Getting different chi square values than sklearn function I have a dataset which looks like this-



I am trying to use chi2 as a feature selction algorithm on it.Here is the code

dataset = pd.read_csv('small_dataset.csv')
print(dataset.shape)


X = dataset.iloc[:, 1:106].values
y = dataset.iloc[:,0].values


print(sklearn.feature_selection.chi2(X, y))


I tried to validate the answers from sklearn and the formula which is 





so I took the first feature and computed the A B C D which are 0 19 73 73 and N is 146.So the X2 value coming is 21 but in sklearn its coming 579.

What am I doing wrong?
I had a similar problem using Scipy's chi2_contingency. It turns out that the Scipy function uses by default correction=True, and the statistic you showed doesn't use the correction. Perhaps sklearn's chi2 uses the correction as well, and that's the reason you don't get the same results. I suggest trying Scipy's with both correction set to true and false to see if it matches the two results.