By: Blog by Bogumił Kamiński

Re-posted from: https://bkamins.github.io/julialang/2021/11/26/clip.html

Introduction

Occasionally I write posts about Julia tools that are often not commonly
known, but are useful in practice. Today I want to talk about
the ClipData.jl package.

The post was written under Julia 1.6.3, DataFrames.jl 1.2.2, and
ClipData.jl 0.2.1.

What is ClipData.jl?

The package does one thing and does it well: it allows you to move
tabular data between your Julia session and the system clipboard both ways.

The to major use cases are:

1. You have a table in e.g. Google Sheet, you copy it to the system clipboard,
   and want to interactively ingest it in the Julia session as a table
   (in my examples I will use DataFrame).
2. You have a DataFrame in your Julia session and you want to copy it to the
   system clipboard so that you can later paste it in e.g. Google Sheet.

Many data scientists need to do both operations virtually every day, and
ClipData.jl comes to the rescue. This package is not only nice, but it
has an excellent visuals explaining how things work. Therefore, since they are
MIT licensed, I just link to the videos prepared by Peter Deffebach here.
Let us get to action.

First you need to know if your data has a header of not. If it has a
header we will work with a DataFrame, if it does not we will work with a
Matrix.

Clipping tables

To work with tabular data (having a header) use the cliptable function. To
copy data from the system clipboard and store it in a DataFrame called df
just write:

df = cliptable() |> DataFrame

On the other hand if you want to copy your df data frame to the system
clipboard use:

cliptable(df)

All this is very nicely presented in the following video (in particular notice
that column element types are automatically detected):

Clipping matrices

To work with arrays use the cliparray function. To copy data from
system clipboard and store it in a Matrix called mat just write:

mat = cliparray()

On the other hand if you want to copy your mat matrix to system clipboard
use:

cliparray(mat)

Here is a video showing the process:

Conclusions

There are several additional features that ClipData.jl provides (like handling
how table cells should be parsed). If you want to know more details please
refer to the ClipData.jl homepage.

I am sure you will find this little package quite useful in your data science
projects!