# Loading .csv into a DataFrame with missing insertion and column-type correction (one-linerish)

**URL:** <https://discourse.julialang.org/t/loading-csv-into-a-dataframe-with-missing-insertion-and-column-type-correction-one-linerish/60088>\
**Category:** Data\
**Tags:** dataframes, csv\
**Created:** [April 27, 2021, 8:35am UTC](https://discourse.julialang.org/t/loading-csv-into-a-dataframe-with-missing-insertion-and-column-type-correction-one-linerish/60088 "2021-04-27T08:35:46Z")\
**Posts on this page:** 2\
**Page:** 1

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**Author:** ![egolep](https://sea2.discourse-cdn.com/julialang/user_avatar/discourse.julialang.org/egolep/32/23498_2.png) [@egolep](https://discourse.julialang.org/u/egolep)\
**Post date:** [April 27, 2021, 8:35am UTC](https://discourse.julialang.org/t/loading-csv-into-a-dataframe-with-missing-insertion-and-column-type-correction-one-linerish/60088/1 "2021-04-27T08:35:47Z")

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Hi,  
forgive me if the question is trivial or if there have been similar or identical questions already answered, but I’ve not been able to find them.  
I have to load a .csv file into a DataFrame, but the file contains “NA” for missing values, so a lot of Int or Float columns are detected as String.  
I then used allowmissing(), replaced the “NA” values with the recode() function but now I’m left with having to re-type all the mistyped columns from String to the correct numerical type.  
Since my solution seems pretty ugly and cumbersome for such a trivial task (allowmissing + recode + go through the DataFrame to see mistyped columns + manually retype any of them) I was wondering if there is a standard solution since this is a quite common (while infamous) task.

I stepped into this problem while converting and old script from Python. Using Pandas, the “NA” are automatically treated as NaN, so the columns are still interpreted as numerical type columns.

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**Author:** ![egolep](https://sea2.discourse-cdn.com/julialang/user_avatar/discourse.julialang.org/egolep/32/23498_2.png) [@egolep](https://discourse.julialang.org/u/egolep)\
**Post date:** [April 27, 2021, 9:02am UTC](https://discourse.julialang.org/t/loading-csv-into-a-dataframe-with-missing-insertion-and-column-type-correction-one-linerish/60088/2 "2021-04-27T09:02:36Z")

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I finally found the missingstring and missingstrings parameters for CSV.File

It completely solves the problem with:

df = CSV.File(“filename.csv”, missingstring=“NA”) |\> DataFrame

if there are more than one string replacing the missing values, it’s:

df = CSV.File(“filename.csv”, missingstrings=[“string1”, “string2”) |\> DataFrame

hope this can help someone else coming from Python