Fix countmostfrequentcontact bug
parent
c1e25ac1ad
commit
cf272793a2
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@ -1,7 +1,10 @@
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filter_by_day_segment <- function(data, day_segment) {
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filter_by_day_segment <- function(data, day_segment) {
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if(day_segment %in% c("morning", "afternoon", "evening", "night"))
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if(day_segment %in% c("morning", "afternoon", "evening", "night"))
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data <- data %>% filter(local_day_segment == day_segment)
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data <- data %>% filter(local_day_segment == day_segment)
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return(data)
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else if(day_segment == "daily")
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return(data)
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else
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return(data %>% head(0))
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}
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}
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base_sms_features <- function(sms, sms_type, day_segment, requested_features){
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base_sms_features <- function(sms, sms_type, day_segment, requested_features){
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@ -15,7 +18,7 @@ base_sms_features <- function(sms, sms_type, day_segment, requested_features){
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features_to_compute <- intersect(base_features_names, requested_features)
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features_to_compute <- intersect(base_features_names, requested_features)
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# Filter rows that belong to the sms type and day segment of interest
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# Filter rows that belong to the sms type and day segment of interest
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sms <- sms %>% filter(message_type == ifelse(sms_type == "received", "1", "2")) %>%
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sms <- sms %>% filter(message_type == ifelse(sms_type == "received", "1", ifelse(sms_type == "sent", 2, NA))) %>%
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filter_by_day_segment(day_segment)
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filter_by_day_segment(day_segment)
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# If there are not features or data to work with, return an empty df with appropiate columns names
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# If there are not features or data to work with, return an empty df with appropiate columns names
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@ -33,7 +36,7 @@ base_sms_features <- function(sms, sms_type, day_segment, requested_features){
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filter(N == max(N)) %>%
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filter(N == max(N)) %>%
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head(1) %>% # if there are multiple contacts with the same amount of messages pick the first one only
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head(1) %>% # if there are multiple contacts with the same amount of messages pick the first one only
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group_by(local_date) %>%
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group_by(local_date) %>%
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summarise(!!paste("sms", sms_type, day_segment, feature_name, sep = "_") := n()) %>%
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summarise(!!paste("sms", sms_type, day_segment, feature_name, sep = "_") := N) %>%
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replace(is.na(.), 0)
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replace(is.na(.), 0)
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features <- merge(features, feature, by="local_date", all = TRUE)
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features <- merge(features, feature, by="local_date", all = TRUE)
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