# Quick DataFrame question: I am trying to read CSVs that, for some reason, have pos

**URL:** <https://discourse.julialang.org/t/quick-dataframe-question-i-am-trying-to-read-csvs-that-for-some-reason-have-pos/55404>\
**Category:** General Usage\
**Created:** [February 16, 2021, 4:49pm UTC](https://discourse.julialang.org/t/quick-dataframe-question-i-am-trying-to-read-csvs-that-for-some-reason-have-pos/55404 "2021-02-16T16:49:26Z")\
**Posts on this page:** 2\
**Page:** 1

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**Post date:** [February 16, 2021, 4:49pm UTC](https://discourse.julialang.org/t/quick-dataframe-question-i-am-trying-to-read-csvs-that-for-some-reason-have-pos/55404/1 "2021-02-16T16:49:26Z")

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quick DataFrame question: I am trying to read CSVs that, for some reason, have possibly many columns of missing data at the end. The columns are entirely missing.

Is there something similar to dropmissing that operates on columns?

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**Author:** ![pdeffebach](https://sea2.discourse-cdn.com/julialang/user_avatar/discourse.julialang.org/pdeffebach/32/10320_2.png) [@pdeffebach](https://discourse.julialang.org/u/pdeffebach)\
**Post date:** [February 16, 2021, 6:22pm UTC](https://discourse.julialang.org/t/quick-dataframe-question-i-am-trying-to-read-csvs-that-for-some-reason-have-pos/55404/2 "2021-02-16T18:22:17Z")

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There are a few options here.

```julia
select(df, Not(names(df, Missing))

```

```julia
df[:, eltype.(eachcol(df)) .!= Missing]

```

If you want to use this solution in the context of piping one solution is

```julia
@chain df begin 
    select(_, Not(names(_, Missing))
end

```