Series API¶

The Bodo DataFrame Library supports Pandas Series methods and accessors that are listed below. They can be accessed through BodoSeries and follow the same behavior as their Pandas equivalents. For details on usage, we link to the corresponding Pandas documentation.

Note

If the user code encounters an unsupported Pandas API or an unsupported parameter, Bodo DataFrame Library gracefully falls back to native Pandas. See overview of the Bodo DataFrame Library for more info.

Computations / descriptive stats¶

Note

For the following reduction methods, only default parameters are currently supported.

Datetimelike properties¶

Note

Input must be a Series of datetime-like data.

Datetime properties¶

Note

For missing datetime values (NaT), Bodo's datetime predicate accessors (e.g., .is_month_end, .is_leap_year) return <NA> to preserve nullability, whereas Pandas returns False.

Datetime methods¶

Note

Locale format must be strict: The locale parameter in month_name and day_name must follow the exact system locale naming convention (e.g., "pt_BR.UTF-8" or "en_US.utf-8"). Variants like "pt_BR.utf8" may not be recognized and trigger an error.

Note

Bodo currently only supports "NaT" for the ambiguous parameter in tz_localize. "raise", "infer", or boolean arrays are not supported and will trigger a fallback to Pandas. Similarly, for the nonexistent parameter, "raise" is not supported and will trigger a fallback. Due to these limitations, the default behavior in Bodo is ambiguous="NaT" and nonexistent="NaT".

bodo.pandas.BodoSeries.dt.tz_localize

Function application¶

Missing data handling¶

Reindexing / Selection / Label manipulation¶

Reshaping, sorting¶

bodo.pandas.BodoSeries.sort_values

String handling¶

Note

cat falls back to Pandas when the others parameter is not specified (i.e., others=None).