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@dcolinmorgan
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for rare cases first encountered in avr-59k['Source_IP4_Subnet_16'] dataset, for example

graphistry.nodes(avr59k_splunk['Source_IP4_Subnet_16'].dropna()).umap()

would throw type error

see end of this thread


def try_coerce_to_numeric(ndf: pd.DataFrame):
try:
nndf = ndf.copy()
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:(

nndf = ndf.copy()
object_columns = nndf.select_dtypes(include=['object']).columns
for j in object_columns:
num_floats = sum(isinstance(x, float) for x in nndf[j].dropna())
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This is slow, and weird to check for floats in a col marked as object?

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@silkspace @tanmoyio this seems slow and surprising to put in the critical path for most gpu umap calls?

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3 participants