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what if target column contains NaN and when pass it as a target col in Pycaret, it's showing missing value error ; all available Imputation Methods working for rest of cols not for chosen target col.
Reproducible Example
'''Dataset at GlanceCountry Year Status Life expectancy Adult Mortality infant deaths Alcohol percentage expenditure Hepatitis B Measles ... Polio Total expenditure Diphtheria HIV/AIDS GDP Population thinness 1-19 years thinness 5-9 years Income composition of resources Schooling0 Afghanistan 2015 Developing 65.0 263.0 62 0.01 71.279624 65.0 1154 ... 6.0 8.16 65.0 0.1 584.259210 33736494.0 17.2 17.3 0.479 10.11 Afghanistan 2014 Developing 59.9 271.0 64 0.01 73.523582 62.0 492 ... 58.0 8.18 62.0 0.1 612.696514 327582.0 17.5 17.5 0.476 10.0'''importpandasaspdfrompycaret.classificationimport*frompycaret.regressionimport*data=pd.read_csv('Life Expectancy.csv')
data.head()
data.columns=data.columns.str.strip()
# Successfully Executed Till Nows=setup(data, target='Life expectancy', numeric_imputation="mean", categorical_imputation="mode")
#error
Expected Behavior
It should have to handle missing values using any type imputation for target column & Setting Up Successfully.
pycaret version checks
I have checked that this issue has not already been reported here.
I have confirmed this bug exists on the latest version of pycaret.
I have confirmed this bug exists on the master branch of pycaret (pip install -U git+https://github.com/pycaret/pycaret.git@master).
Issue Description
what if target column contains NaN and when pass it as a target col in Pycaret, it's showing missing value error ; all available Imputation Methods working for rest of cols not for chosen target col.
Reproducible Example
Expected Behavior
It should have to handle missing values using any type imputation for target column & Setting Up Successfully.
Actual Results
Pycaret 3.2.0
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