# How to get one dataframe from many dataframes in Julia (cf. rbindlist in R)
**URL:** https://discourse.julialang.org/t/how-to-get-one-dataframe-from-many-dataframes-in-julia-cf-rbindlist-in-r/84456
**Category:** New to Julia
**Tags:** dataframes, community
**Created:** [July 19, 2022, 12:36pm UTC](https://discourse.julialang.org/t/how-to-get-one-dataframe-from-many-dataframes-in-julia-cf-rbindlist-in-r/84456 "2022-07-19T12:36:51Z")
**Posts on this page:** 8
**Page:** 1
### Author:  [@bertlhf](https://discourse.julialang.org/u/bertlhf)
#### Post date: [July 19, 2022, 12:36pm UTC](https://discourse.julialang.org/t/how-to-get-one-dataframe-from-many-dataframes-in-julia-cf-rbindlist-in-r/84456/1 "2022-07-19T12:36:51Z")
Below schematically how I’m doing this in R. How can I (Julia newby) do this in Julia
```nohighlight
# file abc.R
df <- rbindlist(list(df,
data.frame(A = "abc1", B = 1),
data.frame(A = "abc2", B = 2)))
# file bcd.R
df <- rbindlist(list(df,
data.frame(A = "bcd1", B = 1),
data.frame(A = "bcd2", B = 2)))
# file df.R
source("abc.R")
source("bcd.R")
# R repl
source("df.R")
# dataframe df
# A B
# abc1 1
# abc2 2
# bcd1 1
# bcd2 2
```
---
### Author:  [@nilshg](https://discourse.julialang.org/u/nilshg)
#### Post date: [July 19, 2022, 12:56pm UTC](https://discourse.julialang.org/t/how-to-get-one-dataframe-from-many-dataframes-in-julia-cf-rbindlist-in-r/84456/2 "2022-07-19T12:56:52Z")
```julia
julia> df1 = DataFrame(A = ["abc1", "abc2"], B = 1:2)
2×2 DataFrame
Row │ A B
│ String Int64
─────┼───────────────
1 │ abc1 1
2 │ abc2 2
julia> df2 = DataFrame(A = ["bcd1", "bcd2"], B = 1:2)
2×2 DataFrame
Row │ A B
│ String Int64
─────┼───────────────
1 │ bcd1 1
2 │ bcd2 2
julia> vcat(df1, df2)
4×2 DataFrame
Row │ A B
│ String Int64
─────┼───────────────
1 │ abc1 1
2 │ abc2 2
3 │ bcd1 1
4 │ bcd2 2
```
If you have a vector of many DataFrames do:
```julia
julia> reduce(vcat, [df1, df2])
4×2 DataFrame
Row │ A B
│ String Int64
─────┼───────────────
1 │ abc1 1
2 │ abc2 2
3 │ bcd1 1
4 │ bcd2 2
```
---
### Author:  [@bertlhf](https://discourse.julialang.org/u/bertlhf)
#### Post date: [July 19, 2022, 1:32pm UTC](https://discourse.julialang.org/t/how-to-get-one-dataframe-from-many-dataframes-in-julia-cf-rbindlist-in-r/84456/3 "2022-07-19T13:32:08Z")
> [@nilshg](#):
>
> `df1 = DataFrame(A = ["abc1", "abc2"], B = 1:2)`
Thanks for your quick reply and solution! I have two points to this.
1. I want to have the dataframe input in “row format”, eg. DataFrame(A = “abc1”, B = 1), DataFrame(A = “abc2”, B = 2). This is easier and more intuitive for an enduser. You see this in my R example above.
2. I only want to define a name for the final dataframe (in my R example “df”). I don’t want to give names to intermediate dataframes (in your solution “df1” and “df2”) since I have many thousands of them in my R application.
Can these points be satisfied in a Julia solution?
---
### Author:  [@nilshg](https://discourse.julialang.org/u/nilshg)
#### Post date: [July 19, 2022, 1:48pm UTC](https://discourse.julialang.org/t/how-to-get-one-dataframe-from-many-dataframes-in-julia-cf-rbindlist-in-r/84456/4 "2022-07-19T13:48:40Z")
Yes you can simply `push!` a tuple onto an existing DataFrame:
```julia
julia> push!(df, ("cde1", 1))
5×2 DataFrame
Row │ A B
│ String Int64
─────┼───────────────
1 │ abc1 1
2 │ abc2 2
3 │ bcd1 1
4 │ bcd2 2
5 │ cde1 1
```
or if you want column names so as not to rely on the ordering of fields in the tuple, you can use a `NamedTuple`:
```julia
julia> push!(df, (B = 3, A = "cde1"))
6×2 DataFrame
Row │ A B
│ String Int64
─────┼───────────────
1 │ abc1 1
2 │ abc2 2
3 │ bcd1 1
4 │ bcd2 2
5 │ cde1 1
6 │ cde1 3
```
---
### Author:  [@bertlhf](https://discourse.julialang.org/u/bertlhf)
#### Post date: [July 19, 2022, 2:05pm UTC](https://discourse.julialang.org/t/how-to-get-one-dataframe-from-many-dataframes-in-julia-cf-rbindlist-in-r/84456/5 "2022-07-19T14:05:48Z")
Thanks, I think this is what I was looking for. I will try this out. I’m very curious about the performance comparison R-Julia for this functionality.
---
### Author:  [@bkamins](https://discourse.julialang.org/u/bkamins)
#### Post date: [July 19, 2022, 8:14pm UTC](https://discourse.julialang.org/t/how-to-get-one-dataframe-from-many-dataframes-in-julia-cf-rbindlist-in-r/84456/6 "2022-07-19T20:14:21Z")
If you `push!` it is faster to use `Tuple` rather than `NamedTuple` as then column names are not checked.
---
### Author:  [@bertlhf](https://discourse.julialang.org/u/bertlhf)
#### Post date: [July 28, 2022, 7:27am UTC](https://discourse.julialang.org/t/how-to-get-one-dataframe-from-many-dataframes-in-julia-cf-rbindlist-in-r/84456/7 "2022-07-28T07:27:16Z")
- Based upon the tips I got from this thread, I tried out Julia dataframes and compared it with my R dataframes-with-rbindlist application.
- I want to give feedback on the result here.
- A little script was used to convert the R data source files to .jl files, at present 9749 files covering 102433 rows with 6 columns.
- A first conclusion is that both solutions are about equally fast in loading the data: 28.3 sec (R) vs 26.5 sec (Julia).
- At a later moment I want to benchmark the queries on the data and report on that as well.
- At present my lack of knowledge of the Julia query commands causes a delay.
- I have a feeling, based on a few small trials, that here Julia will have a better performance.
## R
```julia-auto
> tb_load()
user system elapsed
28.303 1.984 31.529
> nrow(triple)
[1] 102433
> names(triple)
[1] "SUBJECT" "PRIMES" "PREDICATE" "PRIMEP" "OBJECT" "PRIMEO"
> tb_count_out()
Triples: 102433, entities: 36750, pairs: 10076, files: 9749
```
## Julia
```julia-auto
julia> tb_load()
26.549103 seconds (7.53 M allocations: 372.071 MiB, 0.60% gc time)
102433×6 DataFrame
julia> nrow(triple)
102433
julia> names(triple)
6-element Vector{String}:
"SUBJECT"
"PRIMES"
"PREDICATE"
"PRIMEP"
"OBJECT"
"PRIMEO"
```
---
### Author:  [@nilshg](https://discourse.julialang.org/u/nilshg)
#### Post date: [July 28, 2022, 3:30pm UTC](https://discourse.julialang.org/t/how-to-get-one-dataframe-from-many-dataframes-in-julia-cf-rbindlist-in-r/84456/8 "2022-07-28T15:30:16Z")
People on here are generally very helpful to provide help with optimizing code for speed, so if you can create a minimal working example (i.e. a bit of code that generates the files you’re reading in with dummy data, and produces the data set you’re looking to produce) you’ll probably get helpful comments on it.