write python code for the followingConsider the following AllElectronics dataset containing $9$ examples.

Step$1$: Consider Minimum Support Count$=2.$ Calculate C$1,$ L$1,$ C$2,$ L$2,$ C$3$ and L$3$ as shown in the following

diagram. Show the join and prune operations in the output.

Table $5\mathrm{.}1$ Transactional data for an AllElectron$-$

ics branch.

Step $2$: Consider the tri$-$word frequent itemsets generated by the above step i$.$e$.\{|1,12,13\}$ and $\{11,12,15\}.$

For each of the corresponding association rules calculate Confidence using the following equation.

confidence $(A=>B)=P(B|A)=\frac{suppor{t}_c\text{o}\text{u}\text{n}\text{t}(AB)}{suppor{t}_c\text{o}\text{u}\text{n}\text{t}(A)}.$

Now you have understood that this is an implementation of the Apriori algorithm. Rewrite the code in a

simple way. Show the results of each step with values.