From 691f66f00d11e240764d4212eb040baed42c8a6e Mon Sep 17 00:00:00 2001 From: Kimihiro Nakamura <151773686+Kimihiro02399@users.noreply.github.com> Date: Sat, 13 Jan 2024 13:08:46 -0500 Subject: [PATCH] Added new files --- ...th_female_representation_score_by_fips.csv | 127 +++ gender-web-page/county-executive.csv | 807 ++++++++++++++++++ ...square-with-female-representation-score.py | 52 ++ gender-web-page/ledb_candidatelevel.xlsm | Bin 0 -> 24838365 bytes gender-web-page/us_county_map_chi_test.js | 232 +++++ ..._county_map_female_representation_score.js | 235 +++++ 6 files changed, 1453 insertions(+) create mode 100644 gender-web-page/chi_square_results_with_female_representation_score_by_fips.csv create mode 100644 gender-web-page/county-executive.csv create mode 100644 gender-web-page/gender-count-chisquare-with-female-representation-score.py create mode 100644 gender-web-page/ledb_candidatelevel.xlsm create mode 100644 gender-web-page/us_county_map_chi_test.js create mode 100644 gender-web-page/us_county_map_female_representation_score.js diff --git a/gender-web-page/chi_square_results_with_female_representation_score_by_fips.csv b/gender-web-page/chi_square_results_with_female_representation_score_by_fips.csv new file mode 100644 index 0000000..dab7aae --- /dev/null +++ b/gender-web-page/chi_square_results_with_female_representation_score_by_fips.csv @@ -0,0 +1,127 @@ +fips,FemaleCount,MaleCount,TotalCount,Years,ChiSquareStatistic,P-Value,Representation,FemaleRepresentation,FemaleRepresentationScore +1083,0,6,6,"[1994, 1998, 2002, 2006, 2010, 2014]",6.0,0.014305878435429641,Low Gender Representation,0.0,0 +2020,0,1,1,[2018],1.0,0.31731050786291115,Low Gender Representation not Detected,0.0,0 +2090,1,10,11,"[1991, 1994, 1997, 2000, 2003, 2006, 2009, 2012, 2015, 2018, 2021]",7.363636363636363,0.006655605482949389,Low Gender Representation,0.09090909090909091,1 +2122,0,11,11,"[1990, 1993, 1996, 1999, 2002, 2005, 2008, 2011, 2014, 2017, 2020]",11.0,0.0009111188771537126,Low Gender Representation,0.0,0 +2170,3,9,12,"[1991, 1994, 1997, 2000, 2003, 2006, 2009, 2011, 2012, 2015, 2018, 2021]",3.0,0.08326451666355042,Low Gender Representation not Detected,0.25,2 +5031,0,2,2,"[2010, 2014]",2.0,0.15729920705028105,Low Gender Representation not Detected,0.0,0 +5045,0,1,1,[2012],1.0,0.31731050786291115,Low Gender Representation not Detected,0.0,0 +5051,0,1,1,[2014],1.0,0.31731050786291115,Low Gender Representation not Detected,0.0,0 +5069,0,2,2,"[2002, 2012]",2.0,0.15729920705028105,Low Gender Representation not Detected,0.0,0 +5119,0,6,6,"[1998, 2006, 2008, 2010, 2014, 2018]",6.0,0.014305878435429641,Low Gender Representation,0.0,0 +5125,0,2,2,"[2012, 2014]",2.0,0.15729920705028105,Low Gender Representation not Detected,0.0,0 +5131,0,3,3,"[2002, 2006, 2012]",3.0,0.08326451666355042,Low Gender Representation not Detected,0.0,0 +5143,2,0,2,"[2008, 2014]",2.0,0.15729920705028105,Low Gender Representation not Detected,1.0,10 +5145,0,5,5,"[2002, 2006, 2008, 2010, 2014]",5.0,0.025347318677468325,Low Gender Representation,0.0,0 +8031,0,2,2,"[2015, 2019]",2.0,0.15729920705028105,Low Gender Representation not Detected,0.0,0 +10003,0,9,9,"[1992, 1996, 2000, 2004, 2008, 2010, 2012, 2016, 2020]",9.0,0.0026997960632601883,Low Gender Representation,0.0,0 +12086,1,7,8,"[1996, 2000, 2004, 2008, 2011, 2012, 2016, 2020]",4.5,0.033894853524689295,Low Gender Representation,0.125,1 +13021,0,5,5,"[2012, 2012, 2013, 2016, 2020]",5.0,0.025347318677468325,Low Gender Representation,0.0,0 +13045,0,2,2,"[2004, 2008]",2.0,0.15729920705028105,Low Gender Representation not Detected,0.0,0 +13059,5,2,7,"[1994, 1998, 2002, 2006, 2010, 2014, 2018]",1.2857142857142858,0.2568392579578533,Low Gender Representation not Detected,0.7142857142857143,7 +13063,0,1,1,"[2004, 2008, 2012]",1.0,0.31731050786291115,Low Gender Representation not Detected,0.0,0 +13089,0,7,7,"[2000, 2004, 2008, 2012, 2013, 2016, 2020]",7.0,0.008150971593502705,Low Gender Representation,0.0,0 +13153,0,2,2,"[2010, 2014]",2.0,0.15729920705028105,Low Gender Representation not Detected,0.0,0 +13223,0,2,2,"[2012, 2016]",2.0,0.15729920705028105,Low Gender Representation not Detected,0.0,0 +15001,0,9,9,"[1990, 1992, 1996, 2000, 2004, 2008, 2012, 2016, 2020]",9.0,0.0026997960632601883,Low Gender Representation,0.0,0 +15003,0,11,11,"[1992, 1994, 1996, 2000, 2004, 2008, 2010, 2012, 2016, 2020, 2020]",11.0,0.0009111188771537126,Low Gender Representation,0.0,0 +15007,3,6,9,"[1990, 1994, 1998, 2002, 2006, 2008, 2010, 2014, 2018]",1.0,0.31731050786291115,Low Gender Representation not Detected,0.3333333333333333,3 +15009,3,5,8,"[1990, 1994, 1998, 2002, 2006, 2010, 2014, 2018]",0.5,0.47950012218695337,Low Gender Representation not Detected,0.375,4 +17019,1,0,1,[2018],1.0,0.31731050786291115,Low Gender Representation not Detected,1.0,10 +17031,4,6,10,"[1990, 1994, 1998, 2002, 2006, 2006, 2010, 2010, 2014, 2018]",0.4,0.5270892568655381,Low Gender Representation not Detected,0.4,4 +17043,0,5,5,"[1998, 2002, 2006, 2010, 2014]",5.0,0.025347318677468325,Low Gender Representation,0.0,0 +17089,3,2,5,"[1992, 2004, 2008, 2012, 2020]",0.2,0.6547208460185768,Low Gender Representation not Detected,0.6,6 +17197,1,8,9,"[1992, 1996, 2000, 2004, 2008, 2012, 2012, 2016, 2020]",5.444444444444445,0.019630657257290702,Low Gender Representation,0.1111111111111111,1 +17201,1,3,4,"[2000, 2008, 2016, 2020]",1.0,0.31731050786291115,Low Gender Representation not Detected,0.25,2 +18005,0,5,5,"[2006, 2008, 2010, 2012, 2014]",5.0,0.025347318677468325,Low Gender Representation,0.0,0 +18081,0,4,4,"[2008, 2010, 2012, 2014]",4.0,0.04550026389635857,Low Gender Representation,0.0,0 +18157,2,7,9,"[1998, 2000, 2002, 2004, 2006, 2008, 2010, 2012, 2014]",2.7777777777777777,0.09558070454562936,Low Gender Representation not Detected,0.2222222222222222,2 +20091,2,3,5,"[2002, 2006, 2010, 2014, 2018]",0.2,0.6547208460185768,Low Gender Representation not Detected,0.4,4 +20209,2,5,7,"[1997, 2001, 2005, 2009, 2013, 2017, 2021]",1.2857142857142858,0.2568392579578533,Low Gender Representation not Detected,0.2857142857142857,3 +21015,0,3,3,"[2010, 2014, 2018]",3.0,0.08326451666355042,Low Gender Representation not Detected,0.0,0 +21037,0,3,3,"[2002, 2006, 2010]",3.0,0.08326451666355042,Low Gender Representation not Detected,0.0,0 +21047,0,2,2,"[2010, 2014]",2.0,0.15729920705028105,Low Gender Representation not Detected,0.0,0 +21067,2,3,5,"[2002, 2006, 2010, 2014, 2018]",0.2,0.6547208460185768,Low Gender Representation not Detected,0.4,4 +21111,3,5,8,"[1989, 1993, 1998, 2002, 2006, 2010, 2014, 2018]",0.5,0.47950012218695337,Low Gender Representation not Detected,0.375,4 +21117,0,2,2,"[2014, 2018]",2.0,0.15729920705028105,Low Gender Representation not Detected,0.0,0 +21227,0,2,2,"[2010, 2014]",2.0,0.15729920705028105,Low Gender Representation not Detected,0.0,0 +22005,0,8,8,"[1993, 1995, 1999, 2003, 2007, 2011, 2015, 2019]",8.0,0.004677734981047276,Low Gender Representation,0.0,0 +22045,0,9,9,"[1991, 1993, 1995, 1999, 2003, 2007, 2011, 2015, 2019]",9.0,0.0026997960632601883,Low Gender Representation,0.0,0 +22051,1,8,9,"[1991, 1995, 1999, 2003, 2007, 2010, 2011, 2015, 2019]",5.444444444444445,0.019630657257290702,Low Gender Representation,0.1111111111111111,1 +22057,3,5,8,"[1991, 1995, 1999, 2003, 2007, 2011, 2015, 2019]",0.5,0.47950012218695337,Low Gender Representation not Detected,0.375,4 +22063,0,8,8,"[1995, 1999, 2003, 2007, 2010, 2011, 2015, 2019]",8.0,0.004677734981047276,Low Gender Representation,0.0,0 +22089,0,6,6,"[1991, 1995, 1999, 2003, 2007, 2011, 2015, 2019]",6.0,0.014305878435429641,Low Gender Representation,0.0,0 +22097,0,5,5,"[2003, 2007, 2011, 2011, 2015, 2019, 2020, 2021]",5.0,0.025347318677468325,Low Gender Representation,0.0,0 +22099,0,9,9,"[1999, 1999, 2003, 2004, 2007, 2011, 2015, 2018, 2019]",9.0,0.0026997960632601883,Low Gender Representation,0.0,0 +22103,2,4,6,"[1999, 2003, 2007, 2011, 2015, 2019]",0.6666666666666666,0.4142161782425251,Low Gender Representation not Detected,0.3333333333333333,3 +22105,0,9,9,"[1991, 1995, 1995, 1999, 2003, 2007, 2011, 2015, 2019]",9.0,0.0026997960632601883,Low Gender Representation,0.0,0 +22109,0,9,9,"[1991, 1995, 1999, 2003, 2007, 2011, 2011, 2015, 2019]",9.0,0.0026997960632601883,Low Gender Representation,0.0,0 +24003,2,7,9,"[1990, 1994, 1998, 2002, 2006, 2010, 2013, 2014, 2018]",2.7777777777777777,0.09558070454562936,Low Gender Representation not Detected,0.2222222222222222,2 +24005,4,7,11,"[1991, 1995, 1999, 2004, 2004, 2007, 2010, 2011, 2016, 2019, 2020]",0.8181818181818182,0.36571229628151314,Low Gender Representation not Detected,0.36363636363636365,4 +24015,2,1,3,"[2012, 2016, 2020]",0.3333333333333333,0.5637028616507731,Low Gender Representation not Detected,0.6666666666666666,7 +24017,1,3,4,"[2002, 2004, 2006, 2010, 2014, 2018]",1.0,0.31731050786291115,Low Gender Representation not Detected,0.25,2 +24021,2,0,2,"[2014, 2018]",2.0,0.15729920705028105,Low Gender Representation not Detected,1.0,10 +24025,2,7,9,"[1990, 1994, 1998, 2002, 2005, 2006, 2010, 2014, 2018]",2.7777777777777777,0.09558070454562936,Low Gender Representation not Detected,0.2222222222222222,2 +24027,0,8,8,"[1990, 1994, 1998, 2002, 2006, 2010, 2014, 2018]",8.0,0.004677734981047276,Low Gender Representation,0.0,0 +24031,0,9,9,"[1990, 1990, 1994, 1998, 2002, 2006, 2010, 2014, 2018]",9.0,0.0026997960632601883,Low Gender Representation,0.0,0 +24033,1,7,8,"[1990, 1994, 1998, 2002, 2006, 2010, 2014, 2018]",4.5,0.033894853524689295,Low Gender Representation,0.125,1 +24045,0,5,5,"[2006, 2010, 2014, 2018, 2020]",5.0,0.025347318677468325,Low Gender Representation,0.0,0 +26017,0,5,5,"[2004, 2008, 2012, 2016, 2020]",5.0,0.025347318677468325,Low Gender Representation,0.0,0 +26099,0,3,3,"[2010, 2014, 2018]",3.0,0.08326451666355042,Low Gender Representation not Detected,0.0,0 +26125,1,9,10,"[1992, 1996, 2000, 2004, 2008, 2012, 2012, 2016, 2019, 2020]",6.4,0.01141203638600166,Low Gender Representation,0.1,1 +26163,0,5,5,"[2002, 2006, 2010, 2014, 2018]",5.0,0.025347318677468325,Low Gender Representation,0.0,0 +29077,0,6,6,"[1994, 1998, 2002, 2006, 2010, 2014]",6.0,0.014305878435429641,Low Gender Representation,0.0,0 +29095,4,5,9,"[1990, 1994, 1998, 2002, 2006, 2010, 2014, 2016, 2018]",0.1111111111111111,0.7388826803635273,Low Gender Representation not Detected,0.4444444444444444,4 +29097,0,2,2,"[2006, 2010]",2.0,0.15729920705028105,Low Gender Representation not Detected,0.0,0 +29099,0,3,3,"[2010, 2014, 2018]",3.0,0.08326451666355042,Low Gender Representation not Detected,0.0,0 +29183,0,8,8,"[1990, 1994, 1998, 2002, 2006, 2010, 2014, 2018]",8.0,0.004677734981047276,Low Gender Representation,0.0,0 +29189,0,12,12,"[1989, 1990, 1994, 1998, 2002, 2003, 2004, 2006, 2010, 2014, 2018, 2019, 2020]",12.0,0.0005320055051392492,Low Gender Representation,0.0,0 +29510,1,0,1,[2017],1.0,0.31731050786291115,Low Gender Representation not Detected,1.0,10 +34001,0,8,8,"[1991, 1995, 1999, 2003, 2007, 2011, 2015, 2019]",8.0,0.004677734981047276,Low Gender Representation,0.0,0 +34003,1,8,9,"[1990, 1994, 1994, 1998, 2002, 2006, 2010, 2014, 2018]",5.444444444444445,0.019630657257290702,Low Gender Representation,0.1111111111111111,1 +34013,0,8,8,"[1990, 1994, 1998, 2002, 2006, 2010, 2014, 2018]",8.0,0.004677734981047276,Low Gender Representation,0.0,0 +34017,0,12,12,"[1991, 1995, 1999, 2002, 2002, 2003, 2007, 2011, 2015, 2015, 2019, 2019]",12.0,0.0005320055051392492,Low Gender Representation,0.0,0 +34021,0,8,8,"[1991, 1995, 1999, 2003, 2007, 2011, 2015, 2019]",8.0,0.004677734981047276,Low Gender Representation,0.0,0 +36001,0,8,8,"[1991, 1995, 1999, 2003, 2007, 2011, 2015, 2019]",8.0,0.004677734981047276,Low Gender Representation,0.0,0 +36007,4,4,8,"[1992, 1996, 2000, 2004, 2008, 2011, 2012, 2020]",0.0,1.0,Low Gender Representation not Detected,0.5,5 +36013,0,9,9,"[1989, 1993, 1997, 2001, 2005, 2009, 2013, 2020, 2021]",9.0,0.0026997960632601883,Low Gender Representation,0.0,0 +36015,0,1,1,"[1990, 2014]",1.0,0.31731050786291115,Low Gender Representation not Detected,0.0,0 +36027,0,7,7,"[1991, 1999, 2003, 2007, 2011, 2015, 2019]",7.0,0.008150971593502705,Low Gender Representation,0.0,0 +36029,0,8,8,"[1991, 1995, 1999, 2003, 2007, 2011, 2015, 2019]",8.0,0.004677734981047276,Low Gender Representation,0.0,0 +36055,4,5,9,"[1991, 1995, 1999, 2003, 2007, 2007, 2011, 2015, 2019]",0.1111111111111111,0.7388826803635273,Low Gender Representation not Detected,0.4444444444444444,4 +36059,1,8,9,"[1989, 1993, 1997, 2001, 2005, 2009, 2013, 2017, 2021]",5.444444444444445,0.019630657257290702,Low Gender Representation,0.1111111111111111,1 +36065,0,6,6,"[1999, 2003, 2007, 2011, 2015, 2019]",6.0,0.014305878435429641,Low Gender Representation,0.0,0 +36067,3,4,7,"[1991, 2003, 2007, 2011, 2015, 2018, 2019]",0.14285714285714285,0.7054569861112734,Low Gender Representation not Detected,0.42857142857142855,4 +36071,1,6,7,"[1989, 2001, 2005, 2009, 2013, 2017, 2021]",3.5714285714285716,0.05878172135535891,Low Gender Representation not Detected,0.14285714285714285,1 +36079,3,6,9,"[1990, 1994, 1998, 2002, 2006, 2010, 2011, 2014, 2018]",1.0,0.31731050786291115,Low Gender Representation not Detected,0.3333333333333333,3 +36083,4,5,9,"[1989, 1993, 1997, 2001, 2005, 2009, 2013, 2017, 2021]",0.1111111111111111,0.7388826803635273,Low Gender Representation not Detected,0.4444444444444444,4 +36087,0,8,8,"[1993, 1997, 2001, 2005, 2009, 2013, 2017, 2021]",8.0,0.004677734981047276,Low Gender Representation,0.0,0 +36103,0,8,8,"[1991, 1999, 2003, 2007, 2010, 2011, 2015, 2019]",8.0,0.004677734981047276,Low Gender Representation,0.0,0 +36111,1,3,4,"[2008, 2011, 2015, 2019]",1.0,0.31731050786291115,Low Gender Representation not Detected,0.25,2 +36119,0,9,9,"[1989, 1993, 1997, 2001, 2005, 2009, 2013, 2017, 2021]",9.0,0.0026997960632601883,Low Gender Representation,0.0,0 +39035,0,3,3,"[2010, 2014, 2018]",3.0,0.08326451666355042,Low Gender Representation not Detected,0.0,0 +39153,1,6,7,"[1992, 1996, 2000, 2004, 2008, 2012, 2016]",3.5714285714285716,0.05878172135535891,Low Gender Representation not Detected,0.14285714285714285,1 +42003,0,6,6,"[1999, 2003, 2007, 2011, 2015, 2019]",6.0,0.014305878435429641,Low Gender Representation,0.0,0 +42049,4,3,7,"[1989, 1993, 1997, 2001, 2005, 2009, 2013]",0.14285714285714285,0.7054569861112734,Low Gender Representation not Detected,0.5714285714285714,6 +42077,3,6,9,"[1989, 1993, 1997, 2001, 2005, 2009, 2013, 2017, 2021]",1.0,0.31731050786291115,Low Gender Representation not Detected,0.3333333333333333,3 +42095,0,7,7,"[1989, 1993, 1997, 2001, 2005, 2009, 2013]",7.0,0.008150971593502705,Low Gender Representation,0.0,0 +47009,1,4,5,"[1998, 2002, 2006, 2010, 2014]",1.8,0.17971249487899593,Low Gender Representation not Detected,0.2,2 +47065,0,10,10,"[1990, 1994, 1998, 2002, 2006, 2010, 2011, 2012, 2014, 2018]",10.0,0.001565402258002549,Low Gender Representation,0.0,0 +47125,1,3,4,"[1994, 2002, 2010, 2014]",1.0,0.31731050786291115,Low Gender Representation not Detected,0.25,2 +47157,0,9,9,"[1990, 1994, 1998, 2002, 2006, 2009, 2010, 2014, 2018]",9.0,0.0026997960632601883,Low Gender Representation,0.0,0 +48061,0,4,4,"[2010, 2014, 2016, 2018]",4.0,0.04550026389635857,Low Gender Representation,0.0,0 +48085,0,3,3,"[2010, 2014, 2018]",3.0,0.08326451666355042,Low Gender Representation not Detected,0.0,0 +48121,2,1,3,"[2010, 2014, 2018]",0.3333333333333333,0.5637028616507731,Low Gender Representation not Detected,0.6666666666666666,7 +48141,4,2,6,"[1998, 2002, 2006, 2010, 2014, 2018]",0.6666666666666666,0.4142161782425251,Low Gender Representation not Detected,0.6666666666666666,7 +48157,0,2,2,"[2010, 2014, 2018]",2.0,0.15729920705028105,Low Gender Representation not Detected,0.0,0 +48427,1,4,5,"[1998, 2002, 2006, 2010, 2014]",1.8,0.17971249487899593,Low Gender Representation not Detected,0.2,2 +48439,0,6,6,"[1998, 2002, 2006, 2010, 2014, 2018]",6.0,0.014305878435429641,Low Gender Representation,0.0,0 +49035,3,4,7,"[2000, 2004, 2008, 2012, 2016, 2019, 2020]",0.14285714285714285,0.7054569861112734,Low Gender Representation not Detected,0.42857142857142855,4 +53033,0,10,10,"[1989, 1993, 1996, 1997, 2001, 2005, 2009, 2013, 2017, 2021]",10.0,0.001565402258002549,Low Gender Representation,0.0,0 +53053,2,6,8,"[1992, 1996, 2000, 2004, 2008, 2012, 2016, 2020]",2.0,0.15729920705028105,Low Gender Representation not Detected,0.25,2 +53061,0,9,9,"[1991, 1995, 1999, 2003, 2007, 2011, 2013, 2015, 2019]",9.0,0.0026997960632601883,Low Gender Representation,0.0,0 +53073,2,7,9,"[1991, 1995, 1999, 2003, 2007, 2011, 2015, 2015, 2019]",2.7777777777777777,0.09558070454562936,Low Gender Representation not Detected,0.2222222222222222,2 +55025,3,5,8,"[2001, 2005, 2009, 2010, 2011, 2013, 2017, 2021]",0.5,0.47950012218695337,Low Gender Representation not Detected,0.375,4 +55079,0,11,11,"[1992, 2000, 2002, 2004, 2008, 2010, 2011, 2012, 2016, 2020, 2020]",11.0,0.0009111188771537126,Low Gender Representation,0.0,0 +55087,0,4,4,"[2007, 2011, 2015, 2019]",4.0,0.04550026389635857,Low Gender Representation,0.0,0 +55133,0,7,7,"[1991, 1999, 2003, 2007, 2011, 2015, 2019]",7.0,0.008150971593502705,Low Gender Representation,0.0,0 diff --git a/gender-web-page/county-executive.csv b/gender-web-page/county-executive.csv new file mode 100644 index 0000000..56ea407 --- /dev/null +++ b/gender-web-page/county-executive.csv @@ -0,0 +1,807 @@ +fips year gender_est +1083 2006 M +1083 2002 M +1083 2014 M +1083 2010 M +1083 1998 M +1083 1994 M +2020 2018 M +2090 2021 M +2090 2018 M +2090 1997 M +2090 1994 M +2090 1991 M +2090 2006 M +2090 2003 M +2090 2015 M +2090 2009 M +2090 2012 M +2090 2000 F +2122 2020 M +2122 2017 M +2122 2002 M +2122 1999 M +2122 2008 M +2122 1993 M +2122 1990 M +2122 2005 M +2122 2014 M +2122 2011 M +2122 1996 M +2170 1994 F +2170 2006 M +2170 1997 F +2170 1991 M +2170 2021 F +2170 2012 M +2170 2011 M +2170 2003 M +2170 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/dev/null +++ b/gender-web-page/gender-count-chisquare-with-female-representation-score.py @@ -0,0 +1,52 @@ +import pandas as pd +from scipy.stats import chisquare + +# Load your data file +data = pd.read_csv('county-executive.csv', delimiter='\t') + +# Group the data by 'fips' and 'gender_est' and count the occurrences +gender_counts = data.groupby(['fips', 'gender_est']).size().unstack(fill_value=0) + +# Rename columns for clarity if needed +gender_counts.columns = ['FemaleCount', 'MaleCount'] + +# Now, define the 'gender_counts_by_fips' DataFrame by resetting the index to make 'fips' a column +gender_counts_by_fips = gender_counts.reset_index() + +# Add a column for the total count of winners per FIPS code +gender_counts_by_fips['TotalCount'] = gender_counts_by_fips['FemaleCount'] + gender_counts_by_fips['MaleCount'] + +# Group the data by 'fips' and collect the sorted list of years into a new column +years_by_fips = data.groupby('fips')['year'].apply(lambda x: sorted(list(x))).reset_index() +gender_counts_by_fips = gender_counts_by_fips.merge(years_by_fips, on='fips', how='left') + +# Function to apply the Chi-Square Goodness of Fit Test for each row (FIPS code) +def perform_chi_square(row): + observed = [row['FemaleCount'], row['MaleCount']] + expected = [row['TotalCount'] / 2, row['TotalCount'] / 2] # Expected counts if the ratio is 1:1 + chi2_stat, p_val = chisquare(observed, f_exp=expected) + return pd.Series([chi2_stat, p_val], index=['ChiSquareStatistic', 'P-Value']) + +# Apply the function across the rows +chi_square_results = gender_counts_by_fips.apply(perform_chi_square, axis=1) + +# Combine the Chi-Square results with the gender count data +combined_results = pd.concat([gender_counts_by_fips, chi_square_results], axis=1) + +# Add a column to indicate if the p-value is lower than 0.05 +combined_results['Representation'] = combined_results['P-Value'].apply( + lambda p: 'Low Gender Representation' if p < 0.05 else 'Low Gender Representation not Detected' +) + +# Add a column for Female Representation Value (FemaleCount / TotalCount) +combined_results['FemaleRepresentation'] = combined_results['FemaleCount'] / combined_results['TotalCount'] + +# Calculate the Representation Score on a scale of 10 +combined_results['FemaleRepresentationScore'] = (combined_results['FemaleRepresentation'] * 10).round().astype(int) + +# Rename the 'year' column to 'Years' for clarity +combined_results.rename(columns={'year': 'Years'}, inplace=True) + +# Save the results to a CSV file +output_filepath_chi_square = 'chi_square_results_with_female_representation_score_by_fips.csv' +combined_results.to_csv(output_filepath_chi_square, index=False) diff --git a/gender-web-page/ledb_candidatelevel.xlsm b/gender-web-page/ledb_candidatelevel.xlsm new file mode 100644 index 0000000000000000000000000000000000000000..24cf74c9e5c51ad2a191782bd06097ef6271e70a GIT binary patch literal 24838365 zcmeFX^OI=7^B%mmZSUT-@7lI)+qP}nwr$(CZ5z3t;Kh 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