Keep track of warning messages.

These are not runtime errors, but might still indicate a problem.

problems/app_categories.txt

@@ -0,0 +1,33 @@
+Warning: 1241 parsing failures.
+row           col   expected actual                                                                            file
+  1 is_system_app an integer  TRUE  'data/raw/p011/phone_applications_foreground_with_datetime_with_categories.csv'
+  2 is_system_app an integer  FALSE 'data/raw/p011/phone_applications_foreground_with_datetime_with_categories.csv'
+  3 is_system_app an integer  TRUE  'data/raw/p011/phone_applications_foreground_with_datetime_with_categories.csv'
+  4 is_system_app an integer  TRUE  'data/raw/p011/phone_applications_foreground_with_datetime_with_categories.csv'
+  5 is_system_app an integer  TRUE  'data/raw/p011/phone_applications_foreground_with_datetime_with_categories.csv'
+... ............. .......... ...... ...............................................................................
+See problems(...) for more details.
+
+Warning message:
+The following named parsers don't match the column names: application_name
+Error: Problem with `filter()` input `..1`.
+✖ object 'application_name' not found
+ℹ Input `..1` is `!is.na(application_name)`.
+Backtrace:
+     █
+  1. ├─`%>%`(...)
+  2. ├─dplyr::mutate(...)
+  3. ├─utils::head(., -1)
+  4. ├─dplyr::select(., -c("timestamp"))
+  5. ├─dplyr::filter(., !is.na(application_name))
+  6. ├─dplyr:::filter.data.frame(., !is.na(application_name))
+  7. │ └─dplyr:::filter_rows(.data, ...)
+  8. │   ├─base::withCallingHandlers(...)
+  9. │   └─mask$eval_all_filter(dots, env_filter)
+ 10. └─base::.handleSimpleError(...)
+ 11.   └─dplyr:::h(simpleError(msg, call))
+Execution halted
+[Mon Dec 13 17:19:06 2021]
+Error in rule app_episodes:
+    jobid: 54
+    output: data/interim/p011/phone_app_episodes.csv

problems/locations_barnett.txt

@@ -0,0 +1,5 @@
+Warning message:
+In barnett_daily_features(snakemake) :
+  Barnett's location features cannot be computed for data or time segments that do not span one or more entire days (00:00:00 to 23:59:59). Values below point to the problem:
+Location data rows within a daily time segment: 0
+Location data time span in days: 398.6