In this exercise, we will be using the nyc_jan_xdf data from prior exercises. If you need to re-load the data, run the following code:

input_csv <- 'yellow_tripsample_2016-01.csv'
input_xdf <- 'yellow_tripsample_2016-01.xdf'
rxImport(input_csv, input_xdf, overwrite = TRUE)

nyc_jan_xdf <- RxXdfData(input_xdf)

(1) Use rxDataStep along with the rowSelection argument to select the subset of rows with trip_distance greater than some threshold. The threshold is determined by a global variable called dist_threshold set below. Leave out the outFile argument so our result goes into a data.frame (which we call nyc_long_trips_df). We can hard-code this easily if the threshold is fixed, but letting a global variable decide the threshold makes the code more dynamic. Here's a hint: In order to pass a global R object to rowSelection, we need to use the transformObjects argument.

dist_threshold <- 5 # a neighborhood of our choosing

nyc_long_trips_df <- rxDataStep(nyc_jan_xdf
    ## you code goes here

(2) How many rows do you have in the resulting subset nyc_long_trips_df?

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