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y_train[y_train[:] == 1] and y_train[y_train[:] == 0]
y_train[y_train[:] == 1]
y_train[y_train[:] == 0]
both return 537 rows.
The text was updated successfully, but these errors were encountered:
Yes can confirm that with docker jupyter/scipy-notebook:notebook-6.4.12. It uses Python 3.10.6, pandas 1.5.0. It works with:
print("Original True : {0} ({1:0.2f}%)".format(len(df.loc[df['diabetes'] == 1]), (len(df.loc[df['diabetes'] == 1])/len(df.index)) * 100.0)) print("Original False : {0} ({1:0.2f}%)".format(len(df.loc[df['diabetes'] == 0]), (len(df.loc[df['diabetes'] == 0])/len(df.index)) * 100.0)) print("") print("Training True : {0} ({1:0.2f}%)".format(y_train.value_counts()[1], y_train.value_counts()[1] / y_train.size * 100)) print("Training False : {0} ({1:0.2f}%)".format(y_train.value_counts()[0], y_train.value_counts()[0] / y_train.size * 100)) print("") print("Test True : {0} ({1:0.2f}%)".format(y_test.value_counts()[1], y_test.value_counts()[1] / y_test.size * 100)) print("Test False : {0} ({1:0.2f}%)".format(y_test.value_counts()[0], y_test.value_counts()[0] / y_test.size * 100))
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y_train[y_train[:] == 1]
and
y_train[y_train[:] == 0]
both return 537 rows.
The text was updated successfully, but these errors were encountered: