Note
Click here to download the full example code
Mixed Nulls#
import pandas as pd
from deepchecks.tabular.checks import MixedNulls
data = {'col1': ['sog', '1', 'cat', None, None]}
dataframe = pd.DataFrame(data=data)
MixedNulls().run(dataframe)
Out:
/home/runner/work/deepchecks/deepchecks/deepchecks/tabular/dataset.py:886: UserWarning:
Received a "pandas.DataFrame" instance. It is recommended to pass a "deepchecks.tabular.Dataset" instance by doing "Dataset(dataframe)"
/home/runner/work/deepchecks/deepchecks/deepchecks/tabular/dataset.py:581: UserWarning:
It is recommended to initialize Dataset with categorical features by doing "Dataset(df, cat_features=categorical_list)". No categorical features were passed, therefore heuristically inferring categorical features in the data.
0 categorical features were inferred
data = {'col1': ['nan', None, 'null', 'Nan', '1', 'cat'], 'col2':['', '', 'None', 'a', 'b', 'c'], 'col3': [1,2,3,4,5,6]}
dataframe = pd.DataFrame(data=data)
MixedNulls().run(dataframe)
Out:
/home/runner/work/deepchecks/deepchecks/deepchecks/tabular/dataset.py:886: UserWarning:
Received a "pandas.DataFrame" instance. It is recommended to pass a "deepchecks.tabular.Dataset" instance by doing "Dataset(dataframe)"
/home/runner/work/deepchecks/deepchecks/deepchecks/tabular/dataset.py:581: UserWarning:
It is recommended to initialize Dataset with categorical features by doing "Dataset(df, cat_features=categorical_list)". No categorical features were passed, therefore heuristically inferring categorical features in the data.
0 categorical features were inferred
Total running time of the script: ( 0 minutes 0.121 seconds)