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Minor Documentation Changes for the API #1323

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Oct 21, 2020
Merged

Minor Documentation Changes for the API #1323

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8f32128
update docs
Oct 20, 2020
9a03119
update release notes
Oct 20, 2020
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2 changes: 1 addition & 1 deletion docs/source/api_reference.rst
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Expand Up @@ -29,9 +29,9 @@ Utilities to preprocess data before using evalml.
:toctree: generated
:nosignatures:

load_data
drop_nan_target_rows
target_distribution
load_data
number_of_features
split_data

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1 change: 1 addition & 0 deletions docs/source/release_notes.rst
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Expand Up @@ -26,6 +26,7 @@ Release Notes
* Removed conda pre-release testing from the release process document :pr:`1282`
* Updates to contributing guide :pr:`1310`
* Added Alteryx footer to docs with Twitter and Github link :pr:`1312`
* Added documentation changes to make the API Docs easier to understand :pr:`1323`
* Testing Changes
* Added tests for ``jupyter_check`` to handle IPython :pr:`1256`
* Cleaned up ``make_pipeline`` tests to test for all estimators :pr:`1257`
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3 changes: 2 additions & 1 deletion evalml/automl/automl_search.py
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Expand Up @@ -238,13 +238,14 @@ def _validate_objective(self, objective):
if isinstance(objective, type):
if objective in non_core_objectives:
raise ValueError(f"{objective.name.lower()} is not allowed in AutoML! "
"Use evalml.objectives.utils.get_core_objective_names()"
"Use evalml.objectives.utils.get_core_objective_names() "
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Fixed the spacing in this message

"to get all objective names allowed in automl.")
return objective()
return objective

@property
def data_check_results(self):
"""If there are data checks, return any error messages that are found"""
return self._data_check_results

def __str__(self):
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5 changes: 2 additions & 3 deletions evalml/preprocessing/utils.py
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Expand Up @@ -73,11 +73,10 @@ def split_data(X, y, regression=False, test_size=.2, random_state=None):


def number_of_features(dtypes):
"""Get the number of features for specific dtypes.
"""Get the number of features of each specific dtype in a DataFrame.
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Wanted to clear up this description so users know that it takes in pd.DataFrame().dtypes


Arguments:

dtypes (pd.Series): dtypes to get the number of features for
dtypes (pd.Series): DataFrame.dtypes to get the number of features for

Returns:
pd.Series: dtypes and the number of features for each input type
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