# Converting a Matrix to a DataFrame

**URL:** <https://discourse.julialang.org/t/converting-a-matrix-to-a-dataframe/6114>\
**Category:** Data\
**Tags:** question\
**Created:** [September 27, 2017, 2:19pm UTC](https://discourse.julialang.org/t/converting-a-matrix-to-a-dataframe/6114 "2017-09-27T14:19:44Z")\
**Posts on this page:** 5\
**Page:** 1

<div class="post-metadata">

**Author:** ![sylvaticus](https://sea2.discourse-cdn.com/julialang/user_avatar/discourse.julialang.org/sylvaticus/32/203883_2.png) [@sylvaticus](https://discourse.julialang.org/u/sylvaticus)\
**Post date:** [September 27, 2017, 2:19pm UTC](https://discourse.julialang.org/t/converting-a-matrix-to-a-dataframe/6114/1 "2017-09-27T14:19:44Z")

</div>

I am struggling to convert a Matrix where I have the first row as header and possible NA values in a DataFrame.

Actually I did find at least two ways, and the resulting df seems ok, but in reality the individual columns are either `Vector` or `SubArray`, instead of `DataArray`, and this then cause me problems when I try to operate on them (e.g. to remove the NA with dropna() )

So, this is my code:

```julia
using DataFrames, DataFramesMeta

# Original data in Matrix format..
m = ["A" "B" "C"
     1 10 100;
     nothing nothing nothing;
     3 30 300;
     4 40 400]
# Converting to Dataframe..
h = [Symbol(c) for c in m[1,:]]
vals = m[2:end, :]
vals2 = [vals[:,c] for c in 1:size(vals)[2]]
df1 = DataFrame(vals2, h)
# alternative that produce subarrays: df = DataFrame(Any[@view m[2:end, i] for i::Int64 in 1:size(m, 2)], Symbol.(m[1, :]))
# Cleaning to get NA values..
for row in eachrow(df1)
  for name in names(df1)
    if row[name] == nothing
        row[name] = NA
    end
  end
end

```

Now, the problem is the type of dataframe columns, as they are Vectors:

```julia
typeof(df1[:A])
Array{Any,1}

```

And some functions don’t work with them:

```julia
dropna(df1[:A])
4-element Array{Any,1}:
 1  
  NA
 3  
 4

```

For comparison, when I create a df by scratch:

```julia
df2 = DataFrame(
    A = [1, 2, 3, 4],
    B = [10, 20, 30, 40]
)
df2[2,:A] = NA 
df2[2,:B] = NA

```

The type is a DataArray and dropna() works without problems:

```julia
typeof(df2[:A])
DataArrays.DataArray{Int64,1}
dropna(df2[:A])
3-element Array{Int64,1}:
 1
 3
 4

```

---

<div class="post-metadata">

**Author:** ![sylvaticus](https://sea2.discourse-cdn.com/julialang/user_avatar/discourse.julialang.org/sylvaticus/32/203883_2.png) [@sylvaticus](https://discourse.julialang.org/u/sylvaticus)\
**Post date:** [September 27, 2017, 2:33pm UTC](https://discourse.julialang.org/t/converting-a-matrix-to-a-dataframe/6114/2 "2017-09-27T14:33:09Z")

</div>

I solved with:

```julia
matnms2df(mat, headerstrs) = convert(DataFrame,
     Dict(zip(headerstrs,[mat[:,i] for i in 1:size(mat,2)])))
df4 = matnms2df(vals,h)
for row in eachrow(df4)
  for name in names(df4)
    if row[name] == nothing
        row[name] = NA
    end
  end
end
typeof(df4[:A])
DataArrays.DataArray{Any,1}

```

(from [Convert Julia array to dataframe - Stack Overflow](https://stackoverflow.com/a/27284301/1586860))

Still I don’t understand why if you construct the DataFrame in a different way than using a Dict the type of the columns change.

---

<div class="post-metadata">

**Author:** ![hasanOryx](https://sea2.discourse-cdn.com/julialang/user_avatar/discourse.julialang.org/hasanoryx/32/5373_2.png) [@hasanOryx](https://discourse.julialang.org/u/hasanOryx)\
**Post date:** [September 8, 2019, 12:02pm UTC](https://discourse.julialang.org/t/converting-a-matrix-to-a-dataframe/6114/3 "2019-09-08T12:02:49Z")

</div>

Thanks for sharing your solution.

---

<div class="post-metadata">

**Author:** ![anon92994695](https://avatars.discourse-cdn.com/v4/letter/a/ce7236/32.png) [@anon92994695](https://discourse.julialang.org/u/anon92994695)\
**Post date:** [September 8, 2019, 12:44pm UTC](https://discourse.julialang.org/t/converting-a-matrix-to-a-dataframe/6114/4 "2019-09-08T12:44:30Z")

</div>

Can I ask how you ended up in a situation where you have a string/float mixed type array in the first place?

Typically you don’t want to do that, having strings in an otherwise numerical array like that breaks a lot of functionality. Here’s my work around for this…

```julia
using DataFrames
m = ["A" "B" "C"
     1 10 100;
     nothing nothing nothing;
     3 30 300;
     4 40 400]
m[m .== nothing] .= missing
Names = m[1,:]
Numbers = m[2:end,:]

newdf = convert(DataFrame, Numbers);
rename!(newdf, names(newdf) .=> Symbol.(Names[:]))

dropmissing(newdf)

```

---

<div class="post-metadata">

**Author:** ![nalimilan](https://sea2.discourse-cdn.com/julialang/user_avatar/discourse.julialang.org/nalimilan/32/147_2.png) [@nalimilan](https://discourse.julialang.org/u/nalimilan)\
**Post date:** [September 8, 2019, 4:05pm UTC](https://discourse.julialang.org/t/converting-a-matrix-to-a-dataframe/6114/5 "2019-09-08T16:05:14Z")

</div>

Note that your code will create a very inefficient data frame since its columns will have element type `Any`. Here’s an alternative:

```julia
DataFrame([something.(col, missing) for col in eachcol(m[2:end, :])], Symbol.(m[1, :]))

```

Or slightly more efficient (by avoiding an intermediate copy of the data):

```julia
DataFrame([something.(@view(m[2:end, i]), missing) for i in 1:size(m, 2)], Symbol.(m[1, :]))

```