$2.$ Importing Transaction Data File:

$$ To efficiently add multiple records, you can import a transaction data file.

$$ Choose between CSV or XML formats for this task. A sample CSV file is provided for your reference.

$3.$ Transaction Records:

$$ Transactions should be stored as records within an appropriate data structure $($e$.$g$.,$ list of dictionaries$)$ inside each account's dictionary.

$$ Each record must contain details such as transaction amount, type, category, and date.

$4.$ Account Management:

$$ Use a dictionary to manage different accounts $($e$.$g$.,$ Checking, Savings, Credit Card$),$ with each account key holding another dictionary that contains the balance and a list of transactions.

Given this structure, here's how a record could be structured within a Python data structure. In this example, accounts is a dictionary managing different account types $($Checking$,$ Saving, etc.$).$ Each account holds another dictionary containing the account balance and a transactions list. Each item in the transactions list is a dictionary with details about each transaction, including date, type $($Income or Expenses$),$ category, details, and amount. Note that expenses are represented as negative amounts to reflect the deduction from the account balance.

$5.$ Data Filtering:

$$ Implement a PersonalFinanceManager class with methods for adding new transactions, updating and retrieving account balances, and filtering transactions by various criteria such as date, category, transaction type, season, and account type. At least implement $2$ filtering methods.

$$ Data Filtering Requirements:

$$ PersonalFinanceManager Class: The class must include attributes for storing user accounts and their transactions. It should provide methods for data manipulation and retrieval.

$$ Transaction Addition: Implement a method named add$\_$transaction that allows adding new transactions to the specified account. Each transaction should be a dictionary containing keys for date, type, category, details, and amount.

$$ Balance Management: Include methods update$\_$balance and get$\_$balance for updating and retrieving the current balance of specified accounts, respectively.

$$ Filtering Transactions:

$$ Develop a method filter$\_$by$\_$date for retrieving transactions within a specified date range.

$$ Create a method filter$\_$by$\_$category to obtain transactions that match a specific category.

$$ Optionally, additional methods could be implemented to filter transactions by type $($income or expense$),$ season, or account type.

$6.$ Data Visualization:

$$ Integrate an external library $($e$.$g$.,$ Matplotlib, Seaborn$)$ to generate graphs or charts displaying filtered data based on user specifications $($e$.$g$.,$ transaction type, category, period$).$

$$ E$.$g$.,$ the pie chart below visualizes the distribution of income by category during the summer months. Each slice represents a different income category, showing how the total income is divided among these categories