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I'm trying to visualize a relatively big dataset (634785 x 282) with your tool, but the plot just won't show up.
I can see the python console is running from the task manager, however even after a long long while (when python is not using CPU any more), the plot won't show (even the tool bar as well).
Using matplotlib is pretty fast for my dataset, but it's not convenient to switch over columns. So I guess there's efficiency issue here.
The text was updated successfully, but these errors were encountered:
Hm, rendering almost a million points in JS is tough, but it works for me:
importpandasaspdimportnumpyasnpimporttablooN=1000000df=pd.DataFrame({
"id": np.arange(N),
"xs": np.random.uniform(-1, +1, N),
"ys": np.random.uniform(-1, +1, N),
})
df.loc[::10, "xs"] =np.nandf.loc[::20, "ys"] =np.nandf.loc[::47, "xs"] =+np.infdf.loc[::83, "xs"] =-np.inf#df["Column with much too long name"] = 0tabloo.show(df, open_browser=False, debug=True, server_logging=True)
The request in the backend takes a few seconds, then the frontend starts drawing the markers left-to-right. Is there anything unusual about your data?
But like I said, browser based plotting libraries are not made for such large number of points (and actually matplotlib also becomes super slow for me when plotting more then 100k points). You could enter a filtering expression in the table view and only switch to the plot with some strong filter applied. From there you could modify the filter to explore your data further, avoiding to draw the entire dataset.
I'm trying to visualize a relatively big dataset (634785 x 282) with your tool, but the plot just won't show up.
I can see the python console is running from the task manager, however even after a long long while (when python is not using CPU any more), the plot won't show (even the tool bar as well).
Using matplotlib is pretty fast for my dataset, but it's not convenient to switch over columns. So I guess there's efficiency issue here.
The text was updated successfully, but these errors were encountered: