13.4 O pacote dplyr
library(dplyr)Selecionando colunas
Utilize a base imdb nos exercícios a seguir.
1. Teste aplicar a função glimpse() do pacote {dplyr} à base imdb. O que ela faz?
glimpse(imdb)## Rows: 11,340
## Columns: 20
## $ id_filme <chr> "tt0092699", "tt0037931", "tt0183505", "tt0033945…
## $ titulo <chr> "Broadcast News", "Murder, He Says", "Me, Myself …
## $ ano <dbl> 1987, 1945, 2000, 1941, 2005, 2015, 1987, 2008, 1…
## $ data_lancamento <chr> "1988-04-01", "1945-06-23", "2000-09-08", "1947-0…
## $ generos <chr> "Comedy, Drama, Romance", "Comedy, Crime, Mystery…
## $ duracao <dbl> 133, 91, 116, 71, 99, 87, 114, 104, 95, 111, 95, …
## $ pais <chr> "USA", "USA", "USA", "USA", "USA", "USA", "USA", …
## $ idioma <chr> "English, Spanish, French, German", "English", "E…
## $ orcamento <dbl> 20000000, NA, 51000000, NA, NA, NA, 15000000, 350…
## $ receita <dbl> 67331309, NA, 149270999, NA, 309404, NA, 35509515…
## $ receita_eua <dbl> 51249404, NA, 90570999, NA, 309404, NA, 35509515,…
## $ nota_imdb <dbl> 7.2, 7.1, 6.6, 7.2, 5.9, 6.1, 7.1, 5.5, 7.1, 5.7,…
## $ num_avaliacoes <dbl> 26257, 1639, 219069, 2108, 2953, 2364, 34513, 133…
## $ direcao <chr> "James L. Brooks", "George Marshall", "Bobby Farr…
## $ roteiro <chr> "James L. Brooks", "Lou Breslow, Jack Moffitt", "…
## $ producao <chr> "Amercent Films", "Paramount Pictures", "Twentiet…
## $ elenco <chr> "William Hurt, Albert Brooks, Holly Hunter, Rober…
## $ descricao <chr> "Take two rival television reporters: one handsom…
## $ num_criticas_publico <dbl> 142, 35, 502, 35, 48, 26, 125, 45, 145, 52, 179, …
## $ num_criticas_critica <dbl> 62, 10, 161, 18, 15, 14, 72, 74, 55, 29, 121, 12,…A função glimpse() traz um resumo da base, contendo o número de linhas, colunas, o nome e tipo das colunas e as primeiras observações de cada coluna.
2. Crie uma tabela com apenas as colunas titulo, direcao, e orcamento. Salve em um objeto chamado imdb_simples.
imdb_simples <- select(imdb, titulo, direcao, orcamento)
imdb_simples## # A tibble: 11,340 × 3
## titulo direcao orcamento
## <chr> <chr> <dbl>
## 1 Broadcast News James L. Brooks 20000000
## 2 Murder, He Says George Marshall NA
## 3 Me, Myself & Irene Bobby Farrelly, Peter Farrelly 51000000
## 4 Never Give a Sucker an Even Break Edward F. Cline NA
## 5 Adam & Steve Craig Chester NA
## 6 Henry Gamble's Birthday Party Stephen Cone NA
## 7 No Way Out Roger Donaldson 15000000
## 8 Welcome Home, Roscoe Jenkins Malcolm D. Lee 35000000
## 9 Some Kind of Wonderful Howard Deutch NA
## 10 The Family That Preys Tyler Perry NA
## # … with 11,330 more rows3. Selecione apenas as colunas duracao, direcao, descricao e producao usando a função auxiliar contains().
select(imdb, contains("cao"))## # A tibble: 11,340 × 4
## duracao direcao producao descricao
## <dbl> <chr> <chr> <chr>
## 1 133 James L. Brooks Amercent Films Take two…
## 2 91 George Marshall Paramount Pictures A pollst…
## 3 116 Bobby Farrelly, Peter Farrelly Twentieth Century Fox A nice-g…
## 4 71 Edward F. Cline Universal Pictures A filmma…
## 5 99 Craig Chester Funny Boy Films Follows …
## 6 87 Stephen Cone Chicago Media Project Preacher…
## 7 114 Roger Donaldson Orion Pictures A coveru…
## 8 104 Malcolm D. Lee Universal Pictures Dr. RJ S…
## 9 95 Howard Deutch Hughes Entertainment When Kei…
## 10 111 Tyler Perry Louisiana Producers Film So… Two fami…
## # … with 11,330 more rows4. Usando a função select() (e suas funções auxiliares), escreva códigos que retornem a base IMDB sem as colunas num_avaliacoes, num_criticas_publico e num_criticas_critica. Escreva todas as soluções diferentes que você conseguir pensar.
select(imdb, -starts_with("num"))
select(imdb, -num_avaliacoes, -num_criticas_publico, -num_criticas_critica)
select(imdb, id_filme:nota_imdb, direcao)
select(imdb, -contains("num"))Ordenando a base
1. Ordene os filmes em ordem crescente de ano e decrescente de receita e salve em um objeto chamado filmes_ordenados.
filmes_ordenados <- arrange(imdb, ano, desc(receita))
filmes_ordenados## # A tibble: 11,340 × 20
## id_filme titulo ano data_lancamento generos duracao pais idioma orcamento
## <chr> <chr> <dbl> <chr> <chr> <dbl> <chr> <chr> <dbl>
## 1 tt0004707 Tilli… 1914 1914-12-21 Comedy 82 USA None,… 50000
## 2 tt0004181 Judit… 1914 1914-03-08 Drama 61 USA Engli… 40000
## 3 tt0003643 The A… 1914 1914-08-24 Crime,… 78 USA Engli… NA
## 4 tt0005960 The R… 1915 1915-09-13 Biogra… 72 USA Engli… NA
## 5 tt0005078 The C… 1915 1915-12-13 Drama,… 59 USA Engli… 17311
## 6 tt0004972 The B… 1915 1915-03-21 Drama,… 195 USA None 100000
## 7 tt0006864 Intol… 1916 1918-02-24 Drama,… 163 USA Engli… 385907
## 8 tt0006333 20,00… 1916 1916-12-24 Action… 105 USA Engli… 200000
## 9 tt0008443 The P… 1917 1917-03-05 Comedy… 65 USA Engli… NA
## 10 tt0009611 Shoul… 1918 1918-10-27 Comedy… 45 USA None,… NA
## # … with 11,330 more rows, and 11 more variables: receita <dbl>,
## # receita_eua <dbl>, nota_imdb <dbl>, num_avaliacoes <dbl>, direcao <chr>,
## # roteiro <chr>, producao <chr>, elenco <chr>, descricao <chr>,
## # num_criticas_publico <dbl>, num_criticas_critica <dbl>2. Selecione apenas as colunas titulo e orcamento e então ordene de forma decrescente pelo orcamento.
# Aninhando as funções
arrange(select(imdb, titulo, orcamento), desc(orcamento))
# Criando objeto intermediário
imdb_aux <- select(imdb, titulo, orcamento)
arrange(imdb_aux, desc(orcamento))
# Pipe s2
imdb %>%
select(titulo, orcamento) %>%
arrange(desc(orcamento))Filtrando linhas
Utilize a base imdb nos exercícios a seguir.
1. Crie um objeto chamado filmes_ingles apenas com filmes que sejam apenas no idioma inglês (English).
# Vendo categorias da variável cor
unique(imdb$idioma)## [1] "English, Spanish, French, German"
## [2] "English"
## [3] "English, German"
## [4] "English, Russian"
## [5] "English, French"
## [6] "English, Hebrew, Russian, Yiddish"
## [7] "English, Italian, German"
## [8] "English, Ukrainian"
## [9] "English, Pushto, Dari, French"
## [10] "English, Spanish"
## [11] "English, Russian, Ukrainian"
## [12] "English, Yiddish"
## [13] "English, German, French"
## [14] "English, Japanese"
## [15] "English, Danish, German"
## [16] "English, Italian"
## [17] "English, German, Russian"
## [18] "English, French, German"
## [19] "English, None"
## [20] "English, Hebrew"
## [21] "English, French, Latin"
## [22] "English, Polynesian, French, Dutch"
## [23] "English, Chinese"
## [24] "English, French, Spanish, Ladino, Hebrew, Italian, Portuguese, Latin"
## [25] "English, Welsh, Latin, French"
## [26] "English, Spanish, Cantonese"
## [27] NA
## [28] "English, Japanese, Navajo"
## [29] "English, Japanese, French, Russian"
## [30] "English, Portuguese"
## [31] "English, Portuguese, Spanish"
## [32] "English, Hungarian, Latin"
## [33] "English, German, Spanish"
## [34] "English, Mandarin, Spanish, Russian"
## [35] "English, Spanish, Italian"
## [36] "English, Turkish, French, German"
## [37] "English, Korean"
## [38] "English, German, Italian"
## [39] "English, Swedish, Latin, German"
## [40] "English, Latin"
## [41] "English, Greek, Japanese"
## [42] "English, Spanish, French, Korean"
## [43] "English, Spanish, Hindi"
## [44] "Icelandic, Swedish, English"
## [45] "English, Swahili"
## [46] "English, Italian, Arabic"
## [47] "None, English"
## [48] "English, Italian, German, French"
## [49] "English, Cantonese"
## [50] "English, Russian, French, Hawaiian, Spanish"
## [51] "English, Spanish, Latin"
## [52] "English, Thai"
## [53] "English, Italian, Russian, Spanish, German"
## [54] "English, French, Spanish, Korean"
## [55] "English, Spanish, Russian"
## [56] "English, Spanish, French"
## [57] "English, Spanish, Hungarian"
## [58] "Bosnian, Serbian, Croatian, English"
## [59] "English, Italian, Latin"
## [60] "English, Cantonese, German"
## [61] "English, Cheyenne, French"
## [62] "English, German, Turkish, French"
## [63] "English, French, Chinese, Urdu, Mohawk"
## [64] "English, Mandarin"
## [65] "English, Arabic"
## [66] "English, Mandarin, German"
## [67] "English, German, Ukrainian"
## [68] "English, French, North American Indian"
## [69] "English, Hungarian, German, Spanish"
## [70] "English, Spanish, Arabic"
## [71] "English, French, Portuguese"
## [72] "English, Arabic, Italian"
## [73] "English, Hebrew, Mandarin"
## [74] "English, Mandarin, Punjabi"
## [75] "English, Hawaiian"
## [76] "English, Icelandic, Italian"
## [77] "English, American Sign Language"
## [78] "English, Dutch"
## [79] "Spanish, English"
## [80] "English, Russian, Spanish"
## [81] "English, Hindi, Italian"
## [82] "English, Persian, Greek, Arabic, Latin"
## [83] "English, Swedish"
## [84] "English, Spanish, Russian, Italian, French"
## [85] "English, Japanese, French"
## [86] "English, German, Latin"
## [87] "English, Bulgarian"
## [88] "English, Serbian"
## [89] "English, Italian, Latin, Spanish, German"
## [90] "English, Spanish, Japanese"
## [91] "English, Spanish, French, American Sign Language"
## [92] "English, French, Czech"
## [93] "Mandarin, English, Cantonese, Vietnamese, Polish"
## [94] "English, Brazilian Sign Language"
## [95] "English, Spanish, Hungarian, Czech"
## [96] "English, French, Spanish"
## [97] "English, Klingon"
## [98] "French, English"
## [99] "English, Italian, Yiddish"
## [100] "None"
## [101] "English, Navajo, Spanish"
## [102] "English, German, Yiddish"
## [103] "English, Hebrew, Russian"
## [104] "English, Hungarian"
## [105] "English, Latin, Italian, Spanish"
## [106] "English, Mende, Spanish, Portuguese"
## [107] "English, Italian, Spanish, Korean"
## [108] "English, Athapascan languages"
## [109] "English, Esperanto"
## [110] "English, Latin, Greek, French, German, Arabic, Kurdish"
## [111] "English, Finnish"
## [112] "English, French, German, Spanish, Yiddish"
## [113] "English, German, Arabic, Urdu"
## [114] "English, French, Indonesian"
## [115] "English, Indian Sign Language, North American Indian"
## [116] "English, Tagalog, Cantonese, Mandarin, Spanish"
## [117] "English, Chinese, German"
## [118] "English, French, German, Spanish"
## [119] "English, German, Swedish, Norwegian, Danish, French"
## [120] "English, Arabic, Acholi"
## [121] "English, Japanese, Spanish"
## [122] "English, German, French, Latin"
## [123] "English, Navajo, Japanese"
## [124] "English, Cantonese, Korean"
## [125] "English, Serbo-Croatian"
## [126] "Spanish"
## [127] "English, Arabic, French, Italian"
## [128] "English, Hebrew, Latin, Yiddish"
## [129] "English, Italian, Cantonese"
## [130] "English, Italian, Japanese, Spanish"
## [131] "English, French, German, Latin"
## [132] "English, Russian, French"
## [133] "English, Japanese, Italian, French"
## [134] "English, Russian, Punjabi, Arabic"
## [135] "English, Hawaiian, Russian"
## [136] "English, Aramaic"
## [137] "English, Dari"
## [138] "English, German, Cantonese, Japanese, Hungarian, Arabic"
## [139] "English, Brazilian Sign Language, Spanish"
## [140] "English, Swedish, German"
## [141] "English, Spanish, Italian, Inuktitut, Hindi"
## [142] "English, Spanish, Greek, Ancient (to 1453)"
## [143] "English, Mandarin, Spanish"
## [144] "English, French, Cantonese, Japanese"
## [145] "English, Apache languages, Spanish"
## [146] "Portuguese, English, Spanish, German"
## [147] "English, Indonesian"
## [148] "English, Vietnamese"
## [149] "English, Russian, Arabic, Latin"
## [150] "English, Spanish, Portuguese"
## [151] "English, Urdu"
## [152] "English, Italian, Spanish"
## [153] "English, Spanish, German, Russian"
## [154] "English, French, Arabic"
## [155] "Cantonese, English"
## [156] "English, Spanish, Sioux"
## [157] "English, Serbo-Croatian, Spanish"
## [158] "English, Spanish, Assyrian Neo-Aramaic"
## [159] "English, Akan"
## [160] "English, Ukrainian, Russian"
## [161] "English, German, Cantonese"
## [162] "English, Irish, Hebrew"
## [163] "English, Vietnamese, French"
## [164] "English, Spanish, German"
## [165] "English, Saami"
## [166] "English, Latin, Swedish, Norse, Old, Danish, Arabic"
## [167] "English, French, Hindi, Russian"
## [168] "English, Latin, French"
## [169] "English, Italian, Czech"
## [170] "English, Swahili, Kirundi, French"
## [171] "English, Spanish, Greek"
## [172] "English, Italian, French"
## [173] "English, Klingon, German"
## [174] "English, Arabic, Spanish"
## [175] "English, French, Italian, Russian, Spanish"
## [176] "English, Sioux"
## [177] "English, Russian, Spanish, Italian"
## [178] "English, Russian, Chinese"
## [179] "English, French, Italian, German"
## [180] "English, Hindi"
## [181] "English, French, German, Italian"
## [182] "English, Chinese, Japanese"
## [183] "English, French, Romanian, Latin"
## [184] "English, French, Arabic, German, Dutch"
## [185] "English, Danish"
## [186] "English, Spanish, Arabic, Polish, Turkish, Russian, Italian, Persian"
## [187] "English, French, Spanish, Arabic, Italian"
## [188] "English, Polynesian"
## [189] "English, Hebrew, Arabic"
## [190] "Portuguese, English"
## [191] "English, Irish"
## [192] "English, Sign Languages"
## [193] "Greek, English, Italian"
## [194] "English, Spanish, Russian, Italian"
## [195] "English, Polish"
## [196] "English, Polish, German, Arabic, Egyptian (Ancient)"
## [197] "English, Korean, Spanish, Japanese, Latin"
## [198] "English, American Sign Language, Spanish"
## [199] "English, German, Portuguese, French"
## [200] "English, Finnish, German"
## [201] "Russian, English"
## [202] "English, Spanish, French, Russian"
## [203] "English, Hungarian, Hebrew"
## [204] "English, Pushto"
## [205] "English, French, Russian"
## [206] "English, Klingon, Russian, French"
## [207] "English, Syriac, Assyrian Neo-Aramaic"
## [208] "English, Armenian"
## [209] "English, Ibo"
## [210] "English, Spanish, French, Japanese"
## [211] "English, Czech, Serbian"
## [212] "English, French, Italian"
## [213] "Esperanto"
## [214] "English, German, Italian, French"
## [215] "English, Swahili, Xhosa, Zulu"
## [216] "English, German, Italian, Hindi"
## [217] "English, Korean, Russian, Spanish"
## [218] "English, Spanish, Mandarin"
## [219] "English, Spanish, French, Romanian"
## [220] "English, Russian, Sign Languages"
## [221] "English, Hindi, German, Punjabi, Tibetan, French"
## [222] "English, Filipino"
## [223] "English, Hebrew, Spanish"
## [224] "English, Italian, Spanish, Latin, Sicilian"
## [225] "English, Ukrainian, Spanish"
## [226] "English, Mohawk, French"
## [227] "English, Spanish, Chinese, Russian, Portuguese"
## [228] "English, Latin, Spanish"
## [229] "English, Romanian, Spanish"
## [230] "English, German, Japanese, Serbian"
## [231] "English, Arapaho"
## [232] "English, Japanese, Russian, Spanish"
## [233] "English, French, Ukrainian"
## [234] "English, Ukrainian, French, Italian, Spanish"
## [235] "English, Romany, Romanian, Ukrainian"
## [236] "English, Korean, Icelandic, Russian"
## [237] "English, Portuguese, Tupi, Spanish, German"
## [238] "English, Swedish, French, Italian, Russian"
## [239] "English, French, Wolof, Spanish"
## [240] "English, French, Latin, Spanish"
## [241] "English, Welsh"
## [242] "English, German, Norwegian"
## [243] "English, Greek"
## [244] "English, Portuguese, French"
## [245] "English, Portuguese, French, Japanese"
## [246] "French, Russian, Polish, English"
## [247] "Uzbek, English, Dari, Russian, Spanish"
## [248] "English, Japanese, Cantonese, Mandarin"
## [249] "English, Inuktitut"
## [250] "English, French, Swedish"
## [251] "English, Afrikaans"
## [252] "English, French, Spanish, Hindi"
## [253] "English, Hawaiian, French"
## [254] "English, Italian, Latin, French"
## [255] "English, Swedish, Italian, Portuguese, French"
## [256] "English, Spanish, Korean"
## [257] "Spanish, English, Mandarin, French, Hindi"
## [258] "English, Spanish, Quechua"
## [259] "English, Tamil"
## [260] "English, Portuguese, Swedish"
## [261] "English, Russian, Indonesian"
## [262] "English, Cornish"
## [263] "English, Norwegian"
## [264] "English, Polish, German"
## [265] "English, Russian, Mandarin"
## [266] "English, Finnish, Spanish, French"
## [267] "English, Russian, Portuguese"
## [268] "English, Thai, French"
## [269] "English, French, Russian, German, Spanish, Greek"
## [270] "English, French, German, Russian"
## [271] "English, Irish, Greek"
## [272] "English, Russian, Hindi"
## [273] "English, Russian, Spanish, Korean, Greek"
## [274] "English, Albanian"
## [275] "English, Italian, Spanish, German"
## [276] "English, Navajo"
## [277] "English, Italian, French, Japanese"
## [278] "English, Russian, Japanese, Indonesian, Mandarin, Italian, Arabic, Latin"
## [279] "English, Mandarin, Russian"
## [280] "English, Latin, Hungarian"
## [281] "English, Arabic, French"
## [282] "English, German, Hebrew, Spanish, Arabic, Nepali"
## [283] "English, Mandarin, Hindi"
## [284] "English, Greek, Spanish"
## [285] "English, German, Greek, Arabic"
## [286] "English, Cantonese, Spanish"
## [287] "English, Persian, Assyrian Neo-Aramaic"
## [288] "English, French, Bulgarian"
## [289] "English, Apache languages"
## [290] "English, Spanish, Sanskrit"
## [291] "English, Albanian, Spanish"
## [292] "English, German, French, Russian, Arabic, Italian"
## [293] "English, Italian, Portuguese"
## [294] "English, French, Albanian, Spanish, Hungarian"
## [295] "English, Spanish, French, German, Italian, Hebrew"
## [296] "English, French, Russian, Hindi"
## [297] "English, Tonga"
## [298] "English, Yiddish, Hebrew"
## [299] "English, Bulgarian, Spanish, Russian, Mandarin, German, French"
## [300] "English, Persian"
## [301] "English, French, Spanish, Italian, Sign Languages, Russian"
## [302] "English, Italian, Russian"
## [303] "English, Cantonese, Dutch, French, Italian"
## [304] "English, Hebrew, German"
## [305] "English, Serbo-Croatian, Spanish, Czech"
## [306] "Italian, English, German"
## [307] "English, French, Czech, Japanese"
## [308] "English, Syriac, German, Greek, Hebrew, Latin, Aramaic"
## [309] "English, Norwegian, Latin, French"
## [310] "English, French, Turkish, German, Greek, Italian"
## [311] "English, German, Korean"
## [312] "English, Crow, French"
## [313] "English, Algonquin"
## [314] "English, French, Spanish, Italian, German"
## [315] "English, Cantonese, Italian"
## [316] "English, French, Spanish, Italian"
## [317] "English, French, German, Czech"
## [318] "English, Hebrew, French"
## [319] "Spanish, Hungarian"
## [320] "English, Romanian"
## [321] "English, Norwegian, French"
## [322] "English, French, German, Serbian"
## [323] "English, French, Persian"
## [324] "English, Czech"
## [325] "English, French, Cantonese"
## [326] "English, Turkish"
## [327] "English, Persian, Ukrainian"
## [328] "English, Mandarin, Shanghainese"
## [329] "English, French, Italian, Hindi"
## [330] "English, Mandarin, Spanish, French"
## [331] "English, Russian, Hungarian"
## [332] "English, Icelandic"
## [333] "English, Japanese, Korean"
## [334] "Italian, Chinese, English"
## [335] "English, French, Japanese"
## [336] "English, Spanish, Chinese"
## [337] "English, French, German, Chinese, Italian, Arabic"
## [338] "English, French, German, Hebrew, Spanish, Polish, Norwegian"
## [339] "English, Persian, French, Spanish"
## [340] "English, French, Vietnamese"
## [341] "English, German, Italian, Japanese"
## [342] "English, Chinese, Spanish, French, Ukrainian"
## [343] "French, Spanish, English"
## [344] "English, French, Arabic, German"
## [345] "English, French, Tibetan, Mandarin, Russian, Hindi, Portuguese, Latin, Italian, Spanish"
## [346] "Latin, French, English"
## [347] "English, Basque, French, Spanish"
## [348] "English, French, German, Italian, Spanish"
## [349] "English, Mandarin, Korean"
## [350] "English, Croatian, Chinese"
## [351] "English, French, German, Polish"
## [352] "English, French, Arabic, Romanian"
## [353] "English, Indonesian, French"
## [354] "English, Dutch, French, Italian, Mandarin"
## [355] "English, German, Hebrew, French"
## [356] "English, Russian, Esperanto"
## [357] "English, German, French, Swedish"
## [358] "English, French, Portuguese, Spanish"
## [359] "English, Berber languages, French"
## [360] "English, Japanese, German"
## [361] "English, Italian, Japanese, Yiddish"
## [362] "English, Spanish, Urdu, Russian"
## [363] "Persian, English"
## [364] "English, Nahuatl"
## [365] "English, Mandarin, Cantonese"
## [366] "English, French, Sioux"
## [367] "English, Japanese, Italian"
## [368] "English, Romanian, Russian"
## [369] "English, Mandarin, Italian"
## [370] "English, Italian, Japanese"
## [371] "English, Cantonese, Latin"
## [372] "English, German, Italian, Arabic"
## [373] "English, French, German, Spanish, Hawaiian, Japanese, Italian, Hebrew"
## [374] "English, Catalan, Spanish"
## [375] "English, French, Latin, Scottish Gaelic, Italian"
## [376] "English, Japanese, Russian"
## [377] "Aramaic, Latin, Hebrew"
## [378] "English, French, German, Dutch, Italian"
## [379] "Maori, English"
## [380] "English, Korean, Persian, Spanish, Arabic"
## [381] "English, Chinese, Russian"
## [382] "English, Romanian, Greek, Bulgarian, Latin"
## [383] "English, Italian, Ukrainian"
## [384] "English, Cantonese, Japanese"
## [385] "English, Japanese, Xhosa, German"
## [386] "English, French, Spanish, Japanese"
## [387] "Mandarin, English"
## [388] "English, French, Latin, Arabic"
## [389] "English, Spanish, Hebrew"
## [390] "English, Mandarin, Greek"
## [391] "English, Portuguese, Japanese"
## [392] "English, Russian, Spanish, Romanian"
## [393] "English, Serbo-Croatian, Russian, French, Polish, German, Ukrainian"
## [394] "English, German, Spanish, Serbian"
## [395] "German, English"
## [396] "English, Norwegian, French, Spanish"
## [397] "English, German, Swedish, American Sign Language"
## [398] "English, German, Dutch, Polish, Latin"
## [399] "English, Polish, Spanish"
## [400] "English, Russian, Italian, Mandarin, French"
## [401] "English, Italian, Mandarin, Spanish"
## [402] "Russian, English, French, German, Swedish, Italian"
## [403] "English, Papiamento"
## [404] "English, Italian, German, Latin"
## [405] "English, Polish, Russian"
## [406] "English, Japanese, Vietnamese"
## [407] "English, French, Arabic, Spanish"
## [408] "English, Japanese, Italian, Hawaiian, German, French"
## [409] "English, Spanish, Yiddish, Italian"
## [410] "English, Swedish, Norwegian, Danish, Icelandic, French"
## [411] "English, Italian, Swedish"
## [412] "English, Min Nan, Mandarin"
## [413] "English, French, Japanese, Italian, North American Indian"
## [414] "American Sign Language, English"
## [415] "English, Swedish, French, German"
## [416] "English, Sioux, Cantonese"
## [417] "English, Hindi, French, German, Mandarin"
## [418] "English, French, Chinese"
## [419] "English, French, Italian, Japanese"
## [420] "English, Italian, Japanese, Russian"
## [421] "English, German, French, Russian, Italian"
## [422] "English, French, Hebrew, Yiddish"
## [423] "English, Mandarin, French"
## [424] "English, German, Russian, French"
## [425] "English, Hawaiian, German, Japanese"
## [426] "English, Hebrew, Arabic, Spanish"
## [427] "English, Slovak, French"
## [428] "English, Italian, Mandarin"
## [429] "Maya, English, Spanish"
## [430] "English, Hebrew, German, Polish, Latin"
## [431] "English, French, Romanian, Dutch, Mandarin"
## [432] "English, Sinhalese, Hindi"
## [433] "English, Thai, Spanish"
## [434] "English, Greek, French, Spanish"
## [435] "Spanish, French, English"
## [436] "English, Cantonese, Mandarin"
## [437] "English, Cantonese, Spanish, Russian"
## [438] "English, Somali"
## [439] "English, Spanish, Latin, French"
## [440] "English, Chinese, Vietnamese"
## [441] "English, American Sign Language, Dutch, Italian, Russian, Swahili"
## [442] "English, French, German, Greek, Ancient (to 1453)"
## [443] "English, Malay, Japanese"
## [444] "English, American Sign Language, Spanish, Latin"
## [445] "English, Spanish, Russian, German, Lingala"
## [446] "English, Polynesian, Spanish"
## [447] "Arabic, English"
## [448] "English, Polish, Latin"
## [449] "English, German, Xhosa, Russian, Romanian, Hindi"
## [450] "English, German, French, Russian, Spanish"
## [451] "English, Vietnamese, German, Danish"
## [452] "English, Spanish, Latin, French, German"
## [453] "English, Afrikaans, Maori, Zulu, Xhosa, Southern Sotho"
## [454] "English, French, American Sign Language"
## [455] "Korean, English, Spanish"
## [456] "English, German, Portuguese, Turkish, French"
## [457] "English, Cantonese, Mandarin, Spanish"
## [458] "English, Thai, Spanish, Hebrew, French"
## [459] "English, Icelandic, Filipino, Portuguese, French, Tagalog, German, Italian"
## [460] "Yiddish, English, Spanish"
## [461] "English, American Sign Language, Portuguese"
## [462] "Arabic, Hindi, English"
## [463] "English, French, German, Arabic"
## [464] "English, Middle English, Old English, Latin, German"
## [465] "English, Spanish, Russian, Arabic, French"
## [466] "English, Vietnamese, Spanish, Thai"
## [467] "English, Inuktitut, Croatian, Serbian"
## [468] "English, American Sign Language, Latin"
## [469] "English, French, Spanish, Swahili"
## [470] "English, Japanese, Mandarin, Russian, Cantonese"
## [471] "English, Finnish, French, Vietnamese"
## [472] "English, Turkish, Greek, Mandarin, French"
## [473] "English, Belarusian"
## [474] "Japanese"
## [475] "Japanese, Mandarin, English"
## [476] "English, Spanish, Cantonese, Italian"
## [477] "English, French, German, Vietnamese"
## [478] "English, Japanese, French, Arabic"
## [479] "English, French, Turkish, Hebrew, Arabic, Spanish"
## [480] "Persian"
## [481] "English, Spanish, French, Arabic"
## [482] "English, French, German, Russian, Japanese, Latin"
## [483] "English, German, French, Italian"
## [484] "Greek, American Sign Language, English, Portuguese, Spanish, German, French"
## [485] "English, Russian, German, French, Finnish, Italian"
## [486] "English, German, Dutch, Danish, French, American Sign Language"
## [487] "English, Hungarian, Spanish"
## [488] "English, Japanese, Chinese, Spanish"
## [489] "English, German, Japanese"
## [490] "English, Italian, Spanish, French"
## [491] "English, Spanish, Yiddish"
## [492] "Japanese, English, German"
## [493] "English, Serbian, French"
## [494] "English, German, Polish"
## [495] "English, Japanese, Arabic, Persian"
## [496] "English, Spanish, Latin, Italian"
## [497] "English, Swahili, Nama, Xhosa, Korean"
## [498] "English, Hindi, Bengali"
## [499] "English, Mandarin, Persian"
## [500] "English, Hebrew, Yiddish"
## [501] "English, Hebrew, French, German"
## [502] "English, Cantonese, Russian, Hindi, Spanish"
## [503] "English, Russian, Serbian, Bosnian, Croatian, Polish"
## [504] "English, German, Romanian"
## [505] "English, Vietnamese, Spanish"
## [506] "Afrikaans, Zulu, English"
## [507] "English, Spanish, Chinese, Latin"
## [508] "English, French, Italian, Cantonese"
## [509] "English, Italian, Serbo-Croatian"
## [510] "English, Turkmen, Cantonese, Italian, Spanish, Ukrainian, French"
## [511] "English, Chinese, Spanish"
## [512] "English, Japanese, Italian, French, Latin"
## [513] "English, Korean, French"
## [514] "English, Russian, Vietnamese, French, Cantonese"
## [515] "English, Cantonese, Ukrainian"
## [516] "English, French, Khmer, Russian"
## [517] "English, Japanese, German, Spanish"
## [518] "English, North American Indian"
## [519] "English, Russian, Serbian"
## [520] "English, American Sign Language, Chinese"
## [521] "English, German, French, Russian"
## [522] "English, Navajo, Mandarin"
## [523] "English, Spanish, Bulgarian"
## [524] "English, Dutch, German, Latvian"
## [525] "English, Italian, Russian, French, Chinese"
## [526] "English, Russian, Korean"
## [527] "English, Quechua, Romanian, Spanish"
## [528] "English, Japanese, Mandarin"
## [529] "English, Italian, Irish, Yiddish"
## [530] "English, Mandarin, Cantonese, Hokkien, French, Malay"
## [531] "English, Japanese, German, French"
## [532] "English, Lao"
## [533] "English, French, German, Arabic, Italian, Japanese"
## [534] "English, German, Spanish, Russian, Czech"
## [535] "English, Russian, Polish"
## [536] "English, Japanese, Mandarin, Shanghainese"
## [537] "English, Hawaiian, Mandarin, None"
## [538] "English, Latin, Hebrew"
## [539] "English, French, Swahili"
## [540] "English, Ukrainian, German, French"
## [541] "English, Yiddish, German"
## [542] "English, German, Polish, French"# Filtrando
filmes_ingles <- imdb %>% filter(idioma == "English")2. Crie um objeto chamado curtos_legais com filmes de 90 minutos ou menos de duração e nota no imdb maior do que 8.5.
curtos_legais <- imdb %>%
filter(duracao <= 90, nota_imdb > 8.5)3. Retorne tabelas (tibbles) apenas com:
a. filmes de ação anteriores a 1950;
library(stringr)
imdb %>%
filter(str_detect(generos, "Action"), ano < 1950)## # A tibble: 102 × 20
## id_filme titulo ano data_lancamento generos duracao pais idioma orcamento
## <chr> <chr> <dbl> <chr> <chr> <dbl> <chr> <chr> <dbl>
## 1 tt0041098 Afric… 1949 1950-04-08 Action… 79 USA Engli… NA
## 2 tt0037098 The M… 1944 1944-12-22 Action… 60 USA Engli… NA
## 3 tt0034889 In Ol… 1942 1947-06-25 Action… 88 USA Engli… NA
## 4 tt0040946 Wake … 1948 1949-03-01 Action… 106 USA Engli… 1200343
## 5 tt0029843 The A… 1938 1939-01-26 Action… 102 USA Engli… 1900000
## 6 tt0034522 The B… 1942 1942-12-04 Action… 87 USA Engli… NA
## 7 tt0024902 Blue … 1934 1934-05-10 Action… 54 USA Engli… NA
## 8 tt0041841 Sands… 1949 1950-03-01 Action… 100 USA Engli… 1000000
## 9 tt0027438 The C… 1936 1936-10-20 Action… 115 USA Engli… 1200000
## 10 tt0040076 Adven… 1948 1949-04-28 Action… 110 USA Engli… 3500000
## # … with 92 more rows, and 11 more variables: receita <dbl>, receita_eua <dbl>,
## # nota_imdb <dbl>, num_avaliacoes <dbl>, direcao <chr>, roteiro <chr>,
## # producao <chr>, elenco <chr>, descricao <chr>, num_criticas_publico <dbl>,
## # num_criticas_critica <dbl>b. filmes dirigidos por “Woody Allen” ou “Wes Anderson”;
imdb %>%
filter(direcao == "Woody Allen" | direcao == "Wes Anderson")## # A tibble: 42 × 20
## id_filme titulo ano data_lancamento generos duracao pais idioma orcamento
## <chr> <chr> <dbl> <chr> <chr> <dbl> <chr> <chr> <dbl>
## 1 tt0094663 Anoth… 1988 1989-03-17 Drama 81 USA Engli… 10000000
## 2 tt1748122 Moonr… 2012 2012-12-05 Comedy… 94 USA Engli… 16000000
## 3 tt0084329 A Mid… 1982 1982-09-24 Comedy 88 USA Engli… NA
## 4 tt0070707 Sleep… 1973 1974-03-15 Comedy… 89 USA Engli… 2000000
## 5 tt0068555 Every… 1972 1973-03-23 Comedy 88 USA Engli… 2000000
## 6 tt0065063 Take … 1969 1972-12-21 Comedy… 85 USA Engli… 1500000
## 7 tt0278823 Holly… 2002 2002-10-31 Comedy… 112 USA Engli… 16000000
## 8 tt0378947 Melin… 2004 2004-12-22 Comedy… 99 USA Engli… NA
## 9 tt0113819 Might… 1995 1996-01-26 Comedy… 95 USA Engli… 15000000
## 10 tt0091167 Hanna… 1986 1986-05-22 Comedy… 107 USA Engli… 6400000
## # … with 32 more rows, and 11 more variables: receita <dbl>, receita_eua <dbl>,
## # nota_imdb <dbl>, num_avaliacoes <dbl>, direcao <chr>, roteiro <chr>,
## # producao <chr>, elenco <chr>, descricao <chr>, num_criticas_publico <dbl>,
## # num_criticas_critica <dbl>c. filmes do “Steven Spielberg” ordenados de forma decrescente por ano, mostrando apenas as colunas titulo e ano;
imdb %>%
filter(direcao == "Steven Spielberg") %>%
arrange(desc(ano)) %>%
select(titulo, ano)## # A tibble: 21 × 2
## titulo ano
## <chr> <dbl>
## 1 Indiana Jones and the Kingdom of the Crystal Skull 2008
## 2 War of the Worlds 2005
## 3 The Terminal 2004
## 4 Minority Report 2002
## 5 Saving Private Ryan 1998
## 6 Amistad 1997
## 7 The Lost World: Jurassic Park 1997
## 8 Schindler's List 1993
## 9 Jurassic Park 1993
## 10 Hook 1991
## # … with 11 more rowsd. filmes que tenham “Action” ou “Comedy” entre os seus gêneros;
library(stringr)
# Solução 1
imdb %>%
filter(str_detect(generos, "Action") | str_detect(generos, "Comedy"))## # A tibble: 6,035 × 20
## id_filme titulo ano data_lancamento generos duracao pais idioma orcamento
## <chr> <chr> <dbl> <chr> <chr> <dbl> <chr> <chr> <dbl>
## 1 tt0092699 Broad… 1987 1988-04-01 Comedy… 133 USA Engli… 20000000
## 2 tt0037931 Murde… 1945 1945-06-23 Comedy… 91 USA Engli… NA
## 3 tt0183505 Me, M… 2000 2000-09-08 Comedy 116 USA Engli… 51000000
## 4 tt0033945 Never… 1941 1947-05-02 Comedy… 71 USA Engli… NA
## 5 tt0372122 Adam … 2005 2007-05-17 Comedy… 99 USA Engli… NA
## 6 tt0093640 No Wa… 1987 1987-12-11 Action… 114 USA Engli… 15000000
## 7 tt0494652 Welco… 2008 2008-02-08 Comedy… 104 USA Engli… 35000000
## 8 tt0110668 Night… 1995 1995-02-04 Action… 93 USA Engli… NA
## 9 tt0025101 Fashi… 1934 1934-02-14 Comedy… 78 USA Engli… NA
## 10 tt1488555 The C… 2011 2011-12-09 Comedy… 112 USA Engli… 52000000
## # … with 6,025 more rows, and 11 more variables: receita <dbl>,
## # receita_eua <dbl>, nota_imdb <dbl>, num_avaliacoes <dbl>, direcao <chr>,
## # roteiro <chr>, producao <chr>, elenco <chr>, descricao <chr>,
## # num_criticas_publico <dbl>, num_criticas_critica <dbl>e. filmes que tenham “Action” e “Comedy” entre os seus gêneros e tenha nota_imdb maior que 8;
imdb %>%
filter(str_detect(generos, "Action"), str_detect(generos, "Comedy"), nota_imdb > 8)## # A tibble: 4 × 20
## id_filme titulo ano data_lancamento generos duracao pais idioma orcamento
## <chr> <chr> <dbl> <chr> <chr> <dbl> <chr> <chr> <dbl>
## 1 tt4730224 An Hou… 2018 2018-06-12 Action… 96 USA Engli… 60000
## 2 tt0015324 Sherlo… 1924 1924-05-11 Action… 45 USA Engli… NA
## 3 tt0017925 The Ge… 1926 1927-03-30 Action… 67 USA Engli… 750000
## 4 tt0014429 Safety… 1923 1924-12-08 Action… 74 USA Engli… 121000
## # … with 11 more variables: receita <dbl>, receita_eua <dbl>, nota_imdb <dbl>,
## # num_avaliacoes <dbl>, direcao <chr>, roteiro <chr>, producao <chr>,
## # elenco <chr>, descricao <chr>, num_criticas_publico <dbl>,
## # num_criticas_critica <dbl>f. filmes que não possuem informação tanto de receita quanto de orçamento (isto é, possuem NA em ambas as colunas).
imdb %>%
filter(is.na(orcamento), is.na(receita))## # A tibble: 2,921 × 20
## id_filme titulo ano data_lancamento generos duracao pais idioma orcamento
## <chr> <chr> <dbl> <chr> <chr> <dbl> <chr> <chr> <dbl>
## 1 tt0037931 Murde… 1945 1945-06-23 Comedy… 91 USA Engli… NA
## 2 tt0033945 Never… 1941 1947-05-02 Comedy… 71 USA Engli… NA
## 3 tt3703836 Henry… 2015 2016-01-08 Drama 87 USA Engli… NA
## 4 tt0110668 Night… 1995 1995-02-04 Action… 93 USA Engli… NA
## 5 tt0035784 Dead … 1943 1943-04-12 Drama,… 64 USA Engli… NA
## 6 tt0025101 Fashi… 1934 1934-02-14 Comedy… 78 USA Engli… NA
## 7 tt1242423 Dear … 2009 2011-07-01 Comedy 87 USA Engli… NA
## 8 tt0046353 Split… 1953 1953-05-02 Crime,… 85 USA Engli… NA
## 9 tt0482461 Barry… 2010 2018 Comedy… 95 USA Engli… NA
## 10 tt0029992 A Chr… 1938 1938-12-16 Drama,… 69 USA Engli… NA
## # … with 2,911 more rows, and 11 more variables: receita <dbl>,
## # receita_eua <dbl>, nota_imdb <dbl>, num_avaliacoes <dbl>, direcao <chr>,
## # roteiro <chr>, producao <chr>, elenco <chr>, descricao <chr>,
## # num_criticas_publico <dbl>, num_criticas_critica <dbl>Modificando e criando novas colunas
1. Crie uma coluna chamada prejuizo (orcamento - receita) e salve a nova tabela em um objeto chamado imdb_prejuizo. Em seguida, filtre apenas os filmes que deram prejuízo e ordene a tabela por ordem crescente de prejuízo.
imdb_prejuizo <- imdb %>%
mutate(prejuizo = orcamento - receita)
imdb_prejuizo %>%
filter(prejuizo > 0) %>%
arrange(prejuizo)## # A tibble: 1,795 × 21
## id_filme titulo ano data_lancamento generos duracao pais idioma orcamento
## <chr> <chr> <dbl> <chr> <chr> <dbl> <chr> <chr> <dbl>
## 1 tt2063781 Smash… 2012 2012-12-14 Drama 81 USA Engli… 500000
## 2 tt1880418 Newly… 2011 2011-11-04 Comedy… 95 USA Engli… 9000
## 3 tt0067961 Wanda 1970 1971-01-14 Crime,… 102 USA Engli… 115000
## 4 tt0073043 The G… 1975 1975-10-01 Horror… 84 USA Engli… 300000
## 5 tt0083745 Come … 1982 1983-04-06 Comedy… 109 USA Engli… 850000
## 6 tt0045826 Glen … 1953 1953-04-01 Drama 65 USA Engli… 20000
## 7 tt0365960 Zero … 2002 2004-01-23 Drama 92 USA Engli… 20000
## 8 tt0086058 The O… 1983 1983-11-04 Action… 103 USA Engli… 6500000
## 9 tt0037638 Detour 1945 1946-01-25 Crime,… 68 USA Engli… 30000
## 10 tt1294161 The E… 2009 2010-05-06 Drama 79 USA Engli… 40000
## # … with 1,785 more rows, and 12 more variables: receita <dbl>,
## # receita_eua <dbl>, nota_imdb <dbl>, num_avaliacoes <dbl>, direcao <chr>,
## # roteiro <chr>, producao <chr>, elenco <chr>, descricao <chr>,
## # num_criticas_publico <dbl>, num_criticas_critica <dbl>, prejuizo <dbl>2. Fazendo apenas uma chamada da função mutate(), crie as seguintes colunas novas na base imdb:
a. lucro = receita - orcamento
b. lucro_medio
c. lucro_relativo = (lucro - lucro_medio)/lucro_medio
d. houve_lucro = ifelse(lucro > 0, "sim", "não")
imdb %>%
mutate(
lucro = receita - orcamento,
lucro_medio = mean(lucro, na.rm = TRUE),
lucro_relativo = (lucro - lucro_medio) / lucro_medio,
houve_lucro = ifelse(lucro > 0, "sim", "não")
)## # A tibble: 11,340 × 24
## id_filme titulo ano data_lancamento generos duracao pais idioma orcamento
## <chr> <chr> <dbl> <chr> <chr> <dbl> <chr> <chr> <dbl>
## 1 tt0092699 Broad… 1987 1988-04-01 Comedy… 133 USA Engli… 20000000
## 2 tt0037931 Murde… 1945 1945-06-23 Comedy… 91 USA Engli… NA
## 3 tt0183505 Me, M… 2000 2000-09-08 Comedy 116 USA Engli… 51000000
## 4 tt0033945 Never… 1941 1947-05-02 Comedy… 71 USA Engli… NA
## 5 tt0372122 Adam … 2005 2007-05-17 Comedy… 99 USA Engli… NA
## 6 tt3703836 Henry… 2015 2016-01-08 Drama 87 USA Engli… NA
## 7 tt0093640 No Wa… 1987 1987-12-11 Action… 114 USA Engli… 15000000
## 8 tt0494652 Welco… 2008 2008-02-08 Comedy… 104 USA Engli… 35000000
## 9 tt0094006 Some … 1987 1988-01-13 Drama,… 95 USA Engli… NA
## 10 tt1142798 The F… 2008 2008-09-12 Drama 111 USA Engli… NA
## # … with 11,330 more rows, and 15 more variables: receita <dbl>,
## # receita_eua <dbl>, nota_imdb <dbl>, num_avaliacoes <dbl>, direcao <chr>,
## # roteiro <chr>, producao <chr>, elenco <chr>, descricao <chr>,
## # num_criticas_publico <dbl>, num_criticas_critica <dbl>, lucro <dbl>,
## # lucro_medio <dbl>, lucro_relativo <dbl>, houve_lucro <chr>3. Crie uma nova coluna que classifique o filme em "recente" (posterior a 2000) e "antigo" (de 2000 para trás).
imdb %>%
mutate(antigo_ou_recente = ifelse(ano > 2000, "recente", "antigo"))## # A tibble: 11,340 × 21
## id_filme titulo ano data_lancamento generos duracao pais idioma orcamento
## <chr> <chr> <dbl> <chr> <chr> <dbl> <chr> <chr> <dbl>
## 1 tt0092699 Broad… 1987 1988-04-01 Comedy… 133 USA Engli… 20000000
## 2 tt0037931 Murde… 1945 1945-06-23 Comedy… 91 USA Engli… NA
## 3 tt0183505 Me, M… 2000 2000-09-08 Comedy 116 USA Engli… 51000000
## 4 tt0033945 Never… 1941 1947-05-02 Comedy… 71 USA Engli… NA
## 5 tt0372122 Adam … 2005 2007-05-17 Comedy… 99 USA Engli… NA
## 6 tt3703836 Henry… 2015 2016-01-08 Drama 87 USA Engli… NA
## 7 tt0093640 No Wa… 1987 1987-12-11 Action… 114 USA Engli… 15000000
## 8 tt0494652 Welco… 2008 2008-02-08 Comedy… 104 USA Engli… 35000000
## 9 tt0094006 Some … 1987 1988-01-13 Drama,… 95 USA Engli… NA
## 10 tt1142798 The F… 2008 2008-09-12 Drama 111 USA Engli… NA
## # … with 11,330 more rows, and 12 more variables: receita <dbl>,
## # receita_eua <dbl>, nota_imdb <dbl>, num_avaliacoes <dbl>, direcao <chr>,
## # roteiro <chr>, producao <chr>, elenco <chr>, descricao <chr>,
## # num_criticas_publico <dbl>, num_criticas_critica <dbl>,
## # antigo_ou_recente <chr>Sumarizando a base
Utilize a base imdb nos exercícios a seguir.
1. Calcule a duração média e mediana dos filmes da base.
imdb %>%
summarise(
duracao_media = mean(duracao, na.rm = TRUE),
duracao_mediana = median(duracao, na.rm = TRUE)
)## # A tibble: 1 × 2
## duracao_media duracao_mediana
## <dbl> <dbl>
## 1 99.7 972. Calcule o lucro médio dos filmes com duração maior que 2 horas (ou seja, 120 minutos).
imdb %>%
filter(duracao > 120) %>%
mutate(lucro = receita - orcamento) %>%
summarise(lucro_medio = mean(lucro, na.rm = TRUE))## # A tibble: 1 × 1
## lucro_medio
## <dbl>
## 1 126496589.3. Apresente na mesma tabela o lucro médio dos filmes com duracao menor que 120 minutos e o lucro médio dos filmes com duracao maior ou igual a 120 minutos.
imdb %>%
mutate(
lucro = receita - orcamento,
duracao_cat = ifelse(duracao < 120, "menor 2h", "2h ou mais")
) %>%
filter(!is.na(lucro)) %>%
group_by(duracao_cat) %>%
summarise(
lucro_medio = mean(lucro, na.rm = TRUE)
)## # A tibble: 2 × 2
## duracao_cat lucro_medio
## <chr> <dbl>
## 1 2h ou mais 121255603.
## 2 menor 2h 35676085.4. Retorne tabelas (tibbles) apenas com:
a. a nota IMDB média dos filmes por ano de lançamento;
imdb %>%
group_by(ano) %>%
summarise(nota_media = mean(nota_imdb, na.rm = TRUE))## # A tibble: 108 × 2
## ano nota_media
## <dbl> <dbl>
## 1 1914 6.27
## 2 1915 6.57
## 3 1916 7
## 4 1917 6.7
## 5 1918 6.63
## 6 1919 6.9
## 7 1920 6.76
## 8 1921 7.07
## 9 1922 6.9
## 10 1923 7.27
## # … with 98 more rowsb. a receita média e mediana dos filmes por ano;
imdb %>%
filter(!is.na(receita)) %>%
group_by(ano) %>%
summarise(
receita_media = mean(receita, na.rm = TRUE),
receita_mediana = median(receita, na.rm = TRUE)
)## # A tibble: 95 × 3
## ano receita_media receita_mediana
## <dbl> <dbl> <dbl>
## 1 1921 4605294. 4605294.
## 2 1923 11233 11233
## 3 1925 2406972 2834000
## 4 1927 42231. 4841
## 5 1928 589574. 26916
## 6 1929 5277780 5277780
## 7 1931 37363. 31312.
## 8 1932 448907 34649
## 9 1933 33289 14352.
## 10 1934 2198358. 9800
## # … with 85 more rowsc. apenas o nome das pessoas que dirigiram mais de 10 filmes.
imdb %>%
filter(!is.na(direcao)) %>%
group_by(direcao) %>%
summarise(num_filmes = n()) %>%
filter(num_filmes > 10) %>%
select(direcao)## # A tibble: 134 × 1
## direcao
## <chr>
## 1 Alan J. Pakula
## 2 Alan Rudolph
## 3 Albert Pyun
## 4 Alfred Hitchcock
## 5 Andrew V. McLaglen
## 6 Anthony Mann
## 7 Arthur Hiller
## 8 Arthur Penn
## 9 Barry Levinson
## 10 Billy Wilder
## # … with 124 more rowsTambém podemos usar a função count().
imdb %>%
filter(!is.na(direcao)) %>%
count(direcao, name = "num_filmes") %>%
filter(num_filmes > 10) %>%
select(direcao)## # A tibble: 134 × 1
## direcao
## <chr>
## 1 Alan J. Pakula
## 2 Alan Rudolph
## 3 Albert Pyun
## 4 Alfred Hitchcock
## 5 Andrew V. McLaglen
## 6 Anthony Mann
## 7 Arthur Hiller
## 8 Arthur Penn
## 9 Barry Levinson
## 10 Billy Wilder
## # … with 124 more rowsJuntando duas bases
1. Utilize a base imdb para resolver os itens a seguir.
a. Salve em um novo objeto uma tabela com a
nota média dos filmes de cada pessoa que dirigiu filmes. Essa tabela
deve conter duas colunas (direcao e nota_imdb_media)
e cada linha deve ser um pessoa diferente.
nota_direcao <- imdb %>%
group_by(direcao) %>%
summarise(nota_imdb_media = mean(nota_imdb))
nota_direcao## # A tibble: 5,140 × 2
## direcao nota_imdb_media
## <chr> <dbl>
## 1 A. Edward Sutherland 6.62
## 2 A.J. Edwards 6.1
## 3 A.T. White 5.3
## 4 Aaron Blaise, Robert Walker 6.8
## 5 Aaron Hann, Mario Miscione 6
## 6 Aaron Harvey 4.97
## 7 Aaron Horvath, Peter Rida Michail 6.8
## 8 Aaron K. Carter 8.2
## 9 Aaron Katz 6
## 10 Aaron Kaufman 4.5
## # … with 5,130 more rowsb. Use o left_join() para trazer a coluna
nota_imdb_media da tabela do item anterior
para a tabela imdb original.
imdb %>%
left_join(nota_direcao, by = "direcao") %>%
select(nota_imdb_media, everything())## # A tibble: 11,340 × 21
## nota_imdb_media id_filme titulo ano data_lancamento generos duracao pais
## <dbl> <chr> <chr> <dbl> <chr> <chr> <dbl> <chr>
## 1 6.6 tt0092699 Broadc… 1987 1988-04-01 Comedy… 133 USA
## 2 6.8 tt0037931 Murder… 1945 1945-06-23 Comedy… 91 USA
## 3 6.1 tt0183505 Me, My… 2000 2000-09-08 Comedy 116 USA
## 4 7.02 tt0033945 Never … 1941 1947-05-02 Comedy… 71 USA
## 5 5.9 tt0372122 Adam &… 2005 2007-05-17 Comedy… 99 USA
## 6 6.4 tt3703836 Henry … 2015 2016-01-08 Drama 87 USA
## 7 6.29 tt0093640 No Way… 1987 1987-12-11 Action… 114 USA
## 8 6.1 tt0494652 Welcom… 2008 2008-02-08 Comedy… 104 USA
## 9 6.43 tt0094006 Some K… 1987 1988-01-13 Drama,… 95 USA
## 10 5.02 tt1142798 The Fa… 2008 2008-09-12 Drama 111 USA
## # … with 11,330 more rows, and 13 more variables: idioma <chr>,
## # orcamento <dbl>, receita <dbl>, receita_eua <dbl>, nota_imdb <dbl>,
## # num_avaliacoes <dbl>, direcao <chr>, roteiro <chr>, producao <chr>,
## # elenco <chr>, descricao <chr>, num_criticas_publico <dbl>,
## # num_criticas_critica <dbl>