gators.converter.ToPandas¶
-
class
gators.converter.
ToPandas
[source]¶ Convert dataframe and series to a pandas dataframe and series.
Examples
Imports and initialization:
>>> from gators.converter import ToPandas >>> obj = ToPandas()
The fit, transform, and fit_transform methods accept:
dask dataframes:
>>> import dask.dataframe as dd >>> import pandas as pd >>> X = dd.from_pandas(pd.DataFrame({ ... 'A': [0.0, 3.0, 6.0], ... 'B': [1.0, 4.0, 7.0], ... 'C': [2.0, 5.0, 8.0]}), npartitions=1) >>> y = dd.from_pandas(pd.Series([0, 0, 1], name='TARGET'), npartitions=1)
koalas dataframes:
>>> import databricks.koalas as ks >>> X = ks.DataFrame({ ... 'A': [0.0, 3.0, 6.0], ... 'B': [1.0, 4.0, 7.0], ... 'C': [2.0, 5.0, 8.0]}) >>> y = ks.Series([0, 0, 1], name='TARGET')
and pandas dataframes:
>>> import pandas as pd >>> X = pd.DataFrame({ ... 'A': [0.0, 3.0, 6.0], ... 'B': [1.0, 4.0, 7.0], ... 'C': [2.0, 5.0, 8.0]}) >>> y = pd.Series([0, 0, 1], name='TARGET')
The result is a Pandas dataframe and Pandas series.
>>> X, y = obj.transform(X, y) >>> X A B C 0 0.0 1.0 2.0 1 3.0 4.0 5.0 2 6.0 7.0 8.0 >>> y 0 0 1 0 2 1 Name: TARGET, dtype: int64
-
transform
(X: Union[pd.DataFrame, ks.DataFrame, dd.DataFrame], y: Union[pd.Series, ks.Series, dd.Series]) → Tuple[numpy.ndarray, numpy.ndarray][source]¶ Fit the transformer on the dataframe X.
- Parameters
- XDataFrame.
Input dataframe.
- y[pd.Series, ks.Series]:
Target values.
- Returns
- Xpd.DataFrame
Dataframe.
- ynp.ndarray
Target values.
-
static
check_dataframe
(X: Union[pd.DataFrame, ks.DataFrame, dd.DataFrame])¶ Validate dataframe.
- Parameters
- XDataFrame
Input dataframe.
-
static
check_target
(X: Union[pd.DataFrame, ks.DataFrame, dd.DataFrame], y: Union[pd.Series, ks.Series, dd.Series])¶ Validate target.
- Parameters
- XDataFrame
Dataframe.
- ySeries
Target values.