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Describe the bug
Calling a dataframe.repr in a notebook cell either takes very long or results in a kernel failure for large datasets. Steps/Code to reproduce bug
In a jupyterlab environment, run this in a cell:
# [cell 1]%load_extcudf.pandas# [cell 2]importpandasaspdimportnumpyasnp# Define the number of rows and columnsnum_rows=25_000_000num_columns=12# Create a DataFrame with random datadf=pd.DataFrame(np.random.randint(0, 100, size=(num_rows, num_columns)),
columns=[f'Column_{i}'foriinrange(1, num_columns+1)])
# [cell 3]df
Expected behavior
dataframe should render quickly, as is the case when working directly with cudf, or pandas
Note
This works as expected in a python interactive shell, or when calling print(df) in a notebook.
The text was updated successfully, but these errors were encountered:
AjayThorve
changed the title
[BUG] cudf.pandas dataframe.__repr__ fails in jupyterlab for large datasets
[BUG] cudf.pandas dataframe.__repr__ slow in jupyterlab for large datasets
May 14, 2024
Describe the bug
Calling a dataframe.repr in a notebook cell either takes very long or results in a kernel failure for large datasets.
Steps/Code to reproduce bug
In a jupyterlab environment, run this in a cell:
Expected behavior
dataframe should render quickly, as is the case when working directly with cudf, or pandas
Note
This works as expected in a python interactive shell, or when calling
print(df)
in a notebook.The text was updated successfully, but these errors were encountered: