Applied Supervised Learning with R by Karthik Ramasubramanian and Jojo Moolayil

Author:Karthik Ramasubramanian and Jojo Moolayil
Language: eng
Format: epub
Publisher: Packt Publishing Pvt. Ltd.
Published: 2019-05-30T00:00:00+00:00

Reduce the number of distinct locations in the variable. This can be done by tagging all the locations that are not a part of the location_list list as Others:df_new$new_location <- factor(ifelse(df_new$Location %in% location_list,df_new$Location,"Others"))

Delete the old Location variable using the following command:df_new$Location <- NULL

To ensure that the fifth step was correctly performed, we can create a temporary DataFrame and summarize the frequency of records against the new location variable we created:temp <- df_new %>% mutate(loc = as.character(new_location)) %>% group_by(as.character(loc)) %>% summarise(Rain = sum(ifelse(RainTomorrow =="Yes",1,0)), cnt=n()) %>% mutate(pct = Rain/cnt) %>% arrange(desc(pct))

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