Pedestrian counts in Melbourne city

A dataset containing the pedestrian counts at hourly intervals from 2016-01-01 to 2017-04-20 at 7 sensors in the city of Melbourne. The variables are as follows:

hourly_peds

Format

A tibble with 78755 rows and 9 variables:

Date_Time

Date time when the pedestrian counts are recorded

Year

Year associated with Date_Time

Month

Month associated with Date_Time

Mdate

Day of month associated with Date_Time

Day

Weekday associated with Date_Time

Time

Hour associated with Date_Time

Sensor_ID

Sensor identifiers

Sensor_Name

Sensor names

Hourly_Counts

Hourly pedestrian counts

Examples

hourly_peds
#> # A tibble: 78,755 x 10
#>    Date_Time           Date        Year Month Mdate Day    Time Sensor_ID
#>    <dttm>              <date>     <dbl> <ord> <dbl> <ord> <dbl>     <dbl>
#>  1 2016-01-01 00:00:00 2016-01-01  2016 Janu…     1 Frid…     0        18
#>  2 2016-01-01 00:00:00 2016-01-01  2016 Janu…     1 Frid…     0        13
#>  3 2016-01-01 00:00:00 2016-01-01  2016 Janu…     1 Frid…     0         3
#>  4 2016-01-01 00:00:00 2016-01-01  2016 Janu…     1 Frid…     0         9
#>  5 2016-01-01 00:00:00 2016-01-01  2016 Janu…     1 Frid…     0         6
#>  6 2016-01-01 00:00:00 2016-01-01  2016 Janu…     1 Frid…     0        25
#>  7 2016-01-01 00:00:00 2016-01-01  2016 Janu…     1 Frid…     0        30
#>  8 2016-01-01 01:00:00 2016-01-01  2016 Janu…     1 Frid…     1        18
#>  9 2016-01-01 01:00:00 2016-01-01  2016 Janu…     1 Frid…     1        13
#> 10 2016-01-01 01:00:00 2016-01-01  2016 Janu…     1 Frid…     1         3
#> # … with 78,745 more rows, and 2 more variables: Sensor_Name <chr>,
#> #   Hourly_Counts <dbl>