The provided dataset serves as a foundational component for the creation of the demo data source.

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Dataset Overview

The dataset encompasses a detailed record of an individual’s monthly income and expenses over a four-month period. It reflects a continuous effort to monitor personal finances, with a commitment to periodic updates following the conclusion of each month.

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Dataset Structure

The dataset is structured around various financial categories, accompanied by annotations that delineate specific income or expenditure incidents.

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Purpose and Motivation Behind the Dataset

The primary motivation for compiling this dataset stems from the individual’s objective to meticulously analyze their financial habits. By aggregating personal financial data, the aim is to identify patterns of unnecessary expenditure, thereby facilitating informed decisions to rectify financial missteps and optimize fiscal management.

The demo data source incorporates the following columns for comprehensive financial tracking:

  • Date: The date on which the transaction occurred.
  • Account: The financial account from which the transaction was made or into which income was received.
  • Category: The broad classification of the transaction (e.g., Food, Utilities, Rent).
  • Subcategory: More detailed classification under each category.
  • Note (First Instance): Additional details regarding the transaction.
  • INR: Column intended for transaction amounts, though the naming suggests a focus on Indian Rupee, it may serve as a placeholder for general transaction values.
  • Income/Expense: Indicator of whether the transaction is an income or an expense.
  • Note (Second Instance): It appears there is a duplication in the column naming for “Note”. This could either be an error in the documentation or signify a separate note field for additional context.
  • Amount: The value of the transaction.
  • Currency: The currency in which the transaction was conducted.

For access to the dataset, please visit the provided Kaggle link: My Expenses Data on Kaggle.