Importação e exportação de dados
Tutorial
Diretório e pacotes
O pacote
rio é um pacote R relativamente recente utilizado para importação e exportação de dados. Ele faz suposições sobre o formato do arquivo (
veja os formatos suportados aqui), ou seja, adivinha o formato do arquivo que você está tentando importar e, consequentemente, aplica funções de importação apropriadas a esse formato. Tudo isso é feito com a função import().
O primeiro passo sugerido é definir o diretório de trabalho para a pasta dos arquivos. É razoável assumir que se o arquivo está em uma determinada pasta, esta pasta conterá seus scripts e saídas.
# definir diretório
setwd("E:/Desktop/tiagoolivoto/static/tutorials/r_quick_tips/003_import")
library(rio)
# para instalar os pacotes sugeridos e ampliar o leque de formatos
install_formats()
## [1] TRUE
Importar
Do excel
Um arquivo
# primeira planilha do excel
df_excel <- import("df_excel.xlsx")
df_excel
## RAD REP AF_M2 AF MST
## 1 50 1 5.02 5016.429 12.30785
## 2 50 2 3.65 3648.359 10.73315
## 3 50 3 3.93 3925.333 10.86140
## 4 50 4 4.71 4705.269 10.97850
## 5 70 1 6.12 6118.425 15.75180
## 6 70 2 5.61 5614.233 13.30495
## 7 70 3 5.11 5109.944 13.88435
## 8 70 4 4.98 4975.857 13.09225
## 9 100 1 5.46 5464.528 16.92240
## 10 100 2 5.55 5551.951 14.93085
## 11 100 3 5.72 5723.849 16.12900
## 12 100 4 5.87 5869.697 15.78145
# uma planilha específica
# converter para tible
df_excel2 <-
import("df_excel.xlsx",
sheet = "traits",
setclass = "tbl")
df_excel2
## # A tibble: 12 × 2
## AF MST
## <dbl> <dbl>
## 1 5016. 12.3
## 2 3648. 10.7
## 3 3925. 10.9
## 4 4705. 11.0
## 5 6118. 15.8
## 6 5614. 13.3
## 7 5110. 13.9
## 8 4976. 13.1
## 9 5465. 16.9
## 10 5552. 14.9
## 11 5724. 16.1
## 12 5870. 15.8
Vários arquivos
(padrao <- list.files(pattern = "df_excel"))
## [1] "df_excel.xlsx" "df_excel2.xlsx" "df_excel3.xlsx"
df_lista <- import_list(file = padrao)
str(df_lista)
## List of 3
## $ df_excel :'data.frame': 12 obs. of 5 variables:
## ..$ RAD : num [1:12] 50 50 50 50 70 70 70 70 100 100 ...
## ..$ REP : num [1:12] 1 2 3 4 1 2 3 4 1 2 ...
## ..$ AF_M2: num [1:12] 5.02 3.65 3.93 4.71 6.12 5.61 5.11 4.98 5.46 5.55 ...
## ..$ AF : num [1:12] 5016 3648 3925 4705 6118 ...
## ..$ MST : num [1:12] 12.3 10.7 10.9 11 15.8 ...
## ..- attr(*, "filename")= chr "df_excel.xlsx"
## $ df_excel2:'data.frame': 12 obs. of 5 variables:
## ..$ RAD : num [1:12] 50 50 50 50 70 70 70 70 100 100 ...
## ..$ REP : num [1:12] 1 2 3 4 1 2 3 4 1 2 ...
## ..$ AF_M2: num [1:12] 5.02 3.65 3.93 4.71 6.12 5.61 5.11 4.98 5.46 5.55 ...
## ..$ AF : num [1:12] 5016 3648 3925 4705 6118 ...
## ..$ MST : num [1:12] 12.3 10.7 10.9 11 15.8 ...
## ..- attr(*, "filename")= chr "df_excel2.xlsx"
## $ df_excel3:'data.frame': 12 obs. of 5 variables:
## ..$ RAD : num [1:12] 50 50 50 50 70 70 70 70 100 100 ...
## ..$ REP : num [1:12] 1 2 3 4 1 2 3 4 1 2 ...
## ..$ AF_M2: chr [1:12] "5,02" "3,65" "3,93" "4,71" ...
## ..$ AF : chr [1:12] "5016,43" "3648,36" "3925,33" "4705,27" ...
## ..$ MST : chr [1:12] "12,31" "10,73" "10,86" "10,98" ...
## ..- attr(*, "filename")= chr "df_excel3.xlsx"
df_lista_bind <- import_list(file = padrao, rbind = TRUE)
df_lista_bind
## RAD REP AF_M2 AF MST _file
## 1 50 1 5.02 5016.42875 12.30785 df_excel.xlsx
## 2 50 2 3.65 3648.3589 10.73315 df_excel.xlsx
## 3 50 3 3.93 3925.33325 10.8614 df_excel.xlsx
## 4 50 4 4.71 4705.2685 10.9785 df_excel.xlsx
## 5 70 1 6.12 6118.4251 15.7518 df_excel.xlsx
## 6 70 2 5.61 5614.23305 13.30495 df_excel.xlsx
## 7 70 3 5.11 5109.94435 13.88435 df_excel.xlsx
## 8 70 4 4.98 4975.85695 13.09225 df_excel.xlsx
## 9 100 1 5.46 5464.528 16.9224 df_excel.xlsx
## 10 100 2 5.55 5551.95115 14.93085 df_excel.xlsx
## 11 100 3 5.72 5723.84875 16.129 df_excel.xlsx
## 12 100 4 5.87 5869.69745 15.78145 df_excel.xlsx
## 13 50 1 5.02 5016.42875 12.30785 df_excel2.xlsx
## 14 50 2 3.65 3648.3589 10.73315 df_excel2.xlsx
## 15 50 3 3.93 3925.33325 10.8614 df_excel2.xlsx
## 16 50 4 4.71 4705.2685 10.9785 df_excel2.xlsx
## 17 70 1 6.12 6118.4251 15.7518 df_excel2.xlsx
## 18 70 2 5.61 5614.23305 13.30495 df_excel2.xlsx
## 19 70 3 5.11 5109.94435 13.88435 df_excel2.xlsx
## 20 70 4 4.98 4975.85695 13.09225 df_excel2.xlsx
## 21 100 1 5.46 5464.528 16.9224 df_excel2.xlsx
## 22 100 2 5.55 5551.95115 14.93085 df_excel2.xlsx
## 23 100 3 5.72 5723.84875 16.129 df_excel2.xlsx
## 24 100 4 5.87 5869.69745 15.78145 df_excel2.xlsx
## 25 50 1 5,02 5016,43 12,31 df_excel3.xlsx
## 26 50 2 3,65 3648,36 10,73 df_excel3.xlsx
## 27 50 3 3,93 3925,33 10,86 df_excel3.xlsx
## 28 50 4 4,71 4705,27 10,98 df_excel3.xlsx
## 29 70 1 6,12 6118,43 15,75 df_excel3.xlsx
## 30 70 2 5,61 5614,23 13,30 df_excel3.xlsx
## 31 70 3 5,11 5109,94 13,88 df_excel3.xlsx
## 32 70 4 4,98 4975,86 13,09 df_excel3.xlsx
## 33 100 1 5,46 5464,53 16,92 df_excel3.xlsx
## 34 100 2 5,55 5551,95 14,93 df_excel3.xlsx
## 35 100 3 5,72 5723,85 16,13 df_excel3.xlsx
## 36 100 4 5,87 5869,70 15,78 df_excel3.xlsx
Planilha separada por vírgulas
df_csv <- import("df_csv.csv")
df_csv
## RAD REP AF_M2 AF MST
## 1 50 1 5.02 5016.43 12.31
## 2 50 2 3.65 3648.36 10.73
## 3 50 3 3.93 3925.33 10.86
## 4 50 4 4.71 4705.27 10.98
## 5 70 1 6.12 6118.43 15.75
## 6 70 2 5.61 5614.23 13.30
## 7 70 3 5.11 5109.94 13.88
## 8 70 4 4.98 4975.86 13.09
## 9 100 1 5.46 5464.53 16.92
## 10 100 2 5.55 5551.95 14.93
## 11 100 3 5.72 5723.85 16.13
## 12 100 4 5.87 5869.70 15.78
Arquivos de texto
df_txt <- import("df_txt.txt")
df_txt
## RAD REP AF_M2 AF MST
## 1 50 1 5.02 5016.43 12.31
## 2 50 2 3.65 3648.36 10.73
## 3 50 3 3.93 3925.33 10.86
## 4 50 4 4.71 4705.27 10.98
## 5 70 1 6.12 6118.43 15.75
## 6 70 2 5.61 5614.23 13.30
## 7 70 3 5.11 5109.94 13.88
## 8 70 4 4.98 4975.86 13.09
## 9 100 1 5.46 5464.53 16.92
## 10 100 2 5.55 5551.95 14.93
## 11 100 3 5.72 5723.85 16.13
## 12 100 4 5.87 5869.70 15.78
Google sheets
url <- "https://docs.google.com/spreadsheets/d/1b-Sj9l-VwJ-Oy-hFx7j8twsA5oC6-Fr9ukllywfim0E"
df_gsheet <- import(url, dec = ",")
df_gsheet
## RAD REP AF_M2 AF MST
## 1 50 1 5.02 5016.43 12.31
## 2 50 2 3.65 3648.36 10.73
## 3 50 3 3.93 3925.33 10.86
## 4 50 4 4.71 4705.27 10.98
## 5 70 1 6.12 6118.43 15.75
## 6 70 2 5.61 5614.23 13.30
## 7 70 3 5.11 5109.94 13.88
## 8 70 4 4.98 4975.86 13.09
## 9 100 1 5.46 5464.53 16.92
## 10 100 2 5.55 5551.95 14.93
## 11 100 3 5.72 5723.85 16.13
## 12 100 4 5.87 5869.70 15.78
SPSS
O arquivo ".sav" de exemplo foi baixado
deste site
df_spss <- import("df_spss.sav", setclass = "tbl")
df_spss
## # A tibble: 306 × 59
## IDnumber age sex workstat increg incmnth incwk housing living homepay
## <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
## 1 20160186 19 2 3 1 0 0 2 1 1
## 2 20160011 17 2 0 0 0 0 2 1 1
## 3 20160081 18 2 3 1 300 69.2 2 1 1
## 4 20160155 18 2 0 0 0 0 2 1 1
## 5 20160182 19 2 0 1 600 138. 2 1 4
## 6 20160027 17 2 0 0 0 0 2 1 4
## 7 20160188 19 2 0 0 0 0 2 1 99
## 8 20160013 17 2 0 0 0 0 2 1 1
## 9 20160214 20 2 0 1 1500 346. 3 2 4
## 10 20160216 20 2 3 1 400 92.3 3 2 1
## # … with 296 more rows, and 49 more variables: homecost <dbl>,
## # homecostwk <dbl>, mobile <dbl>, mobilepay <dbl>, mobilecost <dbl>,
## # mobilecostwk <dbl>, transport <dbl>, food <dbl>, entertain <dbl>,
## # privhlth <dbl>, fs_illness <dbl>, fs_accident <dbl>, fs_death <dbl>,
## # fs_mtlillness <dbl>, fs_disability <dbl>, fs_divsep <dbl>,
## # fs_nogetjob <dbl>, fs_lossofjob <dbl>, fs_alcdrug <dbl>, fs_witviol <dbl>,
## # fs_absvcrim <dbl>, fs_police <dbl>, fs_gambling <dbl>, famstress <dbl>, …
DBF
O arquivo ".dbf" de exemplo foi baixado
deste site
df_dbf <- import("df_dbf.dbf")
df_dbf
## ID CATCOUNT AGRPCOUNT PGRPCOUNT ORDER CODE
## 1 87 2 0 0 87 1
## 2 26 3 0 0 26 CPKG
## 3 27 3 0 0 27 CHOC
## 4 28 3 0 0 28 PASTEL
## 5 29 2 0 0 29 CKR-1001
## 6 30 3 0 0 30 C
## 7 31 3 0 0 31 TBC01
## 8 32 2 0 0 32 BD01
## 9 33 1 0 0 33 DS02
## 10 34 1 0 0 34 AB01
## 11 35 2 0 0 35 1006
## 12 36 2 0 0 36 BC01
## 13 37 3 0 0 37 CC01
## 14 38 3 0 0 38 D-1005
## 15 39 2 0 0 39 CH-BC01
## 16 40 3 0 0 40 M
## 17 41 3 0 0 41 CR
## 18 42 2 0 0 42 SLEIGH
## 19 43 2 0 0 43 PT01
## 20 44 2 0 0 44 GINGER
## 21 45 3 0 0 45 LB01
## 22 46 2 0 0 46 CRAN
## 23 47 3 0 0 47 SAM02
## 24 48 1 0 0 48 CP01
## 25 49 2 0 0 49 NYEAR
## 26 50 1 0 0 50 CH02
## 27 51 1 0 0 51 CH03
## 28 52 1 0 0 52 CH04
## 29 53 1 0 0 53 CH05
## 30 54 1 0 0 54 CH06
## 31 55 1 0 0 55 MC-Heart
## 32 56 3 0 0 56 VA01
## 33 57 3 0 0 57 VA01A
## 34 58 3 0 0 58 VABC
## 35 59 2 0 0 59 BAS03
## 36 60 2 0 0 60 1004A
## 37 61 3 0 0 61 FUDGE
## 38 62 3 0 0 62 VA-1005
## 39 63 3 0 0 63 CS01
## 40 64 2 0 0 64 D-BCO1
## 41 65 2 0 0 65 SPBC
## 42 66 3 0 0 66 SP-1001
## 43 67 3 0 0 67 FB
## 44 69 3 0 0 69 WC
## 45 70 2 0 0 70 BABY-1002
## 46 71 2 0 0 71 PA03
## 47 72 3 0 0 72 EO
## 48 73 2 0 0 73 E-BC01
## 49 74 2 0 0 74 1101A
## 50 75 2 0 0 75 1101
## 51 76 2 0 0 76 E010
## 52 77 2 0 0 77 DK01
## 53 78 2 0 0 78 MC-EGG
## 54 79 2 0 0 79 BAS02
## 55 80 3 0 0 80 PKG
## 56 81 2 0 0 81 SHOE-BC01
## 57 82 2 0 0 82 TIE-BC01
## 58 83 3 0 0 83 PET
## 59 84 3 0 0 84 STAR-1001
## 60 85 2 0 0 85 STAR-BC01
## 61 86 3 0 0 86 H
## 62 88 3 0 0 88 EYEBALLS
## 63 89 2 0 0 89 H-BC01
## 64 90 3 0 0 90 HRV
## 65 91 2 0 0 91 HRV-BC01
## 66 93 2 0 0 93 D-1001
## 67 94 2 0 0 94 BD02
## NAME
## 1 Assorted Petits Fours
## 2 Christmas Package Collection
## 3 Chocolate Assorted Petits Fours
## 4 Pastel Assorted Petits Fours
## 5 Checkerbites
## 6 Christmas Petits Fours
## 7 Truffled Shortbread
## 8 Biscotti di Divine
## 9 Dresden Stollen
## 10 Apricot Brandy Fruitcake
## 11 Trufflecots
## 12 Butter Cookie Sampler
## 13 Petite Cheesecake Sampler
## 14 Demitasse Truffles & Petits Fours
## 15 Christmas Shortbread
## 16 Mice-A-Fours
## 17 Critters
## 18 Golden Sleigh Sampler
## 19 Pumpkin Spice Teacake
## 20 Ginger Teacake
## 21 Lemon Buttermilk Teacake
## 22 Cranberry Orange Teacake
## 23 Tea Cake Sampler
## 24 Chocolate Pecan Tart
## 25 New Year Petits Fours
## 26 Rose Tea Cup
## 27 Violet Tea Cup
## 28 Pansy Tea Cup
## 29 Forget-me-not Tea Cup
## 30 Morning Glory Tea Cup
## 31 Golden Chocolate Heart
## 32 Valentine Petits Fours
## 33 Valentine Petits Fours
## 34 Valentine Shortbread
## 35 Basket of Romance
## 36 Fudgies
## 37 Tunnel of Fudge
## 38 Valentine Demitasse Truffles & Petits Fours
## 39 Butter Cinnamon Swirl
## 40 Daisy Shortbreads
## 41 Shamrock Shortbread Cookies
## 42 St. Patrick's Day Petits Fours
## 43 Petit Four Favor Boxes
## 44 Wedding Cremes
## 45 Baby Shower Assortment
## 46 Wedding Pastels
## 47 Easter Petits Fours
## 48 Easter Shortbreads
## 49 Baby Hop Basket
## 50 Great Grande Hop Basket
## 51 Truffle Egg Carton
## 52 Milk Chocolate Ducks
## 53 Milk Chocolate Easter Egg
## 54 Tea Basket
## 55 The Package Collection
## 56 Shortbread Shoe Collection
## 57 Tin of Ties
## 58 Petals and Cremes
## 59 Hearts and Stripes
## 60 4th of July Shortbread Cookies
## 61 Hallowed Eve Petits Fours
## 62 Eyeball Truffles
## 63 Halloween Shortbread
## 64 Harvest Petits Fours
## 65 Harvest Shortbread Tin
## 66 Demitasse Christmas Petits Fours
## 67 Trio of Biscotti
## THUMBNAIL IMAGE PRICE
## 1 graphics/00000001/t_1.jpg graphics/00000001/1.jpg 0.00
## 2 graphics/00000001/t_CPKG.jpg graphics/00000001/CPKG.jpg 0.00
## 3 graphics/00000001/t_CHOC.jpg graphics/00000001/CHOC.jpg 0.00
## 4 graphics/00000001/t_PASTEL.jpg graphics/00000001/PASTEL.jpg 0.00
## 5 graphics/00000001/t_CKR-1001.jpg graphics/00000001/CKR-1001.jpg 15.75
## 6 graphics/00000001/t_C.jpg graphics/00000001/C.jpg 0.00
## 7 graphics/00000001/t_TBC01.jpg graphics/00000001/TBC01.jpg 19.25
## 8 graphics/00000001/t_BD01.jpg graphics/00000001/BD01.jpg 28.75
## 9 graphics/00000001/t_DS02.jpg graphics/00000001/DS02.jpg 23.95
## 10 graphics/00000001/t_AB01.jpg graphics/00000001/AB01.jpg 37.95
## 11 graphics/00000001/t_1006.jpg graphics/00000001/1006.jpg 29.95
## 12 graphics/00000001/t_BC01.jpg graphics/00000001/BC01.jpg 28.95
## 13 graphics/00000001/t_CC01.jpg graphics/00000001/CC01.jpg 27.65
## 14 graphics/00000001/t_D-1005.jpg graphics/00000001/D-1005.jpg 27.50
## 15 graphics/00000001/t_CH-BC01.jpg graphics/00000001/CH-BC01.jpg 34.95
## 16 graphics/00000001/t_M.jpg graphics/00000001/M.jpg 0.00
## 17 graphics/00000001/t_CR.jpg graphics/00000001/CR.jpg 0.00
## 18 graphics/00000001/t_SLEIGH.jpg graphics/00000001/SLEIGH.jpg 47.95
## 19 graphics/00000001/t_PT01.jpg graphics/00000001/PT01.jpg 25.75
## 20 graphics/00000001/t_GINGER.jpg graphics/00000001/GINGER.jpg 25.25
## 21 graphics/00000001/t_LB01.jpg graphics/00000001/LB01.jpg 25.70
## 22 graphics/00000001/t_CRAN.jpg graphics/00000001/CRAN.jpg 25.95
## 23 graphics/00000001/t_SAM02.jpg graphics/00000001/SAM02.jpg 26.95
## 24 graphics/00000001/t_CP01.jpg graphics/00000001/CP01.jpg 27.95
## 25 graphics/00000001/t_NYEAR.jpg graphics/00000001/NYEAR.jpg 0.00
## 26 graphics/00000001/t_CH02.jpg graphics/00000001/CH02.jpg 87.00
## 27 graphics/00000001/t_CH03.jpg graphics/00000001/CH03.jpg 87.00
## 28 graphics/00000001/t_CH04.jpg graphics/00000001/CH04.jpg 87.00
## 29 graphics/00000001/t_CH05.jpg graphics/00000001/CH05.jpg 87.00
## 30 graphics/00000001/t_CH06.jpg graphics/00000001/CH06.jpg 87.00
## 31 graphics/00000001/t_MC-HEART.jpg graphics/00000001/MC-HEART.jpg 14.87
## 32 graphics/00000001/t_VA01.jpg graphics/00000001/VA01.jpg 36.95
## 33 graphics/00000001/t_VA01A.jpg graphics/00000001/VA01A.jpg 28.95
## 34 graphics/00000001/t_VABC.jpg graphics/00000001/VABC.jpg 33.75
## 35 graphics/00000001/t_BAS03.jpg graphics/00000001/BAS03.jpg 48.50
## 36 graphics/00000001/t_1004A.jpg graphics/00000001/1004A.jpg 16.95
## 37 graphics/00000001/t_FUDGE.jpg graphics/00000001/FUDGE.jpg 26.75
## 38 graphics/00000001/t_VA-1005.jpg graphics/00000001/VA-1005.jpg 27.50
## 39 graphics/00000001/t_CS01.jpg graphics/00000001/b_CS01.jpg 25.50
## 40 graphics/00000001/t_D-BC01.jpg graphics/00000001/D-BC01.jpg 32.25
## 41 graphics/00000001/t_SPBC.jpg graphics/00000001/SPBC.jpg 32.50
## 42 graphics/00000001/t_SP-1001.jpg graphics/00000001/SP-1001.jpg 27.50
## 43 graphics/00000001/t_FB.jpg graphics/00000001/FB.jpg 17.50
## 44 graphics/00000001/t_WC.jpg graphics/00000001/WC_vs2.jpg 0.00
## 45 graphics/00000001/t_BABY-1002.jpg graphics/00000001/BABY-1002.jpg 44.75
## 46 graphics/00000001/t_PA03.jpg graphics/00000001/PA03_vs2.jpg 49.50
## 47 graphics/00000001/t_EO.jpg graphics/00000001/EO.jpg 0.00
## 48 graphics/00000001/t_E-BC01.jpg graphics/00000001/E-BC01.jpg 35.25
## 49 graphics/00000001/t_1101A.jpg graphics/00000001/1101A.jpg 27.50
## 50 graphics/00000001/t_1101.jpg graphics/00000001/1101.jpg 49.95
## 51 graphics/00000001/t_E010.jpg graphics/00000001/E010.jpg 28.95
## 52 graphics/00000001/t_DK01.jpg graphics/00000001/DK01.jpg 6.95
## 53 graphics/00000001/t_MC-EGG.jpg graphics/00000001/MC-EGG.jpg 28.95
## 54 graphics/00000001/t_BAS02.jpg graphics/00000001/BAS02.jpg 39.75
## 55 graphics/00000001/t_PKG.jpg graphics/00000001/PKG.jpg 0.00
## 56 graphics/00000001/t_SHOE-BC01.jpg graphics/00000001/SHOE-BC01.jpg 33.95
## 57 graphics/00000001/t_TIE-BC01.jpg graphics/00000001/TIE-BC01.jpg 33.50
## 58 graphics/00000001/t_PET.jpg graphics/00000001/PET.jpg 0.00
## 59 graphics/00000001/t_STAR-1001.jpg graphics/00000001/STAR-1001.jpg 28.25
## 60 graphics/00000001/t_STAR-BC01.jpg graphics/00000001/STAR-BC01.jpg 33.75
## 61 graphics/00000001/t_H1.jpg graphics/00000001/H1.jpg 0.00
## 62 graphics/00000001/t_eyeballs.jpg graphics/00000001/eyeballs.jpg 28.95
## 63 graphics/00000001/t_H-BC01.jpg graphics/00000001/H-BC01.jpg 35.95
## 64 graphics/00000001/t_HRV.jpg graphics/00000001/HRV.jpg 0.00
## 65 graphics/00000001/t_HRV-BC01.jpg graphics/00000001/HRV-BC01.jpg 34.25
## 66 graphics/00000001/t_D-1001.jpg graphics/00000001/D-1001.jpg 28.95
## 67 graphics/00000001/t_BD02.jpg graphics/00000001/BD02.jpg 29.75
## COST DESC WEIGHT TAXABLE ACTIVE
## 1 0.00 1 5.51 TRUE TRUE
## 2 28.95 3 0.00 FALSE TRUE
## 3 28.95 6 0.00 FALSE FALSE
## 4 28.95 8 0.00 FALSE TRUE
## 5 15.75 9 0.00 FALSE TRUE
## 6 31.95 10 0.00 FALSE TRUE
## 7 19.25 11 0.00 FALSE FALSE
## 8 28.75 12 0.00 FALSE FALSE
## 9 23.95 13 0.00 FALSE FALSE
## 10 37.95 14 0.00 FALSE TRUE
## 11 29.95 16 0.00 FALSE TRUE
## 12 28.95 17 0.00 FALSE TRUE
## 13 27.65 18 0.00 FALSE TRUE
## 14 27.50 19 0.00 FALSE TRUE
## 15 34.95 20 0.00 FALSE TRUE
## 16 19.75 22 0.00 FALSE FALSE
## 17 28.95 23 0.00 FALSE FALSE
## 18 47.95 24 0.00 FALSE TRUE
## 19 25.75 26 0.00 FALSE TRUE
## 20 25.25 27 0.00 FALSE TRUE
## 21 25.70 28 0.00 FALSE TRUE
## 22 25.95 29 0.00 FALSE TRUE
## 23 26.95 31 0.00 FALSE TRUE
## 24 27.95 32 0.00 FALSE TRUE
## 25 29.95 33 0.00 FALSE FALSE
## 26 0.00 34 0.00 FALSE TRUE
## 27 0.00 35 0.00 FALSE TRUE
## 28 0.00 36 0.00 FALSE TRUE
## 29 0.00 37 0.00 FALSE TRUE
## 30 0.00 38 0.00 FALSE TRUE
## 31 14.87 39 0.00 FALSE FALSE
## 32 36.95 40 0.00 FALSE FALSE
## 33 29.95 41 0.00 FALSE FALSE
## 34 33.75 42 0.00 FALSE FALSE
## 35 48.50 43 0.00 FALSE FALSE
## 36 16.95 44 0.00 FALSE TRUE
## 37 26.75 45 0.00 FALSE FALSE
## 38 27.50 46 0.00 FALSE FALSE
## 39 25.50 47 0.00 FALSE FALSE
## 40 32.25 48 0.00 FALSE FALSE
## 41 32.50 49 0.00 FALSE FALSE
## 42 27.50 51 0.00 FALSE FALSE
## 43 17.50 52 0.00 TRUE TRUE
## 44 28.95 54 0.00 FALSE FALSE
## 45 44.75 56 0.00 FALSE FALSE
## 46 49.50 57 0.00 FALSE TRUE
## 47 28.95 58 0.00 FALSE FALSE
## 48 35.25 59 0.00 FALSE FALSE
## 49 27.50 60 0.00 FALSE FALSE
## 50 49.95 61 0.00 FALSE FALSE
## 51 28.95 62 0.00 FALSE FALSE
## 52 6.95 63 0.00 FALSE FALSE
## 53 28.95 64 0.00 FALSE FALSE
## 54 39.75 65 0.00 FALSE FALSE
## 55 28.95 66 0.00 FALSE FALSE
## 56 33.95 67 0.00 FALSE FALSE
## 57 33.50 68 0.00 FALSE FALSE
## 58 27.50 69 0.00 FALSE FALSE
## 59 28.25 70 0.00 FALSE FALSE
## 60 33.75 71 0.00 FALSE FALSE
## 61 29.95 72 0.00 FALSE FALSE
## 62 28.95 73 0.00 FALSE FALSE
## 63 35.95 74 0.00 FALSE FALSE
## 64 0.00 75 0.00 FALSE TRUE
## 65 0.00 76 0.00 FALSE FALSE
## 66 0.00 77 0.00 FALSE TRUE
## 67 0.00 78 0.00 FALSE TRUE
ODS
df_ods <- import("df_ods.ods")
## Loading required namespace: readODS
df_ods
## RAD REP AF_M2 AF MST
## 1 50 1 5.02 5016.429 12.30785
## 2 50 2 3.65 3648.359 10.73315
## 3 50 3 3.93 3925.333 10.86140
## 4 50 4 4.71 4705.269 10.97850
## 5 70 1 6.12 6118.425 15.75180
## 6 70 2 5.61 5614.233 13.30495
## 7 70 3 5.11 5109.944 13.88435
## 8 70 4 4.98 4975.857 13.09225
## 9 100 1 5.46 5464.528 16.92240
## 10 100 2 5.55 5551.951 14.93085
## 11 100 3 5.72 5723.849 16.12900
## 12 100 4 5.87 5869.697 15.78145
Rdata
df_rdata <- import("df_r.Rdata")
df_rdata
## RAD REP AF_M2 AF MST
## 1 50 1 5.02 5016.43 12.31
## 2 50 2 3.65 3648.36 10.73
## 3 50 3 3.93 3925.33 10.86
## 4 50 4 4.71 4705.27 10.98
## 5 70 1 6.12 6118.43 15.75
## 6 70 2 5.61 5614.23 13.30
## 7 70 3 5.11 5109.94 13.88
## 8 70 4 4.98 4975.86 13.09
## 9 100 1 5.46 5464.53 16.92
## 10 100 2 5.55 5551.95 14.93
## 11 100 3 5.72 5723.85 16.13
## 12 100 4 5.87 5869.70 15.78
Exportar
# exportar para excel
export(df_excel, "exportado.xlsx")
# exportar para txt
export(df_excel, "exportado.txt")
# exportar para csv
export(df_excel, "exportado.csv")
# exportar várias planilhas para um arquivo
export(
list(
plan1 = df_excel,
plan2 = df_excel2
),
file = "minha_lista.xlsx"
)
Versão e pacotes
sessionInfo()
## R version 4.2.0 (2022-04-22 ucrt)
## Platform: x86_64-w64-mingw32/x64 (64-bit)
## Running under: Windows 10 x64 (build 22000)
##
## Matrix products: default
##
## locale:
## [1] LC_COLLATE=Portuguese_Brazil.utf8 LC_CTYPE=Portuguese_Brazil.utf8
## [3] LC_MONETARY=Portuguese_Brazil.utf8 LC_NUMERIC=C
## [5] LC_TIME=Portuguese_Brazil.utf8
##
## attached base packages:
## [1] stats graphics grDevices utils datasets methods base
##
## other attached packages:
## [1] rio_0.5.29
##
## loaded via a namespace (and not attached):
## [1] zip_2.2.0 Rcpp_1.0.8.3 cellranger_1.1.0 bslib_0.3.1
## [5] compiler_4.2.0 pillar_1.7.0 jquerylib_0.1.4 forcats_0.5.1
## [9] tools_4.2.0 digest_0.6.29 jsonlite_1.8.0 evaluate_0.15
## [13] lifecycle_1.0.1 tibble_3.1.7 pkgconfig_2.0.3 rlang_1.0.2
## [17] openxlsx_4.2.5 cli_3.3.0 rstudioapi_0.13 curl_4.3.2
## [21] yaml_2.3.5 blogdown_1.10 haven_2.5.0 xfun_0.31
## [25] fastmap_1.1.0 xml2_1.3.3 stringr_1.4.0 knitr_1.39
## [29] readODS_1.7.0 vctrs_0.4.1 sass_0.4.1 hms_1.1.1
## [33] glue_1.6.2 data.table_1.14.2 R6_2.5.1 fansi_1.0.3
## [37] readxl_1.4.0 foreign_0.8-82 rmarkdown_2.14 bookdown_0.26
## [41] tzdb_0.3.0 readr_2.1.2 magrittr_2.0.3 htmltools_0.5.2
## [45] ellipsis_0.3.2 utf8_1.2.2 stringi_1.7.6 crayon_1.5.1