elshor / dstools Goto Github PK

The link https://elshor.github.io/dstools/
returns cannot get.

Hi, thanks for the cool project.

I wonder if you've come across tslab and could support printing from it?
https://github.com/yunabe/tslab

I have the same issue as in #1 where the wrapper / raw html is displayed. tslab has a html show function which you could hook into, or if there were a way to just get the raw html output, I could push that into the function. For example, I might call it like this:

tslab.display.html(df.histogram('field1').show())

Hi,

I've been doing some data science work in node.js recently, so I'm really excited to check this project out!

I'm currently running node.js in my notebook with the notablemind node.js kernel. I was able to require dstools and I wrapped my array data in the Collection function and called .show() but was returned the Wrapper object for dstools instead of an actual HTML table.

.head() seems to work and modifies the _data key on the Wrapper object, but there's no table output to jupyter.

My guess is that dstools is meant to be used only with ijavascript at this moment.

Do you plan to support other kernels? I'm really excited about this project and would love to use it for my work. Also, let me know if there's any way I can help.

The save method called on the Collection as below

movies = ds.Collection() .loadCSV('.....tmdb_5000_credits.csv'); movies.save('....tmdb-credits.json');

adds '\' to the saved JSON result.

This happens from both the Jupyter Javascript notebook and from node.js app using dstools.

Is it normal behavior?

Sample output below:

[{"movie_id":19995,"title":"Avatar","cast":"[{"cast_id": 242, "character": "Jake Sully", "credit_id": "5602a8a7c3a3685532001c9a",

Hi,

I'm using dstools for datascience. It says that some method would return collection. I don't get understand what type of collection it is. If I try to print the collection.

Why can't I get things. I only want to get columns who are female 'F' sex. How do I do that? I'm really confused right now.

I'm using this dataset

https://www.kaggle.com/open-powerlifting/powerlifting-database