code stringlengths 3 6.57k |
|---|
__finalize__(self) |
__copy__(self: FrameOrSeries, deep: bool_t = True) |
self.copy(deep=deep) |
__deepcopy__(self: FrameOrSeries, memo=None) |
self.copy(deep=True) |
numbers (including strings) |
nulls (NaN or NaT) |
validate_bool_kwarg(datetime, "datetime") |
validate_bool_kwarg(numeric, "numeric") |
validate_bool_kwarg(timedelta, "timedelta") |
validate_bool_kwarg(coerce, "coerce") |
validate_bool_kwarg(copy, "copy") |
__finalize__(self) |
infer_objects(self: FrameOrSeries) |
pd.DataFrame({"A": ["a", 1, 2, 3]}) |
df.infer_objects() |
__finalize__(self) |
StringDtype() |
BooleanDtypes() |
pd.Series([1, 2, 3], dtype=np.dtype("int32") |
pd.Series(["x", "y", "z"], dtype=np.dtype("O") |
pd.Series([True, False, np.nan], dtype=np.dtype("O") |
pd.Series(["h", "i", np.nan], dtype=np.dtype("O") |
pd.Series([10, np.nan, 20], dtype=np.dtype("float") |
pd.Series([np.nan, 100.5, 200], dtype=np.dtype("float") |
df.convert_dtypes() |
pd.Series(["a", "b", np.nan]) |
s.convert_dtypes() |
self.items() |
pd.concat(results, axis=1, copy=False) |
doc(**_shared_doc_kwargs) |
holes (e.g. 0) |
index (for a Series) |
column (for a DataFrame) |
type (e.g. float64 to int64 if possible) |
list('ABCD') |
df.fillna(0) |
df.fillna(method='ffill') |
df.fillna(value=values) |
df.fillna(value=values, limit=1) |
validate_bool_kwarg(inplace, "inplace") |
validate_fillna_kwargs(value, method) |
self._consolidate_inplace() |
set (e.g. in groupby) |
self._get_axis_number(axis) |
NotImplementedError() |
self.T.fillna(method=method, limit=limit) |
result._data.downcast() |
len(self._get_axis(axis) |
isinstance(value, (dict, ABCSeries) |
is_list_like(value) |
type(value) |
isinstance(value, (dict, ABCSeries) |
self.copy() |
value.items() |
obj.fillna(v, limit=limit, inplace=True, downcast=downcast) |
is_list_like(value) |
isinstance(value, ABCDataFrame) |
self.where(self.notna() |
ValueError(f"invalid fill value with a {type(value) |
self._update_inplace(new_data) |
self._constructor(new_data) |
__finalize__(self) |
object (e.g. a column from a DataFrame) |
key(s) |
value(s) |
pd.Series([0, 1, 2, 3, 4]) |
s.replace(0, 5) |
df.replace(0, 5) |
df.replace([0, 1, 2, 3], 4) |
df.replace([0, 1, 2, 3], [4, 3, 2, 1]) |
s.replace([1, 2], method='bfill') |
df.replace({0: 10, 1: 100}) |
df.replace({'A': 0, 'B': 5}, 100) |
df.replace({'A': {0: 100, 4: 400}}) |
df.replace(to_replace=r'^ba.$', value='new', regex=True) |
df.replace({'A': r'^ba.$'}, {'A': 'new'}, regex=True) |
df.replace(regex=r'^ba.$', value='new') |
df.replace(regex={r'^ba.$': 'new', 'foo': 'xyz'}) |
df.replace(regex=[r'^ba.$', 'foo'], value='new') |
df.replace({'a string': 'new value', True: False}) |
Traceback (most recent call last) |
ndarray(dtype=bool) |
s.replace({'a': None}) |
s.replace('a', None) |
pd.Series([10, 'a', 'a', 'b', 'a']) |
value(s) |
s.replace({'a': None}) |
s.replace(to_replace={'a': None}, value=None, method=None) |
s.replace({'a': None}) |
parameter (default 'pad') |
s.replace('a', None) |
s.replace(to_replace='a', value=None, method='pad') |
s.replace('a', None) |
Appender(_shared_docs["replace"] % _shared_doc_kwargs) |
is_scalar(to_replace) |
isinstance(to_replace, pd.Series) |
is_re_compilable(to_replace) |
is_list_like(to_replace) |
repr(type(to_replace) |
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