pandas_profiling.profile_report.ProfileReport

class pandas_profiling.profile_report.ProfileReport(df=None, minimal=False, explorative=False, sensitive=False, dark_mode=False, orange_mode=False, sample=None, config_file=None, lazy=True, typeset=None, summarizer=None, config=None, **kwargs)

Generate a profile report from a Dataset stored as a pandas DataFrame.

Used as is, it will output its content as an HTML report in a Jupyter notebook.

Generate a ProfileReport based on a pandas DataFrame

Parameters

• df (Optional[DataFrame]) – the pandas DataFrame

• minimal (bool) – minimal mode is a default configuration with minimal computation

• config_file (Union[Path, str, None]) – a config file (.yml), mutually exclusive with minimal

• lazy (bool) – compute when needed

• sample (Optional[dict]) – optional dict(name=”Sample title”, caption=”Caption”, data=pd.DataFrame())

• typeset (Optional[VisionsTypeset]) – optional user typeset to use for type inference

• summarizer (Optional[BaseSummarizer]) – optional user summarizer to generate custom summary output

• **kwargs – other arguments, for valid arguments, check the default configuration file.

__init__(df=None, minimal=False, explorative=False, sensitive=False, dark_mode=False, orange_mode=False, sample=None, config_file=None, lazy=True, typeset=None, summarizer=None, config=None, **kwargs)

Generate a ProfileReport based on a pandas DataFrame

Parameters

• df (Optional[DataFrame]) – the pandas DataFrame

• minimal (bool) – minimal mode is a default configuration with minimal computation

• config_file (Union[Path, str, None]) – a config file (.yml), mutually exclusive with minimal

• lazy (bool) – compute when needed

• sample (Optional[dict]) – optional dict(name=”Sample title”, caption=”Caption”, data=pd.DataFrame())

• typeset (Optional[VisionsTypeset]) – optional user typeset to use for type inference

• summarizer (Optional[BaseSummarizer]) – optional user summarizer to generate custom summary output

• **kwargs – other arguments, for valid arguments, check the default configuration file.

Methods

__init__([df, minimal, explorative, ...])	Generate a ProfileReport based on a pandas DataFrame
dump(output_file)	Dump ProfileReport to file
dumps()	Serialize ProfileReport and return bytes for reproducing ProfileReport or Caching.
get_description()	Return the description (a raw statistical summary) of the dataset.
get_duplicates()	Get duplicate rows and counts based on the configuration
get_rejected_variables()	Get variables that are rejected for analysis (e.g.
get_sample()	Get head/tail samples based on the configuration
invalidate_cache([subset])	Invalidate report cache.
load(load_file)	Load ProfileReport from file
loads(data)	Deserialize the serialized report
to_expectation_suite([suite_name, ...])	All parameters default to True to make it easier to access the full functionality of Great Expectations out of the box. :type suite_name: Optional[str] :param suite_name: The name of your expectation suite :type data_context: Optional[Any] :param data_context: A user-specified data context :type save_suite: bool :param save_suite: Boolean to determine whether to save the suite to .json as part of the method :type run_validation: bool :param run_validation: Boolean to determine whether to run validation as part of the method :type build_data_docs: bool :param build_data_docs: Boolean to determine whether to build data docs, save the .html file, and open data docs in your browser :type handler: Optional[Handler] :param handler: The handler to use for building expectation.
to_file(output_file[, silent])	Write the report to a file.
to_html()	Generate and return complete template as lengthy string
to_json()	Represent the ProfileReport as a JSON string
to_notebook_iframe()	Used to output the HTML representation to a Jupyter notebook.
to_widgets()	The ipython notebook widgets user interface.

Attributes

config
description_set	rtype Dict[str, Any]
df
df_hash	rtype Optional[str]
html	rtype str
json	rtype str
report	rtype Root
summarizer	rtype BaseSummarizer
typeset	rtype Optional[VisionsTypeset]
widgets	rtype Renderable