Hi,
I have 3 arrays with which I´d like to make a dataframe where each column corresponds to an array ( column 1 = abc, column 2 = def, column 3 = ghi) and the column names to the names of the arrays. I tried hcat but I get an error because my arrays don`t have the same length.
abc = [6,7,8,9,10]
def = [“a”,“b”,“c”]
ghi = [87]
Does anyone have any ideas ?
Thank you,
The DataFrames.jl documentation is really good, please read it when you find some time.
This should work fine:
DataFrame(abc=abc, def=def, ghi=ghi)
That won’t work, as OP said this will raise an error:
julia> DataFrame(abc = abc, def = def)
ERROR: DimensionMismatch("column :abc has length 5 and column :def has length 3")
This is just how DataFrames works - columns have to be the same length. You need to ask yourself:
Is a DataFrame the right structure for my data? Why do I want to use a DataFrame if the columns aren’t the same length?
If the answer to (1) is yes I really want a DataFrame, what should be stored in shorter columns in those rows for which information in the longer columns is available? To make it concrete, your table looks like this:
| abc | def | ghi |
|---|---|---|
| 6 | “a” | 87 |
| 7 | “b” | ? |
| 8 | “c” | ? |
| 9 | ? | ? |
What’s in those question marks? If there’s no natural correspondence between the value of abc and ghi in a given row, then maybe a DataFrame just isn’t the right storage format for your data.
Thank you @nilshg I did read the first part of his question and skipped the details. Didn’t notice the columns of different size.
@jnewbie what would you expect as the result when columns have different size?
The ? could be replaced “missing”. I need to make that DataFrame so it can be exported as a CSV file for a purpose outside of Julia.
| abc | def | ghi |
|---|---|---|
| 6 | “a” | 87 |
| 7 | “b” | mssing |
| 8 | “c” | missing |
| 9 | missing | missing |
I would like to get this if it is possible.
You could do:
julia> DataFrame(abc = abc,
def = [def; fill(missing, df_length-length(def))],
ghi = [ghi; fill(missing, df_length-length(ghi))])
5×3 DataFrame
Row │ abc def ghi
│ Int64 String? Int64?
─────┼─────────────────────────
1 │ 6 a 87
2 │ 7 b missing
3 │ 8 c missing
4 │ 9 missing missing
5 │ 10 missing missing
With
df_length=maximum(length.([abc,def,ghi]))
for example 
DataFrame(abc = [abc; fill(missing, df_length-length(abc))],
def = [def; fill(missing, df_length-length(def))],
ghi = [ghi; fill(missing, df_length-length(ghi))])
is a bit more generic, if abc isn’t the longest one.
But it’s a great one-liner!
I don’t show you mine 
it works, thanks !
Thanks !
Another option using LazyStack.jl:
DataFrame(rstack(abc, def, ghi, fill=missing), [:abc, :def, :ghi])
Another option using PaddedViews.jl:
n = maximum(length.((abc, def, ghi)))
abc, def, ghi = PaddedView.(missing, (abc,def,ghi), Ref((n,)), Ref((1,)))
df = DataFrame(abc=abc, def=def, ghi=ghi)