{"id":2384,"date":"2023-07-22T12:34:04","date_gmt":"2023-07-22T12:34:04","guid":{"rendered":"https:\/\/statorials.org\/tr\/pandalar-kaydirma-sutunu\/"},"modified":"2023-07-22T12:34:04","modified_gmt":"2023-07-22T12:34:04","slug":"pandalar-kaydirma-sutunu","status":"publish","type":"post","link":"https:\/\/statorials.org\/tr\/pandalar-kaydirma-sutunu\/","title":{"rendered":"Pandalarda s\u00fctun nas\u0131l dengelenir: \u00f6rneklerle"},"content":{"rendered":"

<\/p>\n

\n

Pandas DataFrame’deki de\u011ferleri bir s\u00fctunda yukar\u0131 veya a\u015fa\u011f\u0131 kayd\u0131rmak i\u00e7in Shift()<\/strong> i\u015flevini kullanabilirsiniz:<\/span><\/p>\n

 #shift values down by 1<\/span>\ndf[' column1<\/span> '] = df[' column1<\/span> ']. shift<\/span> (1)\n\n#shift values up by 1<\/span>\ndf[' column1<\/span> '] = df[' column1<\/span> ']. shift<\/span> (-1)\n<\/strong><\/pre>\n
 A\u015fa\u011f\u0131daki \u00f6rnekler, bu i\u015flevin pratikte a\u015fa\u011f\u0131daki pandalar DataFrame ile nas\u0131l kullan\u0131laca\u011f\u0131n\u0131 g\u00f6sterir:<\/span><\/p>\n
 import<\/span> pandas as<\/span> pd\n\n#createDataFrame\n<\/span>df = pd. DataFrame<\/span> ({' product<\/span> ': ['A', 'B', 'C', 'D', 'E', 'F'],\n                   ' sales<\/span> ': [4, 7, 8, 12, 15, 19]})\n\n#view DataFrame\n<\/span>df\n\n        product sales\n0 to 4\n1 B 7\n2 C 8\n3 D 12\n4 E 15\n5 F 19<\/strong><\/pre>\n
 \u00d6rnek 1: Bir s\u00fctunu yukar\u0131 veya a\u015fa\u011f\u0131 ta\u015f\u0131ma<\/strong><\/span><\/h3>\n
 A\u015fa\u011f\u0131daki kod, “\u00fcr\u00fcn” s\u00fctunundaki t\u00fcm de\u011ferlerin 1 birim a\u015fa\u011f\u0131 nas\u0131l kayd\u0131r\u0131laca\u011f\u0131n\u0131 g\u00f6sterir:<\/span><\/p>\n
 #shift all 'product' values down by 1\n<\/span>df[' product<\/span> '] = df[' product<\/span> ']. shift<\/span> (1)\n\n#view updated DataFrame\n<\/span>df\n\n\tproduct sales\n0 NaN 4\n1 to 7\n2 B 8\n3 C 12\n4 D 15\n5 E 19\n<\/span><\/span><\/strong><\/pre>\n
 “\u00dcr\u00fcn” s\u00fctunundaki her de\u011ferin 1 birim kayd\u0131r\u0131ld\u0131\u011f\u0131n\u0131 ve s\u00fctundaki ilk de\u011ferin NaN olarak de\u011fi\u015ftirildi\u011fini unutmay\u0131n.<\/span><\/p>\n
 Ayr\u0131ca \u00dcr\u00fcn s\u00fctunundaki son de\u011ferin (“F”) DataFrame’den tamamen kald\u0131r\u0131ld\u0131\u011f\u0131n\u0131 unutmay\u0131n.<\/span><\/p>\n
 \u201cF\u201d de\u011ferini DataFrame\u2019de tutmak i\u00e7in \u00f6ncelikle DataFrame\u2019in alt\u0131na bo\u015f bir sat\u0131r eklememiz ve ard\u0131ndan offset i\u015flemini yapmam\u0131z gerekiyor:<\/span><\/p>\n
 import<\/span> numpy as<\/span> np\n\n#add empty row to bottom of DataFrame\n<\/span>df. loc<\/span> [len(df. index<\/span> )] = [np. nah<\/span> , np. no<\/span> ]\n\n#shift all 'product' values down by 1\n<\/span>df[' product<\/span> '] = df[' product<\/span> ']. shift<\/span> (1)\n\n#view updated DataFrame\n<\/span>df\n\n\tproduct sales\n0 NaN 4.0\n1 to 7.0\n2B 8.0\n3C 12.0\n4 D 15.0\n5 E 19.0\n6 F NaN\n<\/span><\/span><\/strong><\/pre>\n
 \u201c\u00dcr\u00fcn\u201d s\u00fctununda \u201cF\u201d de\u011ferinin son de\u011fer olarak tutuldu\u011funu unutmay\u0131n.<\/span><\/p>\n
 \u00d6rnek 2: Birden \u00e7ok s\u00fctunu yukar\u0131 veya a\u015fa\u011f\u0131 ta\u015f\u0131ma<\/strong><\/span><\/h3>\n
 A\u015fa\u011f\u0131daki kod, “\u00fcr\u00fcn” ve “sat\u0131\u015f” s\u00fctunlar\u0131ndaki t\u00fcm de\u011ferlerin nas\u0131l 2’ye kadar yukar\u0131 kayd\u0131r\u0131laca\u011f\u0131n\u0131 g\u00f6sterir:<\/span><\/p>\n
 #shift all 'product' and 'sales' values up by 2\n<\/span>df[[' product<\/span> ', ' sales<\/span> ']] = df[[' product<\/span> ', ' sales<\/span> ']]. shift<\/span> (-2)\n\n#view updated DataFrame\n<\/span>df\n\n        product sales\n0 C 8.0\n1 D 12.0\n2 E 15.0\n3 F 19.0\n4 NaN NaN\n5 NaN NaN\n<\/span><\/span><\/strong><\/pre>\n
 “\u00dcr\u00fcn” ve “sat\u0131\u015f” s\u00fctunlar\u0131ndaki her de\u011ferin 2 birim yukar\u0131 kayd\u0131r\u0131ld\u0131\u011f\u0131n\u0131 ve her s\u00fctundaki en alttaki iki de\u011ferin NaN olarak de\u011fi\u015ftirildi\u011fini unutmay\u0131n.<\/span><\/p>\n
 Not<\/strong> : Shift()<\/strong> i\u015flevine ili\u015fkin t\u00fcm belgeleri burada<\/a> bulabilirsiniz.<\/span><\/p>\n
 Ek kaynaklar<\/strong><\/span><\/h3>\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’e sat\u0131rlar nas\u0131l eklenir<\/a>
 Pandas DataFrame’e s\u00fctun nas\u0131l eklenir
 Pandas DataFrame’e ba\u015fl\u0131k sat\u0131r\u0131 nas\u0131l eklenir<\/a><\/p>\n","protected":false},"excerpt":{"rendered":"
Pandas DataFrame’deki de\u011ferleri bir s\u00fctunda yukar\u0131 veya a\u015fa\u011f\u0131 kayd\u0131rmak i\u00e7in Shift() i\u015flevini kullanabilirsiniz: #shift values down by 1 df[‘ column1 ‘] = df[‘ column1 ‘]. shift (1) #shift values up by 1 df[‘ column1 ‘] = df[‘ column1 ‘]. shift (-1) A\u015fa\u011f\u0131daki \u00f6rnekler, bu i\u015flevin pratikte a\u015fa\u011f\u0131daki pandalar DataFrame ile nas\u0131l kullan\u0131laca\u011f\u0131n\u0131 g\u00f6sterir: import pandas […]<\/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-2384","post","type-post","status-publish","format-standard","hentry","category-rehber"],"yoast_head":"\nPandalarda S\u00fctun Nas\u0131l Dengelenir (\u00d6rneklerle) \u2013 Statorials<\/title>\n<meta name=\"description\" content=\"Bu e\u011fitimde, pandas DataFrame'deki bir s\u00fctunun 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