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Method std

dask/dataframe/dask_expr/_collection.py:1537–1630  ·  view source on GitHub ↗
(
        self,
        axis=0,
        skipna=True,
        ddof=1,
        numeric_only=False,
        split_every=False,
        **kwargs,
    )

Source from the content-addressed store, hash-verified

1535
1536 @derived_from(pd.DataFrame)
1537 def std(
1538 self,
1539 axis=0,
1540 skipna=True,
1541 ddof=1,
1542 numeric_only=False,
1543 split_every=False,
1544 **kwargs,
1545 ):
1546 _raise_if_object_series(self, "std")
1547 axis = self._validate_axis(axis)
1548 numeric_dd = self
1549 meta = meta_nonempty(self._meta).std(
1550 axis=axis, skipna=skipna, ddof=ddof, numeric_only=numeric_only
1551 )
1552 needs_time_conversion, time_cols = False, None
1553 if is_dataframe_like(self._meta):
1554 if axis == 0:
1555 numeric_dd = numeric_dd[list(meta.index)]
1556 else:
1557 numeric_dd = numeric_dd.copy()
1558
1559 if numeric_only is True:
1560 _meta = numeric_dd._meta.select_dtypes(include=[np.number])
1561 else:
1562 _meta = numeric_dd._meta
1563 time_cols = _meta.select_dtypes(include=["datetime", "timedelta"]).columns
1564 if len(time_cols) > 0:
1565 if axis == 1 and len(time_cols) != len(self.columns):
1566 numeric_dd = from_pandas(
1567 meta_frame_constructor(self)(
1568 {"_": meta_series_constructor(self)([np.nan])},
1569 index=self.index,
1570 ),
1571 npartitions=self.npartitions,
1572 )
1573 else:
1574 needs_time_conversion = True
1575 if axis == 1:
1576 numeric_dd = numeric_dd.astype(f"datetime64[{meta.array.unit}]")
1577 for col in time_cols:
1578 numeric_dd[col] = _convert_to_numeric(numeric_dd[col], skipna)
1579 else:
1580 needs_time_conversion = is_datetime64_any_dtype(self._meta)
1581 if needs_time_conversion:
1582 numeric_dd = _convert_to_numeric(self, skipna)
1583
1584 units = None
1585 if needs_time_conversion and time_cols is not None:
1586 units = [getattr(self._meta[c].array, "unit", None) for c in time_cols]
1587
1588 if axis == 1:
1589 _kwargs = (
1590 {}
1591 if not needs_time_conversion
1592 else {"unit": meta.array.unit, "dtype": meta.dtype}
1593 )
1594 return numeric_dd.map_partitions(

Callers

nothing calls this directly

Calls 13

_raise_if_object_seriesFunction · 0.90
meta_frame_constructorFunction · 0.90
meta_series_constructorFunction · 0.90
_convert_to_numericFunction · 0.90
is_dataframe_likeFunction · 0.85
from_pandasFunction · 0.85
select_dtypesMethod · 0.80
_validate_axisMethod · 0.45
stdMethod · 0.45
copyMethod · 0.45
astypeMethod · 0.45
map_partitionsMethod · 0.45

Tested by

no test coverage detected