Supporting Statistical Analysis for Research
2.3 More challenging csv and deliminated files
Import the
amis.csvdata set.library(tidyverse)amis_path <- file.path("..", "datasets", "amis.csv") amis <- read_csv(amis_path, col_types = cols())Warning: 8440 parsing failures. row col expected actual file 3 -- 1 columns 2 columns '../datasets/amis.csv' 9 -- 1 columns 3 columns '../datasets/amis.csv' 10 -- 1 columns 5 columns '../datasets/amis.csv' 11 -- 1 columns 5 columns '../datasets/amis.csv' 12 -- 1 columns 5 columns '../datasets/amis.csv' ... ... ......... ......... ...................... See problems(...) for more details.Are there any rows that need to be ignored in the amis data set? If so, modify your import to account for them.
head(amis)# A tibble: 6 x 1 speed <chr> 1 Speeds of cars (in miles per hour). 2 period 3 A numeric column indicating the time that the reading was taken. A value~ 4 warning 5 A numeric column indicating whether the location of the reading was chos~ 6 pairThere are 11 rows that do not contain either data or column names in the file.
amis <- read_csv(amis_path, skip = 11, col_types = cols())Warning: Missing column names filled in: 'X1' [1]Are there any special symbols that need to be set to missing in the
amisdata set? If so, modify your import to account for them.glimpse(amis)Observations: 8,437 Variables: 5 $ X1 <dbl> 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16,... $ speed <dbl> 26, 26, 26, 26, 27, 28, 28, 28, 28, 29, 29, 29, 29, 29... $ period <dbl> 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, ... $ warning <dbl> 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, ... $ pair <dbl> 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, ...There does not appear to be any missing identifiers in the data set.
Import the
mifem.csvdata set.mifem_path <- file.path("..", "datasets", "mifem.csv") mifem <- read_csv(mifem_path, col_types = cols())Warning: Missing column names filled in: 'X1' [1]Is there any meta data at the top or bottom of the
mifemdata set? You will need to determine how to view the bottom of a data set. If so, modify your import to account for them.head(mifem)# A tibble: 6 x 11 X1 outcome age yronset premi smstat diabetes highbp hichol angina <dbl> <chr> <dbl> <dbl> <chr> <chr> <chr> <chr> <chr> <chr> 1 1 live 63 85 n x n y y n 2 6 live 55 85 n c n y y n 3 8 live 68 85 y nk nk y nk y 4 10 live 64 85 n x n y n y 5 11 dead 67 85 n nk nk nk nk nk 6 15 live 66 85 n x nk nk nk nk # ... with 1 more variable: stroke <chr>tail(mifem)# A tibble: 6 x 11 X1 outcome age yronset premi smstat diabetes highbp hichol angina <dbl> <chr> <dbl> <dbl> <chr> <chr> <chr> <chr> <chr> <chr> 1 6345 live 65 93 n n n y n n 2 6347 live 69 93 n x n y nk n 3 6359 live 54 93 n n n y y n 4 6360 live 64 93 n n n y y n 5 6361 live 36 93 n c n n y n 6 6366 live 65 93 n n n n nk n # ... with 1 more variable: stroke <chr>There does not appear to be any meta data at the top or bottom of the data frame.
Are there any special symbols that need to be set to missing in the
mifemdata set? If so, modify your import to account for them.glimpse(mifem)Observations: 1,295 Variables: 11 $ X1 <dbl> 1, 6, 8, 10, 11, 15, 21, 22, 23, 28, 36, 40, 41, 43, ... $ outcome <chr> "live", "live", "live", "live", "dead", "live", "live... $ age <dbl> 63, 55, 68, 64, 67, 66, 63, 68, 46, 66, 59, 63, 55, 5... $ yronset <dbl> 85, 85, 85, 85, 85, 85, 85, 85, 85, 85, 85, 85, 85, 8... $ premi <chr> "n", "n", "y", "n", "n", "n", "n", "y", "n", "y", "n"... $ smstat <chr> "x", "c", "nk", "x", "nk", "x", "n", "n", "c", "c", "... $ diabetes <chr> "n", "n", "nk", "n", "nk", "nk", "n", "n", "n", "n", ... $ highbp <chr> "y", "y", "y", "y", "nk", "nk", "y", "y", "y", "y", "... $ hichol <chr> "y", "y", "nk", "n", "nk", "nk", "n", "y", "nk", "n",... $ angina <chr> "n", "n", "y", "y", "nk", "nk", "n", "y", "nk", "n", ... $ stroke <chr> "n", "n", "n", "n", "nk", "nk", "n", "y", "n", "y", "...There are values of
nkin several of the variables. The data descriptions do not identify any other indicator for missing.mifem <- read_csv(mifem_path, na = c("", "NA", "nk"), col_types = cols())Warning: Missing column names filled in: 'X1' [1]glimpse(mifem)Observations: 1,295 Variables: 11 $ X1 <dbl> 1, 6, 8, 10, 11, 15, 21, 22, 23, 28, 36, 40, 41, 43, ... $ outcome <chr> "live", "live", "live", "live", "dead", "live", "live... $ age <dbl> 63, 55, 68, 64, 67, 66, 63, 68, 46, 66, 59, 63, 55, 5... $ yronset <dbl> 85, 85, 85, 85, 85, 85, 85, 85, 85, 85, 85, 85, 85, 8... $ premi <chr> "n", "n", "y", "n", "n", "n", "n", "y", "n", "y", "n"... $ smstat <chr> "x", "c", NA, "x", NA, "x", "n", "n", "c", "c", "c", ... $ diabetes <chr> "n", "n", NA, "n", NA, NA, "n", "n", "n", "n", "n", "... $ highbp <chr> "y", "y", "y", "y", NA, NA, "y", "y", "y", "y", "y", ... $ hichol <chr> "y", "y", NA, "n", NA, NA, "n", "y", NA, "n", "n", "y... $ angina <chr> "n", "n", "y", "y", NA, NA, "n", "y", NA, "n", "n", "... $ stroke <chr> "n", "n", "n", "n", NA, NA, "n", "y", "n", "y", "n", ...