Standardscaler:
1.In Standardscaler, it assumes that data has normally distributed features and will scale them to zero mean and 1 standard deviation.
2.All the features will be of the same scale after applying the scaler.
Minmaxscaler :
1.Minmaxscaler shrinks the data within the range of -1 to 1(if there are negative values)
2. This responds well if standard deviation is small and is used when distribution is not Gaussian.This scaler is sensitive to outliers.
If you wish to learn more about how to use python for data science, then go through data science python programming course by Intellipaat for more insights.