<\/p>\n
Mo\u017cesz u\u017cy\u0107 nast\u0119puj\u0105cej sk\u0142adni, aby doda\u0107 now\u0105 kolumn\u0119 do ramki danych pandas, kt\u00f3ra wskazuje, czy ka\u017cdy wiersz istnieje w innej ramce danych:<\/span><\/p>\n Poni\u017cszy przyk\u0142ad pokazuje, jak zastosowa\u0107 t\u0119 sk\u0142adni\u0119 w praktyce.<\/span><\/p>\n Za\u0142\u00f3\u017cmy, \u017ce mamy nast\u0119puj\u0105ce dwie ramki danych pandy:<\/span><\/p>\n Mo\u017cemy u\u017cy\u0107 nast\u0119puj\u0105cej sk\u0142adni, aby doda\u0107 kolumn\u0119 o nazwie istnieje<\/strong> do pierwszej ramki danych, kt\u00f3ra wskazuje, czy ka\u017cda warto\u015b\u0107 w kolumnie zespo\u0142u<\/strong> i punkt\u00f3w<\/strong> w ka\u017cdym wierszu istnieje w drugiej ramce danych:<\/span><\/p>\n Nowa kolumna istnieje<\/strong> wskazuje, czy ka\u017cda warto\u015b\u0107 w kolumnie zespo\u0142u<\/strong> i punkt\u00f3w<\/strong> w ka\u017cdym wierszu istnieje w drugiej ramce danych.<\/span><\/span><\/p>\n Z wyniku mo\u017cemy zobaczy\u0107:<\/span><\/p>\n Pami\u0119taj te\u017c, \u017ce mo\u017cesz okre\u015bli\u0107 warto\u015bci inne ni\u017c True i False w istniej\u0105cej<\/strong> kolumnie, zmieniaj\u0105c warto\u015bci w funkcji NumPy Where()<\/strong> .<\/span><\/p>\n Na przyk\u0142ad mo\u017cesz zamiast tego u\u017cy\u0107 s\u0142\u00f3w \u201eistnieje\u201d i \u201enie istnieje\u201d w nast\u0119puj\u0105cy spos\u00f3b:<\/span><\/p>\n Nale\u017cy pami\u0119ta\u0107, \u017ce warto\u015bci w istniej\u0105cej<\/strong> kolumnie zosta\u0142y zmienione.<\/span><\/p>\n Poni\u017csze samouczki wyja\u015bniaj\u0105, jak wykonywa\u0107 inne typowe zadania w pandach:<\/span><\/p>\n Pandy: dodaj kolumn\u0119 z jednej ramki DataFrame do drugiej<\/a> Mo\u017cesz u\u017cy\u0107 nast\u0119puj\u0105cej sk\u0142adni, aby doda\u0107 now\u0105 kolumn\u0119 do ramki danych pandas, kt\u00f3ra wskazuje, czy ka\u017cdy wiersz istnieje w innej ramce danych: #merge two DataFrames on specific columns all_df = pd. merge (df1, df2, on=[’ column1 ’, ’ column2 ’], how=’ left ’, indicator=’ exists ’) #drop unwanted columns all_df = all_df. drop (’ column3 […]<\/p>\n","protected":false},"author":1,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[3],"tags":[],"class_list":["post-3723","post","type-post","status-publish","format-standard","hentry","category-przewodnik"],"yoast_head":"\n #merge two DataFrames on specific columns<\/span>\nall_df = pd. merge<\/span> (df1, df2, on=[' column1<\/span> ', ' column2<\/span> '], how=' left<\/span> ', indicator=' exists<\/span> ')\n\n#drop unwanted columns<\/span>\nall_df = all_df. drop<\/span> (' column3<\/span> ', axis= 1<\/span> )\n\n#add column that shows if each row in one DataFrame exists in another<\/span>\nall_df[' exists<\/span> '] = np. where<\/span> (all_df. exists<\/span> == ' both<\/span> ', True<\/span> , False<\/span> )\n<\/strong><\/pre>\n Przyk\u0142ad: sprawd\u017a, czy wiersz w jednej ramce danych Pandas istnieje w innej<\/strong><\/h2>\n
import<\/span> pandas as<\/span> pd\n\n#create first DataFrame\ndf1 = pd. DataFrame<\/span> ({' team<\/span> ': ['A', 'B', 'C', 'D', 'E'], \n ' points<\/span> ': [12, 15, 22, 29, 24]}) \n\nprint<\/span> (df1)\n\n team points\n0 to 12\n1 B 15\n2 C 22\n3 D 29\n4 E 24\n\n#create second DataFrame\n<\/span>df2 = pd. DataFrame<\/span> ({' team<\/span> ': ['A', 'D', 'F', 'G', 'H'],\n ' points<\/span> ': [12, 29, 15, 19, 10],\n ' assists<\/span> ': [4, 7, 7, 10, 12]})\n\nprint<\/span> (df2)\n\n team points assists\n0 to 12 4\n1 D 29 7\n2 F 15 7\n3 G 19 10\n4:10:12\n<\/span><\/span><\/strong><\/pre>\n import<\/span> numpy as<\/span> np\n\n#merge two dataFrames and add indicator column\n<\/span>all_df = pd. merge<\/span> (df1, df2, on=[' team<\/span> ', ' points<\/span> '], how=' left<\/span> ', indicator=' exists<\/span> ')\n\n#drop assists columns\n<\/span>all_df = all_df. drop<\/span> (' assists<\/span> ', axis= 1<\/span> )\n\n#add column to show if each row in first DataFrame exists in second\n<\/span>all_df[' exists<\/span> '] = np. where<\/span> (all_df. exists<\/span> == ' both<\/span> ', True<\/span> , False<\/span> )\n\n#view updated DataFrame\n<\/span>print<\/span> (all_df)\n\n team points exists\n0 A 12 True\n1 B 15 False\n2 C 22 False\n3 D 29 True\n4 E 24 False\n<\/strong><\/span><\/pre>\n\n
#add column to show if each row in first DataFrame exists in second\n<\/span>all_df[' exists<\/span> '] = np. where<\/span> (all_df. exists<\/span> == ' both<\/span> ', ' exists<\/span> ', ' not exists<\/span> ')<\/span>\n\n#view updated DataFrame\n<\/span>print<\/span> (all_df)\n\n team points exists\n0 to 12 exists\n1 B 15 not exists\n2 C 22 not exists\n3 D 29 exists\n4 E 24 not exists\n<\/strong><\/span><\/pre>\n Dodatkowe zasoby<\/strong><\/span><\/h2>\n
Pandy: Uzyskaj wiersze, kt\u00f3rych nie ma w innej ramce DataFrame<\/a>
Pandy: jak sprawdzi\u0107, czy wiele kolumn jest r\u00f3wnych<\/a><\/p>\n","protected":false},"excerpt":{"rendered":"