Can you please elaborate on what is considered "large amount of data" for facets?

[anshbansal]

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I tried loading a 65.2 MB csv file into facets on Google Chrome on Ubuntu 16.04 LTS following same code as in the demo jupyter notebook. When I started loading the data I had 13 GB RAM available. During the load it used up 4 GB RAM. But it took a few minutes. Google Chrome asked me whether I want to wait or exit the page. I said wait. That happened another time. I said wait. Then the page crashed finally crashed. So I just wanted clarification what is considered "large amount of data" for facets?

[jameswex]

Thanks for the feedback. Some questions to help clarify: Which Facets visualization were you trying to use (Overview or Dive)? And at what step did the RAM usage and freeze/crash occur? How many examples (rows) are in the csv file and how many features (columns)? It would help if you would could share the csv if possible.

[everardogentil]

In my case I load the data below and got the same problem:

<class 'pandas.core.frame.DataFrame'> RangeIndex: 8461352 entries, 0 to 8461351 Data columns (total 10 columns): UC int64 PCR object ENDERECO object MUNICIPIO object LOCALIDADE object COORDENADA_X float64 COORDENADA_Y float64 ESTADO_FORNECIMENTO object ESTADO_CLIENTE object TRAFO object dtypes: float64(2), int64(1), object(7) memory usage: 645.6+ MB

[jameswex]

Can you share a notebook with the problem?

[everardogentil]

The code is here: Data Description.ipynb.zip

[jameswex]

Could you also provide the csv so I can repro? Thanks