# \[ANN\] A new lightning fast package for data manipulation in pure Julia

**URL:** <https://discourse.julialang.org/t/ann-a-new-lightning-fast-package-for-data-manipulation-in-pure-julia/78197>\
**Category:** Package Announcements\
**Tags:** data, dataframes, inmemorydatasets\
**Created:** [March 21, 2022, 7:35am UTC](https://discourse.julialang.org/t/ann-a-new-lightning-fast-package-for-data-manipulation-in-pure-julia/78197 "2022-03-21T07:35:42Z")\
**Posts on this page:** 20\
**Page:** 2

<div class="post-metadata">

**Author:** ![Ronis\_BR](https://sea2.discourse-cdn.com/julialang/user_avatar/discourse.julialang.org/ronis_br/32/50999_2.png) [@Ronis\_BR](https://discourse.julialang.org/u/Ronis_BR)\
**Post date:** [March 21, 2022, 11:21pm UTC](https://discourse.julialang.org/t/ann-a-new-lightning-fast-package-for-data-manipulation-in-pure-julia/78197/21 "2022-03-21T23:21:44Z")

</div>

Congratulations @sl-solution ! It seems a very good package 🙂

Btw, I saw you are using PrettyTables.jl to print the data! Please, feel free to ping me if you need some feature or, specially, if I break something 😃 PrettyTables.jl is passing for a huge rewrite that will greatly increase its performance (time to print the first table is down by almost 50%). I am trying as hard as I can to avoid breaking changes, but it can happen. I will remember to check the interoperability with your package before I release v2.0.

I think the new release will fix this problem in your comments:

```julia
    # Print the table with the selected options.
    # currently pretty_table is very slow for large tables, the workaround is to use only few rows

```

Of course it will always be slow when printing the entire very big table. But it should now be very fast printing any table when cropping is enabled:

```nohighlight
julia> A = rand(1_000_000, 1_000);

julia> @time pretty_table(A)
┌───────────┬──────────┬────────────┬────────────┬───────────┬──────────┬───────────┬───────────┬──────────┬───────────┬──────
│ Col. 1 │ Col. 2 │ Col. 3 │ Col. 4 │ Col. 5 │ Col. 6 │ Col. 7 │ Col. 8 │ Col. 9 │ Col. 10 │ C ⋯
├───────────┼──────────┼────────────┼────────────┼───────────┼──────────┼───────────┼───────────┼──────────┼───────────┼──────
│ 0.675934 │ 0.221392 │ 0.859381 │ 0.00201495 │ 0.656669 │ 0.419674 │ 0.116045 │ 0.555897 │ 0.189247 │ 0.552384 │ 0. ⋯
│ 0.61972 │ 0.964157 │ 0.543965 │ 0.0924698 │ 0.408849 │ 0.22149 │ 0.801567 │ 0.273067 │ 0.185251 │ 0.670841 │ 0. ⋯
│ 0.0341166 │ 0.550614 │ 0.62682 │ 0.0991155 │ 0.435398 │ 0.676617 │ 0.109501 │ 0.620581 │ 0.92127 │ 0.560164 │ 0. ⋯
│ 0.86105 │ 0.587744 │ 0.25295 │ 0.342427 │ 0.602571 │ 0.524927 │ 0.893778 │ 0.925155 │ 0.571104 │ 0.736807 │ 0.0 ⋯
│ 0.435085 │ 0.178483 │ 0.596313 │ 0.488782 │ 0.104792 │ 0.994904 │ 0.08668 │ 0.302552 │ 0.099019 │ 0.448827 │ 0 ⋯
│ 0.658401 │ 0.106824 │ 0.00276253 │ 0.447873 │ 0.0350634 │ 0.800669 │ 0.215574 │ 0.375465 │ 0.11485 │ 0.661147 │ 0. ⋯
│ 0.815405 │ 0.22639 │ 0.585754 │ 0.129567 │ 0.0261965 │ 0.58881 │ 0.575382 │ 0.811007 │ 0.380854 │ 0.890361 │ ⋯
│ 0.0420148 │ 0.917764 │ 0.621537 │ 0.605215 │ 0.0492217 │ 0.182624 │ 0.370627 │ 0.226672 │ 0.597551 │ 0.387021 │ 0. ⋯
│ ⋮ │ ⋮ │ ⋮ │ ⋮ │ ⋮ │ ⋮ │ ⋮ │ ⋮ │ ⋮ │ ⋮ │ ⋱
└───────────┴──────────┴────────────┴────────────┴───────────┴──────────┴───────────┴───────────┴──────────┴───────────┴──────
                                                                                           990 columns and 999992 rows omitted
  0.001633 seconds (11.27 k allocations: 568.234 KiB)

julia> @time pretty_table(A, vcrop_mode = :middle)
┌───────────┬──────────┬────────────┬────────────┬───────────┬──────────┬──────────┬──────────┬──────────┬──────────┬─────────
│ Col. 1 │ Col. 2 │ Col. 3 │ Col. 4 │ Col. 5 │ Col. 6 │ Col. 7 │ Col. 8 │ Col. 9 │ Col. 10 │ Col. ⋯
├───────────┼──────────┼────────────┼────────────┼───────────┼──────────┼──────────┼──────────┼──────────┼──────────┼─────────
│ 0.675934 │ 0.221392 │ 0.859381 │ 0.00201495 │ 0.656669 │ 0.419674 │ 0.116045 │ 0.555897 │ 0.189247 │ 0.552384 │ 0.478 ⋯
│ 0.61972 │ 0.964157 │ 0.543965 │ 0.0924698 │ 0.408849 │ 0.22149 │ 0.801567 │ 0.273067 │ 0.185251 │ 0.670841 │ 0.171 ⋯
│ 0.0341166 │ 0.550614 │ 0.62682 │ 0.0991155 │ 0.435398 │ 0.676617 │ 0.109501 │ 0.620581 │ 0.92127 │ 0.560164 │ 0.854 ⋯
│ 0.86105 │ 0.587744 │ 0.25295 │ 0.342427 │ 0.602571 │ 0.524927 │ 0.893778 │ 0.925155 │ 0.571104 │ 0.736807 │ 0.0752 ⋯
│ ⋮ │ ⋮ │ ⋮ │ ⋮ │ ⋮ │ ⋮ │ ⋮ │ ⋮ │ ⋮ │ ⋮ │ ⋮ ⋱
│ 0.874067 │ 0.689295 │ 0.969623 │ 0.940648 │ 0.932225 │ 0.769949 │ 0.394852 │ 0.600234 │ 0.740254 │ 0.36743 │ 0.870 ⋯
│ 0.489394 │ 0.19652 │ 0.881438 │ 0.29382 │ 0.890437 │ 0.330823 │ 0.139547 │ 0.814829 │ 0.769702 │ 0.584777 │ 0.882 ⋯
│ 0.93291 │ 0.204729 │ 0.236622 │ 0.0458418 │ 0.251297 │ 0.815881 │ 0.404949 │ 0.303269 │ 0.749317 │ 0.827221 │ 0.893 ⋯
│ 0.587404 │ 0.911563 │ 0.193175 │ 0.153903 │ 0.638026 │ 0.426905 │ 0.358063 │ 0.860344 │ 0.108626 │ 0.651241 │ 0.444 ⋯
└───────────┴──────────┴────────────┴────────────┴───────────┴──────────┴──────────┴──────────┴──────────┴──────────┴─────────
                                                                                           990 columns and 999992 rows omitted
  0.001556 seconds (11.50 k allocations: 571.672 KiB)

```

(Notice that those are the second run of the command)

---

<div class="post-metadata">

**Author:** ![monopolynomial](https://sea2.discourse-cdn.com/julialang/user_avatar/discourse.julialang.org/monopolynomial/32/34782_2.png) [@monopolynomial](https://discourse.julialang.org/u/monopolynomial)\
**Post date:** [March 22, 2022, 12:03am UTC](https://discourse.julialang.org/t/ann-a-new-lightning-fast-package-for-data-manipulation-in-pure-julia/78197/22 "2022-03-22T00:03:14Z")

</div>

> [@rafael.guerra](#):
>
> > [@monopolynomial](#):
> >
> > As a data scientists I was avoiding `Julia` as the first choice due to the lack of practical data manipulation tool
> 
> What? Could you please ellaborate.

It’s quite a while I am monitoring julia’s dataframes package but anytime I wanted to use it for a project I hit lack-of-features wall. as examples I frequently need to pivot\_long\_to\_wide or visa versa but nothing was available in dataframes. also functionality which I often need is to non-equi join dataframes which it wasn’t there. but I’m happy to see both of them in this announcement. to be frank, for me a practical solution with more features is more important than obsession with speed or abstractness.

---

<div class="post-metadata">

**Author:** ![qsong](https://avatars.discourse-cdn.com/v4/letter/q/d07c76/32.png) [@qsong](https://discourse.julialang.org/u/qsong)\
**Post date:** [March 22, 2022, 12:29am UTC](https://discourse.julialang.org/t/ann-a-new-lightning-fast-package-for-data-manipulation-in-pure-julia/78197/23 "2022-03-22T00:29:17Z")

</div>

Many thanks for the “[home made](https://discourse.julialang.org/t/ann-a-new-lightning-fast-package-for-data-manipulation-in-pure-julia/78197/14)” algo and implementation. IMHO it is good to the community.

Currently no need to worry about changing several Base functions when `missing` involved because given the long time of testing (and discussion etc.) `DataFrames.jl` will still be #1 choice for most (potential) users.

I’ll set aside some free time to learn/test this new package. So thanks again.

---

<div class="post-metadata">

**Author:** ![ericphanson](https://sea2.discourse-cdn.com/julialang/user_avatar/discourse.julialang.org/ericphanson/32/215186_2.png) [@ericphanson](https://discourse.julialang.org/u/ericphanson)\
**Post date:** [March 22, 2022, 1:06am UTC](https://discourse.julialang.org/t/ann-a-new-lightning-fast-package-for-data-manipulation-in-pure-julia/78197/24 "2022-03-22T01:06:06Z")

</div>

> [@qsong](#):
>
> Currently no need to worry about changing several Base functions when `missing` involved because given the long time of testing (and discussion etc.) `DataFrames.jl` will still be #1 choice for most (potential) users.

The main problem with piracy isn’t really that it is surprising to the immediate users, since they can always read the docs (assuming it is mentioned there); the problem is that it is surprising to users _who don’t know they are using the package_ when it is a dependency of a dependency of a dependency etc. Currently, if any package in a user’s full dependency tree uses InMemoryDatasets, then the behavior of Base functions changes everywhere – and they very well might not know they are depending on InMemoryDatasets! (Consider the user who hasn’t seen this Discourse thread, for example). This could cause all sorts of bugs, since other code (and other packages) will expect those functions to not have been pirated. In other words, it’s non-composable.

> [@davidanthoff](#):
>
> If I had my way, I would actually not allow registration of packages that do things like that in the general registry 🙂

I think this makes sense given the wide-ranging consequences of type piracy, especially if we had a reliable and robust check. File an [issue in RegistryCI](https://github.com/JuliaRegistries/RegistryCI.jl/issues)?

---

<div class="post-metadata">

**Author:** ![DataFrames](https://avatars.discourse-cdn.com/v4/letter/d/e19b73/32.png) [@DataFrames](https://discourse.julialang.org/u/DataFrames)\
**Post date:** [March 22, 2022, 3:01am UTC](https://discourse.julialang.org/t/ann-a-new-lightning-fast-package-for-data-manipulation-in-pure-julia/78197/25 "2022-03-22T03:01:59Z")

</div>

A very nice package indeed, congrats!

The `DataFrames.jl` package is one of the few packages in `Julia` that I frequently use, and honestly is the reason that I started using `Julia` in the first place. I am very glad to see now there are two packages in `Julia` that fit my usage.

I occasionally answers questions related to `DataFrames` in this forum and probably I will use your package in future answers when it is appropriate. Actually, right now, I’m reading your rather comprehensive package documentation and simply enjoying it.

I admire your courage to start working on such a general type of package with those many competitors out there.

PS, the benchmarks are outstanding and I want to thank you personally for beating `polars` and `data.table` in one shot!

---

<div class="post-metadata">

**Author:** ![huang\_min](https://sea2.discourse-cdn.com/julialang/user_avatar/discourse.julialang.org/huang_min/32/34337_2.png) [@huang\_min](https://discourse.julialang.org/u/huang_min)\
**Post date:** [March 22, 2022, 4:25am UTC](https://discourse.julialang.org/t/ann-a-new-lightning-fast-package-for-data-manipulation-in-pure-julia/78197/26 "2022-03-22T04:25:46Z")

</div>

I am also reading the documentation now.

I wonder whether there is a benchmark on datasets with around a few thousand rows without multithreading as we are not always with big data. Will there be significant performance deterioration?

Also, is there a way to skip the warning below?

┌ Warning: Julia started with single thread, to enable multithreaded functionalities in InMemoryDatasets.jl start Julia with multiple threads.

---

<div class="post-metadata">

**Author:** ![DataFrames](https://avatars.discourse-cdn.com/v4/letter/d/e19b73/32.png) [@DataFrames](https://discourse.julialang.org/u/DataFrames)\
**Post date:** [March 22, 2022, 5:19am UTC](https://discourse.julialang.org/t/ann-a-new-lightning-fast-package-for-data-manipulation-in-pure-julia/78197/27 "2022-03-22T05:19:42Z")

</div>

> [@huang\_min](#):
>
> Also, is there a way to skip the warning below?
> 
> ┌ Warning: Julia started with single thread, to enable multithreaded functionalities in InMemoryDatasets.jl start Julia with multiple threads.

You can start `Julia` with multiple threads by setting the environmental variable `JULIA_NUM_THREADS`, more on this is available [here](https://docs.julialang.org/en/v1/manual/multi-threading/) and [here](http://stackoverflow.com/questions/52598046/ddg#52598625).

---

<div class="post-metadata">

**Author:** ![huang\_min](https://sea2.discourse-cdn.com/julialang/user_avatar/discourse.julialang.org/huang_min/32/34337_2.png) [@huang\_min](https://discourse.julialang.org/u/huang_min)\
**Post date:** [March 22, 2022, 5:39am UTC](https://discourse.julialang.org/t/ann-a-new-lightning-fast-package-for-data-manipulation-in-pure-julia/78197/28 "2022-03-22T05:39:40Z")

</div>

I mean I normally start with single thread so I do not want to see this warning.

---

<div class="post-metadata">

**Author:** ![huang\_min](https://sea2.discourse-cdn.com/julialang/user_avatar/discourse.julialang.org/huang_min/32/34337_2.png) [@huang\_min](https://discourse.julialang.org/u/huang_min)\
**Post date:** [March 22, 2022, 7:25am UTC](https://discourse.julialang.org/t/ann-a-new-lightning-fast-package-for-data-manipulation-in-pure-julia/78197/29 "2022-03-22T07:25:57Z")

</div>

Just have a try on the example in the documentation but it seems that byrow does not use multithread and has no efficiency gain.

julia\> Threads.nthreads()  
8

julia\> using InMemoryDatasets, BenchmarkTools

julia\> ds = Dataset(rand(10^5, 100), :auto);

julia\> m = Matrix(ds);

julia\> @btime byrow(ds, sum, 1:100);  
22.097 ms (171 allocations: 889.34 KiB)

julia\> @btime sum(m, dims = 2);  
15.696 ms (6 allocations: 879.06 KiB)

julia\> @btime byrow(ds, sum, 1:100, threads = true);  
22.181 ms (168 allocations: 889.17 KiB)

---

<div class="post-metadata">

**Author:** ![sl-solution](https://sea2.discourse-cdn.com/julialang/user_avatar/discourse.julialang.org/sl-solution/32/34759_2.png) [@sl-solution](https://discourse.julialang.org/u/sl-solution)\
**Post date:** [March 22, 2022, 7:44am UTC](https://discourse.julialang.org/t/ann-a-new-lightning-fast-package-for-data-manipulation-in-pure-julia/78197/30 "2022-03-22T07:44:19Z")

</div>

> [@Ronis\_BR](#):
>
> Congratulations @sl-solution ! It seems a very good package 🙂
> 
> Btw, I saw you are using PrettyTables.jl to print the data! Please, feel free to ping me if you need some feature or, specially, if I break something 😃 PrettyTables.jl is passing for a huge rewrite that will greatly increase its performance (time to print the first table is down by almost 50%). I am trying as hard as I can to avoid breaking changes, but it can happen. I will remember to check the interoperability with your package before I release v2.0.
> 
> I think the new release will fix this problem in your comments:
> 
> ```julia
> # Print the table with the selected options.
> # currently pretty_table is very slow for large tables, the workaround is to use only few rows
> 
> ```
> 
> Of course it will always be slow when printing the entire very big table. But it should now be very fast printing any table when cropping is enabled:

Thanks for you support. `PrettyTables.jl` is great! I am looking forward for the next big release. I have just one issue which you may want to help: printing view of a large data set. In current release it is very slow and I ended with a silly way as workaround.

---

<div class="post-metadata">

**Author:** ![sl-solution](https://sea2.discourse-cdn.com/julialang/user_avatar/discourse.julialang.org/sl-solution/32/34759_2.png) [@sl-solution](https://discourse.julialang.org/u/sl-solution)\
**Post date:** [March 22, 2022, 7:51am UTC](https://discourse.julialang.org/t/ann-a-new-lightning-fast-package-for-data-manipulation-in-pure-julia/78197/31 "2022-03-22T07:51:16Z")

</div>

> [@huang\_min](#):
>
> I mean I normally start with single thread so I do not want to see this warning.

I push a commit to the `master` branch. Now you can set environment variable `IMD_WARN_THREADS` to `0` to suppress the warning.

---

<div class="post-metadata">

**Author:** ![sl-solution](https://sea2.discourse-cdn.com/julialang/user_avatar/discourse.julialang.org/sl-solution/32/34759_2.png) [@sl-solution](https://discourse.julialang.org/u/sl-solution)\
**Post date:** [March 22, 2022, 7:52am UTC](https://discourse.julialang.org/t/ann-a-new-lightning-fast-package-for-data-manipulation-in-pure-julia/78197/32 "2022-03-22T07:52:40Z")

</div>

> [@huang\_min](#):
>
> Just have a try on the example in the documentation but it seems that byrow does not use multithread and has no efficiency gain.
> 
> julia\> Threads.nthreads()  
> 8
> 
> julia\> using InMemoryDatasets, BenchmarkTools
> 
> julia\> ds = Dataset(rand(10^5, 100), :auto);
> 
> julia\> m = Matrix(ds);
> 
> julia\> @btime byrow(ds, sum, 1:100);  
> 22.097 ms (171 allocations: 889.34 KiB)
> 
> julia\> @btime sum(m, dims = 2);  
> 15.696 ms (6 allocations: 879.06 KiB)
> 
> julia\> @btime byrow(ds, sum, 1:100, threads = true);  
> 22.181 ms (168 allocations: 889.17 KiB)

This is strange, which OS?

---

<div class="post-metadata">

**Author:** ![huang\_min](https://sea2.discourse-cdn.com/julialang/user_avatar/discourse.julialang.org/huang_min/32/34337_2.png) [@huang\_min](https://discourse.julialang.org/u/huang_min)\
**Post date:** [March 22, 2022, 8:03am UTC](https://discourse.julialang.org/t/ann-a-new-lightning-fast-package-for-data-manipulation-in-pure-julia/78197/33 "2022-03-22T08:03:52Z")

</div>

On Win10 and WSL2.

---

<div class="post-metadata">

**Author:** ![sl-solution](https://sea2.discourse-cdn.com/julialang/user_avatar/discourse.julialang.org/sl-solution/32/34759_2.png) [@sl-solution](https://discourse.julialang.org/u/sl-solution)\
**Post date:** [March 22, 2022, 8:10am UTC](https://discourse.julialang.org/t/ann-a-new-lightning-fast-package-for-data-manipulation-in-pure-julia/78197/34 "2022-03-22T08:10:42Z")

</div>

This is strange because I expect much more allocations for this example. I don’t have access to a `Windows` machine, however, would you mind continuing this issue on `github`?

---

<div class="post-metadata">

**Author:** ![aplavin](https://sea2.discourse-cdn.com/julialang/user_avatar/discourse.julialang.org/aplavin/32/222056_2.png) [@aplavin](https://discourse.julialang.org/u/aplavin)\
**Post date:** [March 22, 2022, 8:25am UTC](https://discourse.julialang.org/t/ann-a-new-lightning-fast-package-for-data-manipulation-in-pure-julia/78197/35 "2022-03-22T08:25:33Z")

</div>

Performance benchmarks of InMemoryDatasets look great! Would also be useful to extend the size range to small tables to see what packages are feasible for use in tight loops.

Also, nice to see different API syntaxes tried out. I personally still like Base Julia `map/filter/...` more, but choice is good anyway.

I’m curious about the design decision to create both a new data structure, and functions that work on it (and only it). Why not define functions for one of the already existing table types instead, `StructArray/TypedTable/...`? Many of them are column-based and the same performance could be achieved.  
The same question could potentially be asked about DataFrames.jl, but the landscape was quite different when they were created, and this may be a piece of historical baggage (or may be not).

---

<div class="post-metadata">

**Author:** ![huang\_min](https://sea2.discourse-cdn.com/julialang/user_avatar/discourse.julialang.org/huang_min/32/34337_2.png) [@huang\_min](https://discourse.julialang.org/u/huang_min)\
**Post date:** [March 22, 2022, 8:37am UTC](https://discourse.julialang.org/t/ann-a-new-lightning-fast-package-for-data-manipulation-in-pure-julia/78197/36 "2022-03-22T08:37:49Z")

</div>

Done.

---

<div class="post-metadata">

**Author:** ![sl-solution](https://sea2.discourse-cdn.com/julialang/user_avatar/discourse.julialang.org/sl-solution/32/34759_2.png) [@sl-solution](https://discourse.julialang.org/u/sl-solution)\
**Post date:** [March 22, 2022, 9:11am UTC](https://discourse.julialang.org/t/ann-a-new-lightning-fast-package-for-data-manipulation-in-pure-julia/78197/37 "2022-03-22T09:11:45Z")

</div>

`IMD` is designed for data scientists and contains a set of functions which are very useful for data manipulation, wrangling, etc. In general, I like the syntax of base functions, but when I am working with tabular data some of those syntaxes are not intuitive and `IMD` has taken the bold approach to modify them to fit to a data manipulation workflow, e.g. see `transpose` function.

---

<div class="post-metadata">

**Author:** ![sl-solution](https://sea2.discourse-cdn.com/julialang/user_avatar/discourse.julialang.org/sl-solution/32/34759_2.png) [@sl-solution](https://discourse.julialang.org/u/sl-solution)\
**Post date:** [March 22, 2022, 11:16am UTC](https://discourse.julialang.org/t/ann-a-new-lightning-fast-package-for-data-manipulation-in-pure-julia/78197/38 "2022-03-22T11:16:44Z")

</div>

> [@davidanthoff](#):
>
> This is a very cool package!
> 
> The only thing I would _very_ strongly recommend is to not do this:
> 
> > [@jar1](#):
> >
> > by pirating Base’s aggregations
> 
> Changing the semantics of functions from Base in such a fundamental way is really considered bad practice. It is super confusing for users, and it can introduce the most unfortunate bugs for users without them ever being aware of it. If I had my way, I would actually not allow registration of packages that do things like that in the general registry 🙂
> 
> I think if you aren’t happy with the semantics of `Missing` s in base (and I have quite a bit of sympathy for that), you either need to define new functions that behave the way you want or use a different type for missing values that is under your control.

You can track/contribute this issue on [github](https://github.com/sl-solution/InMemoryDatasets.jl/issues/32)

---

<div class="post-metadata">

**Author:** ![sl-solution](https://sea2.discourse-cdn.com/julialang/user_avatar/discourse.julialang.org/sl-solution/32/34759_2.png) [@sl-solution](https://discourse.julialang.org/u/sl-solution)\
**Post date:** [March 22, 2022, 9:55pm UTC](https://discourse.julialang.org/t/ann-a-new-lightning-fast-package-for-data-manipulation-in-pure-julia/78197/39 "2022-03-22T21:55:16Z")

</div>

> [@sl-solution](#):
>
> You can track/contribute this issue on [github](https://github.com/sl-solution/InMemoryDatasets.jl/issues/32)

The fix is uploaded to the `master` branch.

---

<div class="post-metadata">

**Author:** ![Honarvaghtan](https://avatars.discourse-cdn.com/v4/letter/h/53a042/32.png) [@Honarvaghtan](https://discourse.julialang.org/u/Honarvaghtan)\
**Post date:** [March 23, 2022, 11:19am UTC](https://discourse.julialang.org/t/ann-a-new-lightning-fast-package-for-data-manipulation-in-pure-julia/78197/40 "2022-03-23T11:19:32Z")

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congratulations!  
I have posted a question in stackoverflow, can your package row-wise help to solve it. thanks

[stackoverflow - question](https://stackoverflow.com/questions/70750054/the-most-efficient-way-to-check-if-all-values-in-a-row-are-the-same-or-are-missi)

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