Data Wrangling

Build an analytical dataset by combining (joining) the data from the different tables as you see fit, which will be used for the purposes of exploratory data analysis, visualization and reporting. The unit of analysis is the account. This dataset must contain the following information for each account using the following field names:
account_id : Account number
district_name : Name of the district where the account is
open_date : Date when account was opened
statement_frequency : The frequency that statements are generated for the account
num_customers : The total number of clients associated with the account (owner and users)
credit_cards : Number of credit cards for an account or zero if none
loan : T/F if the account has a loan
loan_amount : The amount of the loan if there is one, NA if none
loan_payments : The amount of the loan payment if there is one, NA if none
loan_term : The duration of loan in months, NA if none
loan_status : The status of the loan (current or expired), NA if none
loan_default : T/F if the loan is in default, or NA if none
max_withdrawal : Maximum amount withdrawn for the account
min_withdrawal : Minimum amount withdrawn for the account
cc_payments : Count of credit payments for the account for all cards
max_balance : Maximum balance in the account
min_balance : Minimum balance in the account

The scripts that perform this task are called analytical.R.The scripts will produce CSV files called analytical_r.csv