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Change SMS first and last metrics from hours to minutes

pull/95/head
JulioV 2020-05-29 13:28:39 -04:00
parent f344c14e92
commit c1e25ac1ad
2 changed files with 4 additions and 4 deletions
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4
docs/features/extracted.rst
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@ -108,8 +108,8 @@ Name Units Description
========================= ========= ============= ========================= ========= =============
count SMS Number of SMS of type ``sms_type`` that occurred during a particular ``day_segment``. count SMS Number of SMS of type ``sms_type`` that occurred during a particular ``day_segment``.
distinctcontacts contacts Number of distinct contacts that are associated with a particular ``sms_type`` during a particular ``day_segment``. distinctcontacts contacts Number of distinct contacts that are associated with a particular ``sms_type`` during a particular ``day_segment``.
timefirstsms hours Number of hours between 12:00am (midnight) and the first ``SMS`` of a particular ``sms_type``. timefirstsms minutes Number of minutes between 12:00am (midnight) and the first ``SMS`` of a particular ``sms_type``.
timelastsms hours Number of hours between 12:00am (midnight) and the last ``SMS`` of a particular ``sms_type``. timelastsms minutes Number of minutes between 12:00am (midnight) and the last ``SMS`` of a particular ``sms_type``.
countmostfrequentcontact SMS Number of ``SMS`` messages from the contact with the most messages of ``sms_type`` during a ``day_segment`` throughout the whole dataset of each participant. countmostfrequentcontact SMS Number of ``SMS`` messages from the contact with the most messages of ``sms_type`` during a ``day_segment`` throughout the whole dataset of each participant.
========================= ========= ============= ========================= ========= =============

4
src/features/sms/sms_base.R
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@ -44,8 +44,8 @@ base_sms_features <- function(sms, sms_type, day_segment, requested_features){
feature <- switch(feature_name, feature <- switch(feature_name,
"count" = feature %>% summarise(!!paste("sms", sms_type, day_segment, feature_name, sep = "_") := n()), "count" = feature %>% summarise(!!paste("sms", sms_type, day_segment, feature_name, sep = "_") := n()),
"distinctcontacts" = feature %>% summarise(!!paste("sms", sms_type, day_segment, feature_name, sep = "_") := n_distinct(trace)), "distinctcontacts" = feature %>% summarise(!!paste("sms", sms_type, day_segment, feature_name, sep = "_") := n_distinct(trace)),
"timefirstsms" = feature %>% summarise(!!paste("sms", sms_type, day_segment, feature_name, sep = "_") := first(local_hour) + (first(local_minute)/60)), "timefirstsms" = feature %>% summarise(!!paste("sms", sms_type, day_segment, feature_name, sep = "_") := first(local_hour) * 60 + first(local_minute)),
"timelastsms" = feature %>% summarise(!!paste("sms", sms_type, day_segment, feature_name, sep = "_") := last(local_hour) + (last(local_minute)/60))) "timelastsms" = feature %>% summarise(!!paste("sms", sms_type, day_segment, feature_name, sep = "_") := last(local_hour) * 60 + last(local_minute)))
features <- merge(features, feature, by="local_date", all = TRUE) features <- merge(features, feature, by="local_date", all = TRUE)
} }