library(readr)
read_csv('mtcars.csv')
## # A tibble: 32 x 11
## mpg cyl disp hp drat wt qsec vs am gear carb
## <dbl> <int> <dbl> <int> <dbl> <dbl> <dbl> <int> <int> <int> <int>
## 1 21 6 160 110 3.9 2.62 16.5 0 1 4 4
## 2 21 6 160 110 3.9 2.88 17.0 0 1 4 4
## 3 22.8 4 108 93 3.85 2.32 18.6 1 1 4 1
## 4 21.4 6 258 110 3.08 3.22 19.4 1 0 3 1
## 5 18.7 8 360 175 3.15 3.44 17.0 0 0 3 2
## 6 18.1 6 225 105 2.76 3.46 20.2 1 0 3 1
## 7 14.3 8 360 245 3.21 3.57 15.8 0 0 3 4
## 8 24.4 4 147. 62 3.69 3.19 20 1 0 4 2
## 9 22.8 4 141. 95 3.92 3.15 22.9 1 0 4 2
## 10 19.2 6 168. 123 3.92 3.44 18.3 1 0 4 4
## # ... with 22 more rows
read_delim('mtcars.csv', delim = ",")
## # A tibble: 32 x 11
## mpg cyl disp hp drat wt qsec vs am gear carb
## <dbl> <int> <dbl> <int> <dbl> <dbl> <dbl> <int> <int> <int> <int>
## 1 21 6 160 110 3.9 2.62 16.5 0 1 4 4
## 2 21 6 160 110 3.9 2.88 17.0 0 1 4 4
## 3 22.8 4 108 93 3.85 2.32 18.6 1 1 4 1
## 4 21.4 6 258 110 3.08 3.22 19.4 1 0 3 1
## 5 18.7 8 360 175 3.15 3.44 17.0 0 0 3 2
## 6 18.1 6 225 105 2.76 3.46 20.2 1 0 3 1
## 7 14.3 8 360 245 3.21 3.57 15.8 0 0 3 4
## 8 24.4 4 147. 62 3.69 3.19 20 1 0 4 2
## 9 22.8 4 141. 95 3.92 3.15 22.9 1 0 4 2
## 10 19.2 6 168. 123 3.92 3.44 18.3 1 0 4 4
## # ... with 22 more rows
read_csv('mtcars1.csv')
## Warning: Duplicated column names deduplicated: '4' => '4_1' [11]
## # A tibble: 31 x 11
## `21` `6` `160` `110` `3.9` `2.62` `16.46` `0` `1` `4` `4_1`
## <dbl> <int> <dbl> <int> <dbl> <dbl> <dbl> <int> <int> <int> <int>
## 1 21 6 160 110 3.9 2.88 17.0 0 1 4 4
## 2 22.8 4 108 93 3.85 2.32 18.6 1 1 4 1
## 3 21.4 6 258 110 3.08 3.22 19.4 1 0 3 1
## 4 18.7 8 360 175 3.15 3.44 17.0 0 0 3 2
## 5 18.1 6 225 105 2.76 3.46 20.2 1 0 3 1
## 6 14.3 8 360 245 3.21 3.57 15.8 0 0 3 4
## 7 24.4 4 147. 62 3.69 3.19 20 1 0 4 2
## 8 22.8 4 141. 95 3.92 3.15 22.9 1 0 4 2
## 9 19.2 6 168. 123 3.92 3.44 18.3 1 0 4 4
## 10 17.8 6 168. 123 3.92 3.44 18.9 1 0 4 4
## # ... with 21 more rows
read_csv('mtcars1.csv', col_names = FALSE)
## # A tibble: 32 x 11
## X1 X2 X3 X4 X5 X6 X7 X8 X9 X10 X11
## <dbl> <int> <dbl> <int> <dbl> <dbl> <dbl> <int> <int> <int> <int>
## 1 21 6 160 110 3.9 2.62 16.5 0 1 4 4
## 2 21 6 160 110 3.9 2.88 17.0 0 1 4 4
## 3 22.8 4 108 93 3.85 2.32 18.6 1 1 4 1
## 4 21.4 6 258 110 3.08 3.22 19.4 1 0 3 1
## 5 18.7 8 360 175 3.15 3.44 17.0 0 0 3 2
## 6 18.1 6 225 105 2.76 3.46 20.2 1 0 3 1
## 7 14.3 8 360 245 3.21 3.57 15.8 0 0 3 4
## 8 24.4 4 147. 62 3.69 3.19 20 1 0 4 2
## 9 22.8 4 141. 95 3.92 3.15 22.9 1 0 4 2
## 10 19.2 6 168. 123 3.92 3.44 18.3 1 0 4 4
## # ... with 22 more rows
read_csv('mtcars2.csv')
## Warning: Missing column names filled in: 'X2' [2], 'X3' [3], 'X4' [4],
## 'X5' [5], 'X6' [6], 'X7' [7], 'X8' [8], 'X9' [9], 'X10' [10], 'X11' [11]
## # A tibble: 51 x 11
## `The data was ex~ X2 X3 X4 X5 X6 X7 X8 X9 X10
## <chr> <chr> <chr> <chr> <chr> <chr> <chr> <chr> <chr> <chr>
## 1 <NA> <NA> <NA> <NA> <NA> <NA> <NA> <NA> <NA> <NA>
## 2 A data frame wit~ <NA> <NA> <NA> <NA> <NA> <NA> <NA> <NA> <NA>
## 3 <NA> <NA> <NA> <NA> <NA> <NA> <NA> <NA> <NA> <NA>
## 4 [, 1] mpg Mile~ <NA> <NA> <NA> <NA> <NA> <NA> <NA>
## 5 [, 2] cyl Numb~ <NA> <NA> <NA> <NA> <NA> <NA> <NA>
## 6 [, 3] disp Disp~ <NA> <NA> <NA> <NA> <NA> <NA> <NA>
## 7 [, 4] hp Gros~ <NA> <NA> <NA> <NA> <NA> <NA> <NA>
## 8 [, 5] drat Rear~ <NA> <NA> <NA> <NA> <NA> <NA> <NA>
## 9 [, 6] wt Weig~ <NA> <NA> <NA> <NA> <NA> <NA> <NA>
## 10 [, 7] qsec 1/4 ~ <NA> <NA> <NA> <NA> <NA> <NA> <NA>
## # ... with 41 more rows, and 1 more variable: X11 <chr>
read_csv('mtcars2.csv', skip = 19)
## # A tibble: 32 x 11
## mpg cyl disp hp drat wt qsec vs am gear carb
## <dbl> <int> <dbl> <int> <dbl> <dbl> <dbl> <int> <int> <int> <int>
## 1 21 6 160 110 3.9 2.62 16.5 0 1 4 4
## 2 21 6 160 110 3.9 2.88 17.0 0 1 4 4
## 3 22.8 4 108 93 3.85 2.32 18.6 1 1 4 1
## 4 21.4 6 258 110 3.08 3.22 19.4 1 0 3 1
## 5 18.7 8 360 175 3.15 3.44 17.0 0 0 3 2
## 6 18.1 6 225 105 2.76 3.46 20.2 1 0 3 1
## 7 14.3 8 360 245 3.21 3.57 15.8 0 0 3 4
## 8 24.4 4 147. 62 3.69 3.19 20 1 0 4 2
## 9 22.8 4 141. 95 3.92 3.15 22.9 1 0 4 2
## 10 19.2 6 168. 123 3.92 3.44 18.3 1 0 4 4
## # ... with 22 more rows
read_csv('mtcars.csv', n_max = 20)
## # A tibble: 20 x 11
## mpg cyl disp hp drat wt qsec vs am gear carb
## <dbl> <int> <dbl> <int> <dbl> <dbl> <dbl> <int> <int> <int> <int>
## 1 21 6 160 110 3.9 2.62 16.5 0 1 4 4
## 2 21 6 160 110 3.9 2.88 17.0 0 1 4 4
## 3 22.8 4 108 93 3.85 2.32 18.6 1 1 4 1
## 4 21.4 6 258 110 3.08 3.22 19.4 1 0 3 1
## 5 18.7 8 360 175 3.15 3.44 17.0 0 0 3 2
## 6 18.1 6 225 105 2.76 3.46 20.2 1 0 3 1
## 7 14.3 8 360 245 3.21 3.57 15.8 0 0 3 4
## 8 24.4 4 147. 62 3.69 3.19 20 1 0 4 2
## 9 22.8 4 141. 95 3.92 3.15 22.9 1 0 4 2
## 10 19.2 6 168. 123 3.92 3.44 18.3 1 0 4 4
## 11 17.8 6 168. 123 3.92 3.44 18.9 1 0 4 4
## 12 16.4 8 276. 180 3.07 4.07 17.4 0 0 3 3
## 13 17.3 8 276. 180 3.07 3.73 17.6 0 0 3 3
## 14 15.2 8 276. 180 3.07 3.78 18 0 0 3 3
## 15 10.4 8 472 205 2.93 5.25 18.0 0 0 3 4
## 16 10.4 8 460 215 3 5.42 17.8 0 0 3 4
## 17 14.7 8 440 230 3.23 5.34 17.4 0 0 3 4
## 18 32.4 4 78.7 66 4.08 2.2 19.5 1 1 4 1
## 19 30.4 4 75.7 52 4.93 1.62 18.5 1 1 4 2
## 20 33.9 4 71.1 65 4.22 1.84 19.9 1 1 4 1
spec_csv('mtcars5.csv')
## cols(
## mpg = col_double(),
## cyl = col_integer(),
## disp = col_double(),
## hp = col_integer()
## )
read_csv('mtcars5.csv',
col_types = list(col_double(), col_factor(levels = c(4, 6, 8)),
col_double(), col_integer()))
## # A tibble: 32 x 4
## mpg cyl disp hp
## <dbl> <fct> <dbl> <int>
## 1 21 6 160 110
## 2 21 6 160 110
## 3 22.8 4 108 93
## 4 21.4 6 258 110
## 5 18.7 8 360 175
## 6 18.1 6 225 105
## 7 14.3 8 360 245
## 8 24.4 4 147. 62
## 9 22.8 4 141. 95
## 10 19.2 6 168. 123
## # ... with 22 more rows
read_csv('mtcars5.csv',
col_types = list(col_double(), col_factor(levels = c(4, 6, 8)),
col_skip(), col_integer()))
## # A tibble: 32 x 3
## mpg cyl hp
## <dbl> <fct> <int>
## 1 21 6 110
## 2 21 6 110
## 3 22.8 4 93
## 4 21.4 6 110
## 5 18.7 8 175
## 6 18.1 6 105
## 7 14.3 8 245
## 8 24.4 4 62
## 9 22.8 4 95
## 10 19.2 6 123
## # ... with 22 more rows
read_csv('mtcars5.csv',
col_types = cols_only(mpg = col_double(),
cyl = col_factor(levels = c(4, 6, 8))))
## # A tibble: 32 x 2
## mpg cyl
## <dbl> <fct>
## 1 21 6
## 2 21 6
## 3 22.8 4
## 4 21.4 6
## 5 18.7 8
## 6 18.1 6
## 7 14.3 8
## 8 24.4 4
## 9 22.8 4
## 10 19.2 6
## # ... with 22 more rows