pipelinex.extras.datasets.pandas_profiling package¶
Submodules¶
pipelinex.extras.datasets.pandas_profiling.pandas_profiling module¶
-
class
pipelinex.extras.datasets.pandas_profiling.pandas_profiling.
PandasProfilingDataSet
(filepath, save_args=None, sample_args=None, version=None)[source]¶ Bases:
pipelinex.extras.datasets.core.AbstractVersionedDataSet
PandasProfilingDataSet
is anAbstractVersionedDataSet
to generate pandas profiling report. See https://github.com/pandas-profiling/pandas-profiling for details.-
DEFAULT_SAVE_ARGS
: Dict[str, Any] = {}¶
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__init__
(filepath, save_args=None, sample_args=None, version=None)[source]¶ Creates a new instance of
PandasProfilingDataSet
pointing to a concrete filepath.- Parameters:
filepath (
str
) – path to a local yaml file.save_args (
Optional
[Dict
[str
,Any
]]) – Arguments passed on todf.profile_report
such as title. See https://pandas-profiling.github.io/pandas-profiling/docs/ for details. See https://github.com/pandas-profiling/pandas-profiling/blob/master/pandas_profiling/config_default.yaml for default values.sample_args (
Optional
[Dict
[str
,Any
]]) – Arguments passed on todf.sample
. See https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.DataFrame.sample.html for details.version (
Optional
[Version
]) – If specified, should be an instance ofkedro.io.core.Version
. If itsload
attribute is None, the latest version will be loaded. If itssave
attribute is None, save version will be autogenerated.
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