Datasets:
celinelee
/
python_fn_calls

Dataset card Data Studio Files
xet
 Community
1
code
stringlengths
3
6.57k
self.index.searchsorted(where, side="right")
isna(values[loc])
isinstance(where, Index)
Index(where)
Index([where])
self.isna()
isna()
any(1)
nulls.all()
self._constructor(np.nan, index=where, name=self.name)
DataFrame(np.nan, index=where, columns=self.columns)
Series(np.nan, index=self.columns, name=where[0])
self.index.asof_locs(where, ~(nulls.values)
self.take(locs)
values (unless you set ``pandas.options.mode.use_inf_as_na = True``)
pd.Timestamp('1939-05-27')
pd.Timestamp('1940-04-25')
df.isna()
pd.Series([5, 6, np.NaN])
ser.isna()
Appender(_shared_docs["isna"] % _shared_doc_kwargs)
isna(self: FrameOrSeries)
isna(self)
__finalize__(self)
Appender(_shared_docs["isna"] % _shared_doc_kwargs)
isnull(self: FrameOrSeries)
isna(self)
__finalize__(self)
existing (non-missing)
values (unless you set ``pandas.options.mode.use_inf_as_na = True``)
pd.Timestamp('1939-05-27')
pd.Timestamp('1940-04-25')
df.notna()
pd.Series([5, 6, np.NaN])
ser.notna()
Appender(_shared_docs["notna"] % _shared_doc_kwargs)
notna(self: FrameOrSeries)
notna(self)
__finalize__(self)
Appender(_shared_docs["notna"] % _shared_doc_kwargs)
notnull(self: FrameOrSeries)
notna(self)
__finalize__(self)
_clip_with_scalar(self, lower, upper, inplace: bool_t = False)
if (lower is not None and np.any(isna(lower)
np.any(isna(upper)
ValueError("Cannot use an NA value as a clip threshold")
isna(self.values)
np.errstate(all="ignore")
self.to_numpy()
result.where(subset, upper, axis=None, inplace=False)
self.to_numpy()
result.where(subset, lower, axis=None, inplace=False)
np.any(mask)
self._update_inplace(result)
_clip_with_one_bound(self, threshold, method, axis, inplace)
self._get_axis_number(axis)
is_scalar(threshold)
is_number(threshold)
self._clip_with_scalar(None, threshold, inplace=inplace)
self._clip_with_scalar(threshold, None, inplace=inplace)
method(threshold, axis=axis)
isna(self)
if (not isinstance(threshold, ABCSeries)
is_list_like(threshold)
isinstance(self, ABCSeries)
self._constructor(threshold, index=self.index)
_align_method_FRAME(self, threshold, axis, flex=None)
self.where(subset, threshold, axis=axis, inplace=inplace)
threshold(s)
pd.DataFrame(data)
df.clip(-4, 6)
pd.Series([2, -4, -1, 6, 3])
df.clip(t, t + 4, axis=0)
validate_bool_kwarg(inplace, "inplace")
nv.validate_clip_with_axis(axis, args, kwargs)
self._get_axis_number(axis)
is_list_like(lower)
np.any(isna(lower)
is_list_like(upper)
np.any(isna(upper)
is_scalar(lower)
is_scalar(upper)
min(lower, upper)
max(lower, upper)
if (lower is None or (is_scalar(lower)
is_number(lower)
or (is_scalar(upper)
is_number(upper)
self._clip_with_scalar(lower, upper, inplace=inplace)
align()
a (single)
rows (0)
columns (1)
MultiIndex (hierarchical)
only (see PeriodIndex.asfreq)
pd.date_range('1/1/2000', periods=4, freq='T')
pd.Series([0.0, None, 2.0, 3.0], index=index)
pd.DataFrame({'s':series})
df.asfreq(freq='30S')