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I generated a random dataset that has 1 categorical column and 30 numeric columns. The categorical variable has 3 classes X, Y and Z. See data generation code below I need help with Steps 2,3 and 4: ...
nasa313's user avatar
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I want to obtain a matrix of partial correlatins (for all pairs), removing the effect of all other columns. I am using pingouin, however the function df.pcorr().round(3) only works with pearson ...
Leo's user avatar
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I am sure this is simple but I am still learning python. I need help figuring out how to iterate over columns in a pandas dataframe and run the pingouin analysis for each. As of now, I can run pg....
Sterling Wright's user avatar
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I have a dataset with 2112 features and 2337 entries. I am trying to see the correlation between these features and the dependent variable. All of the features and the outcome variable are numeric. ...
Echo's user avatar
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This issue is appearing in a local Jupyter notebook and I'm using Python 3.10 Importing scipy and scipy.stats is no problem. import scipy import scipy.stats However, I'm trying to use the Pingouin ...
criminal_chili's user avatar
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1 vote
1 answer
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I'm using Pingouin.jl to test normality. In their docs, we have dataset = Pingouin.read_dataset("mediation") Pingouin.normality(dataset, method="jarque_bera") Which should return ...
BuddhiLW's user avatar
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trying with the pg.pairwise_corr method I get the following error: pg.pairwise_corr(df) /usr/local/lib/python3.7/dist-packages/pingouin/correlation.py in corr(x, y, tail, method, **kwargs) 507 ...
Becca's user avatar
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