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

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

I know. And the very fast help 🙏 😀

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

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

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

None

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

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

I also use this: None
Which can give more control

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

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

At least I can do that along with matplotlib

never tried 😛

No worries. Thank you so much.

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()

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

I will have to go for matplotlib or seaborn options.