[R] Help needed in data cleaning

[Jim Lemon]

Hi Nash,
If I understand your question correctly, you want the "mice" package.
Hopefully you have more data than your example.

Jim


On Sat, Dec 19, 2015 at 6:14 AM, Web Web <webweb8537 at gmail.com> wrote:

> Hello,
>            I need some help in data cleaning using R. my CSV file looks as
> follows.
>
>
> "id","gender","age","category1","category2","category3","category4","category5","category6","category7","category8","category9","category10"1,"Male",22,"movies","music","travel","cloths","grocery",,,,,2,"Male",28,"travel","books","movies",,,,,,,3,"Female",27,"rent","fuel","grocery","cloths",,,,,,4,"Female",22,"rent","grocery","travel","movies","cloths",,,,,5,"Female",22,"rent","online-shopping","utiliy",,,,,,,
>
> I need to reformat as follows.
>
> id gender age category            rank1 Male    22  movies
>   11 Male    22  music                21 Male    22  travel
>    31 Male    22  cloths               41 Male    22  grocery
>     51 Male    22  books                NA1 Male    22  rent
>       NA1 Male    22  fuel                 NA1 Male    22  utility
>          NA1 Male    22  online-shopping      NA
> ...................................5 Female    22  movies
> NA5 Female    22  music              NA5 Female    22  travel
>    NA5 Female    22  cloths             NA5 Female    22  grocery
>       NA5 Female    22  books              NA5 Female    22  rent
>          15 Female    22  fuel               NA5 Female    22  utility
>            NA5 Female    22  online-shopping    2
>
> So far My efforts are as follows.
>
> mini <- read.csv("~/MS/coding/mini.csv", header=FALSE)
> mini_clean <- mini[-1,]
> df_mini <- melt(df_clean, id.vars=c("V1","V2","V3"))
> sqldf('select * from df_mini order by  "V1"')
>
> Now I want to know what is the best way to fill all missing categories for
> all users.
>
> Thanks
> Nash
>
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