A data frame with information about traveling to work by respondents to the survey
Source:R/bSantiago-package.R
Santiago_TW.RdA dataset containing information about traveling to work users of active and motorized modes of transportation in Santiago sourced from 2016 survey.
Usage
data(Santiago_TW)Details
@format A data frame with 451 rows and 7 variables:
- ID
Unique identifier of respondent
- TW_JobAccess
How much do respondents think their access to the transport network has affected their chances of having a better job?; this variable is an ordered factor with five levels, "NO IMPACT", "MINOR IMPACT", "SOME IMPACT", "MODERATE IMPACT", "MAJOR IMPACT"
- TW_Job_Opportunity
How do respondents assess the job opportunities available in their commune of residence?; this variable is an ordered factor with five levels, "POOR", "FAIR", "GOOD", "VERY GOOD", "EXCELLENT"
- TW_Interested_Access
What level of access to employment are respondents interested in having in their commune of residence?; this variable is an ordered factor with five levels, "POOR", "FAIR", "GOOD", "VERY GOOD", "EXCELLENT"
- TW_Jobsatisfaction
How satisfied are respondents with their current job?; this variable is an ordered factor with five levels, "NOT SATISFIED", "LOW SATISFIED", "MEDIUM SATISFIED", "HIGH SATIAFIED", "VHIGH SATISFIED"
- TW_Commute_duration
How long is your regular commuting?; this variable is an ordered factor with four levels, "0-20 min", "20-40 min", "40-60 min", "1h and more"
- TW_Commute_schedule
What is the frequent time of their commuting?; this variable is an ordered factor with six levels, "7:00 - 9:00", "9:00 - 13:00", "13:00 - 15:00", "15:00 - 18:00", "18:00 - 21:00", "Others"
- TW_Commute_monthlycost
Monthly expenditure on transport; this variable is an ordered factor with four levels, "Less than 35.000", "35.000-75.000", "75.000-125.000", "More than 125.000"
Examples
data(Santiago_TW)
r8A_ACCESSJOB <- Santiago_TW$r8A_ACCESSJOB
#> Warning: Unknown or uninitialised column: `r8A_ACCESSJOB`.