Here is the file in reprex. The thing is, I seemed to connect to the csv file if I'm not mistaken, in normal coding efforts, and successfully created a str(BankCustomer) profile.
When I tried to convert to factors, the program seemed to register the BankCustomer1 profile, but nothign changed in the data structure. Here is the code in reprex, and the results from which it was taken in regular code. I do that, because ti looks like the results are different.
First the reprex:
BankCustomer <- read.csv("Demo 1_ Identifying Data Structures.csv")
#> Warning in file(file, "rt"): cannot open file 'Demo 1_ Identifying Data
#> Structures.csv': No such file or directory
#> Error in file(file, "rt"): cannot open the connection
getwd()
#> [1] "C:/Users/Administrator/AppData/Local/Temp/RtmpqYfUnp/reprex-22808bf25f4-bad-grub"
View(BankCustomer)
#> Error in as.data.frame(x): object 'BankCustomer' not found
str(BankCustomer)
#> Error in str(BankCustomer): object 'BankCustomer' not found
BankCustomer1 <- read.csv("Demo 1_ Identifying Data Structures.csv",stringsAsFactors=FALSE)
#> Warning in file(file, "rt"): cannot open file 'Demo 1_ Identifying Data
#> Structures.csv': No such file or directory
#> Error in file(file, "rt"): cannot open the connection
str(BankCustomer1)
#> Error in str(BankCustomer1): object 'BankCustomer1' not found
as.factor(BankCustomer1)
#> Error in is.factor(x): object 'BankCustomer1' not found
str(BankCustomer1)
#> Error in str(BankCustomer1): object 'BankCustomer1' not found
Created on 2021-08-05 by the reprex package (v2.0.0)
Now the file as I originally wrote it:
BankCustomer <- read.csv("Demo 1_ Identifying Data Structures.csv")
getwd()
View(BankCustomer)
str(BankCustomer)
BankCustomer1 <- read.csv("Demo 1_ Identifying Data Structures.csv",stringsAsFactors=FALSE)
str(BankCustomer1)
as.factor(BankCustomer1)
str(BankCustomer1)
and the output of the (two) str statements are the same...
str(BankCustomer)
'data.frame': 4521 obs. of 15 variables:
$ ï..age : int 30 33 35 30 59 35 36 39 41 43 ...
$ job : chr "unemployed" "services" "management" "management" ...
$ marital : chr "married" "married" "single" "married" ...
$ education: chr "primary" "secondary" "tertiary" "tertiary" ...
$ default : chr "no" "no" "no" "no" ...
$ housing : chr "no" "yes" "yes" "yes" ...
$ loan : chr "no" "yes" "no" "yes" ...
$ contact : chr "cellular" "cellular" "cellular" "unknown" ...
$ month : chr "oct" "may" "apr" "jun" ...
$ day : int 19 11 16 3 5 23 14 6 14 17 ...
$ duration : int 79 220 185 199 226 141 341 151 57 313 ...
$ campaign : int 1 1 1 4 1 2 1 2 2 1 ...
$ pdays : int -1 339 330 -1 -1 176 330 -1 -1 147 ...
$ previous : int 0 4 1 0 0 3 2 0 0 2 ...
$ poutcome : chr "unknown" "failure" "failure" "unknown" ...
> BankCustomer1 <- read.csv("Demo 1_ Identifying Data Structures.csv",stringsAsFactors=FALSE)
> str(BankCustomer1)
'data.frame': 4521 obs. of 15 variables:
$ ï..age : int 30 33 35 30 59 35 36 39 41 43 ...
$ job : chr "unemployed" "services" "management" "management" ...
$ marital : chr "married" "married" "single" "married" ...
$ education: chr "primary" "secondary" "tertiary" "tertiary" ...
$ default : chr "no" "no" "no" "no" ...
$ housing : chr "no" "yes" "yes" "yes" ...
$ loan : chr "no" "yes" "no" "yes" ...
$ contact : chr "cellular" "cellular" "cellular" "unknown" ...
$ month : chr "oct" "may" "apr" "jun" ...
$ day : int 19 11 16 3 5 23 14 6 14 17 ...
$ duration : int 79 220 185 199 226 141 341 151 57 313 ...
$ campaign : int 1 1 1 4 1 2 1 2 2 1 ...
$ pdays : int -1 339 330 -1 -1 176 330 -1 -1 147 ...
$ previous : int 0 4 1 0 0 3 2 0 0 2 ...
$ poutcome : chr "unknown" "failure" "failure" "unknown" ...
>
> as.factor(Bomer1)
Error in is.factor(x) : object 'Bomer1' not found
> str(BankCustomer1)
'data.frame': 4521 obs. of 15 variables:
$ ï..age : int 30 33 35 30 59 35 36 39 41 43 ...
$ job : chr "unemployed" "services" "management" "management" ...
$ marital : chr "married" "married" "single" "married" ...
$ education: chr "primary" "secondary" "tertiary" "tertiary" ...
$ default : chr "no" "no" "no" "no" ...
$ housing : chr "no" "yes" "yes" "yes" ...
$ loan : chr "no" "yes" "no" "yes" ...
$ contact : chr "cellular" "cellular" "cellular" "unknown" ...
$ month : chr "oct" "may" "apr" "jun" ...
$ day : int 19 11 16 3 5 23 14 6 14 17 ...
$ duration : int 79 220 185 199 226 141 341 151 57 313 ...
$ campaign : int 1 1 1 4 1 2 1 2 2 1 ...
$ pdays : int -1 339 330 -1 -1 176 330 -1 -1 147 ...
$ previous : int 0 4 1 0 0 3 2 0 0 2 ...
$ poutcome : chr "unknown" "failure" "failure" "unknown" ...
> as.factor(BankCustomer1)