In Westat-Transportation/summarizeNHTS: National Household Travel Survey R Analysis Toolkit

Load NHTS tool

library(summarizeNHTS)

Bring a copy or download dataset

download_nhts_data("2009", "C:/NHTS")

# > You are about to download large data files to the directory below. Continue? (y/n):
# > C:/NHTS/csv/2009

Initialize dataset

# unwanted because of how noisy it appears in output
options("datatable.showProgress"=FALSE)

dataset <- read_data("2009", csv_path = "C:/NHTS")

---

Organize Questions

• What does the sample look like?
• How often are people travelling? How far?
• When are people travelling? Where? Why?
• Are there differences by categorical characteristics?
• ... and on and on

Review data documentation

• Makes lists of variables to support analyses
• Categorize and organize
• ... and on and on

Resources

• Data Documentation
• This File's Code

---

Start summarizing...

Annual Vehicle Mileage Accrual

statistic <- summarize_data(
    data = dataset,
    agg = 'avg',
    agg_var = "ANNMILES",
    subset = "(VEHAGE > 0 & VEHAGE < 11) & (ANNMILES > 500 & ANNMILES < 200000)"
)

statistic

Annual Vehicle Mileage Accrual by Vehicle Age

statistic <- summarize_data(
    data = dataset,
    agg = 'avg',
    agg_var = "ANNMILES",
    by = c("VEHAGE"),
    label = TRUE,
    subset = "(VEHAGE > 0 & VEHAGE < 11) & (ANNMILES > 500 & ANNMILES < 200000)"
)

make_table(statistic)

make_chart(statistic)

Household Size by Number of Vehicles

dataset$data$household$HHSIZE <- ifelse(dataset$data$household$HHSIZE > 3, "4+", dataset$data$household$HHSIZE)
dataset$data$household$HHVEHCNT <- ifelse(dataset$data$household$HHVEHCNT > 3, "4+", dataset$data$household$HHVEHCNT)

statistic <- summarize_data(
    data = dataset,
    agg = "household_count",
    label = TRUE,
    by = c("HHSIZE","HHVEHCNT")
)

make_table(statistic, digits = 0)

make_chart(statistic, digits = 0)

Querying at the Trip Level

Average Distance Travelled to Work

Table

stash_WHYTO <- dataset$data$trip$WHYTO
dataset$data$trip$WHYTO <- ifelse(!dataset$data$trip$WHYTO %in% c("-1","-7","-8","-9","11","12"), "Not to Work", dataset$data$trip$WHYTO)
dataset$data$trip$WHYTO <- ifelse(dataset$data$trip$WHYTO == "11", "To Work", dataset$data$trip$WHYTO)

statistic <- summarize_data(
    data = dataset,
    agg = "avg",
    agg_var = c("TRPMILES"),
    by = c("WHYTO"),
    subset = "!WHYTO %in% c('-1','-7','-8','-9','12') & (TRPMILES > 0 & TRPMILES < 200)"
)

make_table(statistic)

Bar Chart

make_chart(statistic)
```
```r
dataset$data$trip$WHYTO <- stash_WHYTO
```
</div>
</div>

<br>

<br>

## Average Dwell Time by Trip Purpose (TRIPPURP)
```r

statistic <- summarize_data(
    data = dataset,
    agg = "avg",
    agg_var = c("DWELTIME"),
    by = c("TRIPPURP"),
    subset = "(!TRIPPURP %in% c('-9'))"
)

make_chart(statistic, order=T, digits=0)

```

<br>

## Average Dwell Time by Trip Purpose (WHYTO)
```r
codebook_2009$values[codebook_2009$values$NAME=="WHYTO"]$LABEL <- substr(codebook_2009$values[codebook_2009$values$NAME=="WHYTO"]$LABEL, 0, 22)
```
```r

statistic <- summarize_data(
    data = dataset,
    agg = "avg",
    agg_var = c("DWELTIME"),
    by = c("WHYTO"),
    subset = "(!WHYTO %in% c('-9','-8','-7','-1','01','10','12'))"
)

make_chart(statistic, order=T, digits=0)

```

```r
library(data.table)
dataset$data$trip[, STRTTIME := substring(sprintf("%s04d", STRTTIME), 0, 2)]
```

<br>

<br>

## Trip Frequency by Start Hour
```r

statistic <- summarize_data(
    data = dataset,
    agg = "trip_count",
    by = c("STRTTIME"),
    subset = "STRTTIME != '00'",
    exclude_missing = TRUE
)

make_chart(statistic, digits=0)

```

<br>

### Big numbers! We can also specify that we want to compute as proportion.
### Trip Frequency over Start Hour
```r

statistic <- summarize_data(
    data = dataset,
    agg = "trip_count",
    by = c("STRTTIME"),
    prop = TRUE,
    subset = "STRTTIME != '00'",
    exclude_missing = TRUE
)

make_chart(statistic)

```

<br>

### Trip Frequency over Start Hour of Full Time Workers
```r

statistic <- summarize_data(
    data = dataset,
    agg = "trip_count",
    by = c("STRTTIME"),
    prop = TRUE,
    subset = "STRTTIME != '00' & WORKER == '01' & WKFTPT == '01'",
    exclude_missing = TRUE

)

make_chart(statistic, digits=0)

```

<br>

<br>

# Trip Rates!

<br>

## Daily Person Trips by Age
```r
library(data.table)
stash_R_AGE <- dataset$data$person$R_AGE
class(dataset$data$person$R_AGE) <- "character"
dataset$data$person[R_AGE %in% as.character(5:14), R_AGE := "05 to 14"]
dataset$data$person[R_AGE %in% as.character(15:19), R_AGE := "15 to 19"]
dataset$data$person[R_AGE %in% as.character(20:24), R_AGE := "20 to 24"]
dataset$data$person[R_AGE %in% as.character(25:29), R_AGE := "25 to 29"]
dataset$data$person[R_AGE %in% as.character(30:34), R_AGE := "30 to 34"]
dataset$data$person[R_AGE %in% as.character(35:39), R_AGE := "35 to 39"]
dataset$data$person[R_AGE %in% as.character(40:44), R_AGE := "40 to 44"]
dataset$data$person[R_AGE %in% as.character(45:49), R_AGE := "45 to 49"]
dataset$data$person[R_AGE %in% as.character(50:54), R_AGE := "50 to 54"]
dataset$data$person[R_AGE %in% as.character(55:59), R_AGE := "55 to 59"]
dataset$data$person[R_AGE %in% as.character(60:64), R_AGE := "60 to 64"]
dataset$data$person[R_AGE %in% as.character(65:69), R_AGE := "65 to 69"]
dataset$data$person[R_AGE %in% as.character(70:74), R_AGE := "70 to 74"]
dataset$data$person[R_AGE %in% as.character(75:79), R_AGE := "75 to 79"]
dataset$data$person[R_AGE %in% as.character(80:84), R_AGE := "80 to 84"]
dataset$data$person[R_AGE %in% as.character(85:99), R_AGE := "85 +"]
```
```r
statistic <- summarize_data(
    data = dataset,
    agg = "person_trip_rate",
    by = c("R_AGE")
)

make_table(statistic)

make_chart(statistic)

```
```r
dataset$data$person$R_AGE <- stash_R_AGE
```

<br>

<br>

<div class = "row">
<div class = "col-md-6">
## Daily Person Trips by Driver Status
```r

statistic <- summarize_data(
    data = dataset,
    agg = "person_trip_rate",
    by = c("DRIVER"),
    subset = "DRIVER %in% c('01','02') & R_AGE > 18"
)

make_chart(statistic)

```
</div>
<div class = "col-md-6">
## And by Worker Status
```r

statistic <- summarize_data(
    data = dataset,
    agg = "person_trip_rate",
    by = c("DRIVER", "WORKER"),
    subset = "DRIVER %in% c('01','02') & WORKER %in% c('01','02') & R_AGE > 18"
)

make_chart(statistic)

```
</div>
</div>

<br>

### Daily Person Trips by Travel Day Public Transit Usage
```r

statistic <- summarize_data(
    data = dataset,
    agg = "person_trip_rate",
    by = c("USEPUBTR"),
    subset = "DRIVER %in% c('01','02') & R_AGE > 18 & USEPUBTR %in% c('01','02')"
)

make_chart(statistic)

```

<br>

## Daily Person Trips by Day of Week
```r

statistic <- summarize_data(
    data = dataset,
    agg = "person_trip_rate",
    by = c("TRAVDAY")
)

make_chart(statistic)

```

<br>

## Daily Person Trips by Day of Week and Worker Status
```r

statistic <- summarize_data(
    data = dataset,
    agg = "person_trip_rate",
    by = c("TRAVDAY","WORKER"),
    subset = "WORKER %in% c('01','02') & R_AGE > 18"
)

make_chart(statistic, x = "TRAVDAY")

```

<br>

## Daily Person Trips by Day of Week and Previous Week's Primary Activity
````r
# nhts_2009$labels$DESCRIPTION <- gsub("Temporarily absent from a job or business", "Temp w/o job", nhts_2009$labels$DESCRIPTION)
# nhts_2009$labels$DESCRIPTION <- gsub("Doing something else", "Something else", nhts_2009$labels$DESCRIPTION)

statistic <- summarize_data(
    data = dataset,
    agg = "person_trip_rate",
    by = c("TRAVDAY","PRMACT"),
    subset = "PRMACT %in% c('01','04','06')"
)

make_chart(statistic, x = "TRAVDAY")

Household Trip Rates

statistic <- summarize_data(
    data = dataset,
    agg = "household_trip_rate"
)

statistic

---

Daily Person Trips per Household by Household Size

statistic <- summarize_data(
    data = dataset,
    agg = "household_trip_rate",
    by = c("HHSIZE"),
    label = FALSE
)

make_chart(statistic)

Trip Rate Maps

Daily Person Trips by State

statistic <- summarize_data(
    data = dataset,
    agg = "person_trip_rate",
    label = FALSE,
    by = "HHSTFIPS"
)

make_map(statistic)

Tilemaps!

make_map(statistic, state_style="tile")

Daily Person Trips by State Where Household Income < 25,000

statistic <- summarize_data(
    data = dataset,
    agg = "person_trip_rate",
    by = c("HHSTFIPS"),
    label = FALSE,
    subset = "HHFAMINC %in% c('01','02','03','04','05')"
)

make_map(statistic)

make_map(statistic, state_style = "tile")

## Younger Age Group By State wzxhzdk:19

## Older Age Group By State wzxhzdk:20

Metro Geographies Supported Too (where available)

Daily Person Trip Rates by Core Based Statistical Area

statistic <- summarize_data(
    data = dataset,
    agg = "person_trip_rate",
    by = c("HH_CBSA"),
    label = FALSE
)

make_map(statistic)

Westat-Transportation/summarizeNHTS documentation built on May 17, 2020, 8:57 p.m.

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