diff --git a/data/wnba_clean.csv b/data/wnba_clean.csv index 3d702f3..b365fcb 100644 --- a/data/wnba_clean.csv +++ b/data/wnba_clean.csv @@ -1,143 +1,143 @@ -Name,Team,Pos,Height,Weight,BMI,Birth_Place,Birthdate,Age,College,Experience,Games Played,MIN,FGM,FGA,FG%,3PM,3PA,3P%,FTM,FTA,FT%,OREB,DREB,REB,AST,STL,BLK,TO,PTS,DD2,TD3 -Aerial Powers,DAL,F,183,71,21.20099137,US,"January 17, 1994",23,Michigan State,2,8,173,30,85,35.3,12,32,37.5,21,26,80.8,6,22,28,12,3,6,12,93,0,0 -Alana Beard,LA,G/F,185,73,21.32943755,US,"May 14, 1982",35,Duke,12,30,947,90,177,50.8,5,18,27.8,32,41,78.0,19,82,101,72,63,13,40,217,0,0 -Alex Bentley,CON,G,170,69,23.87543253,US,"October 27, 1990",26,Penn State,4,26,617,82,218,37.6,19,64,29.7,35,42,83.3,4,36,40,78,22,3,24,218,0,0 -Alex Montgomery,SAN,G/F,185,84,24.54346238,US,"December 11, 1988",28,Georgia Tech,6,31,721,75,195,38.5,21,68,30.9,17,21,81.0,35,134,169,65,20,10,38,188,2,0 -Alexis Jones,MIN,G,175,78,25.46938776,US,"August 5, 1994",23,Baylor,R,24,137,16,50,32.0,7,20,35.0,11,12,91.7,3,9,12,12,7,0,14,50,0,0 -Alexis Peterson,SEA,G,170,63,21.79930796,US,"June 20, 1995",22,Syracuse,R,14,90,9,34,26.5,2,9,22.2,6,6,100.0,3,13,16,11,5,0,11,26,0,0 -Alexis Prince,PHO,G,188,81,22.91760978,US,"February 5, 1994",23,Baylor,R,16,112,9,34,26.5,4,15,26.7,2,2,100.0,1,14,15,5,4,3,3,24,0,0 -Allie Quigley,CHI,G,178,64,20.19946976,US,"June 20, 1986",31,DePaul,8,26,847,166,319,52.0,70,150,46.7,40,46,87.0,9,83,92,95,20,13,59,442,0,0 -Allisha Gray,DAL,G,185,76,22.20598977,US,"October 20, 1992",24,South Carolina,2,30,834,131,346,37.9,29,103,28.2,104,129,80.6,52,75,127,40,47,19,37,395,0,0 -Allison Hightower,WAS,G,178,77,24.30248706,US,"June 4, 1988",29,LSU,5,7,103,14,38,36.8,2,11,18.2,6,6,100.0,3,7,10,10,5,0,2,36,0,0 -Alysha Clark,SEA,F,180,76,23.45679012,US,"July 7, 1987",30,Middle Tennessee,6,30,843,93,183,50.8,20,62,32.3,38,51,74.5,29,97,126,50,22,4,32,244,0,0 -Alyssa Thomas,CON,F,188,84,23.76641014,US,"December 4, 1992",24,Maryland,3,28,833,154,303,50.8,0,3,0.0,91,158,57.6,34,158,192,136,48,11,87,399,4,0 -Amanda Zahui B.,NY,C,196,113,29.41482716,SE,"August 9, 1993",24,Minnesota,3,25,133,20,53,37.7,2,8,25.0,9,12,75.0,5,18,23,7,4,5,12,51,0,0 -Amber Harris,CHI,F,196,88,22.90712203,US,"January 16, 1988",29,Xavier,3,22,146,18,44,40.9,0,10,0.0,5,8,62.5,12,28,40,5,3,9,6,41,0,0 -Aneika Henry,ATL,F/C,193,87,23.35633171,JM,"February 13, 1986",31,Florida,6,4,22,4,4,100.0,0,0,0.0,0,0,0.0,0,4,4,1,2,0,3,8,0,0 -Angel Robinson,PHO,F/C,198,88,22.44668911,US,"August 30, 1995",21,Arizona State,1,15,237,25,44,56.8,1,1,100.0,7,7,100.0,16,42,58,8,1,11,16,58,0,0 -Asia Taylor,WAS,F,185,76,22.20598977,US,"August 22, 1991",26,Louisville,3,20,128,10,31,32.3,0,0,0.0,11,18,61.1,16,21,37,9,5,2,10,31,0,0 -Bashaara Graves,CHI,F,188,91,25.74694432,US,"March 17, 1994",23,Tennessee,1,5,59,8,14,57.1,0,0,0.0,3,4,75.0,4,13,17,3,0,1,3,19,0,0 -Breanna Lewis,DAL,C,196,93,24.20866306,US,"June 22, 1994",23,Kansas State,R,12,50,2,12,16.7,0,0,0.0,3,4,75.0,2,7,9,2,0,0,7,7,0,0 -Breanna Stewart,SEA,F/C,193,77,20.67169588,US,"August 27, 1994",22,Connecticut,2,29,952,201,417,48.2,46,123,37.4,136,171,79.5,43,206,249,78,29,47,68,584,8,0 -Bria Hartley,NY,G,173,66,22.05219018,US,"September 30, 1992",24,Connecticut,4,29,598,80,192,41.7,32,93,34.4,25,33,75.8,7,50,57,58,15,5,44,217,0,0 -Bria Holmes,ATL,G,185,77,22.49817385,US,"April 19, 1994",23,West Virginia,R,28,655,85,231,36.8,9,50,18.0,56,84,66.7,29,56,85,52,23,7,31,235,0,0 -Briann January,IND,G,173,65,21.71806609,US,"November 1, 1987",29,Arizona State,9,25,657,81,205,39.5,18,57,31.6,58,71,81.7,12,25,37,98,23,4,53,238,0,0 -Brionna Jones,CON,F,191,104,28.50799046,US,"December 18, 1995",21,Maryland,R,19,112,14,26,53.8,0,0,0.0,16,19,84.2,11,14,25,2,7,1,7,44,0,0 -Brittany Boyd,NY,G,175,71,23.18367347,US,"November 6, 1993",23,UC Berkeley,3,2,32,9,15,60.0,0,1,0.0,8,11,72.7,3,5,8,5,3,0,2,26,0,0 -Brittney Griner,PHO,C,206,93,21.91535489,US,"October 18, 1990",26,Baylor,5,22,682,167,293,57.0,0,0,0.0,127,154,82.5,43,129,172,39,13,54,52,461,6,0 -Brittney Sykes,ATL,G,175,66,21.55102041,US,"July 2, 1994",23,Rutgers,10,30,734,146,362,40.3,29,87,33.3,76,102,74.5,25,94,119,59,18,17,49,397,1,0 -Camille Little,PHO,F,188,82,23.20054323,US,"January 18, 1985",32,North Carolina,11,30,759,93,219,42.5,9,52,17.3,33,52,63.5,42,71,113,42,28,13,50,228,0,0 -Candace Parker,LA,F/C,193,79,21.20862305,US,"April 19, 1986",31,Tennessee,10,29,889,183,383,47.8,40,114,35.1,88,115,76.5,37,205,242,127,43,53,80,494,10,1 -Candice Dupree,IND,F,188,81,22.91760978,US,"February 25, 1984",33,Temple,12,29,911,189,370,51.1,0,2,0.0,57,65,87.7,31,124,155,47,28,12,42,435,2,0 -Cappie Pondexter,CHI,G,175,73,23.83673469,US,"July 1, 1983",34,Rutgers,11,24,676,94,258,36.4,8,32,25.0,54,67,80.6,10,59,69,104,17,5,56,250,2,0 -Carolyn Swords,SEA,C,198,95,24.2322212,US,"July 19, 1989",28,Boston College,6,26,218,19,39,48.7,0,0,0.0,16,20,80.0,10,29,39,9,5,4,22,54,0,0 -Cayla George,PHO,C,193,87,23.35633171,AU,"April 20, 1987",30,Georgia,1,28,365,40,105,38.1,13,45,28.9,7,12,58.3,10,71,81,15,9,11,13,100,1,0 -Chelsea Gray,LA,G,180,77,23.7654321,US,"August 10, 1992",25,Duke,3,30,996,165,326,50.6,48,100,48.0,78,94,83.0,19,80,99,132,29,7,61,456,1,0 -Cheyenne Parker,CHI,F,193,86,23.08786813,US,"August 22, 1992",25,Middle Tennessee,2,23,286,32,69,46.4,0,3,0.0,23,36,63.9,31,47,78,13,8,15,21,87,0,0 -Clarissa dos Santos,SAN,C,185,89,26.00438276,BR,"October 3, 1988",28,Brazil,4,7,52,8,14,57.1,1,1,100.0,0,0,0.0,3,7,10,7,1,1,5,17,0,0 -Courtney Paris,DAL,C,193,113,30.33638487,US,"September 21, 1987",29,Oklahoma,7,16,217,32,57,56.1,0,0,0.0,6,12,50.0,28,34,62,5,6,8,18,70,0,0 -Courtney Vandersloot,CHI,G,173,66,22.05219018,US,"August 2, 1989",28,Gonzaga,6,22,673,104,199,52.3,23,60,38.3,24,29,82.8,13,75,88,175,22,5,64,255,10,0 -Courtney Williams,CON,G,173,62,20.71569381,US,"November 5, 1994",22,South Florida,1,29,755,168,338,49.7,8,30,26.7,31,36,86.1,38,84,122,60,15,6,39,375,1,0 -Crystal Langhorne,SEA,F/C,188,84,23.76641014,US,"October 27, 1986",30,Maryland,10,30,848,160,240,66.7,1,2,50.0,49,68,72.1,35,140,175,46,16,11,50,370,2,0 -Damiris Dantas,ATL,C,191,89,24.39626107,BR,"November 17, 1992",24,Brazil,4,30,569,98,243,40.3,25,91,27.5,33,43,76.7,29,84,113,19,17,18,26,254,0,0 -Danielle Adams,CON,F/C,185,108,31.555880199999997,US,"February 19, 1989",28,Texas A&M,5,18,81,16,43,37.2,12,30,40.0,5,5,100.0,6,4,10,4,4,4,7,49,0,0 -Danielle Robinson,PHO,G,175,57,18.6122449,US,"October 5, 1989",27,Oklahoma,7,28,680,79,178,44.4,0,5,0.0,51,61,83.6,13,73,86,106,33,4,58,209,0,0 -Dearica Hamby,SAN,F,191,86,23.57391519,US,"June 11, 1993",24,Wake Forest,2,31,650,96,207,46.4,3,8,37.5,58,95,61.1,48,91,139,32,29,8,43,253,1,0 -Devereaux Peters,IND,F,188,79,22.35174287,US,"August 10, 1989",28,Notre Dame,6,28,796,154,380,40.5,88,225,39.1,118,130,90.8,8,69,77,76,16,9,56,514,0,0 -Diana Taurasi,PHO,G,183,74,22.09680791,US,"November 6, 1982",34,Connecticut,13,20,591,121,255,47.5,22,66,33.3,112,118,94.9,31,98,129,32,20,31,28,376,3,0 -Elena Delle Donne,WAS,G/F,196,85,22.12619742,US,"May 9, 1989",28,Delaware,5,30,939,133,272,48.9,0,1,0.0,51,78,65.4,99,116,215,43,32,64,36,317,4,0 -Elizabeth Williams,ATL,F/C,191,87,23.84803048,US,"June 23, 1993",24,Duke,3,30,377,48,96,50.0,0,1,0.0,32,55,58.2,35,61,96,5,5,4,21,128,0,0 -Emma Cannon,PHO,F,188,86,24.33227705,US,"January 6, 1989",28,Central Florida,R,18,508,105,220,47.7,11,33,33.3,31,34,91.2,33,72,105,52,21,27,30,252,1,0 -Emma Meesseman,WAS,C,193,83,22.28247738,BE,"May 13, 1993",24,Belgium,5,23,617,89,233,38.2,25,79,31.6,56,65,86.2,23,58,81,70,34,5,30,259,0,0 -Epiphanny Prince,NY,G,175,81,26.44897959,US,"November 1, 1988",28,Rutgers,8,26,282,36,86,41.9,1,3,33.3,15,22,68.2,17,44,61,5,4,8,17,88,0,0 -Erica Wheeler,IND,G,170,65,22.49134948,US,"February 5, 1991",26,Rutgers,3,30,767,130,321,40.5,42,129,32.6,34,40,85.0,11,57,68,117,38,1,68,336,0,0 -Érika de Souza,SAN,C,196,86,22.38650562,BR,"September 3, 1982",34,Brazil,13,30,579,65,112,58.0,0,0,0.0,29,32,90.6,58,74,132,35,18,7,37,159,0,0 -Erlana Larkins,IND,F,185,93,27.17311907,US,"February 4, 1986",31,North Carolina,9,20,386,36,92,39.1,9,35,25.7,21,24,87.5,9,26,35,24,11,8,13,102,0,0 -Essence Carson,LA,G/F,183,74,22.09680791,US,"July 28, 1986",31,Rutgers,10,15,61,4,16,25.0,0,0,0.0,5,6,83.3,7,2,9,0,1,3,5,13,0,0 -Evelyn Akhator,DAL,F,191,82,22.47745402,NG,"March 2, 1995",22,Kentucky,R,30,926,165,365,45.2,20,60,33.3,92,117,78.6,73,199,272,50,37,13,67,442,13,0 -Glory Johnson,DAL,F,191,77,21.10687755,US,"July 27, 1990",27,Tennessee,4,4,42,3,9,33.3,3,6,50.0,0,0,0.0,0,3,3,1,0,0,4,9,0,0 -Imani Boyette,ATL,C,201,88,21.78163907,US,"November 10, 1992",24,Texas,1,29,410,56,119,47.1,1,3,33.3,14,20,70.0,43,75,118,14,9,23,22,127,1,0 -Isabelle Harrison,SAN,C,191,83,22.75156931,US,"September 27, 1993",23,Kentucky,3,31,832,154,300,51.3,1,2,50.0,55,85,64.7,66,134,200,46,26,24,63,364,5,0 -Ivory Latta,WAS,G,168,63,22.32142857,US,"September 25, 1984",32,North Carolina,12,29,499,79,218,36.2,40,114,35.1,47,55,85.5,7,20,27,49,12,1,22,245,0,0 -Jantel Lavender,LA,C,193,84,22.55094096,US,"December 11, 1988",28,Ohio State,7,28,481,89,184,48.4,4,13,30.8,18,22,81.8,31,56,87,28,8,5,35,200,0,0 -Jasmine Thomas,CON,G,175,66,21.55102041,US,"September 30, 1989",27,Duke,6,27,762,151,341,44.3,50,116,43.1,39,55,70.9,9,55,64,118,45,4,58,391,1,0 -Jazmon Gwathmey,IND,G,188,65,18.39067451,PR,"January 24, 1993",24,James Madison,2,24,371,50,140,35.7,12,49,24.5,30,39,76.9,15,34,49,17,13,19,32,142,0,0 -Jeanette Pohlen,IND,G,183,78,23.29122996,US,"February 5, 1989",28,Stanford,6,25,278,20,52,38.5,13,29,44.8,17,20,85.0,3,19,22,13,5,0,15,70,0,0 -Jennifer Hamson,IND,C,201,95,23.51426945,US,"January 23, 1992",25,Brigham Young,1,10,50,2,12,16.7,0,3,0.0,8,10,80.0,5,6,11,6,2,2,3,12,0,0 -Jessica Breland,CHI,F,191,77,21.10687755,US,"February 23, 1988",29,North Carolina,5,10,78,9,16,56.3,0,0,0.0,4,5,80.0,5,13,18,2,1,9,3,22,0,0 -Jewell Loyd,SEA,G,178,67,21.14631991,US,"May 10, 1993",24,Notre Dame,3,29,715,116,245,47.3,8,21,38.1,28,37,75.7,50,139,189,46,18,50,57,268,4,0 -Jia Perkins,MIN,G,173,75,25.05930703,US,"February 23, 1982",35,Texas Tech,14,30,932,178,420,42.4,47,123,38.2,114,134,85.1,24,72,96,103,41,11,83,517,0,0 -Jonquel Jones,CON,F/C,198,86,21.93653709,BS,"May 1, 1994",23,George Washington,1,29,463,47,124,37.9,11,32,34.4,11,15,73.3,11,46,57,39,30,1,24,116,0,0 -Jordan Hooper,CHI,F,188,84,23.76641014,US,"February 20, 1992",25,Nebraska,3,29,833,164,299,54.8,22,49,44.9,117,142,82.4,108,226,334,40,29,46,46,467,17,0 -Kaela Davis,DAL,G,188,77,21.78587596,US,"March 15, 1995",22,South Carolina,R,23,208,27,75,36.0,20,55,36.4,3,4,75.0,2,20,22,5,7,1,6,77,0,0 -Kahleah Copper,CHI,G/F,185,70,20.45288532,US,"August 28, 1994",22,Rutgers,1,29,475,62,163,38.0,12,32,37.5,49,65,75.4,10,33,43,32,13,3,48,185,0,0 -Kaleena Mosqueda-Lewis,SEA,F,180,82,25.30864198,US,"March 11, 1993",24,Connecticut,3,29,369,60,140,42.9,5,23,21.7,36,45,80.0,11,43,54,11,9,2,22,161,0,0 -Karima Christmas-Kelly,DAL,G/F,183,82,24.48565201,US,"November 9, 1989",27,Duke,6,14,142,23,43,53.5,9,21,42.9,10,10,100.0,4,10,14,6,1,1,13,65,0,0 -Kayla Alexander,SAN,C,193,88,23.624795300000002,CA,"May 1, 1991",26,Arizona State,4,30,889,91,239,38.1,25,83,30.1,111,129,86.0,45,75,120,65,39,5,50,318,0,0 -Kayla McBride,SAN,G/F,180,79,24.38271605,US,"June 25, 1992",25,Notre Dame,3,31,433,78,141,55.3,0,0,0.0,15,16,93.8,40,47,87,17,13,15,30,171,0,0 -Kayla Pedersen,CON,F,193,86,23.08786813,US,"April 14, 1989",28,Stanford,5,27,882,128,337,38.0,47,147,32.0,108,118,91.5,12,93,105,59,32,5,54,411,0,0 -Kayla Thornton,DAL,F,185,86,25.12783053,US,"October 20, 1992",24,Texas–El Paso,2,21,224,11,30,36.7,0,1,0.0,10,14,71.4,19,26,45,13,6,2,9,32,0,0 -Keisha Hampton,CHI,F,185,78,22.79035793,US,"February 22, 1990",27,DePaul,1,30,504,64,157,40.8,14,52,26.9,65,81,80.2,36,59,95,24,20,7,21,207,0,0 -Kelsey Plum,SAN,G,173,66,22.05219018,US,"August 24, 1994",23,Washington,R,28,610,73,210,34.8,29,78,37.2,50,58,86.2,11,42,53,91,13,4,72,225,0,0 -Kia Vaughn,NY,C,193,90,24.16172246,US,"January 24, 1987",30,Rutgers,9,23,455,62,116,53.4,0,0,0.0,10,19,52.6,39,71,110,16,8,9,21,134,1,0 -Kiah Stokes,NY,C,191,87,23.84803048,US,"March 30, 1993",24,Connecticut,3,29,576,50,98,51.0,0,1,0.0,41,52,78.8,63,122,185,21,8,32,33,141,3,0 -Kristi Toliver,WAS,G,170,59,20.41522491,US,"January 27, 1987",30,Maryland,9,29,845,119,284,41.9,67,194,34.5,44,49,89.8,9,50,59,91,20,8,48,349,0,0 -Krystal Thomas,WAS,C,196,88,22.90712203,US,"October 6, 1989",27,Duke,6,29,737,81,149,54.4,0,0,0.0,37,61,60.7,97,172,269,30,15,31,45,199,2,0 -Lanay Montgomery,SEA,C,196,96,24.98958767,US,"September 17, 1993",23,West Virginia,R,7,28,3,7,42.9,0,0,0.0,0,0,0.0,0,5,5,0,1,4,2,6,0,0 -Layshia Clarendon,ATL,G,175,64,20.89795918,US,"February 5, 1991",26,UC Berkeley,5,30,900,124,320,38.8,8,53,15.1,73,81,90.1,27,88,115,206,29,1,82,329,3,0 -Leilani Mitchell,PHO,G,165,58,21.30394858,US,"June 15, 1985",32,Utah,9,30,623,70,182,38.5,31,92,33.7,62,75,82.7,12,57,69,108,26,9,50,233,0,0 -Lindsay Allen,NY,G,173,65,21.71806609,US,"March 20, 1995",22,Notre Dame,R,23,314,21,50,42.0,0,11,0.0,6,9,66.7,8,28,36,47,13,1,18,48,0,0 -Lindsay Whalen,MIN,G,175,78,25.46938776,US,"September 5, 1982",34,Minnesota,14,22,520,69,153,45.1,12,34,35.3,27,36,75.0,8,46,54,90,11,2,44,177,0,0 -Lynetta Kizer,CON,C,193,104,27.92021262,US,"April 4, 1990",27,Maryland,5,20,238,48,100,48.0,0,1,0.0,23,30,76.7,22,35,57,6,11,7,10,119,0,0 -Maimouna Diarra,LA,C,198,90,22.95684114,SN,"January 30, 1991",26,Sengal,R,9,16,1,3,33.3,0,0,0.0,1,2,50.0,3,4,7,1,1,0,3,3,0,0 -Marissa Coleman,IND,G/F,185,73,21.32943755,US,"April 1, 1987",30,Maryland,9,30,539,50,152,32.9,27,79,34.2,27,33,81.8,7,53,60,25,8,4,34,154,0,0 -Matee Ajavon,ATL,G,173,73,24.39105884,US,"July 5, 1986",31,Syracruse,R,27,218,22,69,31.9,0,3,0.0,29,35,82.9,8,26,34,27,10,0,26,73,0,0 -Maya Moore,MIN,F,183,80,23.88844098,US,"November 6, 1989",27,Connecticut,7,29,904,170,398,42.7,52,132,39.4,98,114,86.0,50,106,156,99,53,13,56,490,3,0 -Monique Currie,PHO,G/F,183,80,23.88844098,US,"February 25, 1983",34,Duke,11,32,717,121,284,42.6,37,93,39.8,85,103,82.5,19,103,122,67,22,11,48,364,0,0 -Morgan Tuck,CON,F,188,91,25.74694432,US,"April 30, 1994",23,Connecticut,1,17,294,35,101,34.7,8,28,28.6,13,16,81.3,9,34,43,19,7,0,15,91,1,0 -Moriah Jefferson,SAN,G,168,55,19.48696145,US,"August 3, 1994",23,Connecticut,1,21,514,81,155,52.3,9,20,45.0,20,27,74.1,6,31,37,92,33,2,43,191,0,0 -Natalie Achonwa,IND,C,193,83,22.28247738,CA,"November 22, 1992",24,Notre Dame,3,30,529,82,151,54.3,0,0,0.0,43,55,78.2,31,70,101,21,11,16,25,207,0,0 -Natasha Cloud,WAS,G,183,73,21.79820239,US,"February 22, 1992",25,Saint Joseph's,3,24,448,37,118,31.4,12,51,23.5,20,27,74.1,7,52,59,69,17,3,23,106,0,0 -Natasha Howard,MIN,F,188,75,21.22000905,US,"February 9, 1991",26,Florida State,4,29,315,48,104,46.2,3,13,23.1,17,23,73.9,25,38,63,16,11,19,20,116,0,0 -Nayo Raincock-Ekunwe,NY,F/C,188,79,22.35174287,CA,"August 29, 1991",25,Simon Fraser,R,27,243,33,63,52.4,0,4,0.0,30,49,61.2,24,22,46,8,2,1,13,96,0,0 -Nia Coffey,SAN,F,185,77,22.49817385,US,"May 21, 1995",22,Northwestern,R,25,203,16,59,27.1,0,4,0.0,16,22,72.7,16,30,46,6,5,6,14,48,0,0 -Nneka Ogwumike,LA,F,188,79,22.35174287,US,"February 7, 1990",27,Stanford,6,30,948,215,386,55.7,18,49,36.7,129,148,87.2,57,179,236,63,53,14,47,577,9,0 -Noelle Quinn,SEA,G,183,81,24.18704649,US,"March 1, 1985",32,UCLA,11,29,459,24,58,41.4,14,35,40.0,17,18,94.4,1,48,49,78,12,5,27,79,0,0 -Odyssey Sims,LA,G,173,73,24.39105884,US,"July 13, 1992",25,Baylor,4,27,626,86,198,43.4,11,49,22.4,47,55,85.5,10,34,44,87,38,5,39,230,1,0 -Plenette Pierson,MIN,F/C,188,88,24.89814396,US,"August 31, 1981",35,Texas Tech,15,29,402,54,142,38.0,17,51,33.3,15,20,75.0,13,49,62,48,12,4,33,140,0,0 -Rachel Banham,CON,G,175,76,24.81632653,US,"July 15, 1993",24,Minnesota,2,26,238,32,87,36.8,16,48,33.3,16,20,80.0,2,27,29,20,4,0,12,96,0,0 -Ramu Tokashiki,SEA,F,193,80,21.47708663,JP,"November 6, 1991",25,Japan,1,29,378,42,92,45.7,0,3,0.0,22,27,81.5,19,29,48,16,8,8,25,106,0,0 -Rebecca Allen,NY,G/F,188,74,20.937075600000004,AU,"June 11, 1992",25,Australia,3,28,254,31,86,36.0,14,40,35.0,2,6,33.3,13,51,64,15,9,12,17,78,0,0 -Rebekkah Brunson,MIN,F,188,84,23.76641014,US,"November 12, 1981",35,Georgetown,14,26,719,97,218,44.5,22,60,36.7,62,83,74.7,46,135,181,40,31,9,42,278,2,0 -Renee Montgomery,MIN,G,170,63,21.79930796,US,"February 12, 1986",31,Connecticut,9,29,614,71,181,39.2,30,89,33.7,44,51,86.3,12,34,46,96,24,1,43,216,0,0 -Riquna Williams,LA,G,170,75,25.95155709,US,"May 28, 1990",27,Miami (FL),5,23,408,45,140,32.1,20,74,27.0,38,44,86.4,6,26,32,16,19,3,26,148,0,0 -Sami Whitcomb,SEA,G,178,66,20.83070319,US,"July 20, 1988",29,Washington,R,29,354,46,120,38.3,33,94,35.1,14,17,82.4,12,40,52,24,22,0,24,139,0,0 -Sancho Lyttle,ATL,F,193,79,21.20862305,ES,"September 20, 1983",33,Houston,13,25,703,71,163,43.6,1,7,14.3,13,19,68.4,42,138,180,41,40,17,34,156,0,0 -Sandrine Gruda,LA,F/C,193,84,22.55094096,FR,"June 25, 1987",30,France,5,4,12,1,3,33.3,0,0,0.0,0,0,0.0,0,2,2,0,0,0,2,2,0,0 -Saniya Chong,DAL,G,173,64,21.383942,US,"June 27, 1994",23,Connecticut,R,29,348,27,74,36.5,8,35,22.9,25,29,86.2,9,19,28,33,21,3,23,87,0,0 -Seimone Augustus,MIN,G/F,183,77,22.99262444,US,"April 30, 1984",33,LSU,12,27,756,125,251,49.8,18,41,43.9,30,35,85.7,12,70,82,108,17,1,39,298,1,0 -Sequoia Holmes,SAN,G,185,70,20.45288532,US,"June 13, 1986",31,UNLV,2,24,280,31,89,34.8,13,46,28.3,6,11,54.5,12,12,24,23,13,5,11,81,0,0 -Shatori Walker-Kimbrough,WAS,G,180,64,19.75308642,US,"May 18, 1995",22,Maryland,R,22,260,29,78,37.2,9,26,34.6,29,32,90.6,4,13,17,10,11,1,12,96,0,0 -Shavonte Zellous,NY,G,178,85,26.82742078,US,"August 28, 1986",30,Pittsburgh,9,29,865,107,249,43.0,14,41,34.1,118,144,81.9,30,92,122,87,23,8,62,346,1,0 -Shay Murphy,SAN,G,180,74,22.83950617,US,"April 15, 1985",32,Southern California,9,23,242,23,62,37.1,12,35,34.3,8,12,66.7,12,26,38,17,10,1,12,66,0,0 -Shekinna Stricklen,CON,G/F,188,81,22.91760978,US,"July 30, 1990",27,Tennessee,5,29,795,80,202,39.6,59,149,39.6,26,31,83.9,15,71,86,30,36,2,23,245,0,0 -Shenise Johnson,IND,G,180,78,24.07407407,US,"September 12, 1990",26,Miami (FL),6,14,348,55,127,43.3,10,30,33.3,38,40,95.0,13,35,48,35,21,4,18,158,0,0 -Skylar Diggins-Smith,DAL,G,175,66,21.55102041,US,"February 8, 1990",27,Notre Dame,4,30,1018,167,394,42.4,43,119,36.1,168,186,90.3,21,86,107,173,38,24,83,545,1,0 -Stefanie Dolson,CHI,C,196,97,25.24989588,US,"August 1, 1992",25,Connecticut,3,28,823,162,293,55.3,24,60,40.0,50,58,86.2,35,121,156,65,14,37,65,398,3,0 -Stephanie Talbot,PHO,G,185,87,25.42001461,AU,"December 20, 1990",26,Australia,R,30,555,47,114,41.2,15,38,39.5,29,44,65.9,28,58,86,50,22,8,28,138,0,0 -Sue Bird,SEA,G,175,68,22.20408163,US,"October 16, 1980",36,Connecticut,15,27,806,103,244,42.2,50,134,37.3,17,24,70.8,7,46,53,177,31,3,57,273,1,0 -Sugar Rodgers,NY,G,175,75,24.48979592,US,"August 12, 1989",28,Georgetown,6,28,745,108,310,34.8,59,163,36.2,42,52,80.8,21,85,106,68,28,17,43,317,0,0 -Sydney Colson,SAN,G,173,64,21.383942,US,"June 8, 1989",28,Texas A&M,3,25,296,25,78,32.1,2,10,20.0,20,30,66.7,3,11,14,51,13,2,25,72,0,0 -Sydney Wiese,LA,G,183,68,20.30517483,US,"July 13, 1992",25,Oregon State,R,25,189,19,50,38.0,13,32,40.6,4,8,50.0,3,18,21,6,4,3,2,55,0,0 -Sylvia Fowles,MIN,C,198,96,24.48729721,US,"June 10, 1985",32,LSU,10,29,895,222,336,66.1,0,0,0.0,128,162,79.0,113,184,297,39,39,61,71,572,16,0 -Tamera Young,ATL,G/F,188,77,21.78587596,US,"October 30, 1986",30,Tennessee,9,31,820,105,297,35.4,23,70,32.9,44,65,67.7,23,87,110,66,36,14,61,277,0,0 -Tayler Hill,WAS,G,175,66,21.55102041,US,"October 23, 1990",26,Ohio State,5,18,462,69,191,36.1,27,89,30.3,75,80,93.8,5,29,34,47,16,1,26,240,0,0 -Temi Fagbenle,MIN,C,193,89,23.89325888,UK,"August 9, 1992",25,Southern California,R,17,74,6,14,42.9,0,0,0.0,5,6,83.3,3,13,16,1,3,3,8,17,0,0 -Theresa Plaisance,DAL,F,196,91,23.68804665,US,"May 18, 1992",25,LSU,4,30,604,80,213,37.6,35,101,34.7,22,24,91.7,38,89,127,24,23,22,24,217,1,0 -Tianna Hawkins,WAS,F,191,87,23.84803048,US,"February 3, 1991",26,Maryland,4,29,483,79,165,47.9,11,41,26.8,41,43,95.3,42,82,124,9,15,7,23,210,0,0 -Tierra Ruffin-Pratt,WAS,G,178,83,26.19618735,US,"November 4, 1991",25,North Carolina,5,29,703,77,217,35.5,0,4,0.0,71,96,74.0,45,120,165,68,30,16,47,225,2,0 -Tiffany Hayes,ATL,G,178,70,22.09317005,US,"September 20, 1989",27,Connecticut,6,29,861,144,331,43.5,43,112,38.4,136,161,84.5,28,89,117,69,37,8,50,467,0,0 -Tiffany Jackson,LA,F,191,84,23.0256846,US,"April 26, 1985",32,Texas,9,22,127,12,25,48.0,0,1,0.0,4,6,66.7,5,18,23,3,1,3,8,28,0,0 -Tiffany Mitchell,IND,G,175,69,22.53061224,US,"September 23, 1984",32,South Carolina,2,27,671,83,238,34.9,17,69,24.6,94,102,92.2,16,70,86,39,31,5,40,277,0,0 -Tina Charles,NY,F/C,193,84,22.55094096,US,"May 12, 1988",29,Connecticut,8,29,952,227,509,44.6,18,56,32.1,110,135,81.5,56,212,268,75,21,22,71,582,11,0 -Yvonne Turner,PHO,G,175,59,19.26530612,US,"October 13, 1987",29,Nebraska,2,30,356,59,140,42.1,11,47,23.4,22,28,78.6,11,13,24,30,18,1,32,151,0,0 +,Name,Team,Pos,Height,Weight,BMI,Birth_Place,Birthdate,Age,College,Experience,Games Played,MIN,FGM,FGA,FG%,3PM,3PA,3P%,FTM,FTA,FT%,OREB,DREB,REB,AST,STL,BLK,TO,PTS,DD2,TD3 +0,Aerial Powers,DAL,F,183,71,21.20099137,US,"January 17, 1994",23,Michigan State,2,8,173,30,85,35.3,12,32,37.5,21,26,80.8,6,22,28,12,3,6,12,93,0,0 +1,Alana Beard,LA,G/F,185,73,21.32943755,US,"May 14, 1982",35,Duke,12,30,947,90,177,50.8,5,18,27.8,32,41,78.0,19,82,101,72,63,13,40,217,0,0 +2,Alex Bentley,CON,G,170,69,23.87543253,US,"October 27, 1990",26,Penn State,4,26,617,82,218,37.6,19,64,29.7,35,42,83.3,4,36,40,78,22,3,24,218,0,0 +3,Alex Montgomery,SAN,G/F,185,84,24.54346238,US,"December 11, 1988",28,Georgia Tech,6,31,721,75,195,38.5,21,68,30.9,17,21,81.0,35,134,169,65,20,10,38,188,2,0 +4,Alexis Jones,MIN,G,175,78,25.46938776,US,"August 5, 1994",23,Baylor,R,24,137,16,50,32.0,7,20,35.0,11,12,91.7,3,9,12,12,7,0,14,50,0,0 +5,Alexis Peterson,SEA,G,170,63,21.79930796,US,"June 20, 1995",22,Syracuse,R,14,90,9,34,26.5,2,9,22.2,6,6,100.0,3,13,16,11,5,0,11,26,0,0 +6,Alexis Prince,PHO,G,188,81,22.91760978,US,"February 5, 1994",23,Baylor,R,16,112,9,34,26.5,4,15,26.7,2,2,100.0,1,14,15,5,4,3,3,24,0,0 +7,Allie Quigley,CHI,G,178,64,20.19946976,US,"June 20, 1986",31,DePaul,8,26,847,166,319,52.0,70,150,46.7,40,46,87.0,9,83,92,95,20,13,59,442,0,0 +8,Allisha Gray,DAL,G,185,76,22.20598977,US,"October 20, 1992",24,South Carolina,2,30,834,131,346,37.9,29,103,28.2,104,129,80.6,52,75,127,40,47,19,37,395,0,0 +9,Allison Hightower,WAS,G,178,77,24.30248706,US,"June 4, 1988",29,LSU,5,7,103,14,38,36.8,2,11,18.2,6,6,100.0,3,7,10,10,5,0,2,36,0,0 +10,Alysha Clark,SEA,F,180,76,23.45679012,US,"July 7, 1987",30,Middle Tennessee,6,30,843,93,183,50.8,20,62,32.3,38,51,74.5,29,97,126,50,22,4,32,244,0,0 +11,Alyssa Thomas,CON,F,188,84,23.76641014,US,"December 4, 1992",24,Maryland,3,28,833,154,303,50.8,0,3,0.0,91,158,57.6,34,158,192,136,48,11,87,399,4,0 +12,Amanda Zahui B.,NY,C,196,113,29.41482716,SE,"August 9, 1993",24,Minnesota,3,25,133,20,53,37.7,2,8,25.0,9,12,75.0,5,18,23,7,4,5,12,51,0,0 +13,Amber Harris,CHI,F,196,88,22.90712203,US,"January 16, 1988",29,Xavier,3,22,146,18,44,40.9,0,10,0.0,5,8,62.5,12,28,40,5,3,9,6,41,0,0 +14,Aneika Henry,ATL,F/C,193,87,23.35633171,JM,"February 13, 1986",31,Florida,6,4,22,4,4,100.0,0,0,0.0,0,0,0.0,0,4,4,1,2,0,3,8,0,0 +15,Angel Robinson,PHO,F/C,198,88,22.44668911,US,"August 30, 1995",21,Arizona State,1,15,237,25,44,56.8,1,1,100.0,7,7,100.0,16,42,58,8,1,11,16,58,0,0 +16,Asia Taylor,WAS,F,185,76,22.20598977,US,"August 22, 1991",26,Louisville,3,20,128,10,31,32.3,0,0,0.0,11,18,61.1,16,21,37,9,5,2,10,31,0,0 +17,Bashaara Graves,CHI,F,188,91,25.74694432,US,"March 17, 1994",23,Tennessee,1,5,59,8,14,57.1,0,0,0.0,3,4,75.0,4,13,17,3,0,1,3,19,0,0 +18,Breanna Lewis,DAL,C,196,93,24.20866306,US,"June 22, 1994",23,Kansas State,R,12,50,2,12,16.7,0,0,0.0,3,4,75.0,2,7,9,2,0,0,7,7,0,0 +19,Breanna Stewart,SEA,F/C,193,77,20.67169588,US,"August 27, 1994",22,Connecticut,2,29,952,201,417,48.2,46,123,37.4,136,171,79.5,43,206,249,78,29,47,68,584,8,0 +20,Bria Hartley,NY,G,173,66,22.05219018,US,"September 30, 1992",24,Connecticut,4,29,598,80,192,41.7,32,93,34.4,25,33,75.8,7,50,57,58,15,5,44,217,0,0 +21,Bria Holmes,ATL,G,185,77,22.49817385,US,"April 19, 1994",23,West Virginia,R,28,655,85,231,36.8,9,50,18.0,56,84,66.7,29,56,85,52,23,7,31,235,0,0 +22,Briann January,IND,G,173,65,21.71806609,US,"November 1, 1987",29,Arizona State,9,25,657,81,205,39.5,18,57,31.6,58,71,81.7,12,25,37,98,23,4,53,238,0,0 +23,Brionna Jones,CON,F,191,104,28.50799046,US,"December 18, 1995",21,Maryland,R,19,112,14,26,53.8,0,0,0.0,16,19,84.2,11,14,25,2,7,1,7,44,0,0 +24,Brittany Boyd,NY,G,175,71,23.18367347,US,"November 6, 1993",23,UC Berkeley,3,2,32,9,15,60.0,0,1,0.0,8,11,72.7,3,5,8,5,3,0,2,26,0,0 +25,Brittney Griner,PHO,C,206,93,21.91535489,US,"October 18, 1990",26,Baylor,5,22,682,167,293,57.0,0,0,0.0,127,154,82.5,43,129,172,39,13,54,52,461,6,0 +26,Brittney Sykes,ATL,G,175,66,21.55102041,US,"July 2, 1994",23,Rutgers,10,30,734,146,362,40.3,29,87,33.3,76,102,74.5,25,94,119,59,18,17,49,397,1,0 +27,Camille Little,PHO,F,188,82,23.20054323,US,"January 18, 1985",32,North Carolina,11,30,759,93,219,42.5,9,52,17.3,33,52,63.5,42,71,113,42,28,13,50,228,0,0 +28,Candace Parker,LA,F/C,193,79,21.20862305,US,"April 19, 1986",31,Tennessee,10,29,889,183,383,47.8,40,114,35.1,88,115,76.5,37,205,242,127,43,53,80,494,10,1 +29,Candice Dupree,IND,F,188,81,22.91760978,US,"February 25, 1984",33,Temple,12,29,911,189,370,51.1,0,2,0.0,57,65,87.7,31,124,155,47,28,12,42,435,2,0 +30,Cappie Pondexter,CHI,G,175,73,23.83673469,US,"July 1, 1983",34,Rutgers,11,24,676,94,258,36.4,8,32,25.0,54,67,80.6,10,59,69,104,17,5,56,250,2,0 +31,Carolyn Swords,SEA,C,198,95,24.2322212,US,"July 19, 1989",28,Boston College,6,26,218,19,39,48.7,0,0,0.0,16,20,80.0,10,29,39,9,5,4,22,54,0,0 +32,Cayla George,PHO,C,193,87,23.35633171,AU,"April 20, 1987",30,Georgia,1,28,365,40,105,38.1,13,45,28.9,7,12,58.3,10,71,81,15,9,11,13,100,1,0 +33,Chelsea Gray,LA,G,180,77,23.7654321,US,"August 10, 1992",25,Duke,3,30,996,165,326,50.6,48,100,48.0,78,94,83.0,19,80,99,132,29,7,61,456,1,0 +34,Cheyenne Parker,CHI,F,193,86,23.08786813,US,"August 22, 1992",25,Middle Tennessee,2,23,286,32,69,46.4,0,3,0.0,23,36,63.9,31,47,78,13,8,15,21,87,0,0 +35,Clarissa dos Santos,SAN,C,185,89,26.00438276,BR,"October 3, 1988",28,Brazil,4,7,52,8,14,57.1,1,1,100.0,0,0,0.0,3,7,10,7,1,1,5,17,0,0 +36,Courtney Paris,DAL,C,193,113,30.33638487,US,"September 21, 1987",29,Oklahoma,7,16,217,32,57,56.1,0,0,0.0,6,12,50.0,28,34,62,5,6,8,18,70,0,0 +37,Courtney Vandersloot,CHI,G,173,66,22.05219018,US,"August 2, 1989",28,Gonzaga,6,22,673,104,199,52.3,23,60,38.3,24,29,82.8,13,75,88,175,22,5,64,255,10,0 +38,Courtney Williams,CON,G,173,62,20.71569381,US,"November 5, 1994",22,South Florida,1,29,755,168,338,49.7,8,30,26.7,31,36,86.1,38,84,122,60,15,6,39,375,1,0 +39,Crystal Langhorne,SEA,F/C,188,84,23.76641014,US,"October 27, 1986",30,Maryland,10,30,848,160,240,66.7,1,2,50.0,49,68,72.1,35,140,175,46,16,11,50,370,2,0 +40,Damiris Dantas,ATL,C,191,89,24.39626107,BR,"November 17, 1992",24,Brazil,4,30,569,98,243,40.3,25,91,27.5,33,43,76.7,29,84,113,19,17,18,26,254,0,0 +41,Danielle Adams,CON,F/C,185,108,31.5558802,US,"February 19, 1989",28,Texas A&M,5,18,81,16,43,37.2,12,30,40.0,5,5,100.0,6,4,10,4,4,4,7,49,0,0 +42,Danielle Robinson,PHO,G,175,57,18.6122449,US,"October 5, 1989",27,Oklahoma,7,28,680,79,178,44.4,0,5,0.0,51,61,83.6,13,73,86,106,33,4,58,209,0,0 +43,Dearica Hamby,SAN,F,191,86,23.57391519,US,"June 11, 1993",24,Wake Forest,2,31,650,96,207,46.4,3,8,37.5,58,95,61.1,48,91,139,32,29,8,43,253,1,0 +44,Devereaux Peters,IND,F,188,79,22.35174287,US,"August 10, 1989",28,Notre Dame,6,28,796,154,380,40.5,88,225,39.1,118,130,90.8,8,69,77,76,16,9,56,514,0,0 +45,Diana Taurasi,PHO,G,183,74,22.09680791,US,"November 6, 1982",34,Connecticut,13,20,591,121,255,47.5,22,66,33.3,112,118,94.9,31,98,129,32,20,31,28,376,3,0 +46,Elena Delle Donne,WAS,G/F,196,85,22.12619742,US,"May 9, 1989",28,Delaware,5,30,939,133,272,48.9,0,1,0.0,51,78,65.4,99,116,215,43,32,64,36,317,4,0 +47,Elizabeth Williams,ATL,F/C,191,87,23.84803048,US,"June 23, 1993",24,Duke,3,30,377,48,96,50.0,0,1,0.0,32,55,58.2,35,61,96,5,5,4,21,128,0,0 +48,Emma Cannon,PHO,F,188,86,24.33227705,US,"January 6, 1989",28,Central Florida,R,18,508,105,220,47.7,11,33,33.3,31,34,91.2,33,72,105,52,21,27,30,252,1,0 +49,Emma Meesseman,WAS,C,193,83,22.28247738,BE,"May 13, 1993",24,Belgium,5,23,617,89,233,38.2,25,79,31.6,56,65,86.2,23,58,81,70,34,5,30,259,0,0 +50,Epiphanny Prince,NY,G,175,81,26.44897959,US,"November 1, 1988",28,Rutgers,8,26,282,36,86,41.9,1,3,33.3,15,22,68.2,17,44,61,5,4,8,17,88,0,0 +51,Erica Wheeler,IND,G,170,65,22.49134948,US,"February 5, 1991",26,Rutgers,3,30,767,130,321,40.5,42,129,32.6,34,40,85.0,11,57,68,117,38,1,68,336,0,0 +52,Érika de Souza,SAN,C,196,86,22.38650562,BR,"September 3, 1982",34,Brazil,13,30,579,65,112,58.0,0,0,0.0,29,32,90.6,58,74,132,35,18,7,37,159,0,0 +53,Erlana Larkins,IND,F,185,93,27.17311907,US,"February 4, 1986",31,North Carolina,9,20,386,36,92,39.1,9,35,25.7,21,24,87.5,9,26,35,24,11,8,13,102,0,0 +54,Essence Carson,LA,G/F,183,74,22.09680791,US,"July 28, 1986",31,Rutgers,10,15,61,4,16,25.0,0,0,0.0,5,6,83.3,7,2,9,0,1,3,5,13,0,0 +55,Evelyn Akhator,DAL,F,191,82,22.47745402,NG,"March 2, 1995",22,Kentucky,R,30,926,165,365,45.2,20,60,33.3,92,117,78.6,73,199,272,50,37,13,67,442,13,0 +56,Glory Johnson,DAL,F,191,77,21.10687755,US,"July 27, 1990",27,Tennessee,4,4,42,3,9,33.3,3,6,50.0,0,0,0.0,0,3,3,1,0,0,4,9,0,0 +57,Imani Boyette,ATL,C,201,88,21.78163907,US,"November 10, 1992",24,Texas,1,29,410,56,119,47.1,1,3,33.3,14,20,70.0,43,75,118,14,9,23,22,127,1,0 +58,Isabelle Harrison,SAN,C,191,83,22.75156931,US,"September 27, 1993",23,Kentucky,3,31,832,154,300,51.3,1,2,50.0,55,85,64.7,66,134,200,46,26,24,63,364,5,0 +59,Ivory Latta,WAS,G,168,63,22.32142857,US,"September 25, 1984",32,North Carolina,12,29,499,79,218,36.2,40,114,35.1,47,55,85.5,7,20,27,49,12,1,22,245,0,0 +60,Jantel Lavender,LA,C,193,84,22.55094096,US,"December 11, 1988",28,Ohio State,7,28,481,89,184,48.4,4,13,30.8,18,22,81.8,31,56,87,28,8,5,35,200,0,0 +61,Jasmine Thomas,CON,G,175,66,21.55102041,US,"September 30, 1989",27,Duke,6,27,762,151,341,44.3,50,116,43.1,39,55,70.9,9,55,64,118,45,4,58,391,1,0 +62,Jazmon Gwathmey,IND,G,188,65,18.39067451,PR,"January 24, 1993",24,James Madison,2,24,371,50,140,35.7,12,49,24.5,30,39,76.9,15,34,49,17,13,19,32,142,0,0 +63,Jeanette Pohlen,IND,G,183,78,23.29122996,US,"February 5, 1989",28,Stanford,6,25,278,20,52,38.5,13,29,44.8,17,20,85.0,3,19,22,13,5,0,15,70,0,0 +64,Jennifer Hamson,IND,C,201,95,23.51426945,US,"January 23, 1992",25,Brigham Young,1,10,50,2,12,16.7,0,3,0.0,8,10,80.0,5,6,11,6,2,2,3,12,0,0 +65,Jessica Breland,CHI,F,191,77,21.10687755,US,"February 23, 1988",29,North Carolina,5,10,78,9,16,56.3,0,0,0.0,4,5,80.0,5,13,18,2,1,9,3,22,0,0 +66,Jewell Loyd,SEA,G,178,67,21.14631991,US,"May 10, 1993",24,Notre Dame,3,29,715,116,245,47.3,8,21,38.1,28,37,75.7,50,139,189,46,18,50,57,268,4,0 +67,Jia Perkins,MIN,G,173,75,25.05930703,US,"February 23, 1982",35,Texas Tech,14,30,932,178,420,42.4,47,123,38.2,114,134,85.1,24,72,96,103,41,11,83,517,0,0 +68,Jonquel Jones,CON,F/C,198,86,21.93653709,BS,"May 1, 1994",23,George Washington,1,29,463,47,124,37.9,11,32,34.4,11,15,73.3,11,46,57,39,30,1,24,116,0,0 +69,Jordan Hooper,CHI,F,188,84,23.76641014,US,"February 20, 1992",25,Nebraska,3,29,833,164,299,54.8,22,49,44.9,117,142,82.4,108,226,334,40,29,46,46,467,17,0 +70,Kaela Davis,DAL,G,188,77,21.78587596,US,"March 15, 1995",22,South Carolina,R,23,208,27,75,36.0,20,55,36.4,3,4,75.0,2,20,22,5,7,1,6,77,0,0 +71,Kahleah Copper,CHI,G/F,185,70,20.45288532,US,"August 28, 1994",22,Rutgers,1,29,475,62,163,38.0,12,32,37.5,49,65,75.4,10,33,43,32,13,3,48,185,0,0 +72,Kaleena Mosqueda-Lewis,SEA,F,180,82,25.30864198,US,"March 11, 1993",24,Connecticut,3,29,369,60,140,42.9,5,23,21.7,36,45,80.0,11,43,54,11,9,2,22,161,0,0 +73,Karima Christmas-Kelly,DAL,G/F,183,82,24.48565201,US,"November 9, 1989",27,Duke,6,14,142,23,43,53.5,9,21,42.9,10,10,100.0,4,10,14,6,1,1,13,65,0,0 +74,Kayla Alexander,SAN,C,193,88,23.6247953,CA,"May 1, 1991",26,Arizona State,4,30,889,91,239,38.1,25,83,30.1,111,129,86.0,45,75,120,65,39,5,50,318,0,0 +75,Kayla McBride,SAN,G/F,180,79,24.38271605,US,"June 25, 1992",25,Notre Dame,3,31,433,78,141,55.3,0,0,0.0,15,16,93.8,40,47,87,17,13,15,30,171,0,0 +76,Kayla Pedersen,CON,F,193,86,23.08786813,US,"April 14, 1989",28,Stanford,5,27,882,128,337,38.0,47,147,32.0,108,118,91.5,12,93,105,59,32,5,54,411,0,0 +77,Kayla Thornton,DAL,F,185,86,25.12783053,US,"October 20, 1992",24,Texas–El Paso,2,21,224,11,30,36.7,0,1,0.0,10,14,71.4,19,26,45,13,6,2,9,32,0,0 +78,Keisha Hampton,CHI,F,185,78,22.79035793,US,"February 22, 1990",27,DePaul,1,30,504,64,157,40.8,14,52,26.9,65,81,80.2,36,59,95,24,20,7,21,207,0,0 +79,Kelsey Plum,SAN,G,173,66,22.05219018,US,"August 24, 1994",23,Washington,R,28,610,73,210,34.8,29,78,37.2,50,58,86.2,11,42,53,91,13,4,72,225,0,0 +80,Kia Vaughn,NY,C,193,90,24.16172246,US,"January 24, 1987",30,Rutgers,9,23,455,62,116,53.4,0,0,0.0,10,19,52.6,39,71,110,16,8,9,21,134,1,0 +81,Kiah Stokes,NY,C,191,87,23.84803048,US,"March 30, 1993",24,Connecticut,3,29,576,50,98,51.0,0,1,0.0,41,52,78.8,63,122,185,21,8,32,33,141,3,0 +82,Kristi Toliver,WAS,G,170,59,20.41522491,US,"January 27, 1987",30,Maryland,9,29,845,119,284,41.9,67,194,34.5,44,49,89.8,9,50,59,91,20,8,48,349,0,0 +83,Krystal Thomas,WAS,C,196,88,22.90712203,US,"October 6, 1989",27,Duke,6,29,737,81,149,54.4,0,0,0.0,37,61,60.7,97,172,269,30,15,31,45,199,2,0 +84,Lanay Montgomery,SEA,C,196,96,24.98958767,US,"September 17, 1993",23,West Virginia,R,7,28,3,7,42.9,0,0,0.0,0,0,0.0,0,5,5,0,1,4,2,6,0,0 +85,Layshia Clarendon,ATL,G,175,64,20.89795918,US,"February 5, 1991",26,UC Berkeley,5,30,900,124,320,38.8,8,53,15.1,73,81,90.1,27,88,115,206,29,1,82,329,3,0 +86,Leilani Mitchell,PHO,G,165,58,21.30394858,US,"June 15, 1985",32,Utah,9,30,623,70,182,38.5,31,92,33.7,62,75,82.7,12,57,69,108,26,9,50,233,0,0 +87,Lindsay Allen,NY,G,173,65,21.71806609,US,"March 20, 1995",22,Notre Dame,R,23,314,21,50,42.0,0,11,0.0,6,9,66.7,8,28,36,47,13,1,18,48,0,0 +88,Lindsay Whalen,MIN,G,175,78,25.46938776,US,"September 5, 1982",34,Minnesota,14,22,520,69,153,45.1,12,34,35.3,27,36,75.0,8,46,54,90,11,2,44,177,0,0 +89,Lynetta Kizer,CON,C,193,104,27.92021262,US,"April 4, 1990",27,Maryland,5,20,238,48,100,48.0,0,1,0.0,23,30,76.7,22,35,57,6,11,7,10,119,0,0 +90,Maimouna Diarra,LA,C,198,90,22.95684114,SN,"January 30, 1991",26,Sengal,R,9,16,1,3,33.3,0,0,0.0,1,2,50.0,3,4,7,1,1,0,3,3,0,0 +92,Marissa Coleman,IND,G/F,185,73,21.32943755,US,"April 1, 1987",30,Maryland,9,30,539,50,152,32.9,27,79,34.2,27,33,81.8,7,53,60,25,8,4,34,154,0,0 +93,Matee Ajavon,ATL,G,173,73,24.39105884,US,"July 5, 1986",31,Syracruse,R,27,218,22,69,31.9,0,3,0.0,29,35,82.9,8,26,34,27,10,0,26,73,0,0 +94,Maya Moore,MIN,F,183,80,23.88844098,US,"November 6, 1989",27,Connecticut,7,29,904,170,398,42.7,52,132,39.4,98,114,86.0,50,106,156,99,53,13,56,490,3,0 +95,Monique Currie,PHO,G/F,183,80,23.88844098,US,"February 25, 1983",34,Duke,11,32,717,121,284,42.6,37,93,39.8,85,103,82.5,19,103,122,67,22,11,48,364,0,0 +96,Morgan Tuck,CON,F,188,91,25.74694432,US,"April 30, 1994",23,Connecticut,1,17,294,35,101,34.7,8,28,28.6,13,16,81.3,9,34,43,19,7,0,15,91,1,0 +97,Moriah Jefferson,SAN,G,168,55,19.48696145,US,"August 3, 1994",23,Connecticut,1,21,514,81,155,52.3,9,20,45.0,20,27,74.1,6,31,37,92,33,2,43,191,0,0 +98,Natalie Achonwa,IND,C,193,83,22.28247738,CA,"November 22, 1992",24,Notre Dame,3,30,529,82,151,54.3,0,0,0.0,43,55,78.2,31,70,101,21,11,16,25,207,0,0 +99,Natasha Cloud,WAS,G,183,73,21.79820239,US,"February 22, 1992",25,Saint Joseph's,3,24,448,37,118,31.4,12,51,23.5,20,27,74.1,7,52,59,69,17,3,23,106,0,0 +100,Natasha Howard,MIN,F,188,75,21.22000905,US,"February 9, 1991",26,Florida State,4,29,315,48,104,46.2,3,13,23.1,17,23,73.9,25,38,63,16,11,19,20,116,0,0 +101,Nayo Raincock-Ekunwe,NY,F/C,188,79,22.35174287,CA,"August 29, 1991",25,Simon Fraser,R,27,243,33,63,52.4,0,4,0.0,30,49,61.2,24,22,46,8,2,1,13,96,0,0 +102,Nia Coffey,SAN,F,185,77,22.49817385,US,"May 21, 1995",22,Northwestern,R,25,203,16,59,27.1,0,4,0.0,16,22,72.7,16,30,46,6,5,6,14,48,0,0 +103,Nneka Ogwumike,LA,F,188,79,22.35174287,US,"February 7, 1990",27,Stanford,6,30,948,215,386,55.7,18,49,36.7,129,148,87.2,57,179,236,63,53,14,47,577,9,0 +104,Noelle Quinn,SEA,G,183,81,24.18704649,US,"March 1, 1985",32,UCLA,11,29,459,24,58,41.4,14,35,40.0,17,18,94.4,1,48,49,78,12,5,27,79,0,0 +105,Odyssey Sims,LA,G,173,73,24.39105884,US,"July 13, 1992",25,Baylor,4,27,626,86,198,43.4,11,49,22.4,47,55,85.5,10,34,44,87,38,5,39,230,1,0 +106,Plenette Pierson,MIN,F/C,188,88,24.89814396,US,"August 31, 1981",35,Texas Tech,15,29,402,54,142,38.0,17,51,33.3,15,20,75.0,13,49,62,48,12,4,33,140,0,0 +107,Rachel Banham,CON,G,175,76,24.81632653,US,"July 15, 1993",24,Minnesota,2,26,238,32,87,36.8,16,48,33.3,16,20,80.0,2,27,29,20,4,0,12,96,0,0 +108,Ramu Tokashiki,SEA,F,193,80,21.47708663,JP,"November 6, 1991",25,Japan,1,29,378,42,92,45.7,0,3,0.0,22,27,81.5,19,29,48,16,8,8,25,106,0,0 +109,Rebecca Allen,NY,G/F,188,74,20.9370756,AU,"June 11, 1992",25,Australia,3,28,254,31,86,36.0,14,40,35.0,2,6,33.3,13,51,64,15,9,12,17,78,0,0 +110,Rebekkah Brunson,MIN,F,188,84,23.76641014,US,"November 12, 1981",35,Georgetown,14,26,719,97,218,44.5,22,60,36.7,62,83,74.7,46,135,181,40,31,9,42,278,2,0 +111,Renee Montgomery,MIN,G,170,63,21.79930796,US,"February 12, 1986",31,Connecticut,9,29,614,71,181,39.2,30,89,33.7,44,51,86.3,12,34,46,96,24,1,43,216,0,0 +112,Riquna Williams,LA,G,170,75,25.95155709,US,"May 28, 1990",27,Miami (FL),5,23,408,45,140,32.1,20,74,27.0,38,44,86.4,6,26,32,16,19,3,26,148,0,0 +113,Sami Whitcomb,SEA,G,178,66,20.83070319,US,"July 20, 1988",29,Washington,R,29,354,46,120,38.3,33,94,35.1,14,17,82.4,12,40,52,24,22,0,24,139,0,0 +114,Sancho Lyttle,ATL,F,193,79,21.20862305,ES,"September 20, 1983",33,Houston,13,25,703,71,163,43.6,1,7,14.3,13,19,68.4,42,138,180,41,40,17,34,156,0,0 +115,Sandrine Gruda,LA,F/C,193,84,22.55094096,FR,"June 25, 1987",30,France,5,4,12,1,3,33.3,0,0,0.0,0,0,0.0,0,2,2,0,0,0,2,2,0,0 +116,Saniya Chong,DAL,G,173,64,21.383942,US,"June 27, 1994",23,Connecticut,R,29,348,27,74,36.5,8,35,22.9,25,29,86.2,9,19,28,33,21,3,23,87,0,0 +117,Seimone Augustus,MIN,G/F,183,77,22.99262444,US,"April 30, 1984",33,LSU,12,27,756,125,251,49.8,18,41,43.9,30,35,85.7,12,70,82,108,17,1,39,298,1,0 +118,Sequoia Holmes,SAN,G,185,70,20.45288532,US,"June 13, 1986",31,UNLV,2,24,280,31,89,34.8,13,46,28.3,6,11,54.5,12,12,24,23,13,5,11,81,0,0 +119,Shatori Walker-Kimbrough,WAS,G,180,64,19.75308642,US,"May 18, 1995",22,Maryland,R,22,260,29,78,37.2,9,26,34.6,29,32,90.6,4,13,17,10,11,1,12,96,0,0 +120,Shavonte Zellous,NY,G,178,85,26.82742078,US,"August 28, 1986",30,Pittsburgh,9,29,865,107,249,43.0,14,41,34.1,118,144,81.9,30,92,122,87,23,8,62,346,1,0 +121,Shay Murphy,SAN,G,180,74,22.83950617,US,"April 15, 1985",32,Southern California,9,23,242,23,62,37.1,12,35,34.3,8,12,66.7,12,26,38,17,10,1,12,66,0,0 +122,Shekinna Stricklen,CON,G/F,188,81,22.91760978,US,"July 30, 1990",27,Tennessee,5,29,795,80,202,39.6,59,149,39.6,26,31,83.9,15,71,86,30,36,2,23,245,0,0 +123,Shenise Johnson,IND,G,180,78,24.07407407,US,"September 12, 1990",26,Miami (FL),6,14,348,55,127,43.3,10,30,33.3,38,40,95.0,13,35,48,35,21,4,18,158,0,0 +124,Skylar Diggins-Smith,DAL,G,175,66,21.55102041,US,"February 8, 1990",27,Notre Dame,4,30,1018,167,394,42.4,43,119,36.1,168,186,90.3,21,86,107,173,38,24,83,545,1,0 +125,Stefanie Dolson,CHI,C,196,97,25.24989588,US,"August 1, 1992",25,Connecticut,3,28,823,162,293,55.3,24,60,40.0,50,58,86.2,35,121,156,65,14,37,65,398,3,0 +126,Stephanie Talbot,PHO,G,185,87,25.42001461,AU,"December 20, 1990",26,Australia,R,30,555,47,114,41.2,15,38,39.5,29,44,65.9,28,58,86,50,22,8,28,138,0,0 +127,Sue Bird,SEA,G,175,68,22.20408163,US,"October 16, 1980",36,Connecticut,15,27,806,103,244,42.2,50,134,37.3,17,24,70.8,7,46,53,177,31,3,57,273,1,0 +128,Sugar Rodgers,NY,G,175,75,24.48979592,US,"August 12, 1989",28,Georgetown,6,28,745,108,310,34.8,59,163,36.2,42,52,80.8,21,85,106,68,28,17,43,317,0,0 +129,Sydney Colson,SAN,G,173,64,21.383942,US,"June 8, 1989",28,Texas A&M,3,25,296,25,78,32.1,2,10,20.0,20,30,66.7,3,11,14,51,13,2,25,72,0,0 +130,Sydney Wiese,LA,G,183,68,20.30517483,US,"July 13, 1992",25,Oregon State,R,25,189,19,50,38.0,13,32,40.6,4,8,50.0,3,18,21,6,4,3,2,55,0,0 +131,Sylvia Fowles,MIN,C,198,96,24.48729721,US,"June 10, 1985",32,LSU,10,29,895,222,336,66.1,0,0,0.0,128,162,79.0,113,184,297,39,39,61,71,572,16,0 +132,Tamera Young,ATL,G/F,188,77,21.78587596,US,"October 30, 1986",30,Tennessee,9,31,820,105,297,35.4,23,70,32.9,44,65,67.7,23,87,110,66,36,14,61,277,0,0 +133,Tayler Hill,WAS,G,175,66,21.55102041,US,"October 23, 1990",26,Ohio State,5,18,462,69,191,36.1,27,89,30.3,75,80,93.8,5,29,34,47,16,1,26,240,0,0 +134,Temi Fagbenle,MIN,C,193,89,23.89325888,UK,"August 9, 1992",25,Southern California,R,17,74,6,14,42.9,0,0,0.0,5,6,83.3,3,13,16,1,3,3,8,17,0,0 +135,Theresa Plaisance,DAL,F,196,91,23.68804665,US,"May 18, 1992",25,LSU,4,30,604,80,213,37.6,35,101,34.7,22,24,91.7,38,89,127,24,23,22,24,217,1,0 +136,Tianna Hawkins,WAS,F,191,87,23.84803048,US,"February 3, 1991",26,Maryland,4,29,483,79,165,47.9,11,41,26.8,41,43,95.3,42,82,124,9,15,7,23,210,0,0 +137,Tierra Ruffin-Pratt,WAS,G,178,83,26.19618735,US,"November 4, 1991",25,North Carolina,5,29,703,77,217,35.5,0,4,0.0,71,96,74.0,45,120,165,68,30,16,47,225,2,0 +138,Tiffany Hayes,ATL,G,178,70,22.09317005,US,"September 20, 1989",27,Connecticut,6,29,861,144,331,43.5,43,112,38.4,136,161,84.5,28,89,117,69,37,8,50,467,0,0 +139,Tiffany Jackson,LA,F,191,84,23.0256846,US,"April 26, 1985",32,Texas,9,22,127,12,25,48.0,0,1,0.0,4,6,66.7,5,18,23,3,1,3,8,28,0,0 +140,Tiffany Mitchell,IND,G,175,69,22.53061224,US,"September 23, 1984",32,South Carolina,2,27,671,83,238,34.9,17,69,24.6,94,102,92.2,16,70,86,39,31,5,40,277,0,0 +141,Tina Charles,NY,F/C,193,84,22.55094096,US,"May 12, 1988",29,Connecticut,8,29,952,227,509,44.6,18,56,32.1,110,135,81.5,56,212,268,75,21,22,71,582,11,0 +142,Yvonne Turner,PHO,G,175,59,19.26530612,US,"October 13, 1987",29,Nebraska,2,30,356,59,140,42.1,11,47,23.4,22,28,78.6,11,13,24,30,18,1,32,151,0,0 diff --git a/your-code/1.-Data-Cleaning.ipynb b/your-code/1.-Data-Cleaning.ipynb index 60a0517..abd6f76 100644 --- a/your-code/1.-Data-Cleaning.ipynb +++ b/your-code/1.-Data-Cleaning.ipynb @@ -28,12 +28,11 @@ }, { "cell_type": "code", - "execution_count": 2, + "execution_count": 5, "metadata": {}, "outputs": [], "source": [ - "import pandas as pd\n", - "pd.set_option('max_columns', 100)" + "import pandas as pd\n" ] }, { @@ -47,11 +46,221 @@ }, { "cell_type": "code", - "execution_count": 3, + "execution_count": 9, "metadata": {}, "outputs": [], "source": [ - "#your code here" + "wnba_df= pd.read_csv(\"../data/wnba.csv\")\n" + ] + }, + { + "cell_type": "code", + "execution_count": 10, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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NameTeamPosHeightWeightBMIBirth_PlaceBirthdateAgeCollege...OREBDREBREBASTSTLBLKTOPTSDD2TD3
0Aerial PowersDALF18371.021.200991USJanuary 17, 199423Michigan State...622281236129300
1Alana BeardLAG/F18573.021.329438USMay 14, 198235Duke...19821017263134021700
2Alex BentleyCONG17069.023.875433USOctober 27, 199026Penn State...43640782232421800
3Alex MontgomerySANG/F18584.024.543462USDecember 11, 198828Georgia Tech...351341696520103818820
4Alexis JonesMING17578.025.469388USAugust 5, 199423Baylor...39121270145000
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" + ], + "text/plain": [ + " Name Team Pos Height Weight BMI Birth_Place Birthdate Age \\\n", + "91 Makayla Epps CHI G 178 NaN NaN US June 6, 1995 22 \n", + "\n", + " College ... OREB DREB REB AST STL BLK TO PTS DD2 TD3 \n", + "91 Kentucky ... 2 0 2 4 1 0 4 6 0 0 \n", + "\n", + "[1 rows x 32 columns]" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], "source": [ - "#your code here" + "#your code here\n", + "display(wnba_df[wnba_df[\"Weight\"].isnull()])\n", + "display(wnba_df[wnba_df[\"BMI\"].isnull()])" ] }, { @@ -96,11 +526,24 @@ }, { "cell_type": "code", - "execution_count": 9, + "execution_count": 18, "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "this is the len of our df : 143\n", + "this is the impact of subtracting one row in our df: 0.006993006993006993\n" + ] + } + ], "source": [ - "#your code here" + "#your code here\n", + "# LENTH OF OUR DATAFRAME \n", + "len_dataframe= len(wnba_df)\n", + "print(\"this is the len of our df :\",len_dataframe)\n", + "print(\"this is the impact of subtracting one row in our df:\", (1/len_dataframe))" ] }, { @@ -114,11 +557,12 @@ }, { "cell_type": "code", - "execution_count": 11, + "execution_count": 19, "metadata": {}, "outputs": [], "source": [ - "#your code here" + "#your code here\n", + "wnba_df.dropna(inplace=True)" ] }, { @@ -134,7 +578,8 @@ "metadata": {}, "outputs": [], "source": [ - "#your answer here" + "\n", + "#since it was only one row on the entire data frame it was a good decision " ] }, { @@ -147,11 +592,54 @@ }, { "cell_type": "code", - "execution_count": 14, + "execution_count": 22, "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "text/plain": [ + "Name object\n", + "Team object\n", + "Pos object\n", + "Height int64\n", + "Weight float64\n", + "BMI float64\n", + "Birth_Place object\n", + "Birthdate object\n", + "Age int64\n", + "College object\n", + "Experience object\n", + "Games Played int64\n", + "MIN int64\n", + "FGM int64\n", + "FGA int64\n", + "FG% float64\n", + "3PM int64\n", + "3PA int64\n", + "3P% float64\n", + "FTM int64\n", + "FTA int64\n", + "FT% float64\n", + "OREB int64\n", + "DREB int64\n", + "REB int64\n", + "AST int64\n", + "STL int64\n", + "BLK int64\n", + "TO int64\n", + "PTS int64\n", + "DD2 int64\n", + "TD3 int64\n", + "dtype: object" + ] + }, + "execution_count": 22, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ - "#your code here" + "wnba_df.dtypes" ] }, { @@ -170,11 +658,64 @@ }, { "cell_type": "code", - "execution_count": 16, + "execution_count": 28, "metadata": {}, "outputs": [], "source": [ - "#your code here" + "#your code here\n", + "wnba_df[\"Weight\"]=wnba_df[\"Weight\"].astype(int)" + ] + }, + { + "cell_type": "code", + "execution_count": 29, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "Name object\n", + "Team object\n", + "Pos object\n", + "Height int64\n", + "Weight int32\n", + "BMI float64\n", + "Birth_Place object\n", + "Birthdate object\n", + "Age int64\n", + "College object\n", + "Experience object\n", + "Games Played int64\n", + "MIN int64\n", + "FGM int64\n", + "FGA int64\n", + "FG% float64\n", + "3PM int64\n", + "3PA int64\n", + "3P% float64\n", + "FTM int64\n", + "FTA int64\n", + "FT% float64\n", + "OREB int64\n", + "DREB int64\n", + "REB int64\n", + "AST int64\n", + "STL int64\n", + "BLK int64\n", + "TO int64\n", + "PTS int64\n", + "DD2 int64\n", + "TD3 int64\n", + "dtype: object" + ] + }, + "execution_count": 29, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "wnba_df.dtypes" ] }, { @@ -186,11 +727,303 @@ }, { "cell_type": "code", - "execution_count": 18, + "execution_count": 30, "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "text/html": [ + "
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Unnamed: 0NameTeamPosHeightWeightBMIBirth_PlaceBirthdateAge...OREBDREBREBASTSTLBLKTOPTSDD2TD3
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22Alex BentleyCONG1706923.875433USOctober 27, 199026...43640782232421800
33Alex MontgomerySANG/F1858424.543462USDecember 11, 198828...351341696520103818820
44Alexis JonesMING1757825.469388USAugust 5, 199423...39121270145000
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8 rows × 26 columns

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" + ], + "text/plain": [ + " Unnamed: 0 Height Weight BMI Age \\\n", + "count 142.000000 142.000000 142.000000 142.000000 142.000000 \n", + "mean 70.859155 184.612676 78.978873 23.091214 27.112676 \n", + "std 41.536891 8.698128 10.996110 2.073691 3.667180 \n", + "min 0.000000 165.000000 55.000000 18.390675 21.000000 \n", + "25% 35.250000 175.750000 71.500000 21.785876 24.000000 \n", + "50% 70.500000 185.000000 79.000000 22.873314 27.000000 \n", + "75% 106.750000 191.000000 86.000000 24.180715 30.000000 \n", + "max 142.000000 206.000000 113.000000 31.555880 36.000000 \n", + "\n", + " Games Played MIN FGM FGA FG% ... \\\n", + "count 142.000000 142.000000 142.000000 142.000000 142.000000 ... \n", + "mean 24.429577 500.105634 74.401408 168.704225 43.102817 ... \n", + "std 7.075477 289.373393 55.980754 117.165809 9.855199 ... \n", + "min 2.000000 12.000000 1.000000 3.000000 16.700000 ... \n", + "25% 22.000000 242.250000 27.000000 69.000000 37.125000 ... \n", + "50% 27.500000 506.000000 69.000000 152.500000 42.050000 ... \n", + "75% 29.000000 752.500000 105.000000 244.750000 48.625000 ... \n", + "max 32.000000 1018.000000 227.000000 509.000000 100.000000 ... \n", + "\n", + " OREB DREB REB AST STL BLK \\\n", + "count 142.000000 142.000000 142.000000 142.000000 142.000000 142.000000 \n", + "mean 22.063380 61.591549 83.654930 44.514085 17.725352 9.781690 \n", + "std 21.519648 49.669854 68.200585 41.490790 13.413312 12.537669 \n", + "min 0.000000 2.000000 2.000000 0.000000 0.000000 0.000000 \n", + "25% 7.000000 26.000000 34.250000 11.250000 7.000000 2.000000 \n", + "50% 13.000000 50.000000 62.500000 34.000000 15.000000 5.000000 \n", + "75% 31.000000 84.000000 116.500000 66.750000 27.500000 12.000000 \n", + "max 113.000000 226.000000 334.000000 206.000000 63.000000 64.000000 \n", + "\n", + " TO PTS DD2 TD3 \n", + "count 142.000000 142.000000 142.000000 142.000000 \n", + "mean 32.288732 203.169014 1.140845 0.007042 \n", + "std 21.447141 153.032559 2.909002 0.083918 \n", + "min 2.000000 2.000000 0.000000 0.000000 \n", + "25% 14.000000 77.250000 0.000000 0.000000 \n", + "50% 28.000000 181.000000 0.000000 0.000000 \n", + "75% 48.000000 277.750000 1.000000 0.000000 \n", + "max 87.000000 584.000000 17.000000 1.000000 \n", + "\n", + "[8 rows x 26 columns]" + ] + }, + "execution_count": 3, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ - "#your code here" + "#your code here\n", + "wnba_df.describe()" ] }, { @@ -74,7 +567,8 @@ "metadata": {}, "outputs": [], "source": [ - "#your code here" + "#your code here\n", + "#from the gather data I cannot assess if there are any ouliers weight and age variables" ] }, { @@ -89,11 +583,34 @@ }, { "cell_type": "code", - "execution_count": 8, + "execution_count": 19, "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], "source": [ - "#your code here" + "#your code here\n", + "fig,((ax1, ax2), (ax3, ax4))= plt.subplots(2,2, figsize=(12,12))\n", + "ax1.set_title(\"Height\")\n", + "ax2.set_title(\"weight\")\n", + "ax3.set_title(\"Age\")\n", + "ax4.set_title(\"BMI\")\n", + "ax1.hist(wnba_df[\"Height\"], color=\"g\")\n", + "ax2.hist(wnba_df[\"Weight\"],color=\"r\")\n", + "ax3.hist(wnba_df[\"Age\"],color=\"y\")\n", + "ax4.hist(wnba_df[\"BMI\"],color=\"b\")\n", + "plt.show()" ] }, { @@ -109,7 +626,10 @@ "metadata": {}, "outputs": [], "source": [ - "#your conclusions here" + "#your conclusions here\n", + "#weight and height are very similar regarding is distribution\n", + "#BMI appears to have a normal disto , not having such outlyers \n", + "#regarding the age , the majority of its values are 24 yo" ] }, { @@ -134,11 +654,37 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 20, "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], "source": [ - "#your code here" + "#your code here\n", + "fig,((ax1, ax2), (ax3, ax4), (ax5, ax6))= plt.subplots(3,2, figsize=(12,12))\n", + "ax1.set_title(\"REB\")\n", + "ax2.set_title(\"AST\")\n", + "ax3.set_title(\"STL\")\n", + "ax4.set_title(\"PTS\")\n", + "ax5.set_title(\"BLK\")\n", + "ax1.hist(wnba_df[\"REB\"], color=\"g\")\n", + "ax2.hist(wnba_df[\"AST\"],color=\"r\")\n", + "ax3.hist(wnba_df[\"STL\"],color=\"y\")\n", + "ax4.hist(wnba_df[\"PTS\"],color=\"b\")\n", + "ax5.hist(wnba_df[\"BLK\"],color=\"black\")\n", + "ax6.set_visible(False) # for esthetic purposes I hid the extra subplot\n", + "plt.show()" ] }, { @@ -154,7 +700,8 @@ "metadata": {}, "outputs": [], "source": [ - "#your conclusions here" + "#your conclusions here\n", + "#The data is skewd and the most players have big rotativity and the scores are outlyers " ] }, { @@ -173,11 +720,37 @@ }, { "cell_type": "code", - "execution_count": 10, + "execution_count": 21, "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "image/png": 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" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], "source": [ - "#your code here" + "#your code here\n", + "fig,((ax1, ax2), (ax3, ax4), (ax5, ax6))= plt.subplots(3,2, figsize=(12,12))\n", + "ax1.set_title(\"REB\")\n", + "ax2.set_title(\"AST\")\n", + "ax3.set_title(\"STL\")\n", + "ax4.set_title(\"PTS\")\n", + "ax5.set_title(\"BLK\")\n", + "ax1.hist(wnba_df[\"REB\"]/wnba_df[\"MIN\"], color=\"g\")\n", + "ax2.hist(wnba_df[\"AST\"]/wnba_df[\"MIN\"],color=\"r\")\n", + "ax3.hist(wnba_df[\"STL\"]/wnba_df[\"MIN\"],color=\"y\")\n", + "ax4.hist(wnba_df[\"PTS\"]/wnba_df[\"MIN\"],color=\"b\")\n", + "ax5.hist(wnba_df[\"BLK\"]/wnba_df[\"MIN\"],color=\"black\")\n", + "ax6.set_visible(False) # for esthetic purposes I hid the extra subplot\n", + "plt.show()" ] }, { @@ -193,7 +766,9 @@ "metadata": {}, "outputs": [], "source": [ - "#your conclusions here" + "#your conclusions here\n", + "#due to the ace players the distros are skewd , \n", + "#however some such us blk and pts are closer to normal distros" ] }, { @@ -222,13 +797,14 @@ "metadata": {}, "outputs": [], "source": [ - "#your comments here" + "#your comments here\n", + "#yes it is all in the data set " ] } ], "metadata": { "kernelspec": { - "display_name": "Python 3", + "display_name": "Python 3.9.12 ('base')", "language": "python", "name": "python3" }, @@ -242,7 +818,12 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.6.8" + "version": "3.9.12" + }, + "vscode": { + "interpreter": { + "hash": "ad2bdc8ecc057115af97d19610ffacc2b4e99fae6737bb82f5d7fb13d2f2c186" + } } }, "nbformat": 4, diff --git a/your-code/3.-Inferential-Analysis.ipynb b/your-code/3.-Inferential-Analysis.ipynb index edc1da0..b37908d 100644 --- a/your-code/3.-Inferential-Analysis.ipynb +++ b/your-code/3.-Inferential-Analysis.ipynb @@ -21,7 +21,7 @@ }, { "cell_type": "code", - "execution_count": 3, + "execution_count": 2, "metadata": {}, "outputs": [], "source": [ @@ -29,10 +29,9 @@ "import math\n", "import pandas as pd\n", "import numpy as np\n", - "from scipy import stats\n", + "from scipy import stats as st\n", "import matplotlib.pyplot as plt\n", - "from scipy.stats import ttest_1samp\n", - "pd.set_option('max_columns', 50)" + "from scipy.stats import ttest_1samp\n" ] }, { @@ -46,11 +45,304 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 3, "metadata": {}, - "outputs": [], - "source": [ - "#your code here" + "outputs": [ + { + "data": { + "text/html": [ + "
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8 rows × 25 columns

\n", + "
" + ], + "text/plain": [ + " Height Weight BMI Age Games Played \\\n", + "count 142.000000 142.000000 142.000000 142.000000 142.000000 \n", + "mean 184.612676 78.978873 23.091214 27.112676 24.429577 \n", + "std 8.698128 10.996110 2.073691 3.667180 7.075477 \n", + "min 165.000000 55.000000 18.390675 21.000000 2.000000 \n", + "25% 175.750000 71.500000 21.785876 24.000000 22.000000 \n", + "50% 185.000000 79.000000 22.873314 27.000000 27.500000 \n", + "75% 191.000000 86.000000 24.180715 30.000000 29.000000 \n", + "max 206.000000 113.000000 31.555880 36.000000 32.000000 \n", + "\n", + " MIN FGM FGA FG% 3PM ... \\\n", + "count 142.000000 142.000000 142.000000 142.000000 142.000000 ... \n", + "mean 500.105634 74.401408 168.704225 43.102817 14.830986 ... \n", + "std 289.373393 55.980754 117.165809 9.855199 17.372829 ... \n", + "min 12.000000 1.000000 3.000000 16.700000 0.000000 ... \n", + "25% 242.250000 27.000000 69.000000 37.125000 0.000000 ... \n", + "50% 506.000000 69.000000 152.500000 42.050000 10.500000 ... \n", + "75% 752.500000 105.000000 244.750000 48.625000 22.000000 ... \n", + "max 1018.000000 227.000000 509.000000 100.000000 88.000000 ... \n", + "\n", + " OREB DREB REB AST STL BLK \\\n", + "count 142.000000 142.000000 142.000000 142.000000 142.000000 142.000000 \n", + "mean 22.063380 61.591549 83.654930 44.514085 17.725352 9.781690 \n", + "std 21.519648 49.669854 68.200585 41.490790 13.413312 12.537669 \n", + "min 0.000000 2.000000 2.000000 0.000000 0.000000 0.000000 \n", + "25% 7.000000 26.000000 34.250000 11.250000 7.000000 2.000000 \n", + "50% 13.000000 50.000000 62.500000 34.000000 15.000000 5.000000 \n", + "75% 31.000000 84.000000 116.500000 66.750000 27.500000 12.000000 \n", + "max 113.000000 226.000000 334.000000 206.000000 63.000000 64.000000 \n", + "\n", + " TO PTS DD2 TD3 \n", + "count 142.000000 142.000000 142.000000 142.000000 \n", + "mean 32.288732 203.169014 1.140845 0.007042 \n", + "std 21.447141 153.032559 2.909002 0.083918 \n", + "min 2.000000 2.000000 0.000000 0.000000 \n", + "25% 14.000000 77.250000 0.000000 0.000000 \n", + "50% 28.000000 181.000000 0.000000 0.000000 \n", + "75% 48.000000 277.750000 1.000000 0.000000 \n", + "max 87.000000 584.000000 17.000000 1.000000 \n", + "\n", + "[8 rows x 25 columns]" + ] + }, + "execution_count": 3, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "#your code here\n", + "wnba_df = pd.read_csv('../data/wnba_clean.csv', index_col= 0)\n", + "wnba_df.describe()" ] }, { @@ -70,11 +362,26 @@ }, { "cell_type": "code", - "execution_count": 11, + "execution_count": 8, "metadata": {}, - "outputs": [], - "source": [ - "# your answer here" + "outputs": [ + { + "data": { + "text/plain": [ + "(77.14815649242229, 80.80958998645096)" + ] + }, + "execution_count": 8, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "# your answer here\n", + "#https://www.statology.org/confidence-intervals-python/\n", + "\n", + "confidence_interval = st.t.interval(alpha=0.95,df = len(wnba_df)-1, loc= np.mean(wnba_df['Weight']), scale= wnba_df['Weight'].std()/np.sqrt(len(wnba_df)-1))\n", + "confidence_interval" ] }, { @@ -134,11 +441,35 @@ }, { "cell_type": "code", - "execution_count": 8, - "metadata": {}, - "outputs": [], - "source": [ - "# your code here" + "execution_count": 14, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "# your code here\n", + "weight_dist = st.norm(loc= wnba_df['Weight'].mean(), scale= wnba_df['Weight'].std()/np.sqrt(len(wnba_df)))\n", + "\n", + "x= np.linspace(weight_dist.ppf(0.001), weight_dist.ppf(0.999),1000) # is going to plot a line on the ppf distro of the 1st quantile and the last quantile \n", + "y = weight_dist.pdf(x) # is the probability distro of thw weight\n", + "\n", + "plt.vlines(confidence_interval[0], 0, weight_dist.pdf(confidence_interval[0]), color= 'r') # plots the 1st line \n", + "plt.vlines(confidence_interval[1], 0, weight_dist.pdf(confidence_interval[1]), color= 'r') # plots the 2st line \n", + "plt.xticks(confidence_interval) # going to adjust the scaling on the graph \n", + "plt.plot(x, y, color= 'blue', lw= 2);# is going to plot the emtire graph\n", + "plt.title(\"Weight distro\")\n", + "plt.show()" ] }, { @@ -154,11 +485,24 @@ }, { "cell_type": "code", - "execution_count": 10, + "execution_count": 22, "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "0.09859154929577464\n", + "(0.049558988317297346, 0.14762411027425193)\n" + ] + } + ], "source": [ - "# your answer here" + "# your answer here\n", + "s = len(wnba_df[wnba_df['FT%']< 60]) # calculates the success prob of missing less than 60%\n", + "n = len(wnba_df) # size of the dataset\n", + "probability = s/n\n", + "alpha = .95# ( sig level to consider)\n" ] }, { @@ -170,11 +514,26 @@ }, { "cell_type": "code", - "execution_count": 12, - "metadata": {}, - "outputs": [], - "source": [ - "# your code here" + "execution_count": 23, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "0.09859154929577464\n", + "(0.049558988317297346, 0.14762411027425193)\n" + ] + } + ], + "source": [ + "# your code here\n", + "stdev = np.sqrt((probability*(1-probability)/n))\n", + "\n", + "confidence_interval = st.norm.interval(alpha, loc=probability, scale= stdev)\n", + "\n", + "print(probability)\n", + "print(confidence_interval)\n" ] }, { @@ -186,11 +545,12 @@ }, { "cell_type": "code", - "execution_count": 15, + "execution_count": 24, "metadata": {}, "outputs": [], "source": [ - "#your-answer-here" + "#your-answer-here\n", + "#The probaility of missing more than 40% is very low and is very lower when compared to 50%" ] }, { @@ -202,11 +562,35 @@ }, { "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "#your code here" + "execution_count": 31, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "#your code here\n", + "missthowrs = st.norm(loc=probability, scale = stdev)\n", + "\n", + "x = np.linspace(missthowrs.ppf(0.001), missthowrs.ppf(0.999), 100)\n", + "y= missthowrs.pdf(x)\n", + "\n", + "plt.vlines(confidence_interval[0], 0, missthowrs.pdf(confidence_interval[0]), colors=\"r\")\n", + "plt.vlines(confidence_interval[1], 0, missthowrs.pdf(confidence_interval[1]), colors= \"r\")\n", + "plt.xticks(confidence_interval)\n", + "plt.title(\"Missed Free throws\")\n", + "plt.plot(x,y,color=\"b\", lw=2)\n", + "plt.show()" ] }, { @@ -231,7 +615,9 @@ "metadata": {}, "outputs": [], "source": [ - "#your-answer-here" + "#your-answer-here\n", + "# we need to look at the data and define the hipothesis and perfomr the test \n", + "\n" ] }, { @@ -243,20 +629,42 @@ }, { "cell_type": "code", - "execution_count": 15, - "metadata": {}, - "outputs": [], - "source": [ - "#your code here" + "execution_count": 32, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "-2.1499947192482898 0.033261541354107166\n" + ] + } + ], + "source": [ + "#your code here\n", + "\n", + "tstats , pvalue = st.ttest_1samp(wnba_df.AST, 52)\n", + "print(tstats, pvalue)\n", + "\n", + "# with the pvaule we can reject the null hypothesis " ] }, { "cell_type": "code", - "execution_count": 18, + "execution_count": 35, "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "The mean of Assists is : 44.514084507042256 we can reject the null Hipo as the pvalue is 0.033261541354107166\n" + ] + } + ], "source": [ - "#your-answer-here" + "print(\"The mean of Assists is :\", wnba_df.AST.mean() , \" we can reject the null Hipo as the pvalue is \", pvalue)\n", + "#your-answer-here\n" ] }, { @@ -343,7 +751,7 @@ ], "metadata": { "kernelspec": { - "display_name": "Python 3", + "display_name": "Python 3.9.12 ('base')", "language": "python", "name": "python3" }, @@ -357,7 +765,12 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.6.8" + "version": "3.9.12" + }, + "vscode": { + "interpreter": { + "hash": "ad2bdc8ecc057115af97d19610ffacc2b4e99fae6737bb82f5d7fb13d2f2c186" + } } }, "nbformat": 4,