I created a conda-forge recipe and my PR is merged so you can install this package with conda link using

conda install -c conda-forge hiplot

You might consider to update the README accordingly.

Streamlit currently has a hard limit of 50Mb for a single component. I have dataset that is only 16Mb of data as a .csv, but as HiPlot transfers that as JSON suddenly the data is over 200Mb. Transferring the data like that, every datapoint containsing all column names seems a rather wasteful use of bandwidth.

Not only does it affect the Streamlit component, but also considerably slows down loading large datasets in the standalone HiPlot-application (assuming the data there is transferred the same way).

My suggestion would be to transfer the column names as an array and the datapoints as arrays as well. On the client they then can be matched by position in the array.

Hi @danthe3rd,

Thanks for the nice library. Very lightweight, very useful :slightly_smiling_face:

Background When I have a lot of axes on the parallel plot I always drop uid and from_uid axes, because they add some unnecessary clutter to the chart. I still want to keep these two axes in the table. In my case I have other axes than encode runs.

Request Add an option (maybe to the display function) to not display uid and from_uid axes on the chart.

Best, Kamil

Hello, i want to try the demo but i got this issue, i try to change render.py with encoding but it not works.

i use

• Python 3.7.4
• conda 4.7.12

`import hiplot as hip

data = [{'dropout':0.1, 'lr': 0.001, 'loss': 10.0, 'optimizer': 'SGD'}, {'dropout':0.15, 'lr': 0.01, 'loss': 3.5, 'optimizer': 'Adam'}, {'dropout':0.3, 'lr': 0.1, 'loss': 4.5, 'optimizer': 'Adam'}] hip.Experiment.from_iterable(data).display()`

UnicodeDecodeError: 'charmap' codec can't decode byte 0x9e in position 122350: character maps to <undefined>

Hi,

I have a datatset with 80 columns. Is there any way to configure HiPlot such that I get a horizontal scrollbar in order to go through all columns. Right now, the depiction tries to show all columns within the screensize, which makes the app unusable.

Thank you, Martin

Hi,

I installed hiplot on windows machine using poetry. I am not able to run the hiplot from command line in my python virtual environment.

C:\Users\sarat.chinni\Codes_sequencing\hiplot>hiplot
'hiplot' is not recognized as an internal or external command,
operable program or batch file.

I have added .py extension to hiplot function in my virtual environment Scripts folder then I got the following error:

C:\Users\sarat.chinni\Codes_sequencing\hiplot>hiplot
Traceback (most recent call last):
  File "C:\Users\sarat.chinni\Codes_sequencing\biobench\sandbox\Sarat\supervised_sequencing\.venv\Scripts\hiplot.py", line 6, in <module>
    sys.exit(hip.run_server_main())
AttributeError: module 'hiplot' has no attribute 'run_server_main'

How can I solve this issue on windows? (I am able to install and hiplot in my linux machine and it worked properly)

Thank you

Hi, thank you for introducing the Optuna integration by #215!

I suppose the current implementation does not support study whose objective function returns multiple objective values. More concretely, the following code:

import optuna
import hiplot as hip

def objective(trial: "optuna.trial.Trial") -> float:
    x = trial.suggest_float("x", -1, 1)
    y = trial.suggest_float("y", -1, 1)    

    return x ** 2, y

study = optuna.create_study(directions=["minimize"]*2)
study.optimize(objective, n_trials=3)

xp = hip.Experiment.from_optuna(study)

The error message is as follows.

RuntimeError                              Traceback (most recent call last)
/var/folders/n3/7_7r1yrx6jsc_0780bvg02lr0000gn/T/ipykernel_82314/3836556673.py in <module>
      2 study.optimize(objective, n_trials=3)
      3 
----> 4 xp = hip.Experiment.from_optuna(study)

~/Documents/hiplot/hiplot/experiment.py in from_optuna(study)
    519         hyper_opt_data = []
    520         for each_trial in study.trials:
--> 521             trial_params = {}
    522             trial_params["value"] = each_trial.value # name = value, as it could be RMSE / accuracy, or any value that the user selects for tuning
    523             trial_params["uid"] = each_trial.number

/opt/homebrew/Caskroom/miniconda/base/envs/optuna39/lib/python3.9/site-packages/optuna/trial/_frozen.py in value(self)
    389         if self._values is not None:
    390             if len(self._values) > 1:
--> 391                 raise RuntimeError(
    392                     "This attribute is not available during multi-objective optimization."
    393                 )

RuntimeError: This attribute is not available during multi-objective optimization.

Dependencies:

• Optuna: 2.10.0
• hiplot: https://github.com/facebookresearch/hiplot/tree/79b3d52a6842d6ba12f0a544e27a444562a486df

To clarify it in the documentation, this PR mentions the supported study.

By the way, to access the objective values of either single and multi-objective, we can use tiral.values that contains retuned value by the objective function of Optuna as list.

Hi,

I've come across a weird bug with the parallel plot: One of my float columns/axis contains NaN-values. When plotted with Hiplot only sometimes the entry "nan/inf/null" appears on the axis; more exactly it only appears if there are at least 6 unique values other than NaN in that column. For example, if all entries in that column contain only the values [nan 3. 5. 7. 9. 15. 30. ] the "nan/inf/null" entry shows correctly. If however I replace all 30's with 15's without changing anything else, the entry doesn't show up.

Is that a bug, or am I overseeing something on my side?

I use the Hiplot-Component in Streamlit. When I click the Export button nothing happens. No download starts, no error in the console, no log on the server.

When there are too many columns to display on the screen, there's no way to access the missing ones in the table. It would be helpful if displayed columns could be toggled off or resized, or if reordering the plot columns reordered the table.

Hi again, I work with a large dataset in the Streamlit-component of HiPlot. Whenever I select something in the plot it turns gray, as it's waiting for Streamlit to run, which takes a couple of seconds due to the large dataset. When I repeatedly click around in the plot (firing updates), while it's still loading, at one point Streamlit resets the entire page and all inputs/selections are lost. That might happen after just three clicks or after 20, but it happens. It also happens when the plot is loading and I change other Streamlit inputs, so it might be a Streamlit issue, but I can't say that for sure and I was asked to also open this issue here.

Streamlit issue: https://github.com/streamlit/streamlit/issues/2695

Bumps json5 from 2.1.3 to 2.2.2.

Dependabot will resolve any conflicts with this PR as long as you don't alter it yourself. You can also trigger a rebase manually by commenting @dependabot rebase.

When I upload the attached CSV onto the hosted version of HiPlot some axes of the CSV do not appear in the parallel plot, whereas they correctly appear in the table below. If I right-click on the table's headers I'm not offered to restore these axes onto the plot. These axes are "Ratio" and "Log(ratio)".

Untitled spreadsheet - Sheet5.csv

Scenario: I have a grid-search on parameters A, B and C. For each sample, I have an associated loss which I try to minimize.

I want to know which parameter (A, B or C) has the most influence on the loss automatically.

In python: This can be done by learning a simple RandomForestRegressor (or Classifier depending on the target value type), and then calling permutation_importance to get an importance score for each parameter. For this to be embedded in HiPlot, it would need to be done in JS (for example with this library?)

https://scikit-learn.org/stable/modules/generated/sklearn.ensemble.RandomForestRegressor.html https://scikit-learn.org/stable/modules/permutation_importance.html

UI: This could be triggered by right-clicking a column. The result could be displayed by ordering the column by relative importance. Need a way to select which columns to include/exclude from the calculation, and to display the correlation score

Original change in https://github.com/facebookresearch/hiplot/pull/213 Workaround: Use version <= 0.1.28

hi there. I've tried to track down which recent changes to hiplot resulted in my plots getting significantly harder to read, and narrowed it down to 0.1.28 -> 0.1.29 and believe this is the PR responsible.

This perfectly readable and stacked display: turned into which cuts off the final column name if I make the window any more narrow and causes a weird spacing issue on the right-side.

I very much support improving the visual interface of hiplot but I believe this hurt the overall experience. Would you be open to discussing some of the changes made here and perhaps a partial revert? Or am I best served maintaining a separate fork of the project? (I am not a front-end developer but am trying very hard to use hiplot in a tool I am building).

The above screenshots were in Opera (I've noticed Safari has had existing trouble with dragging columns). I also noticed that on Safari, this same change resulted in "ghosting" of the headers upon scrolling (and did not fix the aforementioned problem):

(that's the "rearranging" problem in safari I mentioned, the annotation divorces from the column)

(original report in https://github.com/facebookresearch/hiplot/pull/214 from @mathematicalmichael )

This is an extremely cool pacakge, many research units that I have been working at are slowly switching from jupyter notebooks to dash type web-apps, would there be a way to get this into plolty dash? That would be an extremely exciting development.