General purpose data filtering for pat time series objects

A generalized data filter for pat objects to choose rows/cases where conditions are true. Multiple conditions are combined with & or separated by a comma. Only rows where the condition evaluates to TRUE are kept. Rows where the condition evaluates to NA are dropped.

If an empty pat object is passed in, it is immediately returned, allowing for multiple filtering steps to be piped together and only checking for an empty pat object at the end of the pipeline.

pat_filter(pat, ...)

Arguments

pat

pat object.

...

Logical predicates defined in terms of the variables in pat$data.

Value

A subset of the incoming pat time series object. (A list with meta and data dataframes.)

Note

Filtering is done on values in pat$data.

See also

pat_filterDate

pat_filterDatetime

Examples

library(AirSensor2)

# Unhealthy values
example_pat %>%
  pat_filter(pm2.5_atm_a > 25, pm2.5_atm_b > 25) %>%
  pat_getData() %>%
  head()
#> # A tibble: 6 × 13
#>   datetime            hardware   firmware_version  rssi uptime pa_latency memory
#>   <dttm>              <chr>                 <dbl> <dbl>  <dbl>      <dbl>  <dbl>
#> 1 2024-03-02 03:16:44 2.0+OPENL…             7.02   -84 2.01e6        850  15744
#> 2 2024-03-02 03:18:42 2.0+OPENL…             7.02   -85 2.01e6       2480  15576
#> 3 2024-03-02 03:20:45 2.0+OPENL…             7.02   -83 2.01e6        517  15744
#> 4 2024-03-02 03:22:43 2.0+OPENL…             7.02   -82 2.01e6       3815  15576
#> 5 2024-03-02 03:24:42 2.0+OPENL…             7.02   -83 2.01e6       1253  15576
#> 6 2024-03-02 03:26:42 2.0+OPENL…             7.02   -82 2.01e6        674  15576
#> # ℹ 6 more variables: humidity <dbl>, temperature <dbl>, pressure <dbl>,
#> #   pm2.5_atm <dbl>, pm2.5_atm_a <dbl>, pm2.5_atm_b <dbl>