python - How do you represent na in a Pandas DataFrame? -

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does pandas have equivalent of r's na (meaning not available)? if not, convention representing missing value, opposed nan represents mathematically impossible value such divide zero?

currently there no na value available in pandas or numpy. section "working missing data" in pandas manual (http://pandas.pydata.org/pandas-docs/stable/missing_data.html):

the choice of using nan internally denote missing data largely simplicity , performance reasons. differs maskedarray approach of, example, scikits.timeseries. hopeful numpy able provide native na type solution (similar r) performant enough used in pandas.

also, part of documentation (http://pandas.pydata.org/pandas-docs/stable/gotchas.html#nan-integer-na-values-and-na-type-promotions) provides more details on trade-offs in choice of na representation.


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