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Fall TermEnrollment Type CodeEnrollment Type DescriptionHead CountFull-time Equivalent (FTE) Enrollment
0Fall 20171Transfer25879NaN
1Fall 20172First-time Freshmen38162NaN
2Fall 20173Graduate2967919522.0
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" ], "text/plain": [ " Fall Term Enrollment Type Code Enrollment Type Description Head Count \\\n", "0 Fall 2017 1 Transfer 25879 \n", "1 Fall 2017 2 First-time Freshmen 38162 \n", "2 Fall 2017 3 Graduate 29679 \n", "\n", " Full-time Equivalent (FTE) Enrollment \n", "0 NaN \n", "1 NaN \n", "2 19522.0 " ] }, "execution_count": 4, "metadata": {}, "output_type": "execute_result" } ], "source": [ "univ_data.head(3)" ] }, { "cell_type": "code", "execution_count": 5, "id": "92580437", "metadata": {}, "outputs": [ { "data": { "text/plain": [ "0 Fall 2017\n", "1 Fall 2017\n", "2 Fall 2017\n", "3 Fall 2017\n", "4 Fall 2017\n", " ... \n", "165 FALL 2021\n", "166 FALL 2021\n", "167 FALL 2021\n", "168 FALL 2021\n", "169 FALL 2021\n", "Name: Fall Term, Length: 170, dtype: object" ] }, "execution_count": 5, "metadata": {}, "output_type": "execute_result" } ], "source": [ "univ_data['Fall Term']" ] }, { "cell_type": "code", "execution_count": 6, "id": "64ebb9e7", "metadata": {}, "outputs": [ { "data": { "text/plain": [ "Fall Term Fall 2009\n", "Enrollment Type Code 3\n", "Enrollment Type Description Graduate\n", "Head Count 33243\n", "Full-time Equivalent (FTE) Enrollment 20659\n", "Name: 42, dtype: object" ] }, "execution_count": 6, "metadata": {}, "output_type": "execute_result" } ], "source": [ "univ_data.iloc[42]" ] }, { "cell_type": "code", "execution_count": 8, "id": "1c038932", "metadata": {}, "outputs": [ { "data": { "text/plain": [ "'Graduate'" ] }, "execution_count": 8, "metadata": {}, "output_type": "execute_result" } ], "source": [ "univ_data.iloc[42]['Enrollment Type Description']" ] }, { "cell_type": "code", "execution_count": 9, "id": "8667d505", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "1 Transfer\n", "2 First-time Freshmen\n", "3 Graduate\n", "4 Undergraduate\n", "5 Total\n" ] } ], "source": [ "for idx, row in univ_data.iterrows():\n", " if idx > 4 :\n", " break\n", " print(row['Enrollment Type Code'], row['Enrollment Type Description'])" ] }, { "cell_type": "code", "execution_count": 10, "id": "e5126308", "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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Fall TermEnrollment Type CodeHead CountFull-time Equivalent (FTE) Enrollment
Enrollment Type Description
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GraduateFall 201732967919522.0
UndergraduateFall 20174244420186338.0
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" ], "text/plain": [ " Fall Term Enrollment Type Code Head Count \\\n", "Enrollment Type Description \n", "Transfer Fall 2017 1 25879 \n", "First-time Freshmen Fall 2017 2 38162 \n", "Graduate Fall 2017 3 29679 \n", "Undergraduate Fall 2017 4 244420 \n", "Total Fall 2017 5 274099 \n", "\n", " Full-time Equivalent (FTE) Enrollment \n", "Enrollment Type Description \n", "Transfer NaN \n", "First-time Freshmen NaN \n", "Graduate 19522.0 \n", "Undergraduate 186338.0 \n", "Total 205860.0 " ] }, "execution_count": 10, "metadata": {}, "output_type": "execute_result" } ], "source": [ "univ_data.set_index('Enrollment Type Description').head(5)" ] }, { "cell_type": "code", "execution_count": 12, "id": "9147892b", "metadata": {}, "outputs": [ { "data": { "text/plain": [ "Fall Term Fall 2017\n", "Enrollment Type Code 5\n", "Head Count 274099\n", "Full-time Equivalent (FTE) Enrollment 205860\n", "Name: Total, dtype: object" ] }, "execution_count": 12, "metadata": {}, "output_type": "execute_result" } ], "source": [ "univ_data.set_index('Enrollment Type Description').iloc[4]" ] }, { "cell_type": "code", "execution_count": 13, "id": "4c3177bf", "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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Fall TermEnrollment Type CodeHead CountFull-time Equivalent (FTE) Enrollment
Enrollment Type Description
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TransferFall 2016125492NaN
TransferFall 2015125548NaN
TransferFall 2014124997NaN
TransferFall 2013122864NaN
TransferFall 2012121683NaN
TransferFall 2011123864NaN
TransferFall 2010118669NaN
TransferFall 2009122530NaN
TransferFall 2008121461NaN
TransferFall 2007120057NaN
TransferFall 2006119926NaN
TransferFall 2005118399NaN
TransferFall 2004118856NaN
TransferFall 2003118075NaN
TransferFall 2002116828NaN
TransferFall 2001115303NaN
TransferFall 2000114329NaN
TransferFall 1999113499NaN
TransferFall 1998113937NaN
TransferFall 1997114480NaN
TransferFall 1996113885NaN
TransferFall 1995113727NaN
TransferFall 1994112550NaN
TransferFall 1993113109NaN
TransferFall 1992112576NaN
TransferFall 1991111655NaN
TransferFall 1990111466NaN
TransferFall 2018125061NaN
TransferFall 2019124150NaN
TransferFall 2019124150NaN
TransferFall 2019124150NaN
TransferFall 2020120028NaN
TransferFALL 2021117943NaN
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" ], "text/plain": [ " Fall Term Enrollment Type Code Head Count \\\n", "Enrollment Type Description \n", "Transfer Fall 2017 1 25879 \n", "Transfer Fall 2016 1 25492 \n", "Transfer Fall 2015 1 25548 \n", "Transfer Fall 2014 1 24997 \n", "Transfer Fall 2013 1 22864 \n", "Transfer Fall 2012 1 21683 \n", "Transfer Fall 2011 1 23864 \n", "Transfer Fall 2010 1 18669 \n", "Transfer Fall 2009 1 22530 \n", "Transfer Fall 2008 1 21461 \n", "Transfer Fall 2007 1 20057 \n", "Transfer Fall 2006 1 19926 \n", "Transfer Fall 2005 1 18399 \n", "Transfer Fall 2004 1 18856 \n", "Transfer Fall 2003 1 18075 \n", "Transfer Fall 2002 1 16828 \n", "Transfer Fall 2001 1 15303 \n", "Transfer Fall 2000 1 14329 \n", "Transfer Fall 1999 1 13499 \n", "Transfer Fall 1998 1 13937 \n", "Transfer Fall 1997 1 14480 \n", "Transfer Fall 1996 1 13885 \n", "Transfer Fall 1995 1 13727 \n", "Transfer Fall 1994 1 12550 \n", "Transfer Fall 1993 1 13109 \n", "Transfer Fall 1992 1 12576 \n", "Transfer Fall 1991 1 11655 \n", "Transfer Fall 1990 1 11466 \n", "Transfer Fall 2018 1 25061 \n", "Transfer Fall 2019 1 24150 \n", "Transfer Fall 2019 1 24150 \n", "Transfer Fall 2019 1 24150 \n", "Transfer Fall 2020 1 20028 \n", "Transfer FALL 2021 1 17943 \n", "\n", " Full-time Equivalent (FTE) Enrollment \n", "Enrollment Type Description \n", "Transfer NaN \n", "Transfer NaN \n", "Transfer NaN \n", "Transfer NaN \n", "Transfer NaN \n", "Transfer NaN \n", "Transfer NaN \n", "Transfer NaN \n", "Transfer NaN \n", "Transfer NaN \n", "Transfer NaN \n", "Transfer NaN \n", "Transfer NaN \n", "Transfer NaN \n", "Transfer NaN \n", "Transfer NaN \n", "Transfer NaN \n", "Transfer NaN \n", "Transfer NaN \n", "Transfer NaN \n", "Transfer NaN \n", "Transfer NaN \n", "Transfer NaN \n", "Transfer NaN \n", "Transfer NaN \n", "Transfer NaN \n", "Transfer NaN \n", "Transfer NaN \n", "Transfer NaN \n", "Transfer NaN \n", "Transfer NaN \n", "Transfer NaN \n", "Transfer NaN \n", "Transfer NaN " ] }, "execution_count": 13, "metadata": {}, "output_type": "execute_result" } ], "source": [ "univ_data.set_index('Enrollment Type Description').loc['Transfer']" ] }, { "cell_type": "code", "execution_count": 14, "id": "925a3937", "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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Enrollment Type CodeHead CountFull-time Equivalent (FTE) Enrollment
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Fall TermEnrollment Type Description
0Fall 2017Transfer
1Fall 2017First-time Freshmen
2Fall 2017Graduate
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165FALL 2021Transfer
166FALL 2021First-time Freshmen
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Fall TermEnrollment Type CodeEnrollment Type DescriptionHead CountFull-time Equivalent (FTE) Enrollment
0Fall 20171Transfer25879NaN
1Fall 20172First-time Freshmen38162NaN
2Fall 20173Graduate2967919522.0
3Fall 20174Undergraduate244420186338.0
4Fall 20175Total274099205860.0
..................
164Fall 20205Total261134198483.0
166FALL 20212First-time Freshmen34719NaN
167FALL 20213Graduate3050320767.0
168FALL 20214Undergraduate212886160267.0
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" ], "text/plain": [ " Fall Term Enrollment Type Code Enrollment Type Description Head Count \\\n", "0 Fall 2017 1 Transfer 25879 \n", "1 Fall 2017 2 First-time Freshmen 38162 \n", "2 Fall 2017 3 Graduate 29679 \n", "3 Fall 2017 4 Undergraduate 244420 \n", "4 Fall 2017 5 Total 274099 \n", ".. ... ... ... ... \n", "164 Fall 2020 5 Total 261134 \n", "166 FALL 2021 2 First-time Freshmen 34719 \n", "167 FALL 2021 3 Graduate 30503 \n", "168 FALL 2021 4 Undergraduate 212886 \n", "169 FALL 2021 5 Total 243389 \n", "\n", " Full-time Equivalent (FTE) Enrollment \n", "0 NaN \n", "1 NaN \n", "2 19522.0 \n", "3 186338.0 \n", "4 205860.0 \n", ".. ... \n", "164 198483.0 \n", "166 NaN \n", "167 20767.0 \n", "168 160267.0 \n", "169 181034.0 \n", "\n", "[137 rows x 5 columns]" ] }, "execution_count": 21, "metadata": {}, "output_type": "execute_result" } ], "source": [ "lapp = univ_data['Head Count'] > 25000\n", "univ_data[lapp]" ] }, { "cell_type": "code", "execution_count": 22, "id": "5817f7ad", "metadata": {}, "outputs": [ { "data": { "text/plain": [ "0 True\n", "1 True\n", "2 True\n", "3 True\n", "4 True\n", " ... \n", "165 False\n", "166 True\n", "167 True\n", "168 True\n", "169 True\n", "Name: Head Count, Length: 170, dtype: bool" ] }, "execution_count": 22, "metadata": {}, "output_type": "execute_result" } ], "source": [ "lapp" ] }, { "cell_type": "code", "execution_count": 24, "id": "e76aa86f", "metadata": {}, "outputs": [ { "data": { "text/plain": [ "0 False\n", "1 False\n", "2 False\n", "3 False\n", "4 True\n", " ... \n", "165 False\n", "166 False\n", "167 False\n", "168 False\n", "169 True\n", "Name: Enrollment Type Description, Length: 170, dtype: bool" ] }, "execution_count": 24, "metadata": {}, "output_type": "execute_result" } ], "source": [ "univ_data['Enrollment Type Description'].apply(lambda string: 'Total' in string)" ] }, { "cell_type": "code", "execution_count": 25, "id": "7ba9a56b", "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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Fall TermEnrollment Type CodeEnrollment Type DescriptionHead CountFull-time Equivalent (FTE) Enrollment
135Fall 19901Transfer11466NaN
130Fall 19911Transfer11655NaN
115Fall 19941Transfer12550NaN
125Fall 19921Transfer12576NaN
120Fall 19931Transfer13109NaN
..................
9Fall 20165Total272957204337.0
4Fall 20175Total274099205860.0
14Fall 20155Total274357204418.0
144Fall 20185Total274906206950.0
19Fall 20145Total275132203996.0
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" ], "text/plain": [ " Fall Term Enrollment Type Code Enrollment Type Description Head Count \\\n", "135 Fall 1990 1 Transfer 11466 \n", "130 Fall 1991 1 Transfer 11655 \n", "115 Fall 1994 1 Transfer 12550 \n", "125 Fall 1992 1 Transfer 12576 \n", "120 Fall 1993 1 Transfer 13109 \n", ".. ... ... ... ... \n", "9 Fall 2016 5 Total 272957 \n", "4 Fall 2017 5 Total 274099 \n", "14 Fall 2015 5 Total 274357 \n", "144 Fall 2018 5 Total 274906 \n", "19 Fall 2014 5 Total 275132 \n", "\n", " Full-time Equivalent (FTE) Enrollment \n", "135 NaN \n", "130 NaN \n", "115 NaN \n", "125 NaN \n", "120 NaN \n", ".. ... \n", "9 204337.0 \n", "4 205860.0 \n", "14 204418.0 \n", "144 206950.0 \n", "19 203996.0 \n", "\n", "[170 rows x 5 columns]" ] }, "execution_count": 25, "metadata": {}, "output_type": "execute_result" } ], "source": [ "univ_data.sort_values(by = ['Head Count', 'Enrollment Type Description'], ascending = [True, False])" ] }, { "cell_type": "code", "execution_count": 26, "id": "3263b471", "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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" ], "text/plain": [ " Fall Term Enrollment Type Code Enrollment Type Description Head Count \\\n", "0 False False False False \n", "1 False False False False \n", "2 False False False False \n", "3 False False False False \n", "4 False False False False \n", ".. ... ... ... ... \n", "165 False False False False \n", "166 False False False False \n", "167 False False False False \n", "168 False False False False \n", "169 False False False False \n", "\n", " Full-time Equivalent (FTE) Enrollment \n", "0 True \n", "1 True \n", "2 False \n", "3 False \n", "4 False \n", ".. ... \n", "165 True \n", "166 True \n", "167 False \n", "168 False \n", "169 False \n", "\n", "[170 rows x 5 columns]" ] }, "execution_count": 26, "metadata": {}, "output_type": "execute_result" } ], "source": [ "univ_data.isnull()" ] }, { "cell_type": "code", "execution_count": 29, "id": "710d9d74", "metadata": {}, "outputs": [ { "data": { "text/plain": [ "0" ] }, "execution_count": 29, "metadata": {}, "output_type": "execute_result" } ], "source": [ "temp = univ_data.fillna('NaN')\n", "temp2 = temp[temp['Enrollment Type Description'] == 'Not specified']\n", "len(temp2)" ] }, { "cell_type": "code", "execution_count": 31, "id": "d6db3158", "metadata": {}, "outputs": [ { "data": { "text/plain": [ "(102, 5)" ] }, "execution_count": 31, "metadata": {}, "output_type": "execute_result" } ], "source": [ "univ_data.dropna(how = 'any', inplace = True)\n", "univ_data.shape" ] }, { "cell_type": "code", "execution_count": 32, "id": "31bd67fc", "metadata": {}, "outputs": [ { "data": { "text/plain": [ "'Graduate'" ] }, "execution_count": 32, "metadata": {}, "output_type": "execute_result" } ], "source": [ "univ_data['Enrollment Type Description'].iloc[0]" ] }, { "cell_type": "code", "execution_count": 33, "id": "eac6cfc9", "metadata": {}, "outputs": [ { "data": { "text/plain": [ "'Fall 2017'" ] }, "execution_count": 33, "metadata": {}, "output_type": "execute_result" } ], "source": [ "univ_data['Fall Term'].iloc[0]" ] }, { "cell_type": "code", "execution_count": 34, "id": "53be7be4", "metadata": {}, "outputs": [ { "data": { "text/plain": [ "3" ] }, "execution_count": 34, "metadata": {}, "output_type": "execute_result" } ], "source": [ "univ_data['Enrollment Type Code'].iloc[3]" ] }, { "cell_type": "code", "execution_count": 38, "id": "73639687", "metadata": {}, "outputs": [], "source": [ "univ_data['Enrollment Type Description'] = univ_data['Fall Term'].apply(lambda x: x.replace('\\n', 'Fall'))" ] }, { "cell_type": "code", "execution_count": 39, "id": "3bebb181", "metadata": {}, "outputs": [ { "data": { "text/plain": [ "'Fall 2017'" ] }, "execution_count": 39, "metadata": {}, "output_type": "execute_result" } ], "source": [ "univ_data['Fall Term'].iloc[0]" ] }, { "cell_type": "code", "execution_count": 40, "id": "37c98445", "metadata": {}, "outputs": [], "source": [ "def removeEnrollment(row):\n", " return row['Enrollment Type Description'].replace(\"%s:\" % row['Enrollment Type Description'], '').strip()" ] }, { "cell_type": "code", "execution_count": 41, "id": "bd3b9c96", "metadata": {}, "outputs": [], "source": [ "univ_data['Enrollment Type Description'] = univ_data.apply(removeEnrollment, axis = 1)" ] }, { "cell_type": "code", "execution_count": 42, "id": "8f49bb20", "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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" ], "text/plain": [ " Fall Term Enrollment Type Code Enrollment Type Description Head Count \\\n", "2 Fall 2017 3 Fall 2017 29679 \n", "3 Fall 2017 4 Fall 2017 244420 \n", "4 Fall 2017 5 Fall 2017 274099 \n", "7 Fall 2016 3 Fall 2016 29431 \n", "8 Fall 2016 4 Fall 2016 243526 \n", "\n", " Full-time Equivalent (FTE) Enrollment \n", "2 19522.0 \n", "3 186338.0 \n", "4 205860.0 \n", "7 19257.0 \n", "8 185080.0 " ] }, "execution_count": 42, "metadata": {}, "output_type": "execute_result" } ], "source": [ "univ_data.head()" ] }, { "cell_type": "code", "execution_count": 43, "id": "52aaa77a", "metadata": {}, "outputs": [], "source": [ "import re" ] }, { "cell_type": "code", "execution_count": 44, "id": "cc12f8f7", "metadata": {}, "outputs": [ { "data": { "image/png": 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\n", 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" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "hists = univ_data.hist()" ] }, { "cell_type": "code", "execution_count": 45, "id": "43d93cbf", "metadata": {}, "outputs": [], "source": [ "import matplotlib.pyplot as plt\n" ] }, { "cell_type": "code", "execution_count": 46, "id": "b3122871", "metadata": {}, "outputs": [ { "data": { "image/png": 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\n", 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" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "hists = univ_data.hist()\n", "plt.tight_layout()\n", "plt.show()\n", "plt.savefig('plot.png')" ] }, { "cell_type": "code", "execution_count": 47, "id": "0dd46a83", "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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Enrollment Type CodeHead CountFull-time Equivalent (FTE) Enrollment
Enrollment Type Code1.0000000.8913600.877848
Head Count0.8913601.0000000.999359
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" ], "text/plain": [ " Enrollment Type Code Head Count \\\n", "Enrollment Type Code 1.000000 0.891360 \n", "Head Count 0.891360 1.000000 \n", "Full-time Equivalent (FTE) Enrollment 0.877848 0.999359 \n", "\n", " Full-time Equivalent (FTE) Enrollment \n", "Enrollment Type Code 0.877848 \n", "Head Count 0.999359 \n", "Full-time Equivalent (FTE) Enrollment 1.000000 " ] }, "execution_count": 47, "metadata": {}, "output_type": "execute_result" } ], "source": [ "univ_data.corr()" ] }, { "cell_type": "code", "execution_count": 48, "id": "581b5fe9", "metadata": {}, "outputs": [], "source": [ "import seaborn as sns" ] }, { "cell_type": "code", "execution_count": 49, "id": "8924b183", "metadata": {}, "outputs": [ { "data": { "text/plain": [ "" ] }, "execution_count": 49, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": 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\n", 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\n", 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" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "sns.heatmap(univ_data.corr(), vmin=-1, vmax=1, cmap = 'seismic', linewidths = 0.2, annot=True);" ] }, { "cell_type": "code", "execution_count": 51, "id": "97d146b3", "metadata": {}, "outputs": [], "source": [ "import numpy as np" ] }, { "cell_type": "code", "execution_count": 52, "id": "c449f015", "metadata": {}, "outputs": [ { "data": { "text/plain": [ "" ] }, "execution_count": 52, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": 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\n", 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\n", 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\n", 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\n", 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" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "univ_data['Full-time Equivalent (FTE) Enrollment'].hist(bins=100)" ] }, { "cell_type": "code", "execution_count": 69, "id": "3b7f7d1e", "metadata": {}, "outputs": [ { "data": { "text/plain": [ "" ] }, "execution_count": 69, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": 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" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "univ_data['Fall Term'].hist(bins=24)" ] }, { "cell_type": "code", "execution_count": 79, "id": "c8f808fb", "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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Fall TermEnrollment Type CodeEnrollment Type DescriptionHead CountFull-time Equivalent (FTE) Enrollment
2Fall 20173Fall 20172967919522.0
3Fall 20174Fall 2017244420186338.0
4Fall 20175Fall 2017274099205860.0
7Fall 20163Fall 20162943119257.0
8Fall 20164Fall 2016243526185080.0
..................
163Fall 20204Fall 2020229992177216.0
164Fall 20205Fall 2020261134198483.0
167FALL 20213FALL 20213050320767.0
168FALL 20214FALL 2021212886160267.0
169FALL 20215FALL 2021243389181034.0
\n", "

102 rows × 5 columns

\n", "
" ], "text/plain": [ " Fall Term Enrollment Type Code Enrollment Type Description Head Count \\\n", "2 Fall 2017 3 Fall 2017 29679 \n", "3 Fall 2017 4 Fall 2017 244420 \n", "4 Fall 2017 5 Fall 2017 274099 \n", "7 Fall 2016 3 Fall 2016 29431 \n", "8 Fall 2016 4 Fall 2016 243526 \n", ".. ... ... ... ... \n", "163 Fall 2020 4 Fall 2020 229992 \n", "164 Fall 2020 5 Fall 2020 261134 \n", "167 FALL 2021 3 FALL 2021 30503 \n", "168 FALL 2021 4 FALL 2021 212886 \n", "169 FALL 2021 5 FALL 2021 243389 \n", "\n", " Full-time Equivalent (FTE) Enrollment \n", "2 19522.0 \n", "3 186338.0 \n", "4 205860.0 \n", "7 19257.0 \n", "8 185080.0 \n", ".. ... \n", "163 177216.0 \n", "164 198483.0 \n", "167 20767.0 \n", "168 160267.0 \n", "169 181034.0 \n", "\n", "[102 rows x 5 columns]" ] }, "execution_count": 79, "metadata": {}, "output_type": "execute_result" } ], "source": [ "univ_data" ] }, { "cell_type": "code", "execution_count": 80, "id": "3fcfe3f5", "metadata": {}, "outputs": [], "source": [ "univ_data.sort_values(by=[\"Fall Term\", \"Enrollment Type Code\"], inplace=True)" ] }, { "cell_type": "code", "execution_count": 81, "id": "ed962881", "metadata": {}, "outputs": [], "source": [ "univ_data['Composite Score'] = univ_data['Full-time Equivalent (FTE) Enrollment']" ] }, { "cell_type": "code", "execution_count": 82, "id": "6d8a723f", "metadata": {}, "outputs": [], "source": [ "univ_data['Rank'] = univ_data['Composite Score'].rank(ascending=False)" ] }, { "cell_type": "code", "execution_count": 83, "id": "5f2e0c76", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ " Fall Term Enrollment Type Description Composite Score Rank\n", "167 FALL 2021 FALL 2021 20767.0 71.0\n", "168 FALL 2021 FALL 2021 160267.0 33.0\n", "169 FALL 2021 FALL 2021 181034.0 24.0\n", "137 Fall 1990 Fall 1990 14566.0 98.5\n", "138 Fall 1990 Fall 1990 127906.0 65.0\n", ".. ... ... ... ...\n", "154 Fall 2019 Fall 2019 204395.0 5.0\n", "159 Fall 2019 Fall 2019 204395.0 5.0\n", "162 Fall 2020 Fall 2020 21267.0 69.0\n", "163 Fall 2020 Fall 2020 177216.0 28.0\n", "164 Fall 2020 Fall 2020 198483.0 12.0\n", "\n", "[102 rows x 4 columns]\n" ] } ], "source": [ "print(univ_data[['Fall Term', 'Enrollment Type Description', 'Composite Score', 'Rank']])" ] }, { "cell_type": "code", "execution_count": 84, "id": "cec313cf", "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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Fall TermEnrollment Type CodeEnrollment Type DescriptionHead CountFull-time Equivalent (FTE) EnrollmentComposite ScoreRank
167FALL 20213FALL 20213050320767.020767.071.0
168FALL 20214FALL 2021212886160267.0160267.033.0
169FALL 20215FALL 2021243389181034.0181034.024.0
137Fall 19903Fall 19902646314566.014566.098.5
138Fall 19904Fall 1990174165127906.0127906.065.0
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" ], "text/plain": [ " Fall Term Enrollment Type Code Enrollment Type Description Head Count \\\n", "167 FALL 2021 3 FALL 2021 30503 \n", "168 FALL 2021 4 FALL 2021 212886 \n", "169 FALL 2021 5 FALL 2021 243389 \n", "137 Fall 1990 3 Fall 1990 26463 \n", "138 Fall 1990 4 Fall 1990 174165 \n", "\n", " Full-time Equivalent (FTE) Enrollment Composite Score Rank \n", "167 20767.0 20767.0 71.0 \n", "168 160267.0 160267.0 33.0 \n", "169 181034.0 181034.0 24.0 \n", "137 14566.0 14566.0 98.5 \n", "138 127906.0 127906.0 65.0 " ] }, "execution_count": 84, "metadata": {}, "output_type": "execute_result" } ], "source": [ "univ_data.head()" ] }, { "cell_type": "code", "execution_count": 85, "id": "d77825ef", "metadata": {}, "outputs": [], "source": [ "correlation = univ_data['Full-time Equivalent (FTE) Enrollment'].corr(univ_data['Head Count'])" ] }, { "cell_type": "code", "execution_count": 86, "id": "de5c5beb", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Correlation between FTE Enrollment and Head Count: 1.00\n" ] } ], "source": [ "print(f\"Correlation between FTE Enrollment and Head Count: {correlation:.2f}\")" ] }, { "cell_type": "code", "execution_count": 87, "id": "b2bd41ae", "metadata": {}, "outputs": [], "source": [ "from scipy.stats import pearsonr" ] }, { "cell_type": "code", "execution_count": 88, "id": "2f6e0d19", "metadata": {}, "outputs": [], "source": [ "correlation, _ = pearsonr(univ_data['Rank'], univ_data['Full-time Equivalent (FTE) Enrollment'])" ] }, { "cell_type": "code", "execution_count": 89, "id": "c64f5fda", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Correlation with 'Full-time Equivalent (FTE) Enrollment': -0.94\n" ] } ], "source": [ "print(f\"Correlation with 'Full-time Equivalent (FTE) Enrollment': {correlation:.2f}\")" ] }, { "cell_type": "code", "execution_count": 90, "id": "523ffde3", "metadata": {}, "outputs": [], "source": [ "correlation, _ = pearsonr(univ_data['Rank'], univ_data['Full-time Equivalent (FTE) Enrollment'])" ] }, { "cell_type": "code", "execution_count": 91, "id": "3421acf2", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Correlation with Internal Measure: -0.94\n" ] } ], "source": [ "print(f\"Correlation with Internal Measure: {correlation:.2f}\")" ] } ], "metadata": { "kernelspec": { "display_name": "Python 3.6", "language": "python", "name": "py36" }, "language_info": { "codemirror_mode": { "name": "ipython", "version": 3 }, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", "version": "3.6.13" } }, "nbformat": 4, "nbformat_minor": 5 }