<\/p>\n
Pandas DataFrame’deki bir dizenin birden fazla alt dize i\u00e7erip i\u00e7ermedi\u011fini kontrol etmek i\u00e7in a\u015fa\u011f\u0131daki y\u00f6ntemleri kullanabilirsiniz:<\/span><\/p>\n Y\u00f6ntem 1: Dizenin birka\u00e7 alt dizeden birini i\u00e7erip i\u00e7ermedi\u011fini kontrol edin<\/strong><\/span><\/p>\n Y\u00f6ntem 2: Dizenin birden fazla alt dize i\u00e7erip i\u00e7ermedi\u011fini kontrol edin<\/strong><\/span><\/p>\n A\u015fa\u011f\u0131daki \u00f6rnekler, her y\u00f6ntemin pratikte a\u015fa\u011f\u0131daki pandalar DataFrame ile nas\u0131l kullan\u0131laca\u011f\u0131n\u0131 g\u00f6sterir:<\/span><\/span><\/p>\n Ekip<\/strong> s\u00fctunundaki her dizenin “\u0130yi” veya<\/strong> “Is” alt dizesini i\u00e7erip i\u00e7ermedi\u011fini kontrol etmek i\u00e7in a\u015fa\u011f\u0131daki s\u00f6zdizimini kullanabiliriz:<\/span><\/p>\n Yeni good_or_east<\/strong> s\u00fctunu a\u015fa\u011f\u0131daki de\u011ferleri d\u00f6nd\u00fcr\u00fcr:<\/span><\/p>\n Not<\/strong> : |<\/strong> Operat\u00f6r pandalarda “veya” anlam\u0131na gelir.<\/span><\/p>\n Tak\u0131m<\/strong> s\u00fctunundaki her dizenin “\u0130yi” ve<\/b> “Is” alt dizesini i\u00e7erip i\u00e7ermedi\u011fini kontrol etmek i\u00e7in a\u015fa\u011f\u0131daki s\u00f6zdizimini kullanabiliriz:<\/span><\/p>\n Yeni good_and_east<\/strong> s\u00fctunu a\u015fa\u011f\u0131daki de\u011ferleri d\u00f6nd\u00fcr\u00fcr:<\/span><\/p>\n “\u0130yi” alt dizesini ve<\/strong> “Do\u011fu” alt dizesini i\u00e7eren yaln\u0131zca bir tak\u0131m ad\u0131 oldu\u011fundan yaln\u0131zca bir Ger\u00e7ek<\/strong> de\u011ferinin d\u00f6nd\u00fcr\u00fcld\u00fc\u011f\u00fcn\u00fc unutmay\u0131n.<\/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: bir DataFrame’den di\u011ferine bir s\u00fctun ekleyin<\/a> Pandas DataFrame’deki bir dizenin birden fazla alt dize i\u00e7erip i\u00e7ermedi\u011fini kontrol etmek i\u00e7in a\u015fa\u011f\u0131daki y\u00f6ntemleri kullanabilirsiniz: Y\u00f6ntem 1: Dizenin birka\u00e7 alt dizeden birini i\u00e7erip i\u00e7ermedi\u011fini kontrol edin df[‘ string_column ‘]. str . contains (‘ | ‘ .join ([‘ string1 ‘,’ string2 ‘])) Y\u00f6ntem 2: Dizenin birden fazla alt dize i\u00e7erip i\u00e7ermedi\u011fini kontrol edin df[‘ string_column […]<\/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-3726","post","type-post","status-publish","format-standard","hentry","category-rehber"],"yoast_head":"\n df[' string_column<\/span> ']. str<\/span> . contains<\/span> (' |<\/span> ' .join<\/span> ([' string1<\/span> ',' string2<\/span> ']))\n<\/strong><\/pre>\n df[' string_column<\/span> ']. str<\/span> . contains<\/span> ( r'^(?=.*string1)(?=.*string2)'<\/span> )<\/strong><\/pre>\n import<\/span> pandas as<\/span> pd\n\n#createDataFrame\n<\/span>df = pd. DataFrame<\/span> ({' team<\/span> ': ['Good East Team', 'Good West Team', 'Great East Team',\n 'Great West Team', 'Bad East Team', 'Bad West Team'],\n ' points<\/span> ': [93, 99, 105, 110, 85, 88]})\n\n#view DataFrame\n<\/span>print<\/span> (df)\n\n team points\n0 Good East Team 93\n1 Good West Team 99\n2 Great East Team 105\n3 Great West Team 110\n4 Bad East Team 85\n5 Bad West Team 88\n<\/strong><\/span><\/pre>\n \u00d6rnek<\/strong> 1: Dizenin birka\u00e7 alt dizeden birini i\u00e7erip i\u00e7ermedi\u011fini kontrol edin<\/span><\/strong><\/h2>\n
#create new column that checks if each team name contains 'Good' or 'East'\n<\/span>df[' good_or_east<\/span> '] = df[' team<\/span> ']. str<\/span> . contains<\/span> (' |<\/span> ' .join<\/span> ([' Good<\/span> ',' East<\/span> ']))\n\n#view updated DataFrame\n<\/span>print<\/span> (df)\n\n team points good_or_east\n0 Good East Team 93 True\n1 Good West Team 99 True\n2 Great East Team 105 True\n3 Great West Team 110 False\n4 Bad East Team 85 True\n5 Bad West Team 88 False<\/span><\/span><\/strong><\/pre>\n\n
\u00d6rnek 2<\/strong> : Dizenin birden fazla alt dize i\u00e7erip i\u00e7ermedi\u011fini kontrol edin<\/span><\/strong><\/h2>\n
#create new column that checks if each team name contains 'Good' and 'East'<\/span>\ndf[' good_and_east<\/span> '] = df[' team<\/span> ']. str<\/span> . contains<\/span> ( r'^(?=.*Good)(?=.*East)'<\/span> )\n\n#view updated DataFrame\n<\/span>print<\/span> (df)\n\n team points good_and_east\n0 Good East Team 93 True\n1 Good West Team 99 False\n2 Great East Team 105 False\n3 Great West Team 110 False\n4 Bad East Team 85 False\n5 Bad West Team 88 False<\/span><\/span><\/strong><\/pre>\n\n
Ek kaynaklar<\/strong><\/span><\/h2>\n
Pandalar: Ba\u015fka bir DataFrame’de olmayan sat\u0131rlar\u0131 al\u0131n<\/a>
Pandalar: birden fazla s\u00fctunun e\u015fit olup olmad\u0131\u011f\u0131 nas\u0131l kontrol edilir<\/a><\/p>\n","protected":false},"excerpt":{"rendered":"