<\/p>\n
Pandalarda birden fazla s\u00fctuna dayal\u0131 bir s\u0131kl\u0131k tablosu olu\u015fturmak i\u00e7in a\u015fa\u011f\u0131daki temel s\u00f6zdizimini kullanabilirsiniz:<\/span><\/p>\n A\u015fa\u011f\u0131daki \u00f6rnek, bu s\u00f6zdiziminin pratikte nas\u0131l kullan\u0131laca\u011f\u0131n\u0131 g\u00f6sterir.<\/span><\/p>\n Tak\u0131m ad\u0131, konumu ve \u00e7e\u015fitli basketbol oyuncular\u0131 taraf\u0131ndan at\u0131lan puanlar hakk\u0131nda bilgi i\u00e7eren a\u015fa\u011f\u0131daki panda DataFrame’e sahip oldu\u011fumuzu varsayal\u0131m:<\/span><\/p>\n Tak\u0131m<\/strong> ve konum<\/strong> s\u00fctunlar\u0131ndaki her de\u011fer kombinasyonunun olu\u015fumunu g\u00f6steren bir s\u0131kl\u0131k tablosu olu\u015fturmak i\u00e7in value_counts()<\/strong> i\u015flevini kullanabiliriz:<\/span><\/p>\n Sonu\u00e7lardan \u015funlar\u0131 g\u00f6rebiliriz:<\/span><\/p>\n Bunun yerine bir DataFrame d\u00f6nd\u00fcrmek i\u00e7in reset_index()<\/strong> i\u015flevini kullanabilece\u011fimizi unutmay\u0131n:<\/span><\/p>\n Say\u0131mlar\u0131 i\u00e7eren s\u00fctunu yeniden adland\u0131rmak i\u00e7in rename()<\/strong> i\u015flevini kullanabiliriz:<\/span><\/p>\n Sonu\u00e7ta Tak\u0131m<\/strong> ve Pozisyon<\/strong> s\u00fctunlar\u0131ndaki her benzersiz de\u011fer kombinasyonunun s\u0131kl\u0131\u011f\u0131n\u0131 i\u00e7eren bir DataFrame elde edilir.<\/span><\/p>\n A\u015fa\u011f\u0131daki e\u011fitimlerde pandalarda di\u011fer ortak g\u00f6revlerin nas\u0131l ger\u00e7ekle\u015ftirilece\u011fi a\u00e7\u0131klanmaktad\u0131r:<\/span><\/p>\n Pandalar: GroupBy ve de\u011fer say\u0131lar\u0131 nas\u0131l kullan\u0131l\u0131r?<\/a> Pandalarda birden fazla s\u00fctuna dayal\u0131 bir s\u0131kl\u0131k tablosu olu\u015fturmak i\u00e7in a\u015fa\u011f\u0131daki temel s\u00f6zdizimini kullanabilirsiniz: df. value_counts ([‘ column1 ‘,’ column2 ‘]) A\u015fa\u011f\u0131daki \u00f6rnek, bu s\u00f6zdiziminin pratikte nas\u0131l kullan\u0131laca\u011f\u0131n\u0131 g\u00f6sterir. \u00d6rnek: Pandas’ta birden \u00e7ok s\u00fctuna dayal\u0131 bir s\u0131kl\u0131k tablosu olu\u015fturma Tak\u0131m ad\u0131, konumu ve \u00e7e\u015fitli basketbol oyuncular\u0131 taraf\u0131ndan at\u0131lan puanlar hakk\u0131nda bilgi i\u00e7eren a\u015fa\u011f\u0131daki panda DataFrame’e […]<\/p>\n","protected":false},"author":1,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[11],"tags":[],"class_list":["post-4042","post","type-post","status-publish","format-standard","hentry","category-rehber"],"yoast_head":"\n df. value_counts<\/span> ([' column1<\/span> ',' column2<\/span> '])\n<\/strong><\/pre>\n \u00d6rnek: Pandas’ta birden \u00e7ok s\u00fctuna dayal\u0131 bir s\u0131kl\u0131k tablosu olu\u015fturma<\/strong><\/span><\/h2>\n
import<\/span> pandas as<\/span> pd\n\n#createDataFrame<\/span>\ndf = pd. DataFrame<\/span> ({' team<\/span> ': ['A', 'A', 'A', 'A', 'B', 'B', 'B', 'B'],\n ' position<\/span> ': ['G', 'G', 'G', 'F', 'G', 'G', 'F', 'F'],\n ' points<\/span> ': [24, 33, 20, 15, 16, 16, 29, 25]})\n\n#view DataFrame\n<\/span>print<\/span> (df)\n\n team position points\n0 AG 24\n1 AG 33\n2 AG 20\n3 AF15\n4 BG 16\n5 BG 16\n6 BF 29\n7 BF 25<\/strong><\/pre>\n #count frequency of values in team and position columns\ndf. value_counts<\/span> ([' team<\/span> ',' position<\/span> '])\n\nteam position\nGA 3\nBF 2\n G2\nAF1\ndtype: int64<\/span><\/span>\n<\/strong><\/pre>\n\n
#count frequency of values in team and position columns and return DataFrame\ndf. value_counts<\/span> ([' team<\/span> ',' position<\/span> ']). reset_index<\/span> ()\n\n team position 0\n0 A G 3\n1 B F 2\n2 B G 2\n3 A F 1<\/span><\/span><\/strong><\/pre>\n #get frequency of values in team and position column and rename count column\n<\/span>df. value_counts<\/span> ([' team<\/span> ',' position<\/span> ']). reset_index<\/span> (). rename<\/span> (columns={0:' count<\/span> '})\n\n team position count\n0 A G 3\n1 B F 2\n2 B G 2\n3 A F 1\n<\/strong><\/pre>\n Ek kaynaklar<\/strong><\/span><\/h2>\n
Pandalar: GroupBy’yi \u00e7\u00f6p kutusu say\u0131m\u0131 ile kullanma<\/a>
Pandalar: Ko\u015fullu bir s\u00fctundaki de\u011ferler nas\u0131l say\u0131l\u0131r?<\/a><\/p>\n","protected":false},"excerpt":{"rendered":"