K Cluster Method


#1

Please I keep getting this error :

> cluster_up <- kmeans(customer_data, 3, iter.max = 10)
Error in do_one(nmeth) : NA/NaN/Inf in foreign function call (arg 1)
In addition: Warning message:
In storage.mode(x) <- "double" : NAs introduced by coercion

The code I am tring to run is

 View(customer_data)
str(customer_data)

cluster_up <- kmeans(customer_data, 3, iter.max = 10)

#data cleaning

del_vars <- names(customer_data) %in% c("job", "marital", "education", "default", "housing", "loan", "contact", "month", "poutcome")
customer_data_num <- customer_data[!del_vars]
customer_data_num <- na.omit(customer_dat_num)
customer_data_num <- scale(customer_dat_num)
View(customer_dat_num)


#k-means clusterig
cluster_up <- kmeans(customer_dat_num, 3, iter.max = 5)
str(cluster_up)

Please assist


#2

Could you please turn this into a self-contained reprex (short for reproducible example)? It will help us help you if we can be sure we're all working with/looking at the same stuff.

install.reprex("reprex")

If you've never heard of a reprex before, you might want to start by reading the tidyverse.org help page. The reprex dos and don'ts are also useful.

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reprex::reprex(input = "fruits_stringdist.R", outfile = "fruits_stringdist.md")

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