<\/p>\n
Bir pandan\u0131n DataFrame alt k\u00fcmesini her olu\u015fturdu\u011funuzda ve alt k\u00fcmesi de\u011fi\u015ftirdi\u011finizde, orijinal DataFrame de de\u011fi\u015ftirilecektir.<\/span><\/p>\n Bu nedenle, alt k\u00fcmede yapt\u0131\u011f\u0131n\u0131z de\u011fi\u015fikliklerin orijinal DataFrame’de de yap\u0131lmamas\u0131 i\u00e7in alt k\u00fcmeleme s\u0131ras\u0131nda .copy()<\/strong> i\u015flevini kullanmak her zaman iyi bir fikirdir.<\/span><\/p>\n A\u015fa\u011f\u0131daki \u00f6rnekler alt k\u00fcmeleme s\u0131ras\u0131nda bir pandan\u0131n DataFrame kopyas\u0131n\u0131n nas\u0131l (ve neden) olu\u015fturulaca\u011f\u0131n\u0131 g\u00f6sterir.<\/span><\/p>\n A\u015fa\u011f\u0131daki pandalara sahip oldu\u011fumuzu varsayal\u0131m DataFrame:<\/span><\/p>\n \u015eimdi orijinal DataFrame’in yaln\u0131zca ilk d\u00f6rt sat\u0131r\u0131n\u0131 i\u00e7eren bir alt k\u00fcme olu\u015fturdu\u011fumuzu varsayal\u0131m:<\/span><\/span><\/p>\n Alt k\u00fcmedeki de\u011ferlerden herhangi birini de\u011fi\u015ftirirsek orijinal DataFrame’in de\u011feri de de\u011fi\u015fecektir:<\/span><\/p>\n Tak\u0131m s\u00fctununun ilk de\u011ferinin hem DataFrame alt k\u00fcmesinde hem de<\/strong> orijinal DataFrame’de “A” yerine “X” olarak de\u011fi\u015ftirildi\u011fini unutmay\u0131n.<\/span><\/span><\/p>\n Bunun nedeni orijinal DataFrame’in bir kopyas\u0131n\u0131 olu\u015fturmam\u0131\u015f olmam\u0131zd\u0131r.<\/span><\/p>\n Tekrar a\u015fa\u011f\u0131daki panda DataFrame’e sahip oldu\u011fumuzu varsayal\u0131m:<\/span><\/p>\n Tekrar, orijinal DataFrame’in yaln\u0131zca ilk d\u00f6rt sat\u0131r\u0131n\u0131 i\u00e7eren bir alt k\u00fcme olu\u015fturdu\u011fumuzu varsayal\u0131m, ancak bu sefer orijinal DataFrame’in bir kopyas\u0131n\u0131 olu\u015fturmak i\u00e7in .copy()<\/strong> y\u00f6ntemini kullan\u0131yoruz:<\/span><\/p>\n \u015eimdi DataFrame alt k\u00fcmesinin tak\u0131m s\u00fctununun ilk de\u011ferini de\u011fi\u015ftirdi\u011fimizi varsayal\u0131m:<\/span><\/p>\n Ekip s\u00fctununun ilk de\u011ferinin yaln\u0131zca DataFrame alt k\u00fcmesinde “A” yerine “X” olarak de\u011fi\u015ftirildi\u011fini unutmay\u0131n.<\/span><\/p>\n Alt k\u00fcmeyi olu\u015ftururken bir kopyas\u0131n\u0131 olu\u015fturmak i\u00e7in .copy()<\/strong> i\u015flevini kulland\u0131\u011f\u0131m\u0131zdan, orijinal DataFrame bozulmadan kal\u0131r.<\/span><\/p>\n A\u015fa\u011f\u0131daki e\u011fitimlerde pandalarda di\u011fer yayg\u0131n i\u015flemlerin nas\u0131l ger\u00e7ekle\u015ftirilece\u011fi a\u00e7\u0131klanmaktad\u0131r:<\/span><\/p>\n Pandas DataFrame’deki sat\u0131rlar duruma g\u00f6re nas\u0131l silinir<\/a> Bir pandan\u0131n DataFrame alt k\u00fcmesini her olu\u015fturdu\u011funuzda ve alt k\u00fcmesi de\u011fi\u015ftirdi\u011finizde, orijinal DataFrame de de\u011fi\u015ftirilecektir. Bu nedenle, alt k\u00fcmede yapt\u0131\u011f\u0131n\u0131z de\u011fi\u015fikliklerin orijinal DataFrame’de de yap\u0131lmamas\u0131 i\u00e7in alt k\u00fcmeleme s\u0131ras\u0131nda .copy() i\u015flevini kullanmak her zaman iyi bir fikirdir. A\u015fa\u011f\u0131daki \u00f6rnekler alt k\u00fcmeleme s\u0131ras\u0131nda bir pandan\u0131n DataFrame kopyas\u0131n\u0131n nas\u0131l (ve neden) olu\u015fturulaca\u011f\u0131n\u0131 g\u00f6sterir. \u00d6rnek 1: Bir DataFrame’i […]<\/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-3270","post","type-post","status-publish","format-standard","hentry","category-rehber"],"yoast_head":"\n \u00d6rnek 1: Bir DataFrame’i kopya olmadan alt k\u00fcmeleme<\/span><\/strong><\/h2>\n
import<\/span> pandas as<\/span> pd\n\n#createDataFrame\n<\/span>df = pd. DataFrame<\/span> ({' team<\/span> ': ['A', 'B', 'C', 'D', 'E', 'F', 'G', 'H'],\n ' points<\/span> ': [18, 22, 19, 14, 14, 11, 20, 28],\n ' assists<\/span> ': [5, 7, 7, 9, 12, 9, 9, 4]})\n\n#view DataFrame\n<\/span>print<\/span> (df)\n\n team points assists\n0 to 18 5\n1 B 22 7\n2 C 19 7\n3 D 14 9\n4 E 14 12\n5 F 11 9\n6 G 20 9\n7:28 a.m. 4<\/strong><\/pre>\n #define subsetted DataFrame\n<\/span>df_subset = df[0:4]\n\n#view subsetted DataFrame\n<\/span>print<\/span> (df_subset)\n\n team points assists rebounds\n0 A 18 5 11\n1 B 22 7 8\n2 C 19 7 10\n3 D 14 9 6<\/strong><\/pre>\n #change first value in team column\n<\/span>df_subset. team<\/span> [0] = ' X<\/span> '\n\n#view subsetted DataFrame\n<\/span>print<\/span> (df_subset)\n\n team points assists\n0X18 5\n1 B 22 7\n2 C 19 7\n3 D 14 9\n\n#view original DataFrame\n<\/span>print<\/span> (df)\n\n team points assists\n0X18 5\n1 B 22 7\n2 C 19 7\n3 D 14 9\n4 E 14 12\n5 F 11 9\n6 G 20 9\n7:28 a.m. 4\n<\/strong><\/span><\/pre>\n \u00d6rnek 2: DataFrame’i Kopyalamayla Alt K\u00fcmeleme<\/span><\/strong><\/h2>\n
import<\/span> pandas as<\/span> pd\n\n#createDataFrame\n<\/span>df = pd. DataFrame<\/span> ({' team<\/span> ': ['A', 'B', 'C', 'D', 'E', 'F', 'G', 'H'],\n ' points<\/span> ': [18, 22, 19, 14, 14, 11, 20, 28],\n ' assists<\/span> ': [5, 7, 7, 9, 12, 9, 9, 4]})\n\n#view DataFrame\n<\/span>print<\/span> (df)\n\n team points assists\n0 to 18 5\n1 B 22 7\n2 C 19 7\n3 D 14 9\n4 E 14 12\n5 F 11 9\n6 G 20 9\n7:28 a.m. 4<\/strong><\/pre>\n #define subsetted DataFrame\n<\/span>df_subset = df[0:4]. copy<\/span> ()<\/strong><\/pre>\n #change first value in team column\n<\/span>df_subset. team<\/span> [0] = ' X<\/span> '\n\n#view subsetted DataFrame\n<\/span>print<\/span> (df_subset)\n\n team points assists\n0X18 5\n1 B 22 7\n2 C 19 7\n3 D 14 9\n\n#view original DataFrame\n<\/span>print<\/span> (df)\n\n team points assists\n0 to 18 5\n1 B 22 7\n2 C 19 7\n3 D 14 9\n4 E 14 12\n5 F 11 9\n6 G 20 9\n7:28 a.m. 4\n<\/strong><\/span><\/pre>\n Ek kaynaklar<\/strong><\/span><\/h2>\n
Pandas DataFrame’i birden \u00e7ok ko\u015fulda filtreleme<\/a>
Pandas DataFrame’de \u201cDE\u011e\u0130L\u201d filtresi nas\u0131l kullan\u0131l\u0131r?<\/a><\/p>\n","protected":false},"excerpt":{"rendered":"