import_capl_data | R Documentation |
This function imports CAPL-2 data from an Excel workbook on a local computer.
import_capl_data(file_path = NA, sheet_name = NA)
file_path |
A character vector representing the file path to an Excel workbook on the user's local computer (e.g., "c:/users/user_name/desktop/file.xlsx"). The file path is not case-sensitive. |
sheet_name |
An optional character vector representing the sheet to import from the Excel workbook. If this argument is not set, the first sheet in the workbook will be imported. |
Other capl
functions called by this function include: validate_character()
.
Returns a data frame if the Excel workbook sheet is successfully imported.
capl_demo_data <- import_capl_data( file_path = "c:/users/joel/desktop/capl_demo_data.xlsx", sheet_name = "Sheet1" ) str(capl_demo_data) # tibble [500 x 60] (S3: tbl_df/tbl/data.frame) # $ age : num [1:500] 8 9 9 8 12 10 12 10 12 9 ... # $ gender : chr [1:500] "Male" "Female" "Male" "f" ... # $ pacer_lap_distance : num [1:500] 15 20 20 15 20 15 15 15 15 NA ... # $ pacer_laps : num [1:500] 23 31 169 50 63 15 32 143 43 182 ... # $ plank_time : num [1:500] 274 282 9 228 252 110 21 185 6 41 ... # $ camsa_skill_score1 : num [1:500] 14 5 6 13 2 9 4 11 5 11 ... # $ camsa_time1 : num [1:500] 34 27 13 35 21 NA NA 16 20 14 ... # $ camsa_skill_score2 : num [1:500] 14 5 13 11 14 14 0 4 0 4 ... # $ camsa_time2 : num [1:500] 35 23 14 35 23 23 33 30 29 18 ... # $ steps1 : num [1:500] 30627 27788 8457 8769 14169 ... # $ time_on1 : chr [1:500] "5:13am" "6:13" "6:07" "6:13" ... # $ time_off1 : chr [1:500] "22:00" NA "21:00" "22:00" ... # $ non_wear_time1 : num [1:500] 25 31 33 25 83 67 20 10 49 64 ... # $ steps2 : num [1:500] 14905 24750 30111 21077 15786 ... # $ time_on2 : chr [1:500] "06:00" "5:13am" "6:13" "6:13" ... # $ time_off2 : chr [1:500] "21:00" "23:00" "11:13pm" "23:00" ... # $ non_wear_time2 : num [1:500] 20 82 4 55 1 53 65 47 82 79 ... # $ steps3 : num [1:500] 21972 15827 14130 13132 18022 ... # $ time_on3 : chr [1:500] "07:00" "05:00" "07:48am" NA ... # $ time_off3 : chr [1:500] "11:57pm" NA "08:30pm" NA ... # $ non_wear_time3 : num [1:500] 6 79 23 65 34 15 72 76 60 40 ... # $ steps4 : num [1:500] 28084 27369 14315 9963 6993 ... # $ time_on4 : chr [1:500] "05:00" "6:13" "6:07" NA ... # $ time_off4 : chr [1:500] "08:30pm" "10:57 pm" "22:00" "11:13pm" ... # $ non_wear_time4 : num [1:500] 32 38 74 20 75 22 84 59 42 22 ... # $ steps5 : num [1:500] 14858 21112 16880 11707 20917 ... # $ time_on5 : chr [1:500] "6:07" "6:13" "06:00" "05:00" ... # $ time_off5 : chr [1:500] "11:57pm" "23:00" "8:17pm" "8:17pm" ... # $ non_wear_time5 : num [1:500] 61 64 73 23 82 42 66 38 55 18 ... # $ steps6 : num [1:500] 17705 5564 16459 12235 27766 ... # $ time_on6 : chr [1:500] "06:00" "06:00" NA "6:07" ... # $ time_off6 : chr [1:500] "21:00" NA "10:57 pm" "08:30pm" ... # $ non_wear_time6 : num [1:500] 33 24 89 8 27 56 66 21 14 7 ... # $ steps7 : num [1:500] 11067 13540 12106 18795 15039 ... # $ time_on7 : chr [1:500] "6:07" "6:07" "8:00am" "06:00" ... # $ time_off7 : chr [1:500] "08:30pm" "11:13pm" "8:17pm" "10:57 pm" ... # $ non_wear_time7 : num [1:500] 8 72 4 38 9 32 49 36 34 43 ... # $ self_report_pa : num [1:500] NA 2 2 4 3 5 NA 7 6 7 ... # $ csappa1 : num [1:500] 1 2 4 2 2 2 3 2 2 3 ... # $ csappa2 : num [1:500] 3 2 1 1 1 1 4 1 4 3 ... # $ csappa3 : num [1:500] 2 3 2 1 NA 1 3 3 4 4 ... # $ csappa4 : num [1:500] 4 1 1 3 4 4 4 4 4 1 ... # $ csappa5 : num [1:500] 4 2 3 2 1 2 2 2 4 1 ... # $ csappa6 : num [1:500] 3 4 1 4 2 2 2 3 4 4 ... # $ why_active1 : num [1:500] 4 3 5 3 1 5 4 1 1 2 ... # $ why_active2 : num [1:500] 5 3 4 2 5 3 5 NA 5 NA ... # $ why_active3 : num [1:500] 3 3 1 4 2 3 4 4 5 3 ... # $ feelings_about_pa1 : num [1:500] 4 3 2 2 1 1 3 4 4 2 ... # $ feelings_about_pa2 : num [1:500] 5 2 2 3 4 2 4 4 2 5 ... # $ feelings_about_pa3 : num [1:500] 2 5 2 5 3 2 2 1 3 5 ... # $ pa_guideline : num [1:500] 2 3 4 1 2 4 3 2 2 2 ... # $ crf_means : num [1:500] 1 4 4 2 2 1 2 1 4 1 ... # $ ms_means : num [1:500] 3 2 1 2 3 1 1 2 4 2 ... # $ sports_skill : num [1:500] 2 4 4 1 3 1 3 1 4 3 ... # $ pa_is : num [1:500] 10 1 1 1 1 1 2 1 3 1 ... # $ pa_is_also : num [1:500] 5 1 4 4 1 7 2 7 2 8 ... # $ improve : num [1:500] 3 3 9 3 9 9 3 3 3 6 ... # $ increase : num [1:500] 2 8 3 8 8 1 3 3 8 8 ... # $ when_cooling_down : num [1:500] 4 2 4 2 2 2 2 5 2 2 ... # $ heart_rate : num [1:500] 5 6 4 4 4 9 4 8 7 4 ...
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