <td> NaN</td>\n",
" <td> NaN</td>\n",
" <td> Environment</td>\n",
" <td> 11.3</td>\n",
" <td> 12.5</td>\n",
" <td> 75</td>\n",
" <td> 12.5</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"metadata": {},
"output_type": "pyout",
"prompt_number": 39,
"text": [
" 2014 Research Excellence Framework Results \\\n",
"0 NaN \n",
"1 Quality profiles for all submissions \n",
"2 Note: In this table, joint submissions are sho... \n",
"3 UKPRN \n",
"4 NaN \n",
"5 NaN \n",
"6 Institution code (UKPRN) \n",
"7 10000291 \n",
"8 10000291 \n",
"9 10000291 \n",
"\n",
" Unnamed: 1 Unnamed: 2 Unnamed: 3 \\\n",
"0 NaN NaN NaN \n",
"1 NaN NaN NaN \n",
"2 NaN NaN NaN \n",
"3 Institution SortOrder MainPanel \n",
"4 NaN NaN NaN \n",
"5 NaN NaN NaN \n",
"6 Institution name Institution sort order Main panel \n",
"7 Anglia Ruskin University 10 A \n",
"8 Anglia Ruskin University 10 A \n",
"9 Anglia Ruskin University 10 A \n",
"\n",
" Unnamed: 4 \\\n",
"0 NaN \n",
"1 NaN \n",
"2 NaN \n",
"3 UOA \n",
"4 NaN \n",
"5 NaN \n",
"6 Unit of assessment number \n",
"7 3 \n",
"8 3 \n",
"9 3 \n",
"\n",
" Unnamed: 5 \\\n",
"0 NaN \n",
"1 NaN \n",
"2 NaN \n",
"3 UnitOfAssessment \n",
"4 NaN \n",
"5 NaN \n",
"6 Unit of assessment name \n",
"7 Allied Health Professions, Dentistry, Nursing ... \n",
"8 Allied Health Professions, Dentistry, Nursing ... \n",
"9 Allied Health Professions, Dentistry, Nursing ... \n",
"\n",
" Unnamed: 6 Unnamed: 7 Unnamed: 8 \\\n",
"0 NaN NaN NaN \n",
"1 NaN NaN NaN \n",
"2 NaN NaN NaN \n",
"3 msubId MultipleSubmission JointSubmission \n",
"4 NaN NaN NaN \n",
"5 NaN NaN NaN \n",
"6 Multiple submission letter Multiple submission name Joint submission \n",
"7 NaN NaN \n",
"8 NaN NaN \n",
"9 NaN NaN \n",
"\n",
" Unnamed: 9 Unnamed: 10 \\\n",
"0 NaN NaN \n",
"1 NaN NaN \n",
"2 NaN NaN \n",
"3 Profile StaffFte \n",
"4 NaN NaN \n",
"5 NaN NaN \n",
"6 Profile FTE Category A staff submitted \n",
"7 Outputs 11.3 \n",
"8 Impact 11.3 \n",
"9 Environment 11.3 \n",
"\n",
" Unnamed: 11 Unnamed: 12 Unnamed: 13 \\\n",
"0 NaN NaN NaN \n",
"1 NaN NaN NaN \n",
"2 NaN NaN NaN \n",
"3 FourStar ThreeStar TwoStar \n",
"4 Percentage of the submission meeting the stand... NaN NaN \n",
"5 NaN NaN NaN \n",
"6 4* 3* 2* \n",
"7 6.4 68.1 25.5 \n",
"8 20 80 0 \n",
"9 12.5 75 12.5 \n",
"\n",
" Unnamed: 14 Unnamed: 15 \n",
"0 NaN NaN \n",
"1 NaN NaN \n",
"2 NaN NaN \n",
"3 OneStar Unclassified \n",
"4 NaN NaN \n",
"5 NaN NaN \n",
"6 1* unclassified \n",
"7 0 0 \n",
"8 0 0 \n",
"9 0 0 "
]
}
],
"prompt_number": 39
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Row 3 (counting form 0) has column codes, row 6 has full column names. Let's load in the data as a simple dataframe using the full column names."
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"#We have some metadata rows so let's try again...\n",
"df=pd.read_excel('ref2014.xlsx',header=6)\n",
"df[:5]"
],
"language": "python",
"metadata": {},
"outputs": [
{
"html": [
"<div style=\"max-height:1000px;max-width:1500px;overflow:auto;\">\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>Institution code (UKPRN)</th>\n",
" <th>Institution name</th>\n",
" <th>Institution sort order</th>\n",
" <th>Main panel</th>\n",
" <th>Unit of assessment number</th>\n",
" <th>Unit of assessment name</th>\n",
" <th>Multiple submission letter</th>\n",
" <th>Multiple submission name</th>\n",
" <th>Joint submission</th>\n",
" <th>Profile</th>\n",
" <th>FTE Category A staff submitted</th>\n",
" <th>4*</th>\n",
" <th>3*</th>\n",
" <th>2*</th>\n",
" <th>1*</th>\n",
" <th>unclassified</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>0</th>\n",
" <td> 10000291</td>\n",
" <td> Anglia Ruskin University</td>\n",
" <td> 10</td>\n",
" <td> A</td>\n",
" <td> 3</td>\n",
" <td> Allied Health Professions, Dentistry, Nursing ...</td>\n",
" <td> </td>\n",
" <td> NaN</td>\n",
" <td> NaN</td>\n",
" <td> Outputs</td>\n",
" <td> 11.3</td>\n",
" <td> 6.4</td>\n",
" <td> 68.1</td>\n",
" <td> 25.5</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1</th>\n",
" <td> 10000291</td>\n",
" <td> Anglia Ruskin University</td>\n",
" <td> 10</td>\n",
" <td> A</td>\n",
" <td> 3</td>\n",
" <td> Allied Health Professions, Dentistry, Nursing ...</td>\n",
" <td> </td>\n",
" <td> NaN</td>\n",
" <td> NaN</td>\n",
" <td> Impact</td>\n",
" <td> 11.3</td>\n",
" <td> 20</td>\n",
" <td> 80</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2</th>\n",
" <td> 10000291</td>\n",
" <td> Anglia Ruskin University</td>\n",
" <td> 10</td>\n",
" <td> A</td>\n",
" <td> 3</td>\n",
" <td> Allied Health Professions, Dentistry, Nursing ...</td>\n",
" <td> </td>\n",
" <td> NaN</td>\n",
" <td> NaN</td>\n",
" <td> Environment</td>\n",
" <td> 11.3</td>\n",
" <td> 12.5</td>\n",
" <td> 75</td>\n",
" <td> 12.5</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>3</th>\n",
" <td> 10000291</td>\n",
" <td> Anglia Ruskin University</td>\n",
" <td> 10</td>\n",
" <td> A</td>\n",
" <td> 3</td>\n",
" <td> Allied Health Professions, Dentistry, Nursing ...</td>\n",
" <td> </td>\n",
" <td> NaN</td>\n",
" <td> NaN</td>\n",
" <td> Overall</td>\n",
" <td> 11.3</td>\n",
" <td> 10</td>\n",
" <td> 72</td>\n",
" <td> 18</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4</th>\n",
" <td> 10000291</td>\n",
" <td> Anglia Ruskin University</td>\n",
" <td> 10</td>\n",
" <td> A</td>\n",
" <td> 4</td>\n",
" <td> Psychology, Psychiatry and Neuroscience</td>\n",
" <td> </td>\n",
" <td> NaN</td>\n",
" <td> NaN</td>\n",
" <td> Outputs</td>\n",
" <td> 13.7</td>\n",
" <td> 10.3</td>\n",
" <td> 61.5</td>\n",
" <td> 25.6</td>\n",
" <td> 2.6</td>\n",
" <td> 0</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"metadata": {},
"output_type": "pyout",
"prompt_number": 40,
"text": [
" Institution code (UKPRN) Institution name Institution sort order \\\n",
"0 10000291 Anglia Ruskin University 10 \n",
"1 10000291 Anglia Ruskin University 10 \n",
"2 10000291 Anglia Ruskin University 10 \n",
"3 10000291 Anglia Ruskin University 10 \n",
"4 10000291 Anglia Ruskin University 10 \n",
"\n",
" Main panel Unit of assessment number \\\n",
"0 A 3 \n",
"1 A 3 \n",
"2 A 3 \n",
"3 A 3 \n",
"4 A 4 \n",
"\n",
" Unit of assessment name \\\n",
"0 Allied Health Professions, Dentistry, Nursing ... \n",
"1 Allied Health Professions, Dentistry, Nursing ... \n",
"2 Allied Health Professions, Dentistry, Nursing ... \n",
"3 Allied Health Professions, Dentistry, Nursing ... \n",
"4 Psychology, Psychiatry and Neuroscience \n",
"\n",
" Multiple submission letter Multiple submission name Joint submission \\\n",
"0 NaN NaN \n",
"1 NaN NaN \n",
"2 NaN NaN \n",
"3 NaN NaN \n",
"4 NaN NaN \n",
"\n",
" Profile FTE Category A staff submitted 4* 3* 2* 1* \\\n",
"0 Outputs 11.3 6.4 68.1 25.5 0 \n",
"1 Impact 11.3 20 80 0 0 \n",
"2 Environment 11.3 12.5 75 12.5 0 \n",
"3 Overall 11.3 10 72 18 0 \n",
"4 Outputs 13.7 10.3 61.5 25.6 2.6 \n",
"\n",
" unclassified \n",
"0 0 \n",
"1 0 \n",
"2 0 \n",
"3 0 \n",
"4 0 "
]
}
],
"prompt_number": 40
},
{
"cell_type": "heading",
"level": 2,
"metadata": {},
"source": [
"Preliminary Exploration of the Data"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"The dataset is completely new to me so let's get a feel for some of the things it contains."
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"#What are the columns?\n",
"for col in df.columns: print(col)"
],
"language": "python",
"metadata": {},
"outputs": [
{
"output_type": "stream",
"stream": "stdout",
"text": [
"Institution code (UKPRN)\n",
"Institution name\n",
"Institution sort order\n",
"Main panel\n",
"Unit of assessment number\n",
"Unit of assessment name\n",
"Multiple submission letter\n",
"Multiple submission name\n",
"Joint submission\n",
"Profile\n",
"FTE Category A staff submitted\n",
"4*\n",
"3*\n",
"2*\n",
"1*\n",
"unclassified\n"
]
}
],
"prompt_number": 24
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Visual inspection of the first few lines of the dataframe shown above suggests that each institution puts in for different units of assessment, and each unit of assessment receives scores on four profile elements:"
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"df['Profile'].unique()"
],
"language": "python",
"metadata": {},
"outputs": [
{
"metadata": {},
"output_type": "pyout",
"prompt_number": 42,
"text": [
"array(['Outputs', 'Impact', 'Environment', 'Overall'], dtype=object)"
]
}
],
"prompt_number": 42
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"#What are the units of assessment?\n",
"df['Unit of assessment name'].unique()"
],
"language": "python",
"metadata": {},
"outputs": [
{
"metadata": {},
"output_type": "pyout",
"prompt_number": 26,
"text": [
"array(['Allied Health Professions, Dentistry, Nursing and Pharmacy',\n",
" 'Psychology, Psychiatry and Neuroscience', 'Biological Sciences',\n",
" 'General Engineering',\n",
" 'Architecture, Built Environment and Planning',\n",
" 'Geography, Environmental Studies and Archaeology',\n",
" 'Business and Management Studies', 'Law',\n",
" 'Social Work and Social Policy', 'Education',\n",
" 'English Language and Literature', 'History',\n",
" 'Art and Design: History, Practice and Theory',\n",
" 'Music, Drama, Dance and Performing Arts',\n",
" 'Communication, Cultural and Media Studies, Library and Information Management',\n",
" 'Computer Science and Informatics',\n",
" 'Electrical and Electronic Engineering, Metallurgy and Materials',\n",
" 'Area Studies', 'Modern Languages and Linguistics', 'Chemistry',\n",
" 'Physics', 'Mathematical Sciences',\n",
" 'Aeronautical, Mechanical, Chemical and Manufacturing Engineering',\n",
" 'Sport and Exercise Sciences, Leisure and Tourism',\n",
" 'Earth Systems and Environmental Sciences',\n",
" 'Economics and Econometrics', 'Politics and International Studies',\n",
" 'Sociology', 'Philosophy', 'Clinical Medicine',\n",
" 'Public Health, Health Services and Primary Care',\n",
" 'Civil and Construction Engineering', 'Classics',\n",
" 'Theology and Religious Studies',\n",
" 'Agriculture, Veterinary and Food Science',\n",
" 'Anthropology and Development Studies'], dtype=object)"
]
}
],
"prompt_number": 26
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"#How many institutions?\n",
"df['Institution code (UKPRN)'].unique().size"
],
"language": "python",
"metadata": {},
"outputs": [
{
"metadata": {},
"output_type": "pyout",
"prompt_number": 30,
"text": [
"154"
]
}
],
"prompt_number": 30
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"#How many institutions by unit of assessment, ordered?\n",
"#Rather than mulitpl count, let's base this on the Overall profile results\n",
"df[df['Profile']=='Overall'].groupby(['Unit of assessment name']).size().order(ascending=False)"
],
"language": "python",
"metadata": {},
"outputs": [
{
"metadata": {},
"output_type": "pyout",
"prompt_number": 34,
"text": [
"Unit of assessment name\n",
"Business and Management Studies 101\n",
"Allied Health Professions, Dentistry, Nursing and Pharmacy 94\n",
"Computer Science and Informatics 89\n",
"English Language and Literature 89\n",
"Music, Drama, Dance and Performing Arts 84\n",
"Art and Design: History, Practice and Theory 84\n",
"History 83\n",
"Psychology, Psychiatry and Neuroscience 82\n",
"Education 76\n",
"Geography, Environmental Studies and Archaeology 74\n",
"Communication, Cultural and Media Studies, Library and Information Management 67\n",
"Law 67\n",
"General Engineering 62\n",
"Social Work and Social Policy 62\n",
"Modern Languages and Linguistics 57\n",
"Politics and International Studies 56\n",
"Mathematical Sciences 53\n",
"Sport and Exercise Sciences, Leisure and Tourism 51\n",
"Architecture, Built Environment and Planning 45\n",
"Earth Systems and Environmental Sciences 45\n",
"Biological Sciences 44\n",
"Physics 41\n",
"Philosophy 40\n",
"Chemistry 37\n",
"Electrical and Electronic Engineering, Metallurgy and Materials 37\n",
"Theology and Religious Studies 33\n",
"Public Health, Health Services and Primary Care 32\n",
"Clinical Medicine 31\n",
"Sociology 29\n",
"Agriculture, Veterinary and Food Science 29\n",
"Economics and Econometrics 28\n",
"Anthropology and Development Studies 25\n",
"Aeronautical, Mechanical, Chemical and Manufacturing Engineering 25\n",
"Area Studies 23\n",
"Classics 22\n",
"Civil and Construction Engineering 14\n",
"dtype: int64"
]
}
],
"prompt_number": 34
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"#Which institutions submitted to most Units of Assessment?\n",
"df[df['Profile']=='Overall'].groupby(['Institution name']).size().order(ascending=False)"
],
"language": "python",
"metadata": {},
"outputs": [
{
"metadata": {},
"output_type": "pyout",
"prompt_number": 46,
"text": [
"Institution name\n",
"University College London 36\n",
"University of Manchester 35\n",
"University of Sheffield 35\n",
"University of Leeds 33\n",
"University of Birmingham 33\n",
"University of Nottingham 32\n",
"University of Cambridge 32\n",
"University of Glasgow 32\n",
"University of Oxford 31\n",
"University of Edinburgh 31\n",
"University of Bristol 31\n",
"Queen's University Belfast 28\n",
"Newcastle University 28\n",
"King's College London 27\n",
"Cardiff University 27\n",
"...\n",
"Royal College of Art 1\n",
"Norwich University of the Arts 1\n",
"Royal College of Music 1\n",
"Royal Conservatoire of Scotland 1\n",
"Royal Northern College of Music 1\n",
"SRUC 1\n",
"Guildhall School of Music & Drama 1\n",
"London Business School 1\n",
"Stranmillis University College 1\n",
"Institute of Zoology 1\n",
"Trinity Laban Conservatoire of Music and Dance 1\n",
"Heythrop College 1\n",
"Royal Academy of Music 1\n",
"Harper Adams University 1\n",
"St Mary's University College 1\n",
"Length: 154, dtype: int64"
]
}
],
"prompt_number": 46
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"The way I phrased the previous question compared to the way I ran the query assumes that an insitution can only appear once per Unit of Assessment. Is that true?"
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"#Can an institution have more than one submission to the same Units of Assessment?\n",
"df[df['Profile']=='Overall'].groupby(['Institution name','Unit of assessment name']).size().order(ascending=False)[:10]"
],
"language": "python",
"metadata": {},
"outputs": [
{
"metadata": {},
"output_type": "pyout",
"prompt_number": 53,
"text": [
"Institution name Unit of assessment name \n",
"King's College London Allied Health Professions, Dentistry, Nursing and Pharmacy 3\n",
"University College London Geography, Environmental Studies and Archaeology 2\n",
"University of Oxford Anthropology and Development Studies 2\n",
"University of Sheffield Allied Health Professions, Dentistry, Nursing and Pharmacy 2\n",
" Aeronautical, Mechanical, Chemical and Manufacturing Engineering 2\n",
"University of East Anglia Allied Health Professions, Dentistry, Nursing and Pharmacy 2\n",
"Swansea University Modern Languages and Linguistics 2\n",
"Liverpool Hope University Music, Drama, Dance and Performing Arts 2\n",
"University of Leeds Music, Drama, Dance and Performing Arts 2\n",
"University of York Music, Drama, Dance and Performing Arts 2\n",
"dtype: int64"
]
}
],
"prompt_number": 53
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Hmmm... so what's going on there then?"
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"dfo=df[df['Profile']=='Overall']\n",
"dfo[(dfo['Institution name']=='King\\'s College London') & (dfo['Unit of assessment name']=='Allied Health Professions, Dentistry, Nursing and Pharmacy')]"
],
"language": "python",
"metadata": {},
"outputs": [
{
"html": [
"<div style=\"max-height:1000px;max-width:1500px;overflow:auto;\">\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>Institution code (UKPRN)</th>\n",
" <th>Institution name</th>\n",
" <th>Institution sort order</th>\n",
" <th>Main panel</th>\n",
" <th>Unit of assessment number</th>\n",
" <th>Unit of assessment name</th>\n",
" <th>Multiple submission letter</th>\n",
" <th>Multiple submission name</th>\n",
" <th>Joint submission</th>\n",
" <th>Profile</th>\n",
" <th>FTE Category A staff submitted</th>\n",
" <th>4*</th>\n",
" <th>3*</th>\n",
" <th>2*</th>\n",
" <th>1*</th>\n",
" <th>unclassified</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>2359</th>\n",
" <td> 10003645</td>\n",
" <td> King's College London</td>\n",
" <td> 690</td>\n",
" <td> A</td>\n",
" <td> 3</td>\n",
" <td> Allied Health Professions, Dentistry, Nursing ...</td>\n",
" <td> A</td>\n",
" <td> Dentistry</td>\n",
" <td> NaN</td>\n",
" <td> Overall</td>\n",
" <td> 52.95</td>\n",
" <td> 42</td>\n",
" <td> 48</td>\n",
" <td> 9</td>\n",
" <td> 1</td>\n",
" <td> 0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2363</th>\n",
" <td> 10003645</td>\n",
" <td> King's College London</td>\n",
" <td> 690</td>\n",
" <td> A</td>\n",
" <td> 3</td>\n",
" <td> Allied Health Professions, Dentistry, Nursing ...</td>\n",
" <td> B</td>\n",
" <td> Pharmacy and Nutritional Sciences</td>\n",
" <td> NaN</td>\n",
" <td> Overall</td>\n",
" <td> 93.93</td>\n",
" <td> 42</td>\n",
" <td> 49</td>\n",
" <td> 8</td>\n",
" <td> 0</td>\n",
" <td> 1</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2367</th>\n",
" <td> 10003645</td>\n",
" <td> King's College London</td>\n",
" <td> 690</td>\n",
" <td> A</td>\n",
" <td> 3</td>\n",
" <td> Allied Health Professions, Dentistry, Nursing ...</td>\n",
" <td> C</td>\n",
" <td> Nursing and Palliative Care</td>\n",
" <td> NaN</td>\n",
" <td> Overall</td>\n",
" <td> 40.75</td>\n",
" <td> 43</td>\n",
" <td> 47</td>\n",
" <td> 10</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"metadata": {},
"output_type": "pyout",
"prompt_number": 58,
"text": [
" Institution code (UKPRN) Institution name Institution sort order \\\n",
"2359 10003645 King's College London 690 \n",
"2363 10003645 King's College London 690 \n",
"2367 10003645 King's College London 690 \n",
"\n",
" Main panel Unit of assessment number \\\n",
"2359 A 3 \n",
"2363 A 3 \n",
"2367 A 3 \n",
"\n",
" Unit of assessment name \\\n",
"2359 Allied Health Professions, Dentistry, Nursing ... \n",
"2363 Allied Health Professions, Dentistry, Nursing ... \n",
"2367 Allied Health Professions, Dentistry, Nursing ... \n",
"\n",
" Multiple submission letter Multiple submission name \\\n",
"2359 A Dentistry \n",
"2363 B Pharmacy and Nutritional Sciences \n",
"2367 C Nursing and Palliative Care \n",
"\n",
" Joint submission Profile FTE Category A staff submitted 4* 3* 2* 1* \\\n",
"2359 NaN Overall 52.95 42 48 9 1 \n",
"2363 NaN Overall 93.93 42 49 8 0 \n",
"2367 NaN Overall 40.75 43 47 10 0 \n",
"\n",
" unclassified \n",
"2359 0 \n",
"2363 1 \n",
"2367 0 "
]
}
],
"prompt_number": 58
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Ah, so we can have multiple submissions... Maybe I should have read some guidance about how the data is presented?!;-)\n",
"\n",
"In that table above, the 4\\*, 3\\*, 2\\* numbers are pretty consistent. Is that unusual? (Perhaps file that thought for later if we have time.)"
]
},
{
"cell_type": "heading",
"level": 3,
"metadata": {},
"source": [
"Ranking in a Unit of Assessment"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Folk always want league tables. How about we rank institutions in a unit of assessment? But what does rank mean? Let's start by just doing it on the basis of the *Overall* scores on the doors, omitting the number of staff submitted."
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"dfo[dfo['Unit of assessment name']=='Civil and Construction Engineering'].sort(['4*','3*','2*','1*','unclassified'],\n",
" ascending=False)[:5]"
],
"language": "python",
"metadata": {},
"outputs": [
{
"html": [
"<div style=\"max-height:1000px;max-width:1500px;overflow:auto;\">\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>Institution code (UKPRN)</th>\n",
" <th>Institution name</th>\n",
" <th>Institution sort order</th>\n",
" <th>Main panel</th>\n",
" <th>Unit of assessment number</th>\n",
" <th>Unit of assessment name</th>\n",
" <th>Multiple submission letter</th>\n",
" <th>Multiple submission name</th>\n",
" <th>Joint submission</th>\n",
" <th>Profile</th>\n",
" <th>FTE Category A staff submitted</th>\n",
" <th>4*</th>\n",
" <th>3*</th>\n",
" <th>2*</th>\n",
" <th>1*</th>\n",
" <th>unclassified</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>7203</th>\n",
" <td> 10007814</td>\n",
" <td> Cardiff University</td>\n",
" <td> 7080</td>\n",
" <td> B</td>\n",
" <td> 14</td>\n",
" <td> Civil and Construction Engineering</td>\n",
" <td> </td>\n",
" <td> NaN</td>\n",
" <td> NaN</td>\n",
" <td> Overall</td>\n",
" <td> 14.30</td>\n",
" <td> 47</td>\n",
" <td> 50</td>\n",
" <td> 3</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2179</th>\n",
" <td> 10003270</td>\n",
" <td> Imperial College London</td>\n",
" <td> 630</td>\n",
" <td> B</td>\n",
" <td> 14</td>\n",
" <td> Civil and Construction Engineering</td>\n",
" <td> </td>\n",
" <td> NaN</td>\n",
" <td> NaN</td>\n",
" <td> Overall</td>\n",
" <td> 56.60</td>\n",
" <td> 47</td>\n",
" <td> 48</td>\n",
" <td> 5</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>6279</th>\n",
" <td> 10007852</td>\n",
" <td> University of Dundee</td>\n",
" <td> 6720</td>\n",
" <td> B</td>\n",
" <td> 14</td>\n",
" <td> Civil and Construction Engineering</td>\n",
" <td> </td>\n",
" <td> NaN</td>\n",
" <td> NaN</td>\n",
" <td> Overall</td>\n",
" <td> 14.50</td>\n",
" <td> 41</td>\n",
" <td> 49</td>\n",
" <td> 10</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>3575</th>\n",
" <td> 10007798</td>\n",
" <td> University of Manchester</td>\n",
" <td> 1220</td>\n",
" <td> B</td>\n",
" <td> 14</td>\n",
" <td> Civil and Construction Engineering</td>\n",
" <td> </td>\n",
" <td> NaN</td>\n",
" <td> NaN</td>\n",
" <td> Overall</td>\n",
" <td> 21.85</td>\n",
" <td> 30</td>\n",
" <td> 60</td>\n",
" <td> 9</td>\n",
" <td> 1</td>\n",
" <td> 0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>3799</th>\n",
" <td> 10007799</td>\n",
" <td> Newcastle University</td>\n",
" <td> 1280</td>\n",
" <td> B</td>\n",
" <td> 14</td>\n",
" <td> Civil and Construction Engineering</td>\n",
" <td> </td>\n",
" <td> NaN</td>\n",
" <td> NaN</td>\n",
" <td> Overall</td>\n",
" <td> 40.60</td>\n",
" <td> 30</td>\n",
" <td> 58</td>\n",
" <td> 12</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"metadata": {},
"output_type": "pyout",
"prompt_number": 62,
"text": [
" Institution code (UKPRN) Institution name \\\n",
"7203 10007814 Cardiff University \n",
"2179 10003270 Imperial College London \n",
"6279 10007852 University of Dundee \n",
"3575 10007798 University of Manchester \n",
"3799 10007799 Newcastle University \n",
"\n",
" Institution sort order Main panel Unit of assessment number \\\n",
"7203 7080 B 14 \n",
"2179 630 B 14 \n",
"6279 6720 B 14 \n",
"3575 1220 B 14 \n",
"3799 1280 B 14 \n",
"\n",
" Unit of assessment name Multiple submission letter \\\n",
"7203 Civil and Construction Engineering \n",
"2179 Civil and Construction Engineering \n",
"6279 Civil and Construction Engineering \n",
"3575 Civil and Construction Engineering \n",
"3799 Civil and Construction Engineering \n",
"\n",
" Multiple submission name Joint submission Profile \\\n",
"7203 NaN NaN Overall \n",
"2179 NaN NaN Overall \n",
"6279 NaN NaN Overall \n",
"3575 NaN NaN Overall \n",
"3799 NaN NaN Overall \n",
"\n",
" FTE Category A staff submitted 4* 3* 2* 1* unclassified \n",
"7203 14.30 47 50 3 0 0 \n",
"2179 56.60 47 48 5 0 0 \n",
"6279 14.50 41 49 10 0 0 \n",
"3575 21.85 30 60 9 1 0 \n",
"3799 40.60 30 58 12 0 0 "
]
}
],
"prompt_number": 62
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"How does this compare with a ranking on the basis of another Profile? eg *Impact*?"
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"dfi=df[df['Profile']=='Impact']\n",
"dfi[dfi['Unit of assessment name']=='Civil and Construction Engineering'].sort(['4*','3*','2*','1*','unclassified'],\n",
" ascending=False)[:5]"
],
"language": "python",
"metadata": {},
"outputs": [
{
"html": [
"<div style=\"max-height:1000px;max-width:1500px;overflow:auto;\">\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>Institution code (UKPRN)</th>\n",
" <th>Institution name</th>\n",
" <th>Institution sort order</th>\n",
" <th>Main panel</th>\n",
" <th>Unit of assessment number</th>\n",
" <th>Unit of assessment name</th>\n",
" <th>Multiple submission letter</th>\n",
" <th>Multiple submission name</th>\n",
" <th>Joint submission</th>\n",
" <th>Profile</th>\n",
" <th>FTE Category A staff submitted</th>\n",
" <th>4*</th>\n",
" <th>3*</th>\n",
" <th>2*</th>\n",
" <th>1*</th>\n",
" <th>unclassified</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>7201</th>\n",
" <td> 10007814</td>\n",
" <td> Cardiff University</td>\n",
" <td> 7080</td>\n",
" <td> B</td>\n",
" <td> 14</td>\n",
" <td> Civil and Construction Engineering</td>\n",
" <td> </td>\n",
" <td> NaN</td>\n",
" <td> NaN</td>\n",
" <td> Impact</td>\n",
" <td> 14.30</td>\n",
" <td> 100</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2177</th>\n",
" <td> 10003270</td>\n",
" <td> Imperial College London</td>\n",
" <td> 630</td>\n",
" <td> B</td>\n",
" <td> 14</td>\n",
" <td> Civil and Construction Engineering</td>\n",
" <td> </td>\n",
" <td> NaN</td>\n",
" <td> NaN</td>\n",
" <td> Impact</td>\n",
" <td> 56.60</td>\n",
" <td> 65.7</td>\n",
" <td> 34.3</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>3573</th>\n",
" <td> 10007798</td>\n",
" <td> University of Manchester</td>\n",
" <td> 1220</td>\n",
" <td> B</td>\n",
" <td> 14</td>\n",
" <td> Civil and Construction Engineering</td>\n",
" <td> </td>\n",
" <td> NaN</td>\n",
" <td> NaN</td>\n",
" <td> Impact</td>\n",
" <td> 21.85</td>\n",
" <td> 50</td>\n",
" <td> 50</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>6277</th>\n",
" <td> 10007852</td>\n",
" <td> University of Dundee</td>\n",
" <td> 6720</td>\n",
" <td> B</td>\n",
" <td> 14</td>\n",
" <td> Civil and Construction Engineering</td>\n",
" <td> </td>\n",
" <td> NaN</td>\n",
" <td> NaN</td>\n",
" <td> Impact</td>\n",
" <td> 14.50</td>\n",
" <td> 50</td>\n",
" <td> 30</td>\n",
" <td> 20</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>3797</th>\n",
" <td> 10007799</td>\n",
" <td> Newcastle University</td>\n",
" <td> 1280</td>\n",
" <td> B</td>\n",
" <td> 14</td>\n",
" <td> Civil and Construction Engineering</td>\n",
" <td> </td>\n",
" <td> NaN</td>\n",
" <td> NaN</td>\n",
" <td> Impact</td>\n",
" <td> 40.60</td>\n",
" <td> 42</td>\n",
" <td> 58</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"metadata": {},
"output_type": "pyout",
"prompt_number": 63,
"text": [
" Institution code (UKPRN) Institution name \\\n",
"7201 10007814 Cardiff University \n",
"2177 10003270 Imperial College London \n",
"3573 10007798 University of Manchester \n",
"6277 10007852 University of Dundee \n",
"3797 10007799 Newcastle University \n",
"\n",
" Institution sort order Main panel Unit of assessment number \\\n",
"7201 7080 B 14 \n",
"2177 630 B 14 \n",
"3573 1220 B 14 \n",
"6277 6720 B 14 \n",
"3797 1280 B 14 \n",
"\n",
" Unit of assessment name Multiple submission letter \\\n",
"7201 Civil and Construction Engineering \n",
"2177 Civil and Construction Engineering \n",
"3573 Civil and Construction Engineering \n",
"6277 Civil and Construction Engineering \n",
"3797 Civil and Construction Engineering \n",
"\n",
" Multiple submission name Joint submission Profile \\\n",
"7201 NaN NaN Impact \n",
"2177 NaN NaN Impact \n",
"3573 NaN NaN Impact \n",
"6277 NaN NaN Impact \n",
"3797 NaN NaN Impact \n",
"\n",
" FTE Category A staff submitted 4* 3* 2* 1* unclassified \n",
"7201 14.30 100 0 0 0 0 \n",
"2177 56.60 65.7 34.3 0 0 0 \n",
"3573 21.85 50 50 0 0 0 \n",
"6277 14.50 50 30 20 0 0 \n",
"3797 40.60 42 58 0 0 0 "
]
}
],
"prompt_number": 63
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"This may be an interesting canned question... Take in the name of a unit of assessment and a profile, and return the sorted table."
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"def rankUoAbyProfile(uoa,profile):\n",
" tmp=df[df['Profile']==profile]\n",
" tmp=tmp[tmp['Unit of assessment name']==uoa].sort(['4*','3*','2*','1*','unclassified'],ascending=False)\n",
" return tmp"
],
"language": "python",
"metadata": {},
"outputs": [],
"prompt_number": 66
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"rankUoAbyProfile('Computer Science and Informatics','Environment')[:5]"
],
"language": "python",
"metadata": {},
"outputs": []
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"I guess another way of looking at insitutions is by the number of people they're submitting? Can we assume that each profile has the same number of FTEs associated with it? Go with that for now, but really should check."
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"def rankUoAbySize(uoa,profile='Overall'):\n",
" tmp=df[df['Profile']==profile]\n",
" tmp=tmp[tmp['Unit of assessment name']==uoa].sort(['FTE Category A staff submitted','4*','3*','2*','1*','unclassified'],ascending=False)\n",
" return tmp"
],
"language": "python",
"metadata": {},
"outputs": [],
"prompt_number": 73
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"rankUoAbySize('History')[:5]"
],
"language": "python",
"metadata": {},
"outputs": [
{
"html": [
"<div style=\"max-height:1000px;max-width:1500px;overflow:auto;\">\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>Institution code (UKPRN)</th>\n",
" <th>Institution name</th>\n",
" <th>Institution sort order</th>\n",
" <th>Main panel</th>\n",
" <th>Unit of assessment number</th>\n",
" <th>Unit of assessment name</th>\n",
" <th>Multiple submission letter</th>\n",
" <th>Multiple submission name</th>\n",
" <th>Joint submission</th>\n",
" <th>Profile</th>\n",
" <th>FTE Category A staff submitted</th>\n",
" <th>4*</th>\n",
" <th>3*</th>\n",
" <th>2*</th>\n",
" <th>1*</th>\n",
" <th>unclassified</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>4399</th>\n",
" <td> 10007774</td>\n",
" <td> University of Oxford</td>\n",
" <td> 1410</td>\n",
" <td> D</td>\n",
" <td> 30</td>\n",
" <td> History</td>\n",
" <td> </td>\n",
" <td> NaN</td>\n",
" <td> NaN</td>\n",
" <td> Overall</td>\n",
" <td> 130.05</td>\n",
" <td> 45</td>\n",
" <td> 37</td>\n",
" <td> 17</td>\n",
" <td> 1</td>\n",
" <td> 0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>915 </th>\n",
" <td> 10007788</td>\n",
" <td> University of Cambridge</td>\n",
" <td> 220</td>\n",
" <td> D</td>\n",
" <td> 30</td>\n",
" <td> History</td>\n",
" <td> </td>\n",
" <td> NaN</td>\n",
" <td> NaN</td>\n",
" <td> Overall</td>\n",
" <td> 115.10</td>\n",
" <td> 44</td>\n",
" <td> 37</td>\n",
" <td> 18</td>\n",
" <td> 1</td>\n",
" <td> 0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>6431</th>\n",
" <td> 10007790</td>\n",
" <td> University of Edinburgh</td>\n",
" <td> 6730</td>\n",
" <td> D</td>\n",
" <td> 30</td>\n",
" <td> History</td>\n",
" <td> </td>\n",
" <td> NaN</td>\n",
" <td> NaN</td>\n",
" <td> Overall</td>\n",
" <td> 61.22</td>\n",
" <td> 32</td>\n",
" <td> 51</td>\n",
" <td> 15</td>\n",
" <td> 2</td>\n",
" <td> 0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>3351</th>\n",
" <td> 10004063</td>\n",
" <td> London School of Economics and Political Science</td>\n",
" <td> 1150</td>\n",
" <td> D</td>\n",
" <td> 30</td>\n",
" <td> History</td>\n",
" <td> </td>\n",
" <td> NaN</td>\n",
" <td> NaN</td>\n",
" <td> Overall</td>\n",
" <td> 44.00</td>\n",
" <td> 34</td>\n",
" <td> 48</td>\n",
" <td> 17</td>\n",
" <td> 1</td>\n",
" <td> 0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>6591</th>\n",
" <td> 10007794</td>\n",
" <td> University of Glasgow</td>\n",
" <td> 6760</td>\n",
" <td> D</td>\n",
" <td> 30</td>\n",
" <td> History</td>\n",
" <td> </td>\n",
" <td> NaN</td>\n",
" <td> NaN</td>\n",
" <td> Overall</td>\n",
" <td> 43.80</td>\n",
" <td> 40</td>\n",
" <td> 40</td>\n",
" <td> 18</td>\n",
" <td> 2</td>\n",
" <td> 0</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"metadata": {},
"output_type": "pyout",
"prompt_number": 74,
"text": [
" Institution code (UKPRN) \\\n",
"4399 10007774 \n",
"915 10007788 \n",
"6431 10007790 \n",
"3351 10004063 \n",
"6591 10007794 \n",
"\n",
" Institution name \\\n",
"4399 University of Oxford \n",
"915 University of Cambridge \n",
"6431 University of Edinburgh \n",
"3351 London School of Economics and Political Science \n",
"6591 University of Glasgow \n",
"\n",
" Institution sort order Main panel Unit of assessment number \\\n",
"4399 1410 D 30 \n",
"915 220 D 30 \n",
"6431 6730 D 30 \n",
"3351 1150 D 30 \n",
"6591 6760 D 30 \n",
"\n",
" Unit of assessment name Multiple submission letter \\\n",
"4399 History \n",
"915 History \n",
"6431 History \n",
"3351 History \n",
"6591 History \n",
"\n",
" Multiple submission name Joint submission Profile \\\n",
"4399 NaN NaN Overall \n",
"915 NaN NaN Overall \n",
"6431 NaN NaN Overall \n",
"3351 NaN NaN Overall \n",
"6591 NaN NaN Overall \n",
"\n",
" FTE Category A staff submitted 4* 3* 2* 1* unclassified \n",
"4399 130.05 45 37 17 1 0 \n",
"915 115.10 44 37 18 1 0 \n",
"6431 61.22 32 51 15 2 0 \n",
"3351 44.00 34 48 17 1 0 \n",
"6591 43.80 40 40 18 2 0 "
]
}
],
"prompt_number": 74
},
{
"cell_type": "heading",
"level": 3,
"metadata": {},
"source": [
"Within an Institution..."
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Which submission attracted most entries?"
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"def internalSize(hei):\n",
" tmp=dfo[dfo['Institution name']==hei]\n",
" tmp=tmp.sort(['FTE Category A staff submitted','4*','3*','2*','1*','unclassified'],ascending=False)\n",
" return tmp"
],
"language": "python",
"metadata": {},
"outputs": [],
"prompt_number": 75
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"internalSize(\"Open University\")"
],
"language": "python",
"metadata": {},
"outputs": [
{
"html": [
"<div style=\"max-height:1000px;max-width:1500px;overflow:auto;\">\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>Institution code (UKPRN)</th>\n",
" <th>Institution name</th>\n",
" <th>Institution sort order</th>\n",
" <th>Main panel</th>\n",
" <th>Unit of assessment number</th>\n",
" <th>Unit of assessment name</th>\n",
" <th>Multiple submission letter</th>\n",
" <th>Multiple submission name</th>\n",
" <th>Joint submission</th>\n",
" <th>Profile</th>\n",
" <th>FTE Category A staff submitted</th>\n",
" <th>4*</th>\n",
" <th>3*</th>\n",
" <th>2*</th>\n",
" <th>1*</th>\n",
" <th>unclassified</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>4187</th>\n",
" <td> 10007773</td>\n",
" <td> Open University</td>\n",
" <td> 1390</td>\n",
" <td> B</td>\n",
" <td> 7</td>\n",
" <td> Earth Systems and Environmental Sciences</td>\n",
" <td> </td>\n",
" <td> NaN</td>\n",
" <td> NaN</td>\n",
" <td> Overall</td>\n",
" <td> 58.01</td>\n",
" <td> 11</td>\n",
" <td> 66</td>\n",
" <td> 22</td>\n",
" <td> 1</td>\n",
" <td> 0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4223</th>\n",
" <td> 10007773</td>\n",
" <td> Open University</td>\n",
" <td> 1390</td>\n",
" <td> C</td>\n",
" <td> 25</td>\n",
" <td> Education</td>\n",
" <td> </td>\n",
" <td> NaN</td>\n",
" <td> NaN</td>\n",
" <td> Overall</td>\n",
" <td> 54.26</td>\n",
" <td> 38</td>\n",
" <td> 31</td>\n",
" <td> 26</td>\n",
" <td> 5</td>\n",
" <td> 0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4215</th>\n",
" <td> 10007773</td>\n",
" <td> Open University</td>\n",
" <td> 1390</td>\n",
" <td> C</td>\n",
" <td> 23</td>\n",
" <td> Sociology</td>\n",
" <td> </td>\n",
" <td> NaN</td>\n",
" <td> NaN</td>\n",
" <td> Overall</td>\n",
" <td> 37.00</td>\n",
" <td> 22</td>\n",
" <td> 42</td>\n",
" <td> 36</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4195</th>\n",
" <td> 10007773</td>\n",
" <td> Open University</td>\n",
" <td> 1390</td>\n",
" <td> B</td>\n",
" <td> 11</td>\n",
" <td> Computer Science and Informatics</td>\n",
" <td> </td>\n",
" <td> NaN</td>\n",
" <td> NaN</td>\n",
" <td> Overall</td>\n",
" <td> 31.10</td>\n",
" <td> 13</td>\n",
" <td> 62</td>\n",
" <td> 24</td>\n",
" <td> 1</td>\n",
" <td> 0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4247</th>\n",
" <td> 10007773</td>\n",
" <td> Open University</td>\n",
" <td> 1390</td>\n",
" <td> D</td>\n",
" <td> 34</td>\n",
" <td> Art and Design: History, Practice and Theory</td>\n",
" <td> </td>\n",
" <td> NaN</td>\n",
" <td> NaN</td>\n",
" <td> Overall</td>\n",
" <td> 23.20</td>\n",
" <td> 29</td>\n",
" <td> 57</td>\n",
" <td> 12</td>\n",
" <td> 2</td>\n",
" <td> 0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4219</th>\n",
" <td> 10007773</td>\n",
" <td> Open University</td>\n",
" <td> 1390</td>\n",
" <td> C</td>\n",
" <td> 24</td>\n",
" <td> Anthropology and Development Studies</td>\n",
" <td> </td>\n",
" <td> NaN</td>\n",
" <td> NaN</td>\n",
" <td> Overall</td>\n",
" <td> 22.10</td>\n",
" <td> 24</td>\n",
" <td> 45</td>\n",
" <td> 27</td>\n",
" <td> 4</td>\n",
" <td> 0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4191</th>\n",
" <td> 10007773</td>\n",
" <td> Open University</td>\n",
" <td> 1390</td>\n",
" <td> B</td>\n",
" <td> 10</td>\n",
" <td> Mathematical Sciences</td>\n",
" <td> </td>\n",
" <td> NaN</td>\n",
" <td> NaN</td>\n",
" <td> Overall</td>\n",
" <td> 18.80</td>\n",
" <td> 9</td>\n",
" <td> 53</td>\n",
" <td> 33</td>\n",
" <td> 0</td>\n",
" <td> 5</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4211</th>\n",
" <td> 10007773</td>\n",
" <td> Open University</td>\n",
" <td> 1390</td>\n",
" <td> C</td>\n",
" <td> 22</td>\n",
" <td> Social Work and Social Policy</td>\n",
" <td> </td>\n",
" <td> NaN</td>\n",
" <td> NaN</td>\n",
" <td> Overall</td>\n",
" <td> 18.60</td>\n",
" <td> 15</td>\n",
" <td> 54</td>\n",
" <td> 29</td>\n",
" <td> 2</td>\n",
" <td> 0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4199</th>\n",
" <td> 10007773</td>\n",
" <td> Open University</td>\n",
" <td> 1390</td>\n",
" <td> B</td>\n",
" <td> 13</td>\n",
" <td> Electrical and Electronic Engineering, Metallu...</td>\n",
" <td> </td>\n",
" <td> NaN</td>\n",
" <td> NaN</td>\n",
" <td> Overall</td>\n",
" <td> 18.00</td>\n",
" <td> 8</td>\n",
" <td> 77</td>\n",
" <td> 15</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4207</th>\n",
" <td> 10007773</td>\n",
" <td> Open University</td>\n",
" <td> 1390</td>\n",
" <td> C</td>\n",
" <td> 19</td>\n",
" <td> Business and Management Studies</td>\n",
" <td> </td>\n",
" <td> NaN</td>\n",
" <td> NaN</td>\n",
" <td> Overall</td>\n",
" <td> 17.90</td>\n",
" <td> 19</td>\n",
" <td> 53</td>\n",
" <td> 25</td>\n",
" <td> 3</td>\n",
" <td> 0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4183</th>\n",
" <td> 10007773</td>\n",
" <td> Open University</td>\n",
" <td> 1390</td>\n",
" <td> A</td>\n",
" <td> 3</td>\n",
" <td> Allied Health Professions, Dentistry, Nursing ...</td>\n",
" <td> </td>\n",
" <td> NaN</td>\n",
" <td> NaN</td>\n",
" <td> Overall</td>\n",
" <td> 17.00</td>\n",
" <td> 16</td>\n",
" <td> 61</td>\n",
" <td> 22</td>\n",
" <td> 1</td>\n",
" <td> 0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4227</th>\n",
" <td> 10007773</td>\n",
" <td> Open University</td>\n",
" <td> 1390</td>\n",
" <td> D</td>\n",
" <td> 29</td>\n",
" <td> English Language and Literature</td>\n",
" <td> </td>\n",
" <td> NaN</td>\n",
" <td> NaN</td>\n",
" <td> Overall</td>\n",
" <td> 16.50</td>\n",
" <td> 26</td>\n",
" <td> 50</td>\n",
" <td> 23</td>\n",
" <td> 1</td>\n",
" <td> 0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4231</th>\n",
" <td> 10007773</td>\n",
" <td> Open University</td>\n",
" <td> 1390</td>\n",
" <td> D</td>\n",
" <td> 30</td>\n",
" <td> History</td>\n",
" <td> </td>\n",
" <td> NaN</td>\n",
" <td> NaN</td>\n",
" <td> Overall</td>\n",
" <td> 14.30</td>\n",
" <td> 27</td>\n",
" <td> 49</td>\n",
" <td> 23</td>\n",
" <td> 1</td>\n",
" <td> 0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4203</th>\n",
" <td> 10007773</td>\n",
" <td> Open University</td>\n",
" <td> 1390</td>\n",
" <td> C</td>\n",
" <td> 17</td>\n",
" <td> Geography, Environmental Studies and Archaeology</td>\n",
" <td> </td>\n",
" <td> NaN</td>\n",
" <td> NaN</td>\n",
" <td> Overall</td>\n",
" <td> 13.00</td>\n",
" <td> 23</td>\n",
" <td> 53</td>\n",
" <td> 21</td>\n",
" <td> 3</td>\n",
" <td> 0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4235</th>\n",
" <td> 10007773</td>\n",
" <td> Open University</td>\n",
" <td> 1390</td>\n",
" <td> D</td>\n",
" <td> 31</td>\n",
" <td> Classics</td>\n",
" <td> </td>\n",
" <td> NaN</td>\n",
" <td> NaN</td>\n",
" <td> Overall</td>\n",
" <td> 11.80</td>\n",
" <td> 16</td>\n",
" <td> 39</td>\n",
" <td> 42</td>\n",
" <td> 3</td>\n",
" <td> 0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4251</th>\n",
" <td> 10007773</td>\n",
" <td> Open University</td>\n",
" <td> 1390</td>\n",
" <td> D</td>\n",
" <td> 35</td>\n",
" <td> Music, Drama, Dance and Performing Arts</td>\n",
" <td> </td>\n",
" <td> NaN</td>\n",
" <td> NaN</td>\n",
" <td> Overall</td>\n",
" <td> 10.60</td>\n",
" <td> 44</td>\n",
" <td> 50</td>\n",
" <td> 6</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4239</th>\n",
" <td> 10007773</td>\n",
" <td> Open University</td>\n",
" <td> 1390</td>\n",
" <td> D</td>\n",
" <td> 32</td>\n",
" <td> Philosophy</td>\n",
" <td> </td>\n",
" <td> NaN</td>\n",
" <td> NaN</td>\n",
" <td> Overall</td>\n",
" <td> 8.00</td>\n",
" <td> 6</td>\n",
" <td> 31</td>\n",
" <td> 59</td>\n",
" <td> 4</td>\n",
" <td> 0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4243</th>\n",
" <td> 10007773</td>\n",
" <td> Open University</td>\n",
" <td> 1390</td>\n",
" <td> D</td>\n",
" <td> 33</td>\n",
" <td> Theology and Religious Studies</td>\n",
" <td> </td>\n",
" <td> NaN</td>\n",
" <td> NaN</td>\n",
" <td> Overall</td>\n",
" <td> 6.00</td>\n",
" <td> 18</td>\n",
" <td> 35</td>\n",
" <td> 47</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"metadata": {},
"output_type": "pyout",
"prompt_number": 76,
"text": [
" Institution code (UKPRN) Institution name Institution sort order \\\n",
"4187 10007773 Open University 1390 \n",
"4223 10007773 Open University 1390 \n",
"4215 10007773 Open University 1390 \n",
"4195 10007773 Open University 1390 \n",
"4247 10007773 Open University 1390 \n",
"4219 10007773 Open University 1390 \n",
"4191 10007773 Open University 1390 \n",
"4211 10007773 Open University 1390 \n",
"4199 10007773 Open University 1390 \n",
"4207 10007773 Open University 1390 \n",
"4183 10007773 Open University 1390 \n",
"4227 10007773 Open University 1390 \n",
"4231 10007773 Open University 1390 \n",
"4203 10007773 Open University 1390 \n",
"4235 10007773 Open University 1390 \n",
"4251 10007773 Open University 1390 \n",
"4239 10007773 Open University 1390 \n",
"4243 10007773 Open University 1390 \n",
"\n",
" Main panel Unit of assessment number \\\n",
"4187 B 7 \n",
"4223 C 25 \n",
"4215 C 23 \n",
"4195 B 11 \n",
"4247 D 34 \n",
"4219 C 24 \n",
"4191 B 10 \n",
"4211 C 22 \n",
"4199 B 13 \n",
"4207 C 19 \n",
"4183 A 3 \n",
"4227 D 29 \n",
"4231 D 30 \n",
"4203 C 17 \n",
"4235 D 31 \n",
"4251 D 35 \n",
"4239 D 32 \n",
"4243 D 33 \n",
"\n",
" Unit of assessment name \\\n",
"4187 Earth Systems and Environmental Sciences \n",
"4223 Education \n",
"4215 Sociology \n",
"4195 Computer Science and Informatics \n",
"4247 Art and Design: History, Practice and Theory \n",
"4219 Anthropology and Development Studies \n",
"4191 Mathematical Sciences \n",
"4211 Social Work and Social Policy \n",
"4199 Electrical and Electronic Engineering, Metallu... \n",
"4207 Business and Management Studies \n",
"4183 Allied Health Professions, Dentistry, Nursing ... \n",
"4227 English Language and Literature \n",
"4231 History \n",
"4203 Geography, Environmental Studies and Archaeology \n",
"4235 Classics \n",
"4251 Music, Drama, Dance and Performing Arts \n",
"4239 Philosophy \n",
"4243 Theology and Religious Studies \n",
"\n",
" Multiple submission letter Multiple submission name Joint submission \\\n",
"4187 NaN NaN \n",
"4223 NaN NaN \n",
"4215 NaN NaN \n",
"4195 NaN NaN \n",
"4247 NaN NaN \n",
"4219 NaN NaN \n",
"4191 NaN NaN \n",
"4211 NaN NaN \n",
"4199 NaN NaN \n",
"4207 NaN NaN \n",
"4183 NaN NaN \n",
"4227 NaN NaN \n",
"4231 NaN NaN \n",
"4203 NaN NaN \n",
"4235 NaN NaN \n",
"4251 NaN NaN \n",
"4239 NaN NaN \n",
"4243 NaN NaN \n",
"\n",
" Profile FTE Category A staff submitted 4* 3* 2* 1* unclassified \n",
"4187 Overall 58.01 11 66 22 1 0 \n",
"4223 Overall 54.26 38 31 26 5 0 \n",
"4215 Overall 37.00 22 42 36 0 0 \n",
"4195 Overall 31.10 13 62 24 1 0 \n",
"4247 Overall 23.20 29 57 12 2 0 \n",
"4219 Overall 22.10 24 45 27 4 0 \n",
"4191 Overall 18.80 9 53 33 0 5 \n",
"4211 Overall 18.60 15 54 29 2 0 \n",
"4199 Overall 18.00 8 77 15 0 0 \n",
"4207 Overall 17.90 19 53 25 3 0 \n",
"4183 Overall 17.00 16 61 22 1 0 \n",
"4227 Overall 16.50 26 50 23 1 0 \n",
"4231 Overall 14.30 27 49 23 1 0 \n",
"4203 Overall 13.00 23 53 21 3 0 \n",
"4235 Overall 11.80 16 39 42 3 0 \n",
"4251 Overall 10.60 44 50 6 0 0 \n",
"4239 Overall 8.00 6 31 59 4 0 \n",
"4243 Overall 6.00 18 35 47 0 0 "
]
}
],
"prompt_number": 76
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"How about ranking on the rankings within an institution?"
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"def internalRanking(hei):\n",
" tmp=dfo[dfo['Institution name']==hei]\n",
" tmp=tmp.sort(['4*','3*','2*','1*','unclassified'],ascending=False)\n",
" return tmp"
],
"language": "python",
"metadata": {},
"outputs": [],
"prompt_number": 77
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"internalRanking(\"Open University\")"
],
"language": "python",
"metadata": {},
"outputs": [
{
"html": [
"<div style=\"max-height:1000px;max-width:1500px;overflow:auto;\">\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>Institution code (UKPRN)</th>\n",
" <th>Institution name</th>\n",
" <th>Institution sort order</th>\n",
" <th>Main panel</th>\n",
" <th>Unit of assessment number</th>\n",
" <th>Unit of assessment name</th>\n",
" <th>Multiple submission letter</th>\n",
" <th>Multiple submission name</th>\n",
" <th>Joint submission</th>\n",
" <th>Profile</th>\n",
" <th>FTE Category A staff submitted</th>\n",
" <th>4*</th>\n",
" <th>3*</th>\n",
" <th>2*</th>\n",
" <th>1*</th>\n",
" <th>unclassified</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>4251</th>\n",
" <td> 10007773</td>\n",
" <td> Open University</td>\n",
" <td> 1390</td>\n",
" <td> D</td>\n",
" <td> 35</td>\n",
" <td> Music, Drama, Dance and Performing Arts</td>\n",
" <td> </td>\n",
" <td> NaN</td>\n",
" <td> NaN</td>\n",
" <td> Overall</td>\n",
" <td> 10.60</td>\n",
" <td> 44</td>\n",
" <td> 50</td>\n",
" <td> 6</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4223</th>\n",
" <td> 10007773</td>\n",
" <td> Open University</td>\n",
" <td> 1390</td>\n",
" <td> C</td>\n",
" <td> 25</td>\n",
" <td> Education</td>\n",
" <td> </td>\n",
" <td> NaN</td>\n",
" <td> NaN</td>\n",
" <td> Overall</td>\n",
" <td> 54.26</td>\n",
" <td> 38</td>\n",
" <td> 31</td>\n",
" <td> 26</td>\n",
" <td> 5</td>\n",
" <td> 0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4247</th>\n",
" <td> 10007773</td>\n",
" <td> Open University</td>\n",
" <td> 1390</td>\n",
" <td> D</td>\n",
" <td> 34</td>\n",
" <td> Art and Design: History, Practice and Theory</td>\n",
" <td> </td>\n",
" <td> NaN</td>\n",
" <td> NaN</td>\n",
" <td> Overall</td>\n",
" <td> 23.20</td>\n",
" <td> 29</td>\n",
" <td> 57</td>\n",
" <td> 12</td>\n",
" <td> 2</td>\n",
" <td> 0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4231</th>\n",
" <td> 10007773</td>\n",
" <td> Open University</td>\n",
" <td> 1390</td>\n",
" <td> D</td>\n",
" <td> 30</td>\n",
" <td> History</td>\n",
" <td> </td>\n",
" <td> NaN</td>\n",
" <td> NaN</td>\n",
" <td> Overall</td>\n",
" <td> 14.30</td>\n",
" <td> 27</td>\n",
" <td> 49</td>\n",
" <td> 23</td>\n",
" <td> 1</td>\n",
" <td> 0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4227</th>\n",
" <td> 10007773</td>\n",
" <td> Open University</td>\n",
" <td> 1390</td>\n",
" <td> D</td>\n",
" <td> 29</td>\n",
" <td> English Language and Literature</td>\n",
" <td> </td>\n",
" <td> NaN</td>\n",
" <td> NaN</td>\n",
" <td> Overall</td>\n",
" <td> 16.50</td>\n",
" <td> 26</td>\n",
" <td> 50</td>\n",
" <td> 23</td>\n",
" <td> 1</td>\n",
" <td> 0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4219</th>\n",
" <td> 10007773</td>\n",
" <td> Open University</td>\n",
" <td> 1390</td>\n",
" <td> C</td>\n",
" <td> 24</td>\n",
" <td> Anthropology and Development Studies</td>\n",
" <td> </td>\n",
" <td> NaN</td>\n",
" <td> NaN</td>\n",
" <td> Overall</td>\n",
" <td> 22.10</td>\n",
" <td> 24</td>\n",
" <td> 45</td>\n",
" <td> 27</td>\n",
" <td> 4</td>\n",
" <td> 0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4203</th>\n",
" <td> 10007773</td>\n",
" <td> Open University</td>\n",
" <td> 1390</td>\n",
" <td> C</td>\n",
" <td> 17</td>\n",
" <td> Geography, Environmental Studies and Archaeology</td>\n",
" <td> </td>\n",
" <td> NaN</td>\n",
" <td> NaN</td>\n",
" <td> Overall</td>\n",
" <td> 13.00</td>\n",
" <td> 23</td>\n",
" <td> 53</td>\n",
" <td> 21</td>\n",
" <td> 3</td>\n",
" <td> 0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4215</th>\n",
" <td> 10007773</td>\n",
" <td> Open University</td>\n",
" <td> 1390</td>\n",
" <td> C</td>\n",
" <td> 23</td>\n",
" <td> Sociology</td>\n",
" <td> </td>\n",
" <td> NaN</td>\n",
" <td> NaN</td>\n",
" <td> Overall</td>\n",
" <td> 37.00</td>\n",
" <td> 22</td>\n",
" <td> 42</td>\n",
" <td> 36</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4207</th>\n",
" <td> 10007773</td>\n",
" <td> Open University</td>\n",
" <td> 1390</td>\n",
" <td> C</td>\n",
" <td> 19</td>\n",
" <td> Business and Management Studies</td>\n",
" <td> </td>\n",
" <td> NaN</td>\n",
" <td> NaN</td>\n",
" <td> Overall</td>\n",
" <td> 17.90</td>\n",
" <td> 19</td>\n",
" <td> 53</td>\n",
" <td> 25</td>\n",
" <td> 3</td>\n",
" <td> 0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4243</th>\n",
" <td> 10007773</td>\n",
" <td> Open University</td>\n",
" <td> 1390</td>\n",
" <td> D</td>\n",
" <td> 33</td>\n",
" <td> Theology and Religious Studies</td>\n",
" <td> </td>\n",
" <td> NaN</td>\n",
" <td> NaN</td>\n",
" <td> Overall</td>\n",
" <td> 6.00</td>\n",
" <td> 18</td>\n",
" <td> 35</td>\n",
" <td> 47</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4183</th>\n",
" <td> 10007773</td>\n",
" <td> Open University</td>\n",
" <td> 1390</td>\n",
" <td> A</td>\n",
" <td> 3</td>\n",
" <td> Allied Health Professions, Dentistry, Nursing ...</td>\n",
" <td> </td>\n",
" <td> NaN</td>\n",
" <td> NaN</td>\n",
" <td> Overall</td>\n",
" <td> 17.00</td>\n",
" <td> 16</td>\n",
" <td> 61</td>\n",
" <td> 22</td>\n",
" <td> 1</td>\n",
" <td> 0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4235</th>\n",
" <td> 10007773</td>\n",
" <td> Open University</td>\n",
" <td> 1390</td>\n",
" <td> D</td>\n",
" <td> 31</td>\n",
" <td> Classics</td>\n",
" <td> </td>\n",
" <td> NaN</td>\n",
" <td> NaN</td>\n",
" <td> Overall</td>\n",
" <td> 11.80</td>\n",
" <td> 16</td>\n",
" <td> 39</td>\n",
" <td> 42</td>\n",
" <td> 3</td>\n",
" <td> 0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4211</th>\n",
" <td> 10007773</td>\n",
" <td> Open University</td>\n",
" <td> 1390</td>\n",
" <td> C</td>\n",
" <td> 22</td>\n",
" <td> Social Work and Social Policy</td>\n",
" <td> </td>\n",
" <td> NaN</td>\n",
" <td> NaN</td>\n",
" <td> Overall</td>\n",
" <td> 18.60</td>\n",
" <td> 15</td>\n",
" <td> 54</td>\n",
" <td> 29</td>\n",
" <td> 2</td>\n",
" <td> 0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4195</th>\n",
" <td> 10007773</td>\n",
" <td> Open University</td>\n",
" <td> 1390</td>\n",
" <td> B</td>\n",
" <td> 11</td>\n",
" <td> Computer Science and Informatics</td>\n",
" <td> </td>\n",
" <td> NaN</td>\n",
" <td> NaN</td>\n",
" <td> Overall</td>\n",
" <td> 31.10</td>\n",
" <td> 13</td>\n",
" <td> 62</td>\n",
" <td> 24</td>\n",
" <td> 1</td>\n",
" <td> 0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4187</th>\n",
" <td> 10007773</td>\n",
" <td> Open University</td>\n",
" <td> 1390</td>\n",
" <td> B</td>\n",
" <td> 7</td>\n",
" <td> Earth Systems and Environmental Sciences</td>\n",
" <td> </td>\n",
" <td> NaN</td>\n",
" <td> NaN</td>\n",
" <td> Overall</td>\n",
" <td> 58.01</td>\n",
" <td> 11</td>\n",
" <td> 66</td>\n",
" <td> 22</td>\n",
" <td> 1</td>\n",
" <td> 0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4191</th>\n",
" <td> 10007773</td>\n",
" <td> Open University</td>\n",
" <td> 1390</td>\n",
" <td> B</td>\n",
" <td> 10</td>\n",
" <td> Mathematical Sciences</td>\n",
" <td> </td>\n",
" <td> NaN</td>\n",
" <td> NaN</td>\n",
" <td> Overall</td>\n",
" <td> 18.80</td>\n",
" <td> 9</td>\n",
" <td> 53</td>\n",
" <td> 33</td>\n",
" <td> 0</td>\n",
" <td> 5</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4199</th>\n",
" <td> 10007773</td>\n",
" <td> Open University</td>\n",
" <td> 1390</td>\n",
" <td> B</td>\n",
" <td> 13</td>\n",
" <td> Electrical and Electronic Engineering, Metallu...</td>\n",
" <td> </td>\n",
" <td> NaN</td>\n",
" <td> NaN</td>\n",
" <td> Overall</td>\n",
" <td> 18.00</td>\n",
" <td> 8</td>\n",
" <td> 77</td>\n",
" <td> 15</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4239</th>\n",
" <td> 10007773</td>\n",
" <td> Open University</td>\n",
" <td> 1390</td>\n",
" <td> D</td>\n",
" <td> 32</td>\n",
" <td> Philosophy</td>\n",
" <td> </td>\n",
" <td> NaN</td>\n",
" <td> NaN</td>\n",
" <td> Overall</td>\n",
" <td> 8.00</td>\n",
" <td> 6</td>\n",
" <td> 31</td>\n",
" <td> 59</td>\n",
" <td> 4</td>\n",
" <td> 0</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"metadata": {},
"output_type": "pyout",
"prompt_number": 78,
"text": [
" Institution code (UKPRN) Institution name Institution sort order \\\n",
"4251 10007773 Open University 1390 \n",
"4223 10007773 Open University 1390 \n",
"4247 10007773 Open University 1390 \n",
"4231 10007773 Open University 1390 \n",
"4227 10007773 Open University 1390 \n",
"4219 10007773 Open University 1390 \n",
"4203 10007773 Open University 1390 \n",
"4215 10007773 Open University 1390 \n",
"4207 10007773 Open University 1390 \n",
"4243 10007773 Open University 1390 \n",
"4183 10007773 Open University 1390 \n",
"4235 10007773 Open University 1390 \n",
"4211 10007773 Open University 1390 \n",
"4195 10007773 Open University 1390 \n",
"4187 10007773 Open University 1390 \n",
"4191 10007773 Open University 1390 \n",
"4199 10007773 Open University 1390 \n",
"4239 10007773 Open University 1390 \n",
"\n",
" Main panel Unit of assessment number \\\n",
"4251 D 35 \n",
"4223 C 25 \n",
"4247 D 34 \n",
"4231 D 30 \n",
"4227 D 29 \n",
"4219 C 24 \n",
"4203 C 17 \n",
"4215 C 23 \n",
"4207 C 19 \n",
"4243 D 33 \n",
"4183 A 3 \n",
"4235 D 31 \n",
"4211 C 22 \n",
"4195 B 11 \n",
"4187 B 7 \n",
"4191 B 10 \n",
"4199 B 13 \n",
"4239 D 32 \n",
"\n",
" Unit of assessment name \\\n",
"4251 Music, Drama, Dance and Performing Arts \n",
"4223 Education \n",
"4247 Art and Design: History, Practice and Theory \n",
"4231 History \n",
"4227 English Language and Literature \n",
"4219 Anthropology and Development Studies \n",
"4203 Geography, Environmental Studies and Archaeology \n",
"4215 Sociology \n",
"4207 Business and Management Studies \n",
"4243 Theology and Religious Studies \n",
"4183 Allied Health Professions, Dentistry, Nursing ... \n",
"4235 Classics \n",
"4211 Social Work and Social Policy \n",
"4195 Computer Science and Informatics \n",
"4187 Earth Systems and Environmental Sciences \n",
"4191 Mathematical Sciences \n",
"4199 Electrical and Electronic Engineering, Metallu... \n",
"4239 Philosophy \n",
"\n",
" Multiple submission letter Multiple submission name Joint submission \\\n",
"4251 NaN NaN \n",
"4223 NaN NaN \n",
"4247 NaN NaN \n",
"4231 NaN NaN \n",
"4227 NaN NaN \n",
"4219 NaN NaN \n",
"4203 NaN NaN \n",
"4215 NaN NaN \n",
"4207 NaN NaN \n",
"4243 NaN NaN \n",
"4183 NaN NaN \n",
"4235 NaN NaN \n",
"4211 NaN NaN \n",
"4195 NaN NaN \n",
"4187 NaN NaN \n",
"4191 NaN NaN \n",
"4199 NaN NaN \n",
"4239 NaN NaN \n",
"\n",
" Profile FTE Category A staff submitted 4* 3* 2* 1* unclassified \n",
"4251 Overall 10.60 44 50 6 0 0 \n",
"4223 Overall 54.26 38 31 26 5 0 \n",
"4247 Overall 23.20 29 57 12 2 0 \n",
"4231 Overall 14.30 27 49 23 1 0 \n",
"4227 Overall 16.50 26 50 23 1 0 \n",
"4219 Overall 22.10 24 45 27 4 0 \n",
"4203 Overall 13.00 23 53 21 3 0 \n",
"4215 Overall 37.00 22 42 36 0 0 \n",
"4207 Overall 17.90 19 53 25 3 0 \n",
"4243 Overall 6.00 18 35 47 0 0 \n",
"4183 Overall 17.00 16 61 22 1 0 \n",
"4235 Overall 11.80 16 39 42 3 0 \n",
"4211 Overall 18.60 15 54 29 2 0 \n",
"4195 Overall 31.10 13 62 24 1 0 \n",
"4187 Overall 58.01 11 66 22 1 0 \n",
"4191 Overall 18.80 9 53 33 0 5 \n",
"4199 Overall 18.00 8 77 15 0 0 \n",
"4239 Overall 8.00 6 31 59 4 0 "
]
}
],
"prompt_number": 78
},
{
"cell_type": "heading",
"level": 2,
"metadata": {},
"source": [
"What other data could we bring in?"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Funding from [Gateway to Research](http://gtr.rcuk.ac.uk/)?"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"*Okay... that's it, time up....*"
]
}
],
"metadata": {}
}
]
}
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