add_blank_rows

trashpanda.add_blank_rows(source: pandas.core.series.Series, indexes_to_add: Union[Iterable, pandas.core.indexes.base.Index], fill_value: Optional[Any] = None, override: bool = False) → pandas.core.series.Series

trashpanda.add_blank_rows(source: pandas.core.frame.DataFrame, indexes_to_add: Union[Iterable, pandas.core.indexes.base.Index], fill_value: Optional[Any] = None, override: bool = False) → pandas.core.frame.DataFrame

Adds blank rows into a Series or DataFrame with numpy.nan by default. Double indexes are either overriden if argumend override is True or ignored.

Parameters

• source (Union[Series, DataFrame]) – Series or DataFrame in which additional ‘blank’ rows should be filled.

• indexes_to_add (Union[Iterable, pandas.Index]) – The targeted indexes, which are going to be added or overriden.

• fill_value (Optional[Any]) – Default numpy.nan; value which is going to be used as the added rows values.

• override (bool) – States if the indexes to add are overriding the source or ignored.

Returns

Union[Series, DataFrame]

Examples

Usage with a pandas.Series

>>> from pandas import Series, Index
>>> import numpy as np
>>> from doctestprinter import doctest_print
>>> from trashpanda import add_blank_rows
>>> sample_series = Series(
...     np.arange(3.0), name="a", index=Index([0.1, 0.2, 0.3], name="x")
... )
>>> prepared_frame = add_blank_rows(
...     source=sample_series, indexes_to_add=[0.15, 0.3, 0.35]
... )
>>> doctest_print(prepared_frame)
x
0.10    0.0
0.15    NaN
0.20    1.0
0.30    2.0
0.35    NaN
Name: a, dtype: float64
>>> doctest_print(
...     prepared_frame.interpolate(method="index", limit_area="inside")
... )
x
0.10    0.0
0.15    0.5
0.20    1.0
0.30    2.0
0.35    NaN
Name: a, dtype: float64
>>> doctest_print(
...     add_blank_rows(
...         source=sample_series,
...         indexes_to_add=[0.15, 0.3, 0.35],
...         override=True
...     )
... )
x
0.10    0.0
0.15    NaN
0.20    1.0
0.30    NaN
0.35    NaN
Name: a, dtype: float64
>>> doctest_print(
...     add_blank_rows(
...         source=sample_series, indexes_to_add=[],
...     )
... )
x
0.1    0.0
0.2    1.0
0.3    2.0
Name: a, dtype: float64

Usage with a pandas.DataFrame

>>> from pandas import DataFrame, Index
>>> import numpy as np
>>> from doctestprinter import doctest_print
>>> from trashpanda import add_blank_rows
>>> sample_series = DataFrame(
...     np.arange(6.0).reshape(3, 2),
...     columns=["b", "a"],
...     index=Index([0.1, 0.2, 0.3], name="x")
... )
>>> prepared_frame = add_blank_rows(
...     source=sample_series, indexes_to_add=[0.15, 0.3, 0.35]
... )
>>> doctest_print(prepared_frame)
        b    a
x
0.10  0.0  1.0
0.15  NaN  NaN
0.20  2.0  3.0
0.30  4.0  5.0
0.35  NaN  NaN
>>> doctest_print(
...     prepared_frame.interpolate(method="index", limit_area="inside")
... )
        b    a
x
0.10  0.0  1.0
0.15  1.0  2.0
0.20  2.0  3.0
0.30  4.0  5.0
0.35  NaN  NaN
>>> doctest_print(
...     add_blank_rows(
...         source=sample_series,
...         indexes_to_add=[0.15, 0.3, 0.35],
...         override=True
...     )
... )
        b    a
x
0.10  0.0  1.0
0.15  NaN  NaN
0.20  2.0  3.0
0.30  NaN  NaN
0.35  NaN  NaN
>>> doctest_print(
...     add_blank_rows(
...         source=sample_series, indexes_to_add=[],
...     )
... )
       b    a
x
0.1  0.0  1.0
0.2  2.0  3.0
0.3  4.0  5.0