I would like to suggest you to follow : https://stackoverflow.com/questions/25009284/how-to-plot-roc-curve-in-python

https://stackabuse.com/understanding-roc-curves-with-python/

https://machinelearningmastery.com/roc-curves-and-precision-recall-curves-for-imbalanced-classification/

Amna Arshad Accuracy is defined as TP+TN/P+N where as ROC curve is a curve between TP/P (sensitivity) and FP/N (False positive rate).

TP: True positive

TN: True negative

FP: False positive

P: total positive

N: total negative

Could you elaborate a lil more on the problem you are facing? is it conceptual or in implementing python ?

Please go through this link, it is easy to follow...

https://intellipaat.com/blog/roc-curve-in-machine-learning/