Let us visualize the class-imbalance using Seaborn countplot.
Note:
sns.countplot shows the counts of observations in each categorical bin using bars.Mention the colors of the bars to be displayed for each class in the count plot.
colors = ['blue','red']
Use sns.countplot and pass 'Class', data=data and palette=colors as input arguments.
<< your code comes here >>('Class', data=data, palette=colors)
We observe that the classes are highly imbalanced with most of the transactions are non-fraud.
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