I also use this: None
Which can give more control

None

you can upload the df as artifact.
Or the statistics as a DataFrame and upload as artifact ?

if you want plot, you can simply generate plot with matplotlib and clearml can upload them in the Plot or Debug Sample section

Pefect, thanks. I will take a look at that.

report_table seems to be the most straight forward without matplotlib integration. Do you think it has plotting features?

because, the param name that takes in the df is table_plot

with

    df = pd.DataFrame({'num_legs': [2, 4, 8, 0],
                       'num_wings': [2, 0, 0, 0],
                       'num_specimen_seen': [10, 2, 1, 8]},
                      index=['falcon', 'dog', 'spider', 'fish'])

    import clearml
    task = clearml.Task.current_task()
    task.get_logger().report_table(title='table example', series='pandas DataFrame', iteration=0, table_plot=df)
    # logger.report_table(title='table example',series='pandas DataFrame',iteration=0,table_plot=df)
    task.close()

never tried 😛

No worries. Thank you so much.

I mean, depend on what do you want to report ... if you want to stick to table, I suggest earlier to gather your stats in table format ...
Otherwise, matplotlib seems to be the most user friendly way

Yeah actually you are right. I can report the stats as a table, not the whole data.

yup, you have the flexibility and option, that what so nice with ClearML

Oh, I think that is for a very small data. I don't think it works for me.

I will have to go for matplotlib or seaborn options.

I know. And the very fast help 🙏 😀

and just came across this: None
That sounds like what you may be looking for

Can I see visualization of for example categorical columns as bar graphs?

At least I can do that along with matplotlib