📂Julia

Removing Missing Values in DataFrames in Julia

Overview ¹

In Julia, you can easily remove missing values using the dropmissing() function.

Code

julia> df = DataFrame(x = ["i", missing, "k", "j"], y = [1, 2, 3, missing])
4×2 DataFrame
 Row │ x        y       
     │ String?  Int64?  
─────┼──────────────────
   1 │ i              1
   2 │ missing        2
   3 │ k              3
   4 │ j        missing 

Suppose we have a dataframe with missing values missing as shown above.

julia> dropmissing(df, :x)
3×2 DataFrame
 Row │ x       y       
     │ String  Int64?  
─────┼─────────────────
   1 │ i             1
   2 │ k             3
   3 │ j       missing 

julia> dropmissing(df, :y)
3×2 DataFrame
 Row │ x        y     
     │ String?  Int64 
─────┼────────────────
   1 │ i            1
   2 │ missing      2
   3 │ k            3

To remove missing values from the column you want, just put the symbol of the column as an argument.

julia> dropmissing(df)
2×2 DataFrame
 Row │ x       y     
     │ String  Int64
─────┼───────────────
   1 │ i           1
   2 │ k           3

If you want to remove all missing values from the entire dataframe, you don’t need to input any column.

Full Code

using DataFrames

df = DataFrame(x = ["i", missing, "k", "j"], y = [1, 2, 3, missing])

dropmissing(df, :x)
dropmissing(df, :y)
dropmissing(df)

Environment

• OS: Windows
• julia: v1.7.3